2026-06-21 03:06:18 [scrapy.utils.log] INFO: Scrapy 2.12.0 started (bot: ZomatoReviewData)
2026-06-21 03:06:18 [scrapy.utils.log] INFO: Versions: lxml 6.0.2.0, libxml2 2.14.6, cssselect 1.3.0, parsel 1.10.0, w3lib 2.3.1, Twisted 25.5.0, Python 3.12.3 (main, Mar 23 2026, 19:04:32) [GCC 13.3.0], pyOpenSSL 25.1.0 (OpenSSL 3.5.2 5 Aug 2025), cryptography 45.0.6, Platform Linux-6.17.0-1013-aws-x86_64-with-glibc2.39
2026-06-21 03:06:18 [scrapy.addons] INFO: Enabled addons:
[]
2026-06-21 03:06:18 [asyncio] DEBUG: Using selector: EpollSelector
2026-06-21 03:06:18 [scrapy.utils.log] DEBUG: Using reactor: twisted.internet.asyncioreactor.AsyncioSelectorReactor
2026-06-21 03:06:18 [scrapy.utils.log] DEBUG: Using asyncio event loop: asyncio.unix_events._UnixSelectorEventLoop
2026-06-21 03:06:18 [scrapy.utils.log] DEBUG: Using reactor: twisted.internet.asyncioreactor.AsyncioSelectorReactor
2026-06-21 03:06:18 [scrapy.utils.log] DEBUG: Using asyncio event loop: asyncio.unix_events._UnixSelectorEventLoop
2026-06-21 03:06:18 [scrapy.extensions.telnet] INFO: Telnet Password: 594e7340554a1636
2026-06-21 03:06:18 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.corestats.CoreStats',
 'scrapy.extensions.telnet.TelnetConsole',
 'scrapy.extensions.memusage.MemoryUsage',
 'scrapy.extensions.logstats.LogStats']
2026-06-21 03:06:18 [scrapy.crawler] INFO: Overridden settings:
{'BOT_NAME': 'ZomatoReviewData',
 'CONCURRENT_REQUESTS': 32,
 'DOWNLOAD_DELAY': 0.3,
 'FEED_EXPORT_ENCODING': 'utf-8',
 'LOG_FILE': '/home/ubuntu/logs/ZomatoReviewData/zomato_review_data/2934db706d1e11f1bc0c0aab37b1cebd.log',
 'NEWSPIDER_MODULE': 'ZomatoReviewData.spiders',
 'SPIDER_MODULES': ['ZomatoReviewData.spiders'],
 'TWISTED_REACTOR': 'twisted.internet.asyncioreactor.AsyncioSelectorReactor'}
2026-06-21 03:06:18 [scrapy.middleware] INFO: Enabled downloader middlewares:
['scrapy.downloadermiddlewares.offsite.OffsiteMiddleware',
 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',
 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware',
 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware',
 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',
 'scrapy.downloadermiddlewares.retry.RetryMiddleware',
 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',
 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware',
 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',
 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',
 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',
 'scrapy.downloadermiddlewares.stats.DownloaderStats']
2026-06-21 03:06:18 [scrapy.middleware] INFO: Enabled spider middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
 'scrapy.spidermiddlewares.referer.RefererMiddleware',
 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
 'scrapy.spidermiddlewares.depth.DepthMiddleware']
2026-06-21 03:06:18 [scrapy.middleware] INFO: Enabled item pipelines:
['ZomatoReviewData.pipelines.ZomatoreviewdataPipeline']
2026-06-21 03:06:18 [scrapy.core.engine] INFO: Spider opened
2026-06-21 03:06:18 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2026-06-21 03:06:18 [scrapy.extensions.telnet] INFO: Telnet console listening on 127.0.0.1:6023
2026-06-21 03:06:18 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:92: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.

2026-06-21 03:06:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:20 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:21 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:21 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:22 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:22 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:22 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:23 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:23 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:23 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:24 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:24 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:24 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:24 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:25 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:26 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:26 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:27 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:27 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:27 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:27 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:28 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:29 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:30 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:30 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:31 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216298&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:32 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21163973&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21676822&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20364493&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20558426&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:34 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121219&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:34 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:06:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47458&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20583150&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48924&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34269&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18670791&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18635722&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=36115&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22569440&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21485445&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18306453&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19539841&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18596333&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22364196&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21008097&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22455507&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19294645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21595781&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21548299&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21389292&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22555365&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22423992&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22584894&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20835029&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21541542&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21760482&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20936876&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21607045&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20450710&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21397635&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473630866> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19428676&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19363966&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473639196> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473660523> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106292&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261801065> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473643246> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261801065>
None
2026-06-21 03:06:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=473677611> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22246289&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22118624&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238196278> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238196278>
None
2026-06-21 03:06:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18349461&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584538&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21088985&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253510110> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253510110>
None
2026-06-21 03:06:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19562464&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260807749> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260807749>
None
2026-06-21 03:06:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252908547> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252908547>
None
2026-06-21 03:06:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227558&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542907&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22169265&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21921775&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22220059&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19548739&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068198&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22555365&review_id=473664614> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063494&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21745864&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21671884&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21568377&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257297091> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257297091>
None
2026-06-21 03:06:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106370&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21700572&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531025&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068186&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21665093&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20030720&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530778&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531051&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063645&review_id=473629895> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106292&review_id=473663916> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473656064> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:06:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777641&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21328904&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259856242> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259856242>
None
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8263192816> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063561&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8263192816>
None
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266142&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266188&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227536&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165882&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20877428&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21281252&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22113355&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21585021&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542907&review_id=473663034> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098456&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777831&review_id=473666586> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473665476> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19548739&review_id=473656765> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259725458> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18646161&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259725458>
None
2026-06-21 03:07:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098442&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259725220> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259725220>
None
2026-06-21 03:07:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21745864&review_id=473677088> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257680287> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257680287>
None
2026-06-21 03:07:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21671884&review_id=473673564> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903328&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772907&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8237203154> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8237203154>
None
2026-06-21 03:07:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22118595&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8234841770> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8234841770>
None
2026-06-21 03:07:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266169&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248827453> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248827453>
None
2026-06-21 03:07:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531025&review_id=473631215> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068186&review_id=473631270> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22139797&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165905&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530778&review_id=473665529> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903289&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260993389> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260993389>
None
2026-06-21 03:07:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22048924&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21766954&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824195&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261144373> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261144373>
None
2026-06-21 03:07:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227497&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261417561> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227433&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261417561>
None
2026-06-21 03:07:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531041&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068202&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227536&review_id=473654279> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22755866&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22279509&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22113355&review_id=473652007> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772956&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21619787&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261954164> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106341&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261954164>
None
2026-06-21 03:07:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227467&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257153515> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257153515>
None
2026-06-21 03:07:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21766765&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542895&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21060957&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261675762> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261675762>
None
2026-06-21 03:07:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21764424&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227479&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473655203> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21339862&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772853&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22169299&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21240266&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:18 [scrapy.extensions.logstats] INFO: Crawled 183 pages (at 183 pages/min), scraped 20 items (at 20 items/min)
2026-06-21 03:07:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257189219> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21819938&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257189219>
None
2026-06-21 03:07:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22139797&review_id=473674852> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068175&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18165905&review_id=473666405> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18165905&review_id=473683006> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473639711> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250855595> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22532270&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250855595>
None
2026-06-21 03:07:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21766954&review_id=473632142> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21061214&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253394542> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253394542>
None
2026-06-21 03:07:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254001470> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824183&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254001470>
None
2026-06-21 03:07:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256131929> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256131929>
None
2026-06-21 03:07:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22084334&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22230657&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261222776> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772919&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261222776>
None
2026-06-21 03:07:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824211&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21581112&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18624714&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530561&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777752&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542894&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21365545&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098418&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106325&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584519&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063613&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21293253&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165909&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542914&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21619757&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068209&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106399&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21921871&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530900&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531023&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22137335&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068175&review_id=473649031> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777671&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063677&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098343&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21656481&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584394&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244703242> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244703242>
None
2026-06-21 03:07:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21726472&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21061156&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22208312&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777802&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106292&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22246289&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22118624&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21581112&review_id=473648164> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584538&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18349461&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262475766> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262475766>
None
2026-06-21 03:07:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542894&review_id=473673320> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473640836> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473667152> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21088985&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19562464&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255041691> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255041691>
None
2026-06-21 03:07:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227558&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8231373676> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8231373676>
None
2026-06-21 03:07:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473671424> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18165909&review_id=473650158> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542907&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473654719> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22169265&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106399&review_id=473673909> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257214315> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254189307> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257214315>
None
2026-06-21 03:07:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254189307>
None
2026-06-21 03:07:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068209&review_id=473677338> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531023&review_id=473666594> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530900&review_id=473653824> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531023&review_id=473673419> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256267043> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256267043>
None
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261132946> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261132946>
None
2026-06-21 03:07:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21921775&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777671&review_id=473629333> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261817886> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256488737> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261817886>
None
2026-06-21 03:07:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256488737>
None
2026-06-21 03:07:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22220059&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256724234> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256724234>
None
2026-06-21 03:07:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250626405> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21656481&review_id=473660519> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250626405>
None
2026-06-21 03:07:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258579412> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261849374> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258579412>
None
2026-06-21 03:07:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261849374>
None
2026-06-21 03:07:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584394&review_id=473632894> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584394&review_id=473660520> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19548739&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258677637> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258677637>
None
2026-06-21 03:07:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068198&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261695293> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063494&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261695293>
None
2026-06-21 03:07:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259254714> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259254714>
None
2026-06-21 03:07:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063645&review_id=473551502> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106292&review_id=473570010> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106292&review_id=473345721> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22246289&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251613619> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18349461&review_id=473285160> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251613619>
None
2026-06-21 03:07:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584538&review_id=473413552> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248032585> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248032585>
None
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256921493> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106292&review_id=473587943> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256921493>
None
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584538&review_id=473521391> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256102050> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256102050>
None
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19562464&review_id=473126821> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250604978> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250604978>
None
2026-06-21 03:07:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21088985&review_id=473140353> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227558&review_id=473537958> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19562464&review_id=473606505> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261173044> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245046099> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261173044>
None
2026-06-21 03:07:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245046099>
None
2026-06-21 03:07:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257399352> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257399352>
None
2026-06-21 03:07:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227558&review_id=473590856> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21088985&review_id=473307910> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258670523> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258670523>
None
2026-06-21 03:07:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256411126> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256411126>
None
2026-06-21 03:07:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542907&review_id=473250495> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259354303> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261459015> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22169265&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259354303>
None
2026-06-21 03:07:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261459015>
None
2026-06-21 03:07:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542907&review_id=473552787> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542907&review_id=473320535> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244303602> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244303602>
None
2026-06-21 03:07:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255114851> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255114851>
None
2026-06-21 03:07:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21088985&review_id=473446329> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21088985&review_id=473587674> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063645&review_id=473581731> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258924217> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258924217>
None
2026-06-21 03:07:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22220059&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260424728> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063645&review_id=473610194> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260424728>
None
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21745864&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254402090> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254402090>
None
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250017735> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254655911> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250017735>
None
2026-06-21 03:07:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254655911>
None
2026-06-21 03:07:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21671884&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21568377&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260400076> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260400076>
None
2026-06-21 03:07:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106370&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21700572&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531025&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063494&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068186&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:07:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21665093&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473197470> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777831&review_id=473150967> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473455502> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777831&review_id=473144811> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473512462> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252316156> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:01 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252316156>
None
2026-06-21 03:08:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473575704> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260661807> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260661807>
None
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473592897> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257123600> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257123600>
None
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20030720&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22246289&review_id=473607799> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530778&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255752462> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255752462>
None
2026-06-21 03:08:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255851560> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254887108> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255851560>
None
2026-06-21 03:08:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254887108>
None
2026-06-21 03:08:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777641&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531051&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21328904&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252948396> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261337418> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252948396>
None
2026-06-21 03:08:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261337418>
None
2026-06-21 03:08:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266142&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473159673> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473334168> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473449048> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473507532> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473195855> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258671108> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258671108>
None
2026-06-21 03:08:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473196938> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473154417> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260056162> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473491018> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260056162>
None
2026-06-21 03:08:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473557561> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22220059&review_id=473536218> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8246368486> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8246368486>
None
2026-06-21 03:08:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21671884&review_id=473392113> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257877689> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256036178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257877689>
None
2026-06-21 03:08:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256036178>
None
2026-06-21 03:08:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245402597> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21671884&review_id=473608238> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245402597>
None
2026-06-21 03:08:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249544371> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249544371>
None
2026-06-21 03:08:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21568377&review_id=473363183> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257281019> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257281019>
None
2026-06-21 03:08:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473509757> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106370&review_id=473338335> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531025&review_id=473148862> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251366879> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251366879>
None
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253033892> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253033892>
None
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261749573> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068186&review_id=473129046> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531025&review_id=473594710> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261749573>
None
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259954444> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259954444>
None
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21665093&review_id=473415287> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260749893> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260749893>
None
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068186&review_id=473196776> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253126650> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253126650>
None
2026-06-21 03:08:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068186&review_id=473586526> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256819915> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256819915>
None
2026-06-21 03:08:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473190715> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20030720&review_id=473238453> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256047965> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256047965>
None
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258808259> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254983181> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258808259>
None
2026-06-21 03:08:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254983181>
None
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251396515> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251396515>
None
2026-06-21 03:08:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068186&review_id=473612485> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530778&review_id=473124300> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530778&review_id=473301525> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20030720&review_id=473489229> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20030720&review_id=473598792> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252417302> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252417302>
None
2026-06-21 03:08:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531051&review_id=473577530> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254951168> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254951168>
None
2026-06-21 03:08:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777641&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258688605> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258688605>
None
2026-06-21 03:08:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255340930> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257038161> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255340930>
None
2026-06-21 03:08:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257038161>
None
2026-06-21 03:08:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247221200> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247221200>
None
2026-06-21 03:08:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473282221> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260639972> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473451721> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260639972>
None
2026-06-21 03:08:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266142&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473509033> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257839269> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473574483> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261602273> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257839269>
None
2026-06-21 03:08:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261602273>
None
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063494&review_id=473606441> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255982409> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247672536> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255982409>
None
2026-06-21 03:08:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247672536>
None
2026-06-21 03:08:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260255696> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260255696>
None
2026-06-21 03:08:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21700572&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:18 [scrapy.extensions.logstats] INFO: Crawled 425 pages (at 242 pages/min), scraped 102 items (at 82 items/min)
2026-06-21 03:08:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251711397> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251711397>
None
2026-06-21 03:08:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169265&review_id=473546292> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259257984> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259257984>
None
2026-06-21 03:08:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227536&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165882&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20877428&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21281252&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266188&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22113355&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21585021&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098456&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18646161&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253025143> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098442&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253025143>
None
2026-06-21 03:08:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903328&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22118595&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22266169&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772907&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22139797&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165905&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473201862> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473453714> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473193308> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473595824> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473593054> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777641&review_id=473606813> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255656897> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255656897>
None
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254725308> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254725308>
None
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473194416> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473198196> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248116450> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248116450>
None
2026-06-21 03:08:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473391509> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473202381> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251402713> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251402713>
None
2026-06-21 03:08:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250519745> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250519745>
None
2026-06-21 03:08:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473454387> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255423460> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473413028> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255423460>
None
2026-06-21 03:08:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8240895188> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8240895188>
None
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21700572&get_filters_v2=1&detailed_filters=delivery&offset=10&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473510568> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8213396891> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8213396891>
None
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473549373> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249991799> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249991799>
None
2026-06-21 03:08:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256367632> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227536&review_id=473131254> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256367632>
None
2026-06-21 03:08:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18165882&review_id=473527594> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257289878> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257289878>
None
2026-06-21 03:08:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20877428&review_id=473221506> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259472679> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259472679>
None
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20877428&review_id=473602715> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259404128> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259404128>
None
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266188&review_id=473334942> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247757303> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22113355&review_id=473122991> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247757303>
None
2026-06-21 03:08:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260332594> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260332594>
None
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21585021&review_id=473519823> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255739476> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266188&review_id=473352000> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255739476>
None
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256078465> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256078465>
None
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8240426410> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266188&review_id=473584398> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8240426410>
None
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254998294> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254998294>
None
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21281252&review_id=473196632> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21281252&review_id=473470116> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254289832> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254289832>
None
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903328&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063561&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250510948> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250510948>
None
2026-06-21 03:08:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21281252&review_id=473487747> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254698092> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21281252&review_id=473583816> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254698092>
None
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252677817> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261649501> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21772907&review_id=473134949> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252677817>
None
2026-06-21 03:08:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261649501>
None
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261397730> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261397730>
None
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22139797&review_id=473125672> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260386995> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22139797&review_id=473143190> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260386995>
None
2026-06-21 03:08:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22139797&review_id=473146202> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258130171> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260662603> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258130171>
None
2026-06-21 03:08:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260662603>
None
2026-06-21 03:08:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266169&review_id=473584526> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258924151> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258924151>
None
2026-06-21 03:08:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22118595&review_id=473122498> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22118595&review_id=473192218> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257532799> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256228558> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257532799>
None
2026-06-21 03:08:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256228558>
None
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22118595&review_id=473552453> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260023166> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260023166>
None
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22118595&review_id=473582655> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22118595&review_id=473610482> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252572444> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21281252&review_id=473611659> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252572444>
None
2026-06-21 03:08:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473192833> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258110444> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258110444>
None
2026-06-21 03:08:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256618696> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256618696>
None
2026-06-21 03:08:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473198959> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473200372> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254660696> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254660696>
None
2026-06-21 03:08:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257891001> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260221979> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257891001>
None
2026-06-21 03:08:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260221979>
None
2026-06-21 03:08:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473428035> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473493257> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473505432> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473560205> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258273610> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258273610>
None
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253722399> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253722399>
None
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473564914> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248567486> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248567486>
None
2026-06-21 03:08:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248524141> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248524141>
None
2026-06-21 03:08:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473565711> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473565257> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257608990> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257608990>
None
2026-06-21 03:08:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260872550> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260872550>
None
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18165882&review_id=473622436> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21700572&review_id=473601315> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260244151> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227536&review_id=473375755> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260244151>
None
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473133173> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258395624> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261261857> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258395624>
None
2026-06-21 03:08:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261261857>
None
2026-06-21 03:08:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260182498> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260182498>
None
2026-06-21 03:08:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063561&review_id=473352520> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063561&review_id=473450560> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261716739> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261716739>
None
2026-06-21 03:08:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260408028> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260408028>
None
2026-06-21 03:08:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063561&review_id=473595060> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063561&review_id=473605375> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258550316> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258550316>
None
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473261956> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253398357> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253398357>
None
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473148922> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473336698> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258842127> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258842127>
None
2026-06-21 03:08:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260168370> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260168370>
None
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473540168> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473368197> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253010528> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253010528>
None
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260210230> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260210230>
None
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473576404> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255390653> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255390653>
None
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903328&review_id=473593723> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227536&review_id=473504972> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257178661> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257178661>
None
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259002463> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258346442> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259002463>
None
2026-06-21 03:08:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258346442>
None
2026-06-21 03:08:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22266142&review_id=473607093> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903289&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258676827> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254535158> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258676827>
None
2026-06-21 03:08:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254535158>
None
2026-06-21 03:08:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22048924&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21766954&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824195&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8236569497> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255973742> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227433&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227497&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8236569497>
None
2026-06-21 03:08:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255973742>
None
2026-06-21 03:08:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255734145> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255734145>
None
2026-06-21 03:08:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531041&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068202&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258082555> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258082555>
None
2026-06-21 03:08:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22755866&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21619787&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22279509&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772956&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106341&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227467&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542895&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21766765&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21060957&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22227479&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21339862&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21764424&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772853&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21240266&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22169299&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21819938&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068175&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22532270&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21061214&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824183&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:08:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20903289&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22084334&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22048924&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22230657&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21766954&review_id=473379494> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21824195&review_id=473284374> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21824195&review_id=473186949> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21824195&review_id=473593818> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227497&review_id=473196306> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8221298353> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8221298353>
None
2026-06-21 03:09:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227497&review_id=473532969> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260154728> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260154728>
None
2026-06-21 03:09:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227497&review_id=473556141> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244621003> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244621003>
None
2026-06-21 03:09:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227497&review_id=473585220> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259899837> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255105825> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531041&review_id=473120892> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259899837>
None
2026-06-21 03:09:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255105825>
None
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22755866&review_id=473193160> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260791317> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22755866&review_id=473483390> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260791317>
None
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21619787&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255586743> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255586743>
None
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252260575> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252260575>
None
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22279509&review_id=473197193> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248362883> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250017176> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248362883>
None
2026-06-21 03:09:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250017176>
None
2026-06-21 03:09:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22279509&review_id=473492120> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22279509&review_id=473586971> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251493400> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542895&review_id=473273018> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251493400>
None
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542895&review_id=473525878> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242666399> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251815083> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242666399>
None
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21060957&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251815083>
None
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227479&review_id=473191955> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250659926> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250659926>
None
2026-06-21 03:09:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21339862&review_id=473516718> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255239384> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255239384>
None
2026-06-21 03:09:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260751774> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227479&review_id=473459340> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260751774>
None
2026-06-21 03:09:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21240266&review_id=473492893> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253961971> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227479&review_id=473576345> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253961971>
None
2026-06-21 03:09:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255936937> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255936937>
None
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22169299&review_id=473315379> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259115431> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259115431>
None
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068175&review_id=473607559> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259974680> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21240266&review_id=473559250> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259974680>
None
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22532270&review_id=473169772> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250444840> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250444840>
None
2026-06-21 03:09:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061214&review_id=473588628> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061214&review_id=473537072> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258345385> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258345385>
None
2026-06-21 03:09:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256577863> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473144080> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256577863>
None
2026-06-21 03:09:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248981835> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248981835>
None
2026-06-21 03:09:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259088938> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22084334&review_id=473195070> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473153507> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259088938>
None
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245133132> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245133132>
None
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473154636> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259623356> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473191492> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259623356>
None
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473307612> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242197925> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242197925>
None
2026-06-21 03:09:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255412565> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473323668> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255412565>
None
2026-06-21 03:09:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473451205> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244498236> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244498236>
None
2026-06-21 03:09:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250952316> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250952316>
None
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473547942> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473568333> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256968942> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245879655> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256968942>
None
2026-06-21 03:09:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245879655>
None
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259700534> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473196512> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259700534>
None
2026-06-21 03:09:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473269097> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473514515> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260288703> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260288703>
None
2026-06-21 03:09:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251840041> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251840041>
None
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473577133> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253899581> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245046071> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473581707> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253899581>
None
2026-06-21 03:09:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245046071>
None
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619787&review_id=473609382> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255734925> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22048924&review_id=473606088> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255734925>
None
2026-06-21 03:09:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260480159> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260480159>
None
2026-06-21 03:09:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254241051> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254241051>
None
2026-06-21 03:09:18 [scrapy.extensions.logstats] INFO: Crawled 698 pages (at 273 pages/min), scraped 212 items (at 110 items/min)
2026-06-21 03:09:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473138245> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473190957> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22084334&review_id=473489523> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253463949> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253463949>
None
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473406852> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257299060> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260053311> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257299060>
None
2026-06-21 03:09:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260053311>
None
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473505051> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249975275> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249975275>
None
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473565390> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21060957&review_id=473545495> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22084334&review_id=473534817> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258988080> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258988080>
None
2026-06-21 03:09:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22084334&review_id=473556769> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253112899> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253112899>
None
2026-06-21 03:09:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252643475> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252643475>
None
2026-06-21 03:09:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256543584> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256543584>
None
2026-06-21 03:09:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22084334&review_id=473614763> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258701537> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258701537>
None
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473189548> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254144451> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254144451>
None
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473238412> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257494069> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257494069>
None
2026-06-21 03:09:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256901143> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256901143>
None
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253871257> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253871257>
None
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473268714> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473270694> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473543010> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255952625> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255952625>
None
2026-06-21 03:09:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473226460> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259547846> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259547846>
None
2026-06-21 03:09:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20903289&review_id=473543321> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22532270&review_id=473192582> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259837229> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22532270&review_id=473488687> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259837229>
None
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257211429> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257211429>
None
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259126885> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259126885>
None
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22532270&review_id=473586041> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258213785> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22532270&review_id=473612205> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258213785>
None
2026-06-21 03:09:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256478428> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21240266&review_id=473591519> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256478428>
None
2026-06-21 03:09:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238805536> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255772762> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238805536>
None
2026-06-21 03:09:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255772762>
None
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227479&review_id=473609016> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22279509&review_id=473613024> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260001261> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252963040> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260001261>
None
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22227467&review_id=473211186> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252963040>
None
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22755866&review_id=473551044> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259737234> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259737234>
None
2026-06-21 03:09:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21772919&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22755866&review_id=473577514> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21824211&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258051109> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258051109>
None
2026-06-21 03:09:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253527823> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253527823>
None
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256264018> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21581112&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256264018>
None
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253128829> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18624714&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253128829>
None
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530561&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777752&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542894&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260593044> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260593044>
None
2026-06-21 03:09:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098418&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21365545&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106325&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584519&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21293253&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21619757&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063613&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18165909&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19542914&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22106399&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22068209&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21921871&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19531023&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19530900&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22137335&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777671&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063677&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098343&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21584394&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21656481&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21061156&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21726472&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21824211&review_id=473323725> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22208312&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19430760&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777802&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260029001> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19428676&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260029001>
None
2026-06-21 03:09:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19363966&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18624714&review_id=473385178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19430760&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18624714&review_id=473523179> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21760482&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21607045&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258518270> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20936876&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258518270>
None
2026-06-21 03:09:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473194587> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255992214> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255992214>
None
2026-06-21 03:09:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106325&review_id=473197515> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584519&review_id=473175176> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619757&review_id=473248092> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21584519&review_id=473322006> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253064506> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253064506>
None
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619757&review_id=473570942> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22063613&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256756109> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19542914&review_id=473338080> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256756109>
None
2026-06-21 03:09:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258242125> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258242125>
None
2026-06-21 03:09:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247355233> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:45 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247355233>
None
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106399&review_id=473196203> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068209&review_id=473555179> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22068209&review_id=473486873> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241780647> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241780647>
None
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238129511> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8238129511>
None
2026-06-21 03:09:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259775128> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259775128>
None
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19531023&review_id=473389364> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106399&review_id=473527596> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242328840> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22137335&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242328840>
None
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259443922> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777671&review_id=473540118> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259443922>
None
2026-06-21 03:09:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259440454> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259440454>
None
2026-06-21 03:09:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248971544> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248971544>
None
2026-06-21 03:09:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098343&review_id=473507937> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063677&review_id=473196070> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257339096> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257339096>
None
2026-06-21 03:09:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098343&review_id=473547170> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243216290> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243216290>
None
2026-06-21 03:09:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21656481&review_id=473229474> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248616893> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061156&review_id=473142475> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248616893>
None
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21726472&review_id=473336231> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259017625> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21726472&review_id=473568171> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259017625>
None
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252605203> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252605203>
None
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061156&review_id=473485056> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259530004> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259530004>
None
2026-06-21 03:09:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21777802&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251541425> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251541425>
None
2026-06-21 03:09:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061156&review_id=473517556> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8239074901> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8239074901>
None
2026-06-21 03:09:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098343&review_id=473567309> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260198535> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21061156&review_id=473609778> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260198535>
None
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098343&review_id=473604479> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255810263> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255810263>
None
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063677&review_id=473527244> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21607045&review_id=473604651> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259339734> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063677&review_id=473528966> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259339734>
None
2026-06-21 03:09:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252308178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252308178>
None
2026-06-21 03:09:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063677&review_id=473583378> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251788330> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251788330>
None
2026-06-21 03:09:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256404073> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256404073>
None
2026-06-21 03:09:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777671&review_id=473548447> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255246382> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255246382>
None
2026-06-21 03:09:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252986821> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473189980> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252986821>
None
2026-06-21 03:09:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530900&review_id=473369472> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473308311> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258744467> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258744467>
None
2026-06-21 03:09:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259056295> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473448294> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259056295>
None
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261591044> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261591044>
None
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473504149> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254581193> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254581193>
None
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8177497454> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8177497454>
None
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473563690> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22063613&review_id=473603974> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8233193941> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8233193941>
None
2026-06-21 03:09:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530900&review_id=473524287> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473194177> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259157378> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253400403> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259157378>
None
2026-06-21 03:09:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253400403>
None
2026-06-21 03:09:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473296510> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249961771> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:58 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249961771>
None
2026-06-21 03:09:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473456823> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258049179> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:58 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258049179>
None
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473513903> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255552697> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254508574> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255552697>
None
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19530900&review_id=473608658> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254508574>
None
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473550144> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22137335&review_id=473608483> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256862150> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241115196> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:09:59 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256862150>
None
2026-06-21 03:10:00 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241115196>
None
2026-06-21 03:10:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106399&review_id=473582994> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259690368> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22106399&review_id=473611212> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:00 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259690368>
None
2026-06-21 03:10:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261533444> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:01 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261533444>
None
2026-06-21 03:10:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243234320> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:01 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243234320>
None
2026-06-21 03:10:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254090241> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21293253&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:01 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254090241>
None
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21619757&review_id=473588234> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473367934> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250050363> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473197336> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258673904> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250050363>
None
2026-06-21 03:10:02 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258673904>
None
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473538595> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473557747> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473558449> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260784049> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260784049>
None
2026-06-21 03:10:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21777802&review_id=473588786> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250225595> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250225595>
None
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255687013> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473199844> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255687013>
None
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473521133> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259638093> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259638093>
None
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473610871> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8235909302> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8235909302>
None
2026-06-21 03:10:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20450710&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21365545&review_id=473554132> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251333069> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21397635&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251333069>
None
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258608343> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258608343>
None
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20818448&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249053358> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249053358>
None
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21537644&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21537645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254370497> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254370497>
None
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20835029&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256334925> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260350374> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256334925>
None
2026-06-21 03:10:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260350374>
None
2026-06-21 03:10:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21541542&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21537644&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20818448&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21537645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22584894&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22423992&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34485&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22555365&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34485&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19596438&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20825115&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22286044&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473189779> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473197075> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473309604> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21670583&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254578973> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473514880> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254578973>
None
2026-06-21 03:10:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249083155> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249083155>
None
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473552705> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21293253&review_id=473580363> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22147659&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098336&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260114456> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260114456>
None
2026-06-21 03:10:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20100306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261476839> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261476839>
None
2026-06-21 03:10:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259099531> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259099531>
None
2026-06-21 03:10:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262236285> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262236285>
None
2026-06-21 03:10:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19596438&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20825115&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22286044&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21670583&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22147659&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22098336&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20100306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20823682&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20631505&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:18 [scrapy.extensions.logstats] INFO: Crawled 962 pages (at 264 pages/min), scraped 309 items (at 97 items/min)
2026-06-21 03:10:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21389292&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21548299&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21537644&review_id=473372311> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20169774&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20631505&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259085070> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259085070>
None
2026-06-21 03:10:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21537645&review_id=473375722> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20169774&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34485&review_id=473667462> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21162306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20823682&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257677515> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257677515>
None
2026-06-21 03:10:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20770901&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21162306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256102992> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256102992>
None
2026-06-21 03:10:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21166088&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20719746&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21750487&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19294645&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20770901&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21595781&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21166088&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22147659&review_id=473635592> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20719746&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21750487&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22455507&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21008097&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262526878> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262526878>
None
2026-06-21 03:10:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22667532&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22286044&review_id=473605808> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20825115&review_id=473332332> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22702511&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098336&review_id=473539859> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22098336&review_id=473296122> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254499865> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254499865>
None
2026-06-21 03:10:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259989560> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259989560>
None
2026-06-21 03:10:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22667532&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22702511&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259229417> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22364196&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18594999&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259229417>
None
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19539841&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18596333&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254847445> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254847445>
None
2026-06-21 03:10:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18594999&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18673927&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18382999&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18198742&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20823682&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18537203&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18306453&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18673927&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18382999&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21162306&review_id=473439069> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18537203&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18198742&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20471053&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22393549&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251786076> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20608491&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251786076>
None
2026-06-21 03:10:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20157208&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21166088&review_id=473303950> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20719746&review_id=473314385> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22455507&review_id=473417464> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20510729&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20989480&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21956336&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259649658> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259649658>
None
2026-06-21 03:10:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245557204> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245557204>
None
2026-06-21 03:10:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21485445&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22393549&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255452213> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255452213>
None
2026-06-21 03:10:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20471053&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20608491&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20157208&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20510729&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20989480&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22643394&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21956336&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22702674&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22565422&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18594999&review_id=473244036> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18594999&review_id=473548526> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22387831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22435121&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253976967> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253976967>
None
2026-06-21 03:10:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473123028> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473123277> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257660164> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257660164>
None
2026-06-21 03:10:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18673927&review_id=473127249> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473123870> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473122647> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245035573> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18537203&review_id=473554236> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245035573>
None
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247623650> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473123929> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247623650>
None
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256101146> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473124413> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256101146>
None
2026-06-21 03:10:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473125806> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473125808> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=473126233> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253555899> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251127714> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253555899>
None
2026-06-21 03:10:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251127714>
None
2026-06-21 03:10:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252485923> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252485923>
None
2026-06-21 03:10:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253469759> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253469759>
None
2026-06-21 03:10:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22622118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253060822> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253060822>
None
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21992187&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22208828&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254840695> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22569440&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254840695>
None
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22643394&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250214106> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22702674&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250214106>
None
2026-06-21 03:10:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256304606> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256304606>
None
2026-06-21 03:10:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22565422&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22387831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21992187&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22622118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22208828&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22455300&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22435121&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20989480&review_id=473605304> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18635722&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22455300&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247650005> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=36115&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247650005>
None
2026-06-21 03:10:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=35658&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=35658&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=32835&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18735687&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20516112&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48323&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48323&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=32835&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18735687&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20516112&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:10:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=39642&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=41769&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19771076&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21992187&review_id=473672717> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20583150&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48924&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18670791&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=39642&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=41769&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247679722> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247679722>
None
2026-06-21 03:11:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19771076&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34269&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19470793&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18324118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21992187&review_id=473150295> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21992187&review_id=473386317> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18887194&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22455300&review_id=473666398> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22208828&review_id=473214466> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21196973&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18635722&review_id=473136055> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256470905> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256470905>
None
2026-06-21 03:11:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18635722&review_id=473303567> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22455300&review_id=473291088> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8231897748> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256671472> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8231897748>
None
2026-06-21 03:11:07 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256671472>
None
2026-06-21 03:11:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=35658&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259159711> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259159711>
None
2026-06-21 03:11:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=35658&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258515842> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258515842>
None
2026-06-21 03:11:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259160796> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255924319> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473646207> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473641353> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259160796>
None
2026-06-21 03:11:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255924319>
None
2026-06-21 03:11:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473652269> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=36115&review_id=473263138> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48323&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473653095> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48323&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18735687&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244618186> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261994769> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244618186>
None
2026-06-21 03:11:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261994769>
None
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=39642&review_id=473659486> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20516112&review_id=473361795> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249101291> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249101291>
None
2026-06-21 03:11:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245842258> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:11 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245842258>
None
2026-06-21 03:11:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473132533> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=473279417> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258421577> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473135225> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473129889> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258421577>
None
2026-06-21 03:11:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247680776> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247680776>
None
2026-06-21 03:11:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=473138813> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=39642&review_id=473364403> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249615582> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256677416> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249615582>
None
2026-06-21 03:11:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256677416>
None
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249893765> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18670791&review_id=473496159> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249893765>
None
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=41769&review_id=473158491> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18670791&review_id=473575110> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258299856> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258299856>
None
2026-06-21 03:11:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=473235625> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258516008> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258516008>
None
2026-06-21 03:11:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247716870> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18324118&review_id=473643771> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247716870>
None
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473638506> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256369726> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256369726>
None
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473674247> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248422257> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248422257>
None
2026-06-21 03:11:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256364544> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256364544>
None
2026-06-21 03:11:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473651349> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473635756> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257306246> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257306246>
None
2026-06-21 03:11:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262199336> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256184045> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262199336>
None
2026-06-21 03:11:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256184045>
None
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473665213> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257974308> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257974308>
None
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473650838> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262882860> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473632063> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262882860>
None
2026-06-21 03:11:18 [scrapy.extensions.logstats] INFO: Crawled 1179 pages (at 217 pages/min), scraped 363 items (at 54 items/min)
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473635406> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473344698> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256539344> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256539344>
None
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473368701> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261063398> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261606188> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261063398>
None
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262852855> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261606188>
None
2026-06-21 03:11:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473487985> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262852855>
None
2026-06-21 03:11:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258188051> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258188051>
None
2026-06-21 03:11:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473491679> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258657390> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258657390>
None
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257989395> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257989395>
None
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473631866> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256176802> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256176802>
None
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473531979> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473636310> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258019583> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473161698> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258019583>
None
2026-06-21 03:11:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241281809> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8241281809>
None
2026-06-21 03:11:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473236904> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473261582> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260905393> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473397546> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260905393>
None
2026-06-21 03:11:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253765210> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253765210>
None
2026-06-21 03:11:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473526743> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256243551> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473543432> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256051694> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260853848> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256243551>
None
2026-06-21 03:11:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256051694>
None
2026-06-21 03:11:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260853848>
None
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473577071> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473587524> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251353398> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251353398>
None
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473607436> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255836031> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=48323&get_filters_v2=1&detailed_filters=delivery&offset=10&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255836031>
None
2026-06-21 03:11:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473653275> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255112190> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257771470> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255112190>
None
2026-06-21 03:11:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257771470>
None
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473655642> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260283705> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260283705>
None
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258158824> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473667421> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258158824>
None
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473534114> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261473716> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261473716>
None
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473665944> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473599436> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473600656> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257993247> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473610169> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257993247>
None
2026-06-21 03:11:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247801642> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247801642>
None
2026-06-21 03:11:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259994170> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259994170>
None
2026-06-21 03:11:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473640166> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262213735> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473664992> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8262213735>
None
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473660036> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259397395> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259397395>
None
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255788084> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255788084>
None
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473665989> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261126795> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261126795>
None
2026-06-21 03:11:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=473667195> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473546767> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260158336> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473488223> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256322624> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260158336>
None
2026-06-21 03:11:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256322624>
None
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257209196> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473568223> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473600313> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257209196>
None
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257582036> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257582036>
None
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253849555> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34269&review_id=473609310> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253849555>
None
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473586469> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261219054> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=32835&review_id=473620289> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261219054>
None
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473656209> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259426157> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259426157>
None
2026-06-21 03:11:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473666710> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258935082> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258935082>
None
2026-06-21 03:11:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253914579> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253914579>
None
2026-06-21 03:11:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=36115&review_id=473525206> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18735687&review_id=473667501> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261263126> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261263126>
None
2026-06-21 03:11:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258130033> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=36115&review_id=473526178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258130033>
None
2026-06-21 03:11:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=36115&review_id=473539854> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18635722&review_id=473309310> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259684408> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259684408>
None
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18635722&review_id=473538171> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8239545201> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8239545201>
None
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259516708> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473134755> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259516708>
None
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258957274> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258957274>
None
2026-06-21 03:11:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473229702> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257024055> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257024055>
None
2026-06-21 03:11:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473347520> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258433076> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258433076>
None
2026-06-21 03:11:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473474107> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259523528> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473366809> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259523528>
None
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259019178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473476855> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473489339> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259019178>
None
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250660808> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250660808>
None
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473508587> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473525339> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253203309> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253203309>
None
2026-06-21 03:11:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257647520> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257647520>
None
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473621133> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260318299> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48323&review_id=473595190> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260318299>
None
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8232677875> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257782078> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8232677875>
None
2026-06-21 03:11:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257782078>
None
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21401321&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22208828&review_id=473437237> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47458&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256826981> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256826981>
None
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19470793&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260204522> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260204522>
None
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259530363> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259530363>
None
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21196973&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251928138> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251928138>
None
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259046031> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18324118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259046031>
None
2026-06-21 03:11:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259354395> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259354395>
None
2026-06-21 03:11:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242957021> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21401321&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242957021>
None
2026-06-21 03:11:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454627&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918603&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18887194&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257370667> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20233989&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257370667>
None
2026-06-21 03:11:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20020122&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454636&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20620727&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20379354&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22243603&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20274785&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400105&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20223317&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20698004&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20356956&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21155912&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400091&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121242&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20337226&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20797495&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21401321&review_id=473656103> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121262&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47458&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19470793&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918660&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20132118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261889026> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261889026>
None
2026-06-21 03:11:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473144060> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473151368> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473593393> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18324118&review_id=473463186> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18324118&review_id=473584911> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473625179> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260458433> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21401321&review_id=473155771> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260458433>
None
2026-06-21 03:11:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253798353> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253798353>
None
2026-06-21 03:11:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21401321&review_id=473305056> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21401321&review_id=473255572> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257121635> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21401321&review_id=473335328> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257121635>
None
2026-06-21 03:11:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261525683> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=473626239> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261525683>
None
2026-06-21 03:11:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18887194&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254131895> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254131895>
None
2026-06-21 03:11:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20281056&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260407032> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253695610> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260407032>
None
2026-06-21 03:11:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253695610>
None
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259417137> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259417137>
None
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20797534&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20297585&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260429373> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260429373>
None
2026-06-21 03:11:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249602582> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249602582>
None
2026-06-21 03:11:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20916935&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20809442&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19129110&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261855348> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22243456&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261855348>
None
2026-06-21 03:11:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20627306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400098&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20337312&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454622&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918656&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121219&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:11:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918603&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454627&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20233989&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473254656> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47458&get_filters_v2=1&detailed_filters=delivery&offset=10&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473258231> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473406703> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473459086> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473466559> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473506188> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473516934> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249088058> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249088058>
None
2026-06-21 03:12:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473546716> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244396661> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:03 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8244396661>
None
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473576727> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18887194&get_filters_v2=1&detailed_filters=delivery&offset=10&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19470793&review_id=473622902> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257819792> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255832560> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257819792>
None
2026-06-21 03:12:04 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255832560>
None
2026-06-21 03:12:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20020122&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454636&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258363202> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258363202>
None
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251408063> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251408063>
None
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20620727&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260334690> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260334690>
None
2026-06-21 03:12:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257666580> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257666580>
None
2026-06-21 03:12:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20379354&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257748108> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:06 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257748108>
None
2026-06-21 03:12:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400105&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20274785&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22243603&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20223317&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20698004&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20356956&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21155912&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121242&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400091&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20797495&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20337226&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21121262&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20132118&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918660&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20281056&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20797534&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20297585&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249217682> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20233989&review_id=473541400> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249217682>
None
2026-06-21 03:12:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473246232> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473254170> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473336282> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473320082> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473212934> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257922152> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257922152>
None
2026-06-21 03:12:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473321097> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255324262> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255324262>
None
2026-06-21 03:12:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255752471> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255752471>
None
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473324671> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473322597> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473331555> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260284463> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260284463>
None
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473370215> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253397657> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253397657>
None
2026-06-21 03:12:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256772907> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256772907>
None
2026-06-21 03:12:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473348871> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473387673> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258421256> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258421256>
None
2026-06-21 03:12:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473458143> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260293528> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473464025> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260293528>
None
2026-06-21 03:12:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257026575> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257026575>
None
2026-06-21 03:12:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259188841> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473561451> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259188841>
None
2026-06-21 03:12:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255597822> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259654514> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473583283> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255597822>
None
2026-06-21 03:12:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259654514>
None
2026-06-21 03:12:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18887194&review_id=473471356> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260539229> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:18 [scrapy.extensions.logstats] INFO: Crawled 1444 pages (at 265 pages/min), scraped 459 items (at 96 items/min)
2026-06-21 03:12:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260539229>
None
2026-06-21 03:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260090858> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260090858>
None
2026-06-21 03:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473445030> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473459001> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252850828> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8237858926> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252850828>
None
2026-06-21 03:12:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8237858926>
None
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249573726> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249573726>
None
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473461863> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473603102> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473369219> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258837355> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258837355>
None
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473624252> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257521876> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257521876>
None
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252681110> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255525802> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8252681110>
None
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473626852> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255525802>
None
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47458&review_id=473627492> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20809442&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254798662> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254798662>
None
2026-06-21 03:12:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257515633> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257515633>
None
2026-06-21 03:12:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20916935&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255730258> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260474351> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255730258>
None
2026-06-21 03:12:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260474351>
None
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20132118&review_id=473521199> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22243456&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19129110&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256984776> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256984776>
None
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20337312&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20627306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20400098&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20454622&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257802549> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257802549>
None
2026-06-21 03:12:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22394537&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20918656&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20259662&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20558426&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20259662&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22394537&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19978680&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20670097&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20244307&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20693405&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18784164&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20364428&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=38378&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19625831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20350258&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19646158&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19310144&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19811192&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20681599&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18995602&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20809442&review_id=473338182> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20364493&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19978680&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20670097&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257690007> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257690007>
None
2026-06-21 03:12:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20693405&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20244307&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18784164&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20364428&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19625831&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=38378&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20350258&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19646158&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19811192&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=19310144&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20681599&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=18995602&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20627254&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21676822&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20558426&review_id=473131475> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20627254&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21019923&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21163970&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20244307&review_id=473673200> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21163973&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259110891> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259110891>
None
2026-06-21 03:12:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21163970&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21019923&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22707053&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21716636&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261841993> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261841993>
None
2026-06-21 03:12:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34306&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22707053&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21716636&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19811192&review_id=473642924> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216228&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:43 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47568&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216091&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20670097&review_id=473421539> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216283&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:44 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260968381> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:44 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260968381>
None
2026-06-21 03:12:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20267173&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=37824&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21831182&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:45 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248347468> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20364428&review_id=473420008> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:46 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248347468>
None
2026-06-21 03:12:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216477&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:46 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=38378&review_id=473587303> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=38378&review_id=473533093> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251076398> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:47 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=38378&review_id=473588233> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:47 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251076398>
None
2026-06-21 03:12:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19811192&review_id=473571804> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216216&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216466&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:48 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253068600> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:48 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253068600>
None
2026-06-21 03:12:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261610244> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:49 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261610244>
None
2026-06-21 03:12:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216302&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21722471&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260890982> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:49 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251626237> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216471&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260890982>
None
2026-06-21 03:12:50 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251626237>
None
2026-06-21 03:12:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21676822&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21831210&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22215802&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216195&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216274&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22107768&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34157&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216156&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20517146&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21019656&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34306&review_id=473450434> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=37823&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22469494&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21716636&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473633794> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473637678> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258143929> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473647040> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258143929>
None
2026-06-21 03:12:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20881305&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21722119&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:56 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250586322> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:56 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8250586322>
None
2026-06-21 03:12:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258771874> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:57 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258771874>
None
2026-06-21 03:12:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=41143&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216298&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:57 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216228&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=47568&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216091&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259504735> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:58 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259504735>
None
2026-06-21 03:12:58 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216283&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:12:59 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20267173&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=37824&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21831182&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216477&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:00 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216216&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216466&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:01 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216302&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:02 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21722471&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21676822&get_filters_v2=1&detailed_filters=delivery&offset=10&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216471&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21831210&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22216195&review_id=473648451> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:03 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22215802&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216195&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:04 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22107768&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258371500> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216274&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:05 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258371500>
None
2026-06-21 03:13:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22216156&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:05 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34157&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20517146&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21019656&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:06 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473120654> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473188978> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:07 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473246925> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473270351> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473309599> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256385905> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256385905>
None
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473377129> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253495618> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:08 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253495618>
None
2026-06-21 03:13:08 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21716636&review_id=473392559> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=37823&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=22469494&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257845216> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257845216>
None
2026-06-21 03:13:09 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251545416> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:09 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251545416>
None
2026-06-21 03:13:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248925251> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=20881305&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248925251>
None
2026-06-21 03:13:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21722119&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254465511> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254465511>
None
2026-06-21 03:13:10 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257861277> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:10 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257861277>
None
2026-06-21 03:13:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473332526> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473529126> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20267173&review_id=473623582> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:11 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=37824&review_id=473232954> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=37824&review_id=473278548> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:12 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257076090> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:12 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257076090>
None
2026-06-21 03:13:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21831182&review_id=473393758> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21831182&review_id=473585387> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256106178> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256106178>
None
2026-06-21 03:13:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=37824&review_id=473444461> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:13 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261884716> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:13 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261884716>
None
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=37824&review_id=473587173> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259173744> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257641012> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259173744>
None
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21722471&review_id=473125587> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257641012>
None
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21722471&review_id=473183402> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248561980> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8248561980>
None
2026-06-21 03:13:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473129573> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260366437> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261477694> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8260366437>
None
2026-06-21 03:13:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261477694>
None
2026-06-21 03:13:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21831210&review_id=473389188> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254919679> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:15 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254919679>
None
2026-06-21 03:13:15 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22216471&review_id=473593365> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258003326> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258754967> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473284171> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258003326>
None
2026-06-21 03:13:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258754967>
None
2026-06-21 03:13:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22107768&review_id=473186902> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22107768&review_id=473269927> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22216274&review_id=473208834> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257766300> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245373100> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257766300>
None
2026-06-21 03:13:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8245373100>
None
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22216274&review_id=473608162> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242142856> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:17 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8242142856>
None
2026-06-21 03:13:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249362786> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:18 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8249362786>
None
2026-06-21 03:13:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=34157&get_filters_v2=1&detailed_filters=delivery&offset=5&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22107768&review_id=473556753> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:18 [scrapy.extensions.logstats] INFO: Crawled 1660 pages (at 216 pages/min), scraped 511 items (at 52 items/min)
2026-06-21 03:13:18 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257790602> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8257790602>
None
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20517146&review_id=473175776> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256814590> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259595938> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20517146&review_id=473312645> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258184410> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256814590>
None
2026-06-21 03:13:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259595938>
None
2026-06-21 03:13:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258184410>
None
2026-06-21 03:13:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20517146&review_id=473569068> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22107768&review_id=473557076> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255674674> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255674674>
None
2026-06-21 03:13:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473295081> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253761564> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254925255> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8253761564>
None
2026-06-21 03:13:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254925255>
None
2026-06-21 03:13:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473342995> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261021846> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473350112> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261021846>
None
2026-06-21 03:13:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256988965> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256988965>
None
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258347441> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473360611> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473460992> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258347441>
None
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258657805> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473464718> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258657805>
None
2026-06-21 03:13:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473490642> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473491986> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255736904> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255736904>
None
2026-06-21 03:13:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247238089> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8247238089>
None
2026-06-21 03:13:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255193564> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473494432> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8255193564>
None
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259953857> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473527394> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259953857>
None
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21676822&review_id=473600755> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251787690> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258582206> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251787690>
None
2026-06-21 03:13:24 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258582206>
None
2026-06-21 03:13:24 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=47568&review_id=473618879> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=41143&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256700436> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8256700436>
None
2026-06-21 03:13:25 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoReviewData.py:148: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.
  comp_response = pd.read_sql_query(comp_query, self.conn)

2026-06-21 03:13:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243174856> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243174856>
None
2026-06-21 03:13:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473182572> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259810827> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258709752> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259810827>
None
2026-06-21 03:13:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8258709752>
None
2026-06-21 03:13:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473216212> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243300882> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473568344> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473581832> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243300882>
None
2026-06-21 03:13:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473514653> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=34157&review_id=473592382> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251816982> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8251816982>
None
2026-06-21 03:13:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=41143&review_id=473430870> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243126310> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=41143&review_id=473452218> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:28 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243126310>
None
2026-06-21 03:13:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254183762> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8254183762>
None
2026-06-21 03:13:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21548102&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-21&end_date=2026-06-21> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243322008> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8243322008>
None
2026-06-21 03:13:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8236439351> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259499846> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8236439351>
None
2026-06-21 03:13:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8259499846>
None
2026-06-21 03:13:30 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261149712> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:30 [scrapy.core.scraper] DEBUG: Scraped from <200 https://www.zomato.com/merchant-api/orders/order-details?tab_id=8261149712>
None
2026-06-21 03:13:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/all?res_id=21548102&get_filters_v2=1&detailed_filters=delivery&offset=0&start_date=2026-06-20&end_date=2026-06-20> (referer: https://www.zomato.com/partners/login)
2026-06-21 03:13:31 [scrapy.core.engine] INFO: Closing spider (finished)
2026-06-21 03:13:32 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-51825ef4-5981-4cc1-a582-81546c0b1bd3', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            today I have ordered butter garlic naan and prawn Schezwan fried rice from peppertwist marol outlet. prawns Schezwan rice was so good in taste. prawns piece and sauces enhance the rice taste. garlic naan was so soft and tasty must try.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:32 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:32 [httpcore.connection] DEBUG: connect_tcp.started host='bedrock-mantle.ap-south-1.api.aws' port=443 local_address=None timeout=5.0 socket_options=None
2026-06-21 03:13:32 [httpcore.connection] DEBUG: connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x78f135d4ea20>
2026-06-21 03:13:32 [httpcore.connection] DEBUG: start_tls.started ssl_context=<ssl.SSLContext object at 0x78f135d15ed0> server_hostname='bedrock-mantle.ap-south-1.api.aws' timeout=5.0
2026-06-21 03:13:32 [httpcore.connection] DEBUG: start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x78f135c9e5a0>
2026-06-21 03:13:32 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:32 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:32 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:32 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:32 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:33 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:33 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2787'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_4y3cns7zdtkdskhuvov725fx5tvkier2tmqkgpgxkukxg6rg7fpq'), (b'x-request-id', b'req_4y3cns7zdtkdskhuvov725fx5tvkier2tmqkgpgxkukxg6rg7fpq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:33 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:33 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:33 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:33 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:33 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:33 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:33 GMT', 'content-type': 'application/json', 'content-length': '2787', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_4y3cns7zdtkdskhuvov725fx5tvkier2tmqkgpgxkukxg6rg7fpq', 'x-request-id': 'req_4y3cns7zdtkdskhuvov725fx5tvkier2tmqkgpgxkukxg6rg7fpq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:33 [openai._base_client] DEBUG: request_id: req_4y3cns7zdtkdskhuvov725fx5tvkier2tmqkgpgxkukxg6rg7fpq
2026-06-21 03:13:33 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6ca1e494-7dd6-418d-8094-e8d22118c72d', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Veg Persia Special Meal Box from Persia Darbar = complete meal. Fragrant veg biryani, soft chapati + spicy Veg Kolhapuri, and 2 juicy paneer tikka kebabs with good char. Packaging kept everything separate and portions were filling. Gulab jamun was soft, spongy, not too sweet. Great value for variety.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:33 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:33 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:33 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:33 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:33 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:33 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:37 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:37 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7096'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_javukbgbyfqxm7ob5v5lryswrbu3tmmdr4oyevhz72wnyherww4q'), (b'x-request-id', b'req_javukbgbyfqxm7ob5v5lryswrbu3tmmdr4oyevhz72wnyherww4q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:37 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:37 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:37 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:37 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:37 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:37 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:37 GMT', 'content-type': 'application/json', 'content-length': '7096', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_javukbgbyfqxm7ob5v5lryswrbu3tmmdr4oyevhz72wnyherww4q', 'x-request-id': 'req_javukbgbyfqxm7ob5v5lryswrbu3tmmdr4oyevhz72wnyherww4q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:37 [openai._base_client] DEBUG: request_id: req_javukbgbyfqxm7ob5v5lryswrbu3tmmdr4oyevhz72wnyherww4q
2026-06-21 03:13:37 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-57f9b0a8-f958-4f51-8da9-327ce68b2955', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Just ordered the Egg Masala Fry paired with a hot Roti from Persia Darbar (Marol), and it was incredible. The egg masala fry was perfectly spiced, rich, and full of bold, aromatic flavors that instantly hit the spot. Scooping up that thick, delicious masala gravy with their soft roti makes for the ultimate comfort food combination. It arrived super fresh, well-packaged, and piping hot. If you\'re looking for a satisfying, flavorful meal delivered right to your doorstep, this is it!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:37 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:37 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:37 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:37 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:37 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:37 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:40 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:40 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6664'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_otyhuv7bon3t4axemrulbwpx7xc44wvrienmrk5hvf2dkc5ps3ka'), (b'x-request-id', b'req_otyhuv7bon3t4axemrulbwpx7xc44wvrienmrk5hvf2dkc5ps3ka'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:40 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:40 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:40 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:40 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:40 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:40 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:40 GMT', 'content-type': 'application/json', 'content-length': '6664', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_otyhuv7bon3t4axemrulbwpx7xc44wvrienmrk5hvf2dkc5ps3ka', 'x-request-id': 'req_otyhuv7bon3t4axemrulbwpx7xc44wvrienmrk5hvf2dkc5ps3ka', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:40 [openai._base_client] DEBUG: request_id: req_otyhuv7bon3t4axemrulbwpx7xc44wvrienmrk5hvf2dkc5ps3ka
2026-06-21 03:13:40 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-59906f93-fb2a-4419-8386-652b43965376', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Very disgusting food\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:40 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:40 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:40 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:40 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:40 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:40 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:42 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:42 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1976'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_si6eqtpgmxnauvidt5nzqwfoozk5lqzd6cxj7jmgu6e4s6ptjatq'), (b'x-request-id', b'req_si6eqtpgmxnauvidt5nzqwfoozk5lqzd6cxj7jmgu6e4s6ptjatq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:42 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:42 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:42 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:42 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:42 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:42 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:42 GMT', 'content-type': 'application/json', 'content-length': '1976', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_si6eqtpgmxnauvidt5nzqwfoozk5lqzd6cxj7jmgu6e4s6ptjatq', 'x-request-id': 'req_si6eqtpgmxnauvidt5nzqwfoozk5lqzd6cxj7jmgu6e4s6ptjatq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:42 [openai._base_client] DEBUG: request_id: req_si6eqtpgmxnauvidt5nzqwfoozk5lqzd6cxj7jmgu6e4s6ptjatq
2026-06-21 03:13:42 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-86b62125-8360-48f4-a400-814d8505320a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            tasty but green sauce high \n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:42 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:42 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:42 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:42 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:42 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:42 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:45 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:45 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4067'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_4qw4ln4c42omx2ogx75uvig2tqokmfr74nngczornyxtlqcietcq'), (b'x-request-id', b'req_4qw4ln4c42omx2ogx75uvig2tqokmfr74nngczornyxtlqcietcq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:45 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:45 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:45 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:45 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:45 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:45 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:45 GMT', 'content-type': 'application/json', 'content-length': '4067', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_4qw4ln4c42omx2ogx75uvig2tqokmfr74nngczornyxtlqcietcq', 'x-request-id': 'req_4qw4ln4c42omx2ogx75uvig2tqokmfr74nngczornyxtlqcietcq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:45 [openai._base_client] DEBUG: request_id: req_4qw4ln4c42omx2ogx75uvig2tqokmfr74nngczornyxtlqcietcq
2026-06-21 03:13:45 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b02b3194-a2a5-4555-9ea9-e8d2b4adfd21', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            quality and quantity 💯\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:45 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:45 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:45 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:45 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:45 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:45 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:46 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:46 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2859'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_34ldc2w7ci54yfxbwyo6owyqyxh62k7rc6ymzapjorvjuicekxea'), (b'x-request-id', b'req_34ldc2w7ci54yfxbwyo6owyqyxh62k7rc6ymzapjorvjuicekxea'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:46 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:46 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:46 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:46 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:46 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:46 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:46 GMT', 'content-type': 'application/json', 'content-length': '2859', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_34ldc2w7ci54yfxbwyo6owyqyxh62k7rc6ymzapjorvjuicekxea', 'x-request-id': 'req_34ldc2w7ci54yfxbwyo6owyqyxh62k7rc6ymzapjorvjuicekxea', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:46 [openai._base_client] DEBUG: request_id: req_34ldc2w7ci54yfxbwyo6owyqyxh62k7rc6ymzapjorvjuicekxea
2026-06-21 03:13:46 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c3d13b86-26c6-4b88-adf9-9dc9d74e04d2', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            good \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:46 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:46 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:46 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:46 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:46 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:46 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:47 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:47 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1563'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_tuy2fyexpzus6unmwdstg2ulxha4ulzu4t7b4ldhhc7sx3c375ea'), (b'x-request-id', b'req_tuy2fyexpzus6unmwdstg2ulxha4ulzu4t7b4ldhhc7sx3c375ea'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:47 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:47 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:47 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:47 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:47 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:47 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:47 GMT', 'content-type': 'application/json', 'content-length': '1563', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_tuy2fyexpzus6unmwdstg2ulxha4ulzu4t7b4ldhhc7sx3c375ea', 'x-request-id': 'req_tuy2fyexpzus6unmwdstg2ulxha4ulzu4t7b4ldhhc7sx3c375ea', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:47 [openai._base_client] DEBUG: request_id: req_tuy2fyexpzus6unmwdstg2ulxha4ulzu4t7b4ldhhc7sx3c375ea
2026-06-21 03:13:47 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-a000c591-06f2-4922-84fb-be1e07ed25c3', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            too much oily and so less quantity \n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:47 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:47 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:47 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:47 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:47 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:47 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:49 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:49 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2362'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rrs4oxlthfhbfnfstz7jgboe647a53fsbs4cfogyj4grzk5rufya'), (b'x-request-id', b'req_rrs4oxlthfhbfnfstz7jgboe647a53fsbs4cfogyj4grzk5rufya'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:49 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:49 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:49 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:49 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:49 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:49 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:49 GMT', 'content-type': 'application/json', 'content-length': '2362', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rrs4oxlthfhbfnfstz7jgboe647a53fsbs4cfogyj4grzk5rufya', 'x-request-id': 'req_rrs4oxlthfhbfnfstz7jgboe647a53fsbs4cfogyj4grzk5rufya', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:49 [openai._base_client] DEBUG: request_id: req_rrs4oxlthfhbfnfstz7jgboe647a53fsbs4cfogyj4grzk5rufya
2026-06-21 03:13:49 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-34c74498-b51d-4856-9679-fa27c3cae19d', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The food was amazing, hats of to the chef! God bless!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:49 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:49 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:49 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:49 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:49 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:49 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:50 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:50 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2965'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ebryku2smk7edezee6broy664ztlxhcqgqey3se2k7t7drllmp5q'), (b'x-request-id', b'req_ebryku2smk7edezee6broy664ztlxhcqgqey3se2k7t7drllmp5q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:50 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:50 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:50 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:50 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:50 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:50 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:50 GMT', 'content-type': 'application/json', 'content-length': '2965', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ebryku2smk7edezee6broy664ztlxhcqgqey3se2k7t7drllmp5q', 'x-request-id': 'req_ebryku2smk7edezee6broy664ztlxhcqgqey3se2k7t7drllmp5q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:50 [openai._base_client] DEBUG: request_id: req_ebryku2smk7edezee6broy664ztlxhcqgqey3se2k7t7drllmp5q
2026-06-21 03:13:50 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-afee006d-5b57-43f4-9eb8-91903307fd17', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            good food \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:50 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:50 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:50 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:50 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:50 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:50 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:52 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2344'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_opbil6uho66auckejuashyfgm2d4utecqb2lbt5cbolpa6nbdaoq'), (b'x-request-id', b'req_opbil6uho66auckejuashyfgm2d4utecqb2lbt5cbolpa6nbdaoq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:52 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:52 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:52 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:52 GMT', 'content-type': 'application/json', 'content-length': '2344', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_opbil6uho66auckejuashyfgm2d4utecqb2lbt5cbolpa6nbdaoq', 'x-request-id': 'req_opbil6uho66auckejuashyfgm2d4utecqb2lbt5cbolpa6nbdaoq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:52 [openai._base_client] DEBUG: request_id: req_opbil6uho66auckejuashyfgm2d4utecqb2lbt5cbolpa6nbdaoq
2026-06-21 03:13:52 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0a052b52-40f9-412d-b583-b3fcacf315f1', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            it was tasty and delicious \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:52 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:52 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1711'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_4o4w53klx2ehyixpcdboutv2hurq33wpdto2io2dh6bxpbxaojyq'), (b'x-request-id', b'req_4o4w53klx2ehyixpcdboutv2hurq33wpdto2io2dh6bxpbxaojyq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:52 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:52 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:52 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:52 GMT', 'content-type': 'application/json', 'content-length': '1711', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_4o4w53klx2ehyixpcdboutv2hurq33wpdto2io2dh6bxpbxaojyq', 'x-request-id': 'req_4o4w53klx2ehyixpcdboutv2hurq33wpdto2io2dh6bxpbxaojyq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:52 [openai._base_client] DEBUG: request_id: req_4o4w53klx2ehyixpcdboutv2hurq33wpdto2io2dh6bxpbxaojyq
2026-06-21 03:13:52 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-d304cc6f-ed7c-4fac-932c-2d2b94dcf2b3', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            taste is ok quantity was very less for the price was to high \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:52 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:52 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:52 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:55 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:55 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3879'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_sd3drhauf5sfhmgszpdpo3c3ivclt7evk32gcsmbgsyfx6fuwymq'), (b'x-request-id', b'req_sd3drhauf5sfhmgszpdpo3c3ivclt7evk32gcsmbgsyfx6fuwymq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:55 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:55 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:55 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:55 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:55 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:55 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:55 GMT', 'content-type': 'application/json', 'content-length': '3879', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_sd3drhauf5sfhmgszpdpo3c3ivclt7evk32gcsmbgsyfx6fuwymq', 'x-request-id': 'req_sd3drhauf5sfhmgszpdpo3c3ivclt7evk32gcsmbgsyfx6fuwymq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:55 [openai._base_client] DEBUG: request_id: req_sd3drhauf5sfhmgszpdpo3c3ivclt7evk32gcsmbgsyfx6fuwymq
2026-06-21 03:13:55 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-edf96968-0143-4993-8789-9fa280d86ba4', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Very tasty biryani but raita quantity can be increased next time . Only less raita was the issue , I think we pay a good price for the biryani so you can give a good quantity of dahi in raita\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:55 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:55 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:55 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:55 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:55 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:55 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:13:58 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:13:58 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5329'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fghiiwaa27vkrjz7suixwyc25rylhuqebq7sn5ubhkdosc5mfora'), (b'x-request-id', b'req_fghiiwaa27vkrjz7suixwyc25rylhuqebq7sn5ubhkdosc5mfora'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:13:58 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:13:58 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:13:58 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:13:58 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:13:58 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:13:58 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:13:58 GMT', 'content-type': 'application/json', 'content-length': '5329', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fghiiwaa27vkrjz7suixwyc25rylhuqebq7sn5ubhkdosc5mfora', 'x-request-id': 'req_fghiiwaa27vkrjz7suixwyc25rylhuqebq7sn5ubhkdosc5mfora', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:13:58 [openai._base_client] DEBUG: request_id: req_fghiiwaa27vkrjz7suixwyc25rylhuqebq7sn5ubhkdosc5mfora
2026-06-21 03:13:58 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-4f253342-c331-40bc-8fdc-d6f1bc3ee355', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The quantiry for the biryani that cost 400 is not enough even for a single person\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:13:58 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:13:58 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:13:58 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:13:58 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:13:58 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:13:58 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:00 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:00 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3144'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_n5dn64qqatkkyzbx6n52gilldppzk3lwgw22suf6r6z4xrlsbqea'), (b'x-request-id', b'req_n5dn64qqatkkyzbx6n52gilldppzk3lwgw22suf6r6z4xrlsbqea'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:00 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:00 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:00 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:00 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:00 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:00 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:00 GMT', 'content-type': 'application/json', 'content-length': '3144', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_n5dn64qqatkkyzbx6n52gilldppzk3lwgw22suf6r6z4xrlsbqea', 'x-request-id': 'req_n5dn64qqatkkyzbx6n52gilldppzk3lwgw22suf6r6z4xrlsbqea', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:00 [openai._base_client] DEBUG: request_id: req_n5dn64qqatkkyzbx6n52gilldppzk3lwgw22suf6r6z4xrlsbqea
2026-06-21 03:14:00 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fcce2ddb-efb6-4415-b30d-4981bfc64c2f', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Everything is scrumptious. Thank you charcoal eats :)\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:00 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:00 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:00 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:00 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:00 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:00 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:01 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:01 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2506'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2yyaqxx6r4sb3eunzpk7n5jwltgjkbrctsr3hqljbctjexairlna'), (b'x-request-id', b'req_2yyaqxx6r4sb3eunzpk7n5jwltgjkbrctsr3hqljbctjexairlna'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:01 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:01 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:01 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:01 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:01 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:01 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:01 GMT', 'content-type': 'application/json', 'content-length': '2506', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2yyaqxx6r4sb3eunzpk7n5jwltgjkbrctsr3hqljbctjexairlna', 'x-request-id': 'req_2yyaqxx6r4sb3eunzpk7n5jwltgjkbrctsr3hqljbctjexairlna', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:01 [openai._base_client] DEBUG: request_id: req_2yyaqxx6r4sb3eunzpk7n5jwltgjkbrctsr3hqljbctjexairlna
2026-06-21 03:14:01 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b0899359-f130-48dc-8c8d-06dd80cd4e7d', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            i loved it Quite tasty food came within the budget \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:01 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:01 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:01 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:01 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:01 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:01 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2970'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fgi4fd25bzr5h6wjviov3nirbdxzwoqqnnmkua2yjk2f6zwjpefq'), (b'x-request-id', b'req_fgi4fd25bzr5h6wjviov3nirbdxzwoqqnnmkua2yjk2f6zwjpefq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:02 GMT', 'content-type': 'application/json', 'content-length': '2970', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fgi4fd25bzr5h6wjviov3nirbdxzwoqqnnmkua2yjk2f6zwjpefq', 'x-request-id': 'req_fgi4fd25bzr5h6wjviov3nirbdxzwoqqnnmkua2yjk2f6zwjpefq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:02 [openai._base_client] DEBUG: request_id: req_fgi4fd25bzr5h6wjviov3nirbdxzwoqqnnmkua2yjk2f6zwjpefq
2026-06-21 03:14:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8d619a7a-8e68-4f48-84ac-abfcb8cfe300', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            pathetic service and pathetic food. we ordered paneer tikka roll - but we recvd simple paneer cubes wraped in a chapati with lotsa onions and mayonise.. it was tasteless.. there was nothing like a tikka roll in it.. very very expensive, quantity is very very less compared to prices charged. \n\nNOT AT ALL RECOMMENDED !!! \nNegative rating  to the resturant !! \n\nAmit - manager at resturant was also not cooperative and rude. \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:07 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:07 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7540'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_f7d4qnwpy7usalcej4zsejmios33t7viiqvkxh6q5bkq5nrx3kiq'), (b'x-request-id', b'req_f7d4qnwpy7usalcej4zsejmios33t7viiqvkxh6q5bkq5nrx3kiq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:07 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:07 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:07 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:07 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:07 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:07 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:07 GMT', 'content-type': 'application/json', 'content-length': '7540', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_f7d4qnwpy7usalcej4zsejmios33t7viiqvkxh6q5bkq5nrx3kiq', 'x-request-id': 'req_f7d4qnwpy7usalcej4zsejmios33t7viiqvkxh6q5bkq5nrx3kiq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:07 [openai._base_client] DEBUG: request_id: req_f7d4qnwpy7usalcej4zsejmios33t7viiqvkxh6q5bkq5nrx3kiq
2026-06-21 03:14:07 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8700f863-b7b5-4915-babf-b55d06270a82', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The taste was really good, it was warm. I really liked it. \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:07 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:07 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:07 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:07 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:07 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:07 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:08 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:08 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2500'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_vs5xgnt3yl2peywj6taozwl4vogdb24u7jgyrdyinyn6cvxwfr3a'), (b'x-request-id', b'req_vs5xgnt3yl2peywj6taozwl4vogdb24u7jgyrdyinyn6cvxwfr3a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:08 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:08 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:08 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:08 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:08 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:08 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:08 GMT', 'content-type': 'application/json', 'content-length': '2500', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_vs5xgnt3yl2peywj6taozwl4vogdb24u7jgyrdyinyn6cvxwfr3a', 'x-request-id': 'req_vs5xgnt3yl2peywj6taozwl4vogdb24u7jgyrdyinyn6cvxwfr3a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:08 [openai._base_client] DEBUG: request_id: req_vs5xgnt3yl2peywj6taozwl4vogdb24u7jgyrdyinyn6cvxwfr3a
2026-06-21 03:14:08 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-633f05a5-b856-486d-9df2-5be49521e4ed', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            good job \n\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:08 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:08 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:08 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:08 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:08 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:08 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:09 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:09 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1759'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_y4umnpopizn6hpwchuhbefabpcgk2ivsxomeqpnejzvikowuaxaq'), (b'x-request-id', b'req_y4umnpopizn6hpwchuhbefabpcgk2ivsxomeqpnejzvikowuaxaq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:09 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:09 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:09 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:09 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:09 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:09 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:09 GMT', 'content-type': 'application/json', 'content-length': '1759', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_y4umnpopizn6hpwchuhbefabpcgk2ivsxomeqpnejzvikowuaxaq', 'x-request-id': 'req_y4umnpopizn6hpwchuhbefabpcgk2ivsxomeqpnejzvikowuaxaq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:09 [openai._base_client] DEBUG: request_id: req_y4umnpopizn6hpwchuhbefabpcgk2ivsxomeqpnejzvikowuaxaq
2026-06-21 03:14:09 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-976ef8de-68da-4260-b61a-e67230c06cbb', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            taste has gone down too oily \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:09 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:09 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:09 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:09 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:09 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:09 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2501'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ordkn5rwbntd65r44fu54b5ltrcxnogtum6m4gq4ilzddx5yweoq'), (b'x-request-id', b'req_ordkn5rwbntd65r44fu54b5ltrcxnogtum6m4gq4ilzddx5yweoq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:11 GMT', 'content-type': 'application/json', 'content-length': '2501', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ordkn5rwbntd65r44fu54b5ltrcxnogtum6m4gq4ilzddx5yweoq', 'x-request-id': 'req_ordkn5rwbntd65r44fu54b5ltrcxnogtum6m4gq4ilzddx5yweoq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:11 [openai._base_client] DEBUG: request_id: req_ordkn5rwbntd65r44fu54b5ltrcxnogtum6m4gq4ilzddx5yweoq
2026-06-21 03:14:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1fb39d41-d57b-496e-a691-602f1647cc57', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            thank u \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1848'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_nynr772ws2re4o5vdjo7a3lhxpcobwglg3j5uhwwetoxqjo6meea'), (b'x-request-id', b'req_nynr772ws2re4o5vdjo7a3lhxpcobwglg3j5uhwwetoxqjo6meea'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:11 GMT', 'content-type': 'application/json', 'content-length': '1848', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_nynr772ws2re4o5vdjo7a3lhxpcobwglg3j5uhwwetoxqjo6meea', 'x-request-id': 'req_nynr772ws2re4o5vdjo7a3lhxpcobwglg3j5uhwwetoxqjo6meea', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:11 [openai._base_client] DEBUG: request_id: req_nynr772ws2re4o5vdjo7a3lhxpcobwglg3j5uhwwetoxqjo6meea
2026-06-21 03:14:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5805cb27-4b3e-4bd6-96c8-032f5b430bac', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Your muradabadi biryani not even a pinch of that stop making it\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:13 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:13 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2350'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_oifqqc6i7rq3lvxprsua732ctbves2olkggayi7vqvrlge2g7ryq'), (b'x-request-id', b'req_oifqqc6i7rq3lvxprsua732ctbves2olkggayi7vqvrlge2g7ryq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:13 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:13 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:13 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:13 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:13 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:13 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:13 GMT', 'content-type': 'application/json', 'content-length': '2350', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_oifqqc6i7rq3lvxprsua732ctbves2olkggayi7vqvrlge2g7ryq', 'x-request-id': 'req_oifqqc6i7rq3lvxprsua732ctbves2olkggayi7vqvrlge2g7ryq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:13 [openai._base_client] DEBUG: request_id: req_oifqqc6i7rq3lvxprsua732ctbves2olkggayi7vqvrlge2g7ryq
2026-06-21 03:14:13 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fc111e36-2527-4d8f-a38a-3907895b66a6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            very \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:13 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:13 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:13 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:13 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:13 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:13 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:15 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1878'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_llhcv3a5dxo3pqvv2qjyz3nlr3jg6nnsiio4ailq6ib46gl4chza'), (b'x-request-id', b'req_llhcv3a5dxo3pqvv2qjyz3nlr3jg6nnsiio4ailq6ib46gl4chza'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:15 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:15 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:15 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:15 GMT', 'content-type': 'application/json', 'content-length': '1878', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_llhcv3a5dxo3pqvv2qjyz3nlr3jg6nnsiio4ailq6ib46gl4chza', 'x-request-id': 'req_llhcv3a5dxo3pqvv2qjyz3nlr3jg6nnsiio4ailq6ib46gl4chza', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:15 [openai._base_client] DEBUG: request_id: req_llhcv3a5dxo3pqvv2qjyz3nlr3jg6nnsiio4ailq6ib46gl4chza
2026-06-21 03:14:15 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0c461fa9-4740-4a9e-90e0-55bcd7a64900', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            One if the best biryani i had in my life\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:15 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:15 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2608'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_jnoewslxdfsndixtjhkm6l6ujeuwzzth7676sn5j5fdzunzkdkmq'), (b'x-request-id', b'req_jnoewslxdfsndixtjhkm6l6ujeuwzzth7676sn5j5fdzunzkdkmq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:15 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:15 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:15 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:15 GMT', 'content-type': 'application/json', 'content-length': '2608', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_jnoewslxdfsndixtjhkm6l6ujeuwzzth7676sn5j5fdzunzkdkmq', 'x-request-id': 'req_jnoewslxdfsndixtjhkm6l6ujeuwzzth7676sn5j5fdzunzkdkmq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:15 [openai._base_client] DEBUG: request_id: req_jnoewslxdfsndixtjhkm6l6ujeuwzzth7676sn5j5fdzunzkdkmq
2026-06-21 03:14:15 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-88f99d28-48c4-4c72-a2c6-30b698190310', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Very oily\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:15 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:15 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:15 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:17 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:17 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2348'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fspj4cyy4tf54y4zd57gyset2paasgq6duddppuzpn6kbvlfqxkq'), (b'x-request-id', b'req_fspj4cyy4tf54y4zd57gyset2paasgq6duddppuzpn6kbvlfqxkq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:17 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:17 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:17 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:17 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:17 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:17 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:17 GMT', 'content-type': 'application/json', 'content-length': '2348', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fspj4cyy4tf54y4zd57gyset2paasgq6duddppuzpn6kbvlfqxkq', 'x-request-id': 'req_fspj4cyy4tf54y4zd57gyset2paasgq6duddppuzpn6kbvlfqxkq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:17 [openai._base_client] DEBUG: request_id: req_fspj4cyy4tf54y4zd57gyset2paasgq6duddppuzpn6kbvlfqxkq
2026-06-21 03:14:17 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-273e257a-c767-49df-ac0e-7fd7742f59db', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Best biryani till the date ....everything was perfect packaging food and taste was awsome after long time had the best one\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:17 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:17 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:17 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:17 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:17 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:17 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:18 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:18 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3818'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_t4xnz6pvvlpo3c73tjphgwth5wvgax7l7t2bsmwew7z6fkrk4cxa'), (b'x-request-id', b'req_t4xnz6pvvlpo3c73tjphgwth5wvgax7l7t2bsmwew7z6fkrk4cxa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:18 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:18 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:18 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:18 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:18 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:18 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:18 GMT', 'content-type': 'application/json', 'content-length': '3818', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_t4xnz6pvvlpo3c73tjphgwth5wvgax7l7t2bsmwew7z6fkrk4cxa', 'x-request-id': 'req_t4xnz6pvvlpo3c73tjphgwth5wvgax7l7t2bsmwew7z6fkrk4cxa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:18 [openai._base_client] DEBUG: request_id: req_t4xnz6pvvlpo3c73tjphgwth5wvgax7l7t2bsmwew7z6fkrk4cxa
2026-06-21 03:14:18 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-bfac4fe0-2ef8-4a72-962b-935aa9a3af2a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Nice food thanks charcoal eat\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:18 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:18 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:18 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:18 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:18 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:18 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:20 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:20 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2740'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_hngcgev3qxjwxuiptwikiblgod6ob7habojkjcvf5t2vsei3drqq'), (b'x-request-id', b'req_hngcgev3qxjwxuiptwikiblgod6ob7habojkjcvf5t2vsei3drqq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:20 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:20 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:20 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:20 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:20 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:20 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:20 GMT', 'content-type': 'application/json', 'content-length': '2740', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_hngcgev3qxjwxuiptwikiblgod6ob7habojkjcvf5t2vsei3drqq', 'x-request-id': 'req_hngcgev3qxjwxuiptwikiblgod6ob7habojkjcvf5t2vsei3drqq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:20 [openai._base_client] DEBUG: request_id: req_hngcgev3qxjwxuiptwikiblgod6ob7habojkjcvf5t2vsei3drqq
2026-06-21 03:14:20 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9b095c66-e0bc-4678-8347-fd8b076867a4', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            best tasting Egg biryani I had till now. Thank you so much this made my day\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:20 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:20 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:20 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:20 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:20 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:20 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:21 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:21 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1988'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_u6n2p256rq7i5rbrduzjx654zrgfx2e43l6oju7po6oj4cfetuha'), (b'x-request-id', b'req_u6n2p256rq7i5rbrduzjx654zrgfx2e43l6oju7po6oj4cfetuha'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:21 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:21 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:21 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:21 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:21 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:21 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:21 GMT', 'content-type': 'application/json', 'content-length': '1988', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_u6n2p256rq7i5rbrduzjx654zrgfx2e43l6oju7po6oj4cfetuha', 'x-request-id': 'req_u6n2p256rq7i5rbrduzjx654zrgfx2e43l6oju7po6oj4cfetuha', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:21 [openai._base_client] DEBUG: request_id: req_u6n2p256rq7i5rbrduzjx654zrgfx2e43l6oju7po6oj4cfetuha
2026-06-21 03:14:21 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-e3024f53-cfe0-48dd-a4f1-2225a15750bf', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            worst roll ever go and learn how to roll a roll from a street vendor even i dont want a refund this is true feedback to you worst ever roll you think by filling onion only it will workout no never learn you people if you want ti be in this business\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:21 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:21 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:21 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:21 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:21 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:21 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:23 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:23 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3470'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_wfmu7l62jrlbsnlhj336migujwga6tfmdv3dh3sbfewy7fbouj3a'), (b'x-request-id', b'req_wfmu7l62jrlbsnlhj336migujwga6tfmdv3dh3sbfewy7fbouj3a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:23 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:23 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:23 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:23 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:23 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:23 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:23 GMT', 'content-type': 'application/json', 'content-length': '3470', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_wfmu7l62jrlbsnlhj336migujwga6tfmdv3dh3sbfewy7fbouj3a', 'x-request-id': 'req_wfmu7l62jrlbsnlhj336migujwga6tfmdv3dh3sbfewy7fbouj3a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:23 [openai._base_client] DEBUG: request_id: req_wfmu7l62jrlbsnlhj336migujwga6tfmdv3dh3sbfewy7fbouj3a
2026-06-21 03:14:23 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-df8b6010-5d81-4592-9774-2be7f92f4e2e', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I ordered paneer biryani they sent chicken biryani\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:23 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:23 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:23 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:23 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:23 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:23 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:24 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:24 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2747'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_xxvv6w7opnm2zcxjt7sg44ydhnjonevg6zan7q2r7ecz5iaf4qsa'), (b'x-request-id', b'req_xxvv6w7opnm2zcxjt7sg44ydhnjonevg6zan7q2r7ecz5iaf4qsa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:24 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:24 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:24 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:24 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:24 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:24 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:24 GMT', 'content-type': 'application/json', 'content-length': '2747', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_xxvv6w7opnm2zcxjt7sg44ydhnjonevg6zan7q2r7ecz5iaf4qsa', 'x-request-id': 'req_xxvv6w7opnm2zcxjt7sg44ydhnjonevg6zan7q2r7ecz5iaf4qsa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:24 [openai._base_client] DEBUG: request_id: req_xxvv6w7opnm2zcxjt7sg44ydhnjonevg6zan7q2r7ecz5iaf4qsa
2026-06-21 03:14:24 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-df13cae7-3349-4c25-82aa-1de4730a9a83', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Both biryani and dal were stale\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:24 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:24 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:24 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:24 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:24 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:24 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:26 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:26 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3022'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_t7k2sfdop2g76mi2622qrbfsn4pygr4s4i45pfjaq7jsbn6hovuq'), (b'x-request-id', b'req_t7k2sfdop2g76mi2622qrbfsn4pygr4s4i45pfjaq7jsbn6hovuq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:26 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:26 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:26 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:26 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:26 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:26 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:26 GMT', 'content-type': 'application/json', 'content-length': '3022', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_t7k2sfdop2g76mi2622qrbfsn4pygr4s4i45pfjaq7jsbn6hovuq', 'x-request-id': 'req_t7k2sfdop2g76mi2622qrbfsn4pygr4s4i45pfjaq7jsbn6hovuq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:26 [openai._base_client] DEBUG: request_id: req_t7k2sfdop2g76mi2622qrbfsn4pygr4s4i45pfjaq7jsbn6hovuq
2026-06-21 03:14:26 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-3c0cafbf-cd63-4e0f-aa04-c943b14c36fc', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Keema was very less in pulav\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:26 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:26 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:26 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:26 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:26 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:26 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:27 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:27 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2795'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zfppb6mclipc54x5u6y4th3scy74fabrmgz5pjh2hcricojowdtq'), (b'x-request-id', b'req_zfppb6mclipc54x5u6y4th3scy74fabrmgz5pjh2hcricojowdtq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:27 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:27 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:27 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:27 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:27 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:27 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:27 GMT', 'content-type': 'application/json', 'content-length': '2795', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zfppb6mclipc54x5u6y4th3scy74fabrmgz5pjh2hcricojowdtq', 'x-request-id': 'req_zfppb6mclipc54x5u6y4th3scy74fabrmgz5pjh2hcricojowdtq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:27 [openai._base_client] DEBUG: request_id: req_zfppb6mclipc54x5u6y4th3scy74fabrmgz5pjh2hcricojowdtq
2026-06-21 03:14:27 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9e3a0bcc-f290-497e-b5aa-1be9980c05fd', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Delivered wrong order\n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:27 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:27 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:27 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:27 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:27 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:27 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:28 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:28 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2350'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_xvwynmshktvvyc3yvevzbhlawuvjzmyjkz5v6omcungx4snlmwya'), (b'x-request-id', b'req_xvwynmshktvvyc3yvevzbhlawuvjzmyjkz5v6omcungx4snlmwya'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:28 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:28 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:28 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:28 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:28 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:28 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:28 GMT', 'content-type': 'application/json', 'content-length': '2350', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_xvwynmshktvvyc3yvevzbhlawuvjzmyjkz5v6omcungx4snlmwya', 'x-request-id': 'req_xvwynmshktvvyc3yvevzbhlawuvjzmyjkz5v6omcungx4snlmwya', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:28 [openai._base_client] DEBUG: request_id: req_xvwynmshktvvyc3yvevzbhlawuvjzmyjkz5v6omcungx4snlmwya
2026-06-21 03:14:28 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f361f688-9c6a-47c0-8972-b1912947096c', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I ordered chicken dum biryani which the restaurant says comes with 2 pieces of chicken but no chicken was sent only rice, it\'s a fraud they\'re running in the name of food\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:28 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:28 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:28 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:28 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:28 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:28 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:30 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:30 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3521'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_uycn4gl4pwhzrvi7pldvmxvoe2d55inpcttb5elk7xgwparywdpa'), (b'x-request-id', b'req_uycn4gl4pwhzrvi7pldvmxvoe2d55inpcttb5elk7xgwparywdpa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:30 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:30 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:30 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:30 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:30 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:30 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:30 GMT', 'content-type': 'application/json', 'content-length': '3521', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_uycn4gl4pwhzrvi7pldvmxvoe2d55inpcttb5elk7xgwparywdpa', 'x-request-id': 'req_uycn4gl4pwhzrvi7pldvmxvoe2d55inpcttb5elk7xgwparywdpa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:30 [openai._base_client] DEBUG: request_id: req_uycn4gl4pwhzrvi7pldvmxvoe2d55inpcttb5elk7xgwparywdpa
2026-06-21 03:14:30 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-e28d97b3-f922-482a-aa1c-6ff9b84b51ec', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            It always delivers the best quality food. \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:30 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:30 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:30 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:30 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:30 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:30 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:31 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:31 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2519'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_mars7tsbbaaetc6r6wade3d67gmmihfdmpjqtm4btsall4ujdi4q'), (b'x-request-id', b'req_mars7tsbbaaetc6r6wade3d67gmmihfdmpjqtm4btsall4ujdi4q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:31 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:31 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:31 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:31 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:31 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:31 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:31 GMT', 'content-type': 'application/json', 'content-length': '2519', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_mars7tsbbaaetc6r6wade3d67gmmihfdmpjqtm4btsall4ujdi4q', 'x-request-id': 'req_mars7tsbbaaetc6r6wade3d67gmmihfdmpjqtm4btsall4ujdi4q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:31 [openai._base_client] DEBUG: request_id: req_mars7tsbbaaetc6r6wade3d67gmmihfdmpjqtm4btsall4ujdi4q
2026-06-21 03:14:31 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-407483f9-c625-40cb-baae-d888e233b2ba', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            bad\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:31 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:31 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:31 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:31 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:31 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:31 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:33 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:33 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1936'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_srkdd422a57xpy5er7jyqcw7ujvin3czscrt47p4aiuwm2ct7fcq'), (b'x-request-id', b'req_srkdd422a57xpy5er7jyqcw7ujvin3czscrt47p4aiuwm2ct7fcq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:33 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:33 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:33 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:33 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:33 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:33 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:33 GMT', 'content-type': 'application/json', 'content-length': '1936', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_srkdd422a57xpy5er7jyqcw7ujvin3czscrt47p4aiuwm2ct7fcq', 'x-request-id': 'req_srkdd422a57xpy5er7jyqcw7ujvin3czscrt47p4aiuwm2ct7fcq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:33 [openai._base_client] DEBUG: request_id: req_srkdd422a57xpy5er7jyqcw7ujvin3czscrt47p4aiuwm2ct7fcq
2026-06-21 03:14:33 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-89f87d7a-6438-466f-9ec6-5e276a592402', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Good Service \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:33 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:33 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:33 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:33 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:33 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:33 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:35 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:35 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4226'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zvl4ncmokwvox5lnrjfuk3btvnzwzp25sztedet2msqepah5wbha'), (b'x-request-id', b'req_zvl4ncmokwvox5lnrjfuk3btvnzwzp25sztedet2msqepah5wbha'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:35 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:35 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:35 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:35 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:35 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:35 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:35 GMT', 'content-type': 'application/json', 'content-length': '4226', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zvl4ncmokwvox5lnrjfuk3btvnzwzp25sztedet2msqepah5wbha', 'x-request-id': 'req_zvl4ncmokwvox5lnrjfuk3btvnzwzp25sztedet2msqepah5wbha', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:35 [openai._base_client] DEBUG: request_id: req_zvl4ncmokwvox5lnrjfuk3btvnzwzp25sztedet2msqepah5wbha
2026-06-21 03:14:35 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-65d649f2-e970-47d7-8889-672a8489bc71', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            i have not received your item \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:35 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:35 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:35 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:35 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:35 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:35 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:37 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:37 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3419'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_qrl35jco62invavf5ognoljh73qo7myeuwreac5d4w3qymysvajq'), (b'x-request-id', b'req_qrl35jco62invavf5ognoljh73qo7myeuwreac5d4w3qymysvajq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:37 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:37 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:37 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:37 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:37 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:37 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:37 GMT', 'content-type': 'application/json', 'content-length': '3419', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_qrl35jco62invavf5ognoljh73qo7myeuwreac5d4w3qymysvajq', 'x-request-id': 'req_qrl35jco62invavf5ognoljh73qo7myeuwreac5d4w3qymysvajq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:37 [openai._base_client] DEBUG: request_id: req_qrl35jco62invavf5ognoljh73qo7myeuwreac5d4w3qymysvajq
2026-06-21 03:14:37 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-3fa2bbd0-5427-46b6-8602-462991634099', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Lucknowi Chicken Mini Biryani Bowl ka overall experience kaafi premium laga. Chicken juicy aur spicy tha aur uska dum aroma bahut appetizing lag raha tha. Rice soft aur fresh the aur masalon ka balance kaafi delicious tha. Food timely deliver hua aur packaging clean aur secure thi. Quantity filling thi aur quality bhi proper value for money lagi. Lucknowi Chicken Mini Biryani Bowl ka flavor rich aur authentic feel ho raha tha. Will definitely order again because taste aur freshness dono hi outstanding the.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:37 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:37 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:37 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:37 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:37 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:37 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:41 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:41 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6769'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ved7yv2xqpl5ba6eh2kicbrygzpcxk54u74acnc3tbwdnys7mlva'), (b'x-request-id', b'req_ved7yv2xqpl5ba6eh2kicbrygzpcxk54u74acnc3tbwdnys7mlva'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:41 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:41 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:41 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:41 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:41 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:41 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:41 GMT', 'content-type': 'application/json', 'content-length': '6769', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ved7yv2xqpl5ba6eh2kicbrygzpcxk54u74acnc3tbwdnys7mlva', 'x-request-id': 'req_ved7yv2xqpl5ba6eh2kicbrygzpcxk54u74acnc3tbwdnys7mlva', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:41 [openai._base_client] DEBUG: request_id: req_ved7yv2xqpl5ba6eh2kicbrygzpcxk54u74acnc3tbwdnys7mlva
2026-06-21 03:14:41 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ada50d62-3014-4563-aea1-23bfd5994316', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Barely any chicken in biryani\n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:41 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:41 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:41 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:41 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:41 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:41 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:43 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:43 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2540'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_joiuhwg3ywtox5t2q56hnwkkqa7ftorgwzlqkxcjtsm6jtqoh7mq'), (b'x-request-id', b'req_joiuhwg3ywtox5t2q56hnwkkqa7ftorgwzlqkxcjtsm6jtqoh7mq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:43 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:43 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:43 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:43 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:43 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:43 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:43 GMT', 'content-type': 'application/json', 'content-length': '2540', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_joiuhwg3ywtox5t2q56hnwkkqa7ftorgwzlqkxcjtsm6jtqoh7mq', 'x-request-id': 'req_joiuhwg3ywtox5t2q56hnwkkqa7ftorgwzlqkxcjtsm6jtqoh7mq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:43 [openai._base_client] DEBUG: request_id: req_joiuhwg3ywtox5t2q56hnwkkqa7ftorgwzlqkxcjtsm6jtqoh7mq
2026-06-21 03:14:43 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b03e9a0e-0800-4b39-8b0b-4ee72ce0ac8d', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Good packaging. chicken was very soft and juicy. \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:43 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:43 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:43 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:43 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:43 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:43 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:44 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:44 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2720'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_hyroeueqirvzjqmqpkg5vesqwcldhe7ajoghf4r3rojiqcfk3deq'), (b'x-request-id', b'req_hyroeueqirvzjqmqpkg5vesqwcldhe7ajoghf4r3rojiqcfk3deq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:44 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:44 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:44 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:44 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:44 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:44 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:44 GMT', 'content-type': 'application/json', 'content-length': '2720', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_hyroeueqirvzjqmqpkg5vesqwcldhe7ajoghf4r3rojiqcfk3deq', 'x-request-id': 'req_hyroeueqirvzjqmqpkg5vesqwcldhe7ajoghf4r3rojiqcfk3deq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:44 [openai._base_client] DEBUG: request_id: req_hyroeueqirvzjqmqpkg5vesqwcldhe7ajoghf4r3rojiqcfk3deq
2026-06-21 03:14:44 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f1364391-5651-4337-977c-b09a972688fa', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            It was tasty. Recommended!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:44 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:44 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:44 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:44 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:44 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:44 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:45 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:45 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2105'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_eelueuq2nurt4f54jxlazshi3rfiudxm7m6liig5lyzopvkjuoia'), (b'x-request-id', b'req_eelueuq2nurt4f54jxlazshi3rfiudxm7m6liig5lyzopvkjuoia'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:45 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:45 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:45 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:45 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:45 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:45 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:45 GMT', 'content-type': 'application/json', 'content-length': '2105', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_eelueuq2nurt4f54jxlazshi3rfiudxm7m6liig5lyzopvkjuoia', 'x-request-id': 'req_eelueuq2nurt4f54jxlazshi3rfiudxm7m6liig5lyzopvkjuoia', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:45 [openai._base_client] DEBUG: request_id: req_eelueuq2nurt4f54jxlazshi3rfiudxm7m6liig5lyzopvkjuoia
2026-06-21 03:14:45 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-7a4c8201-6fab-4b9f-9550-78d276933c08', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I loved the taste.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:45 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:45 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:45 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:45 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:45 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:45 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:46 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:46 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2174'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_5nswjzx2kqwjs63sornjrx7trasj7be2aoky7v54xkehdjd7pvlq'), (b'x-request-id', b'req_5nswjzx2kqwjs63sornjrx7trasj7be2aoky7v54xkehdjd7pvlq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:46 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:46 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:46 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:46 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:46 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:46 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:46 GMT', 'content-type': 'application/json', 'content-length': '2174', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_5nswjzx2kqwjs63sornjrx7trasj7be2aoky7v54xkehdjd7pvlq', 'x-request-id': 'req_5nswjzx2kqwjs63sornjrx7trasj7be2aoky7v54xkehdjd7pvlq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:46 [openai._base_client] DEBUG: request_id: req_5nswjzx2kqwjs63sornjrx7trasj7be2aoky7v54xkehdjd7pvlq
2026-06-21 03:14:46 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8dccfe7c-36c5-4093-9830-3c74a84ef7bc', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            biryani not good raita good biriyani test is freegy\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:46 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:46 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:46 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:46 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:46 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:46 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:49 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:49 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3419'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_c46nmkfmdinm33hb7gd2onhs7bobpd5d6xrehadlmyj7ypti7idq'), (b'x-request-id', b'req_c46nmkfmdinm33hb7gd2onhs7bobpd5d6xrehadlmyj7ypti7idq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:49 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:49 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:49 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:49 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:49 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:49 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:49 GMT', 'content-type': 'application/json', 'content-length': '3419', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_c46nmkfmdinm33hb7gd2onhs7bobpd5d6xrehadlmyj7ypti7idq', 'x-request-id': 'req_c46nmkfmdinm33hb7gd2onhs7bobpd5d6xrehadlmyj7ypti7idq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:49 [openai._base_client] DEBUG: request_id: req_c46nmkfmdinm33hb7gd2onhs7bobpd5d6xrehadlmyj7ypti7idq
2026-06-21 03:14:49 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-58171d42-dd00-461d-aaf0-6030a4221337', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            quantity too much less does not suffice one person also either price should be less or qty to be increased \n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:49 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:49 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:49 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:49 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:49 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:49 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:52 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:52 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4682'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_gglwgeaxlro7cjrxfilgh4bqxn2d4qrscvt4pdpz26blpdq6wjoa'), (b'x-request-id', b'req_gglwgeaxlro7cjrxfilgh4bqxn2d4qrscvt4pdpz26blpdq6wjoa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:52 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:52 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:52 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:52 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:52 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:52 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:52 GMT', 'content-type': 'application/json', 'content-length': '4682', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_gglwgeaxlro7cjrxfilgh4bqxn2d4qrscvt4pdpz26blpdq6wjoa', 'x-request-id': 'req_gglwgeaxlro7cjrxfilgh4bqxn2d4qrscvt4pdpz26blpdq6wjoa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:52 [openai._base_client] DEBUG: request_id: req_gglwgeaxlro7cjrxfilgh4bqxn2d4qrscvt4pdpz26blpdq6wjoa
2026-06-21 03:14:52 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ce3c779c-d59a-4bd9-8c37-fee6a1f234e8', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Hands down the worst biryani I\'ve ever had.\nIf I could give it zero stars, I would.\n⭐ Food Quality: 0/10\n⭐ Taste: 0/10\n⭐ Quantity for the Price: 0/10\n⭐ Packaging: 5/10\nCompletely disappointing. Poor quality, terrible taste, and the portion size was nowhere near worth the amount paid. Save your money and avoid this place.\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:52 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:52 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:52 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:52 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:52 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:52 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:54 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:54 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3579'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2btyschsgxnhwhsjc27jiauyfnfwiczvzkj5jdzza26dx3tcb57a'), (b'x-request-id', b'req_2btyschsgxnhwhsjc27jiauyfnfwiczvzkj5jdzza26dx3tcb57a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:54 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:54 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:54 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:54 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:54 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:54 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:54 GMT', 'content-type': 'application/json', 'content-length': '3579', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2btyschsgxnhwhsjc27jiauyfnfwiczvzkj5jdzza26dx3tcb57a', 'x-request-id': 'req_2btyschsgxnhwhsjc27jiauyfnfwiczvzkj5jdzza26dx3tcb57a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:54 [openai._base_client] DEBUG: request_id: req_2btyschsgxnhwhsjc27jiauyfnfwiczvzkj5jdzza26dx3tcb57a
2026-06-21 03:14:54 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-97ff96b0-dd9a-4e7b-a311-64d8134c7df6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl was one of the best protein bowls I have ordered online recently. The eggs were juicy, flavorful, and perfectly cooked with authentic spices. The rice paired beautifully with the masala which made the bowl even tastier. Food arrived fresh and hot with secure and professionally packaged wrapping. Portion size was filling and ideal for a proper meal. The freshness, hygiene, and overall quality made the Dum Spicy Egg 2X Protein Mini Bowl feel trustworthy and premium.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:54 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:54 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:54 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:54 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:54 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:54 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:57 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:57 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6483'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_45n4h5x5xrl7tiaglqbw77fdgqb3lf5wp7jyz33szqxq6g7vprpq'), (b'x-request-id', b'req_45n4h5x5xrl7tiaglqbw77fdgqb3lf5wp7jyz33szqxq6g7vprpq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:57 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:57 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:57 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:57 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:57 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:57 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:57 GMT', 'content-type': 'application/json', 'content-length': '6483', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_45n4h5x5xrl7tiaglqbw77fdgqb3lf5wp7jyz33szqxq6g7vprpq', 'x-request-id': 'req_45n4h5x5xrl7tiaglqbw77fdgqb3lf5wp7jyz33szqxq6g7vprpq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:57 [openai._base_client] DEBUG: request_id: req_45n4h5x5xrl7tiaglqbw77fdgqb3lf5wp7jyz33szqxq6g7vprpq
2026-06-21 03:14:57 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-669e0c0f-9741-409d-8966-b5817fb5d464', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Like the sweetness, siftbess and ut was amazing .It arrived hot and fresh . \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:57 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:57 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:57 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:57 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:57 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:57 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:14:58 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:14:58 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3460'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_tnchaliuwncqvlwsq6bgbqq6jsdj4kjfwziwxyvxlh6wdko334vq'), (b'x-request-id', b'req_tnchaliuwncqvlwsq6bgbqq6jsdj4kjfwziwxyvxlh6wdko334vq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:14:58 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:14:58 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:14:58 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:14:58 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:14:58 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:14:58 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:14:58 GMT', 'content-type': 'application/json', 'content-length': '3460', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_tnchaliuwncqvlwsq6bgbqq6jsdj4kjfwziwxyvxlh6wdko334vq', 'x-request-id': 'req_tnchaliuwncqvlwsq6bgbqq6jsdj4kjfwziwxyvxlh6wdko334vq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:14:58 [openai._base_client] DEBUG: request_id: req_tnchaliuwncqvlwsq6bgbqq6jsdj4kjfwziwxyvxlh6wdko334vq
2026-06-21 03:14:58 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1121c9c4-caaf-487e-9fd4-44f5cb868de5', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Thank you disha .. the dum soya chaap biryani is my favourite .. just delicious\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:14:58 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:14:58 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:14:58 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:14:58 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:14:58 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:14:58 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:00 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:00 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2668'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_vc23gwnyft4fqr3h3vbwvmloapxzmpkuvcp4fyj3elbvmfvsjphq'), (b'x-request-id', b'req_vc23gwnyft4fqr3h3vbwvmloapxzmpkuvcp4fyj3elbvmfvsjphq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:00 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:00 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:00 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:00 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:00 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:00 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:00 GMT', 'content-type': 'application/json', 'content-length': '2668', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_vc23gwnyft4fqr3h3vbwvmloapxzmpkuvcp4fyj3elbvmfvsjphq', 'x-request-id': 'req_vc23gwnyft4fqr3h3vbwvmloapxzmpkuvcp4fyj3elbvmfvsjphq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:00 [openai._base_client] DEBUG: request_id: req_vc23gwnyft4fqr3h3vbwvmloapxzmpkuvcp4fyj3elbvmfvsjphq
2026-06-21 03:15:00 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-a92eff72-64ae-4e23-ad53-50442d84e2f2', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The order was late. Very late - we ended up ordering food from a different place that was faster and now have extra food that we\'ll have to give away\n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:00 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:00 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:00 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:00 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:00 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:00 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:01 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:01 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2882'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_stwhch4giwbkh7ptqpkw6ercshjuqe65bl6ear5u56mzddawlm7q'), (b'x-request-id', b'req_stwhch4giwbkh7ptqpkw6ercshjuqe65bl6ear5u56mzddawlm7q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:01 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:01 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:01 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:01 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:01 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:01 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:01 GMT', 'content-type': 'application/json', 'content-length': '2882', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_stwhch4giwbkh7ptqpkw6ercshjuqe65bl6ear5u56mzddawlm7q', 'x-request-id': 'req_stwhch4giwbkh7ptqpkw6ercshjuqe65bl6ear5u56mzddawlm7q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:01 [openai._base_client] DEBUG: request_id: req_stwhch4giwbkh7ptqpkw6ercshjuqe65bl6ear5u56mzddawlm7q
2026-06-21 03:15:01 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f18dd4f4-c79c-497e-b5cb-185e77a86285', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            loved the biryani, quantity could have been more.\n\nbut good taste\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:01 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:01 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:01 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:01 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:03 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:03 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2989'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_5pmkt2ewoonsooklfcnmfrb2kj3ksb2zjwzruoeygzluutiezpiq'), (b'x-request-id', b'req_5pmkt2ewoonsooklfcnmfrb2kj3ksb2zjwzruoeygzluutiezpiq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:03 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:03 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:03 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:03 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:03 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:03 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:03 GMT', 'content-type': 'application/json', 'content-length': '2989', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_5pmkt2ewoonsooklfcnmfrb2kj3ksb2zjwzruoeygzluutiezpiq', 'x-request-id': 'req_5pmkt2ewoonsooklfcnmfrb2kj3ksb2zjwzruoeygzluutiezpiq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:03 [openai._base_client] DEBUG: request_id: req_5pmkt2ewoonsooklfcnmfrb2kj3ksb2zjwzruoeygzluutiezpiq
2026-06-21 03:15:03 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9d533814-9b53-4282-9002-d2d81f6d2cde', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Not up to the mark not even a single piece of chicken they fooled us\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:03 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:03 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:03 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:03 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:03 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:03 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:08 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:08 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2928'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_bnkzmnopijuekgnberixx3lue3zf6cc2qzu2dam7hx5wyolz77fq'), (b'x-request-id', b'req_bnkzmnopijuekgnberixx3lue3zf6cc2qzu2dam7hx5wyolz77fq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:08 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:08 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:08 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:08 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:08 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:08 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:08 GMT', 'content-type': 'application/json', 'content-length': '2928', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_bnkzmnopijuekgnberixx3lue3zf6cc2qzu2dam7hx5wyolz77fq', 'x-request-id': 'req_bnkzmnopijuekgnberixx3lue3zf6cc2qzu2dam7hx5wyolz77fq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:08 [openai._base_client] DEBUG: request_id: req_bnkzmnopijuekgnberixx3lue3zf6cc2qzu2dam7hx5wyolz77fq
2026-06-21 03:15:08 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-35af49b8-9bd4-48a6-9035-8fadf2014e0a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            after applying coupons, this biryani costed me Rs.331, it is no where spending this much for one piece small of chicken and rice.\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:08 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:08 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:08 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:08 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:08 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:08 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:10 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:10 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3457'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_5fft6buzdda4mwssjd27p6ukoi7fr4aqixdayxhknvcvrcho2wba'), (b'x-request-id', b'req_5fft6buzdda4mwssjd27p6ukoi7fr4aqixdayxhknvcvrcho2wba'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:10 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:10 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:10 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:10 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:10 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:10 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:10 GMT', 'content-type': 'application/json', 'content-length': '3457', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_5fft6buzdda4mwssjd27p6ukoi7fr4aqixdayxhknvcvrcho2wba', 'x-request-id': 'req_5fft6buzdda4mwssjd27p6ukoi7fr4aqixdayxhknvcvrcho2wba', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:10 [openai._base_client] DEBUG: request_id: req_5fft6buzdda4mwssjd27p6ukoi7fr4aqixdayxhknvcvrcho2wba
2026-06-21 03:15:10 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-67b5f787-1921-43de-b75c-86887c3ae6e8', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Spicy Chicken Dum Mini Biryani Bowl khane me bahut hi tasty aur satisfying laga. Chicken ka spicy masala aur rice ka dum flavor bahut amazing combination create kar raha tha. Rice aromatic aur fresh the jo overall meal ko aur enjoyable bana rahe the. Food warm deliver hua aur packaging neatly packed aur hygienic thi. Quantity bhi achhi thi aur quality kaafi premium feel hui. Spicy Chicken Dum Mini Biryani Bowl ka freshness level bahut impressive laga aur har bite enjoyable thi. Will definitely order again because overall experience bahut delicious tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:10 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:10 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:10 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:10 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:10 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:10 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:13 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:13 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5740'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_7pecvxszbjqi5macjngenqmzod5eiasn6nieclrhawxndtuo6jga'), (b'x-request-id', b'req_7pecvxszbjqi5macjngenqmzod5eiasn6nieclrhawxndtuo6jga'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:13 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:13 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:13 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:13 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:13 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:13 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:13 GMT', 'content-type': 'application/json', 'content-length': '5740', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_7pecvxszbjqi5macjngenqmzod5eiasn6nieclrhawxndtuo6jga', 'x-request-id': 'req_7pecvxszbjqi5macjngenqmzod5eiasn6nieclrhawxndtuo6jga', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:13 [openai._base_client] DEBUG: request_id: req_7pecvxszbjqi5macjngenqmzod5eiasn6nieclrhawxndtuo6jga
2026-06-21 03:15:13 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8cac1165-a2af-41a0-8f1f-1014a367fd24', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Double Egg Roll ka overall taste bahut hi impressive tha. Eggs juicy aur perfectly seasoned the aur sauces ka flavor bahut authentic lag raha tha. Food fresh aur garam deliver hua jis wajah se experience aur better ho gaya. Packaging neat thi aur quantity kaafi satisfying lagi. Har bite flavorful aur spicy thi jo egg lovers ko definitely pasand aayegi. Double Egg Roll ka masala balance genuinely bahut achha tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:13 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:13 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:13 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:13 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:13 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:13 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:17 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:17 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7218'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_v647thspkrtmdrykrnue7tlygkib3kvswhh25lnh6eys4vtulrpa'), (b'x-request-id', b'req_v647thspkrtmdrykrnue7tlygkib3kvswhh25lnh6eys4vtulrpa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:17 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:17 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:17 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:17 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:17 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:17 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:17 GMT', 'content-type': 'application/json', 'content-length': '7218', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_v647thspkrtmdrykrnue7tlygkib3kvswhh25lnh6eys4vtulrpa', 'x-request-id': 'req_v647thspkrtmdrykrnue7tlygkib3kvswhh25lnh6eys4vtulrpa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:17 [openai._base_client] DEBUG: request_id: req_v647thspkrtmdrykrnue7tlygkib3kvswhh25lnh6eys4vtulrpa
2026-06-21 03:15:17 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-3f290d1c-6d42-4ce4-8c78-2d6832e84f26', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Aaj lunch mein Chicken Keema Roll try kiya aur yaar, ekdum mast tha! Keema itna flavorful tha — spices perfectly balanced aur filling generous thi. Wrap soft tha aur delivery bhi quick aayi. Charcoal Eats ka packaging bhi acha hai, sab intact aaya. Highly recommend karta hoon, ordering again for sure.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:17 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:17 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:17 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:17 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:17 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:17 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:20 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:20 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5129'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_jaqdt5kup3ravlaekmquv6hmkuau4nnat7ja6l5aszs5bl3jytiq'), (b'x-request-id', b'req_jaqdt5kup3ravlaekmquv6hmkuau4nnat7ja6l5aszs5bl3jytiq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:20 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:20 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:20 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:20 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:20 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:20 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:20 GMT', 'content-type': 'application/json', 'content-length': '5129', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_jaqdt5kup3ravlaekmquv6hmkuau4nnat7ja6l5aszs5bl3jytiq', 'x-request-id': 'req_jaqdt5kup3ravlaekmquv6hmkuau4nnat7ja6l5aszs5bl3jytiq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:20 [openai._base_client] DEBUG: request_id: req_jaqdt5kup3ravlaekmquv6hmkuau4nnat7ja6l5aszs5bl3jytiq
2026-06-21 03:15:20 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-652ba342-c7d2-4346-89e6-46eccaca8092', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I truly enjoyed the Charcoal Veg Mini Biryani Bowl because the flavors felt authentic and perfectly balanced. The vegetables were soft, flavorful, and cooked beautifully while the rice remained fluffy and aromatic throughout the meal. Delivery was quick and the food came hot with secure and clean packaging. The freshness of ingredients was clearly noticeable and every bite tasted delicious. Portion size was generous enough for a satisfying meal and the quality felt premium. Charcoal Veg Mini  Biryani Bowl exceeded my expectations with its great taste and presentation. Will definitely order again because it delivered a wonderful restaurant-style biryani experience.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:20 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:20 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:20 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:20 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:20 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:20 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:23 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:23 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7002'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_uzconpwmr4bqpiusvulso7tnkriz7liayumztc66pbnfzclrnt2q'), (b'x-request-id', b'req_uzconpwmr4bqpiusvulso7tnkriz7liayumztc66pbnfzclrnt2q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:23 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:23 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:23 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:23 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:23 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:23 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:23 GMT', 'content-type': 'application/json', 'content-length': '7002', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_uzconpwmr4bqpiusvulso7tnkriz7liayumztc66pbnfzclrnt2q', 'x-request-id': 'req_uzconpwmr4bqpiusvulso7tnkriz7liayumztc66pbnfzclrnt2q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:23 [openai._base_client] DEBUG: request_id: req_uzconpwmr4bqpiusvulso7tnkriz7liayumztc66pbnfzclrnt2q
2026-06-21 03:15:23 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5cf1bb61-7524-4300-9e57-c3da70ebd763', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            the freshness and hot temperature of the roll was such that it made me feel like I was eating right over there in the outlet \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:23 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:23 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:23 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:23 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:23 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:23 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:25 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:25 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2800'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_gjoosrp6hbxuleqzpvkw2z2yd5mknozq2mjte4g466bjxhh2mt2a'), (b'x-request-id', b'req_gjoosrp6hbxuleqzpvkw2z2yd5mknozq2mjte4g466bjxhh2mt2a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:25 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:25 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:25 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:25 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:25 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:25 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:25 GMT', 'content-type': 'application/json', 'content-length': '2800', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_gjoosrp6hbxuleqzpvkw2z2yd5mknozq2mjte4g466bjxhh2mt2a', 'x-request-id': 'req_gjoosrp6hbxuleqzpvkw2z2yd5mknozq2mjte4g466bjxhh2mt2a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:25 [openai._base_client] DEBUG: request_id: req_gjoosrp6hbxuleqzpvkw2z2yd5mknozq2mjte4g466bjxhh2mt2a
2026-06-21 03:15:25 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6aad03e0-dc24-45b2-9d02-66e1b2562888', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            A small cup for 349 bucks.....fraudsters \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:25 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:25 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:25 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:25 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:25 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:25 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:26 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:26 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2566'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_s7jgsk3wogzmco3c2ypb6prlijcymmhntfzjybaqdly3qyrzphkq'), (b'x-request-id', b'req_s7jgsk3wogzmco3c2ypb6prlijcymmhntfzjybaqdly3qyrzphkq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:26 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:26 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:26 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:26 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:26 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:26 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:26 GMT', 'content-type': 'application/json', 'content-length': '2566', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_s7jgsk3wogzmco3c2ypb6prlijcymmhntfzjybaqdly3qyrzphkq', 'x-request-id': 'req_s7jgsk3wogzmco3c2ypb6prlijcymmhntfzjybaqdly3qyrzphkq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:26 [openai._base_client] DEBUG: request_id: req_s7jgsk3wogzmco3c2ypb6prlijcymmhntfzjybaqdly3qyrzphkq
2026-06-21 03:15:26 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-797e9a4d-3e5e-4856-b3b1-09ebf52aef24', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Charcoal Veg Mini Biryani Bowl ka flavor honestly bahut hi rich aur tasty tha. Vegetables perfectly seasoned the aur rice me proper biryani masalon ka authentic taste aa raha tha. Food fresh aur warm tha jis wajah se overall experience aur enjoyable ho gaya. Packaging secure aur hygienic thi jo quality ko aur premium bana rahi thi. Portion size filling thi aur meal proper value for money laga. Charcoal Veg Mini Biryani Bowl ka authentic restaurant style taste bahut impressive laga. \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:26 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:26 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:26 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:26 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:26 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:26 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:29 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:29 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5976'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_w5ddzas2umzdijksmcvdir6fjmgkivvxymosjtqptwmumrsjk4ka'), (b'x-request-id', b'req_w5ddzas2umzdijksmcvdir6fjmgkivvxymosjtqptwmumrsjk4ka'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:29 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:29 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:29 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:29 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:29 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:29 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:29 GMT', 'content-type': 'application/json', 'content-length': '5976', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_w5ddzas2umzdijksmcvdir6fjmgkivvxymosjtqptwmumrsjk4ka', 'x-request-id': 'req_w5ddzas2umzdijksmcvdir6fjmgkivvxymosjtqptwmumrsjk4ka', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:29 [openai._base_client] DEBUG: request_id: req_w5ddzas2umzdijksmcvdir6fjmgkivvxymosjtqptwmumrsjk4ka
2026-06-21 03:15:29 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b52c89f3-8e95-469f-b908-fc3d426f0cf7', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Spicy Veg Dum Biryani Bowl had an amazing spicy aroma and authentic flavor that felt very satisfying. The vegetables were juicy, flavorful, and cooked beautifully with balanced spices. The rice stayed fluffy and fresh till the last bite which made the meal even more enjoyable. Food arrived hot with secure clean packaging that maintained hygiene properly. Portion size was filling and ideal for one complete meal. Spicy Veg Dum Biryani Bowl impressed me with its freshness and restaurant style taste. Will definitely order again because the flavor was truly memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:29 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:29 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:29 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:29 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:29 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:29 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:32 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:32 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5772'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_f5g25zzvvwki55wjhmqe7yyrsiimnlbff2t36tyxqxg2amwbhuaa'), (b'x-request-id', b'req_f5g25zzvvwki55wjhmqe7yyrsiimnlbff2t36tyxqxg2amwbhuaa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:32 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:32 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:32 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:32 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:32 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:32 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:32 GMT', 'content-type': 'application/json', 'content-length': '5772', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_f5g25zzvvwki55wjhmqe7yyrsiimnlbff2t36tyxqxg2amwbhuaa', 'x-request-id': 'req_f5g25zzvvwki55wjhmqe7yyrsiimnlbff2t36tyxqxg2amwbhuaa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:32 [openai._base_client] DEBUG: request_id: req_f5g25zzvvwki55wjhmqe7yyrsiimnlbff2t36tyxqxg2amwbhuaa
2026-06-21 03:15:32 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5958da46-da41-445a-b335-b45b7353cf42', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Chicken Seekh Roll ka flavor honestly bahut hi rich aur tasty tha. Chicken perfectly seasoned tha aur wrap ke saath uska combination bahut delicious lag raha tha. Food fresh aur warm tha jis wajah se overall experience aur enjoyable ho gaya. Packaging secure aur hygienic thi jo quality ko aur premium bana rahi thi. Portion size filling thi aur meal proper value for money laga. Chicken Seekh Roll ka authentic restaurant style taste bahut impressive laga. Will definitely order again because freshness, taste, aur quality tino hi top class the.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:32 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:32 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:32 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:32 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:32 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:32 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:36 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:36 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7204'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_yugy2ectaa54mfaeyww732cmdpegihhk524wzydsgasiy6c25c3a'), (b'x-request-id', b'req_yugy2ectaa54mfaeyww732cmdpegihhk524wzydsgasiy6c25c3a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:36 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:36 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:36 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:36 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:36 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:36 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:36 GMT', 'content-type': 'application/json', 'content-length': '7204', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_yugy2ectaa54mfaeyww732cmdpegihhk524wzydsgasiy6c25c3a', 'x-request-id': 'req_yugy2ectaa54mfaeyww732cmdpegihhk524wzydsgasiy6c25c3a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:36 [openai._base_client] DEBUG: request_id: req_yugy2ectaa54mfaeyww732cmdpegihhk524wzydsgasiy6c25c3a
2026-06-21 03:15:36 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1b9d4162-c037-46d6-9174-c306c9226669', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            it was around 300 gm whereas the order was for 600 gm\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:36 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:36 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:36 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:36 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:36 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:36 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:38 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:38 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3622'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_34mcmtb3mrtigcwdk2hi6she4amn3avdkrnchpdobkvvcz24sgfa'), (b'x-request-id', b'req_34mcmtb3mrtigcwdk2hi6she4amn3avdkrnchpdobkvvcz24sgfa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:38 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:38 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:38 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:38 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:38 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:38 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:38 GMT', 'content-type': 'application/json', 'content-length': '3622', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_34mcmtb3mrtigcwdk2hi6she4amn3avdkrnchpdobkvvcz24sgfa', 'x-request-id': 'req_34mcmtb3mrtigcwdk2hi6she4amn3avdkrnchpdobkvvcz24sgfa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:38 [openai._base_client] DEBUG: request_id: req_34mcmtb3mrtigcwdk2hi6she4amn3avdkrnchpdobkvvcz24sgfa
2026-06-21 03:15:38 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-30fb3fc6-2276-4e33-a3dd-22c8b1bf90aa', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            the image and size doesn\'t match at all. \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:38 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:38 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:38 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:38 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:38 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:38 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:40 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:40 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2632'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_eytd3627hcds77a2fbnqiipc4abej25tgfk7mdkdvcnk2puwxhjq'), (b'x-request-id', b'req_eytd3627hcds77a2fbnqiipc4abej25tgfk7mdkdvcnk2puwxhjq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:40 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:40 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:40 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:40 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:40 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:40 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:40 GMT', 'content-type': 'application/json', 'content-length': '2632', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_eytd3627hcds77a2fbnqiipc4abej25tgfk7mdkdvcnk2puwxhjq', 'x-request-id': 'req_eytd3627hcds77a2fbnqiipc4abej25tgfk7mdkdvcnk2puwxhjq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:40 [openai._base_client] DEBUG: request_id: req_eytd3627hcds77a2fbnqiipc4abej25tgfk7mdkdvcnk2puwxhjq
2026-06-21 03:15:40 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ecb88d75-9773-47cf-b681-87ff3a950d7b', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Gulab Jamun delivered a perfect traditional dessert experience with impressive quality. The jamuns were tender, flavorful, and soaked beautifully in rich syrup that enhanced the overall taste. Food arrived fresh and was well packaged in a hygienic container that preserved quality perfectly. Every bite felt balanced and satisfying because the sweetness level was managed very well. Portion size was ideal and worth the money spent. Gulab Jamun impressed me with its freshness and authentic flavor. Will definitely order again because every bite felt delightful and comforting.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:40 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:40 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:40 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:40 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:40 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:40 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:44 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:44 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7145'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_lnk6wjgcu7iw3iitboi46qrlfg53wj5cguwrhpboa2ukk3s3k5ua'), (b'x-request-id', b'req_lnk6wjgcu7iw3iitboi46qrlfg53wj5cguwrhpboa2ukk3s3k5ua'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:44 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:44 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:44 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:44 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:44 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:44 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:44 GMT', 'content-type': 'application/json', 'content-length': '7145', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_lnk6wjgcu7iw3iitboi46qrlfg53wj5cguwrhpboa2ukk3s3k5ua', 'x-request-id': 'req_lnk6wjgcu7iw3iitboi46qrlfg53wj5cguwrhpboa2ukk3s3k5ua', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:44 [openai._base_client] DEBUG: request_id: req_lnk6wjgcu7iw3iitboi46qrlfg53wj5cguwrhpboa2ukk3s3k5ua
2026-06-21 03:15:44 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ed3571d1-c11f-4019-ac8b-690b474fbf00', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Paneer 2X Protein Mini Bowl tasted absolutely delicious and had a rich spicy aroma that instantly made it more appetizing. The paneer pieces were soft, fresh, and perfectly cooked with flavorful spices that blended beautifully with the aromatic rice. The extra protein portion made the bowl more satisfying and filling while maintaining great taste in every bite. Food arrived hot and fresh with clean packaging that maintained quality exceptionally well. The meal felt hygienic, professionally packaged, and offered excellent value for money. Portion size was generous and perfect for a complete meal. Dum Spicy Paneer 2X Protein Mini Bowl impressed me with its freshness, premium quality, and bold flavor. Will definitely order again because the taste was genuinely unforgettable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:44 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:44 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:44 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:44 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:44 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:44 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:49 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:49 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'8716'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_wfiidiotsvklpxpmrw3gfqzpswyiaesa7tu6kxs67ck2wxnwgwwa'), (b'x-request-id', b'req_wfiidiotsvklpxpmrw3gfqzpswyiaesa7tu6kxs67ck2wxnwgwwa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:49 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:49 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:49 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:49 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:49 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:49 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:49 GMT', 'content-type': 'application/json', 'content-length': '8716', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_wfiidiotsvklpxpmrw3gfqzpswyiaesa7tu6kxs67ck2wxnwgwwa', 'x-request-id': 'req_wfiidiotsvklpxpmrw3gfqzpswyiaesa7tu6kxs67ck2wxnwgwwa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:49 [openai._base_client] DEBUG: request_id: req_wfiidiotsvklpxpmrw3gfqzpswyiaesa7tu6kxs67ck2wxnwgwwa
2026-06-21 03:15:49 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-dac8f0d7-dbae-4a81-a2f3-c4e975c947f7', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            the food and the portion of the meal was good...and it was tasty\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:49 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:49 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:49 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:49 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:49 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:49 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:51 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:51 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3211'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_vkzmtdjholnhvezvmietrmgarzbqrbean56dd3ehxqdw65onlz7a'), (b'x-request-id', b'req_vkzmtdjholnhvezvmietrmgarzbqrbean56dd3ehxqdw65onlz7a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:51 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:51 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:51 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:51 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:51 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:51 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:51 GMT', 'content-type': 'application/json', 'content-length': '3211', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_vkzmtdjholnhvezvmietrmgarzbqrbean56dd3ehxqdw65onlz7a', 'x-request-id': 'req_vkzmtdjholnhvezvmietrmgarzbqrbean56dd3ehxqdw65onlz7a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:51 [openai._base_client] DEBUG: request_id: req_vkzmtdjholnhvezvmietrmgarzbqrbean56dd3ehxqdw65onlz7a
2026-06-21 03:15:51 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5b2daef0-15c0-4d26-b068-31d24c527755', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The taste is so so, but the portion is very small\nfirst time experience is not so good \n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:51 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:51 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:51 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:51 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:51 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:51 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:53 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:53 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3769'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_aus72d4p4a5nssmtpq5j5uhw6vxsfqe3qwoliud4nsfyhsemkosa'), (b'x-request-id', b'req_aus72d4p4a5nssmtpq5j5uhw6vxsfqe3qwoliud4nsfyhsemkosa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:53 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:53 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:53 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:53 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:53 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:53 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:53 GMT', 'content-type': 'application/json', 'content-length': '3769', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_aus72d4p4a5nssmtpq5j5uhw6vxsfqe3qwoliud4nsfyhsemkosa', 'x-request-id': 'req_aus72d4p4a5nssmtpq5j5uhw6vxsfqe3qwoliud4nsfyhsemkosa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:53 [openai._base_client] DEBUG: request_id: req_aus72d4p4a5nssmtpq5j5uhw6vxsfqe3qwoliud4nsfyhsemkosa
2026-06-21 03:15:53 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-89b966ac-3f11-4620-b159-ee7fd5547206', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Maine Spicy Veg Dum Biryani Bowl order kiya tha aur genuinely bahut pasand aaya. Rice perfectly cooked the aur unka spicy dum aroma bahut delicious lag raha tha. Vegetables soft aur flavorful the jo biryani ke saath bahut amazing combination bana rahe the. Delivery timely hui aur food warm condition me mila jis wajah se freshness properly maintain thi. Packaging hygienic aur professionally packed thi jo kaafi premium feel ho rahi thi. Portion size satisfying tha aur quality bhi impressive lagi. Will definitely order again because Spicy Veg Dum Biryani Bowl ka taste kaafi memorable tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:53 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:53 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:53 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:53 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:53 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:53 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:15:56 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:15:56 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6180'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_reredfrmispy2c7twrvaitayhjjhwrgn3up425c25c7shlj6r3vq'), (b'x-request-id', b'req_reredfrmispy2c7twrvaitayhjjhwrgn3up425c25c7shlj6r3vq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:15:56 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:15:56 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:15:56 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:15:56 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:15:56 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:15:56 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:15:56 GMT', 'content-type': 'application/json', 'content-length': '6180', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_reredfrmispy2c7twrvaitayhjjhwrgn3up425c25c7shlj6r3vq', 'x-request-id': 'req_reredfrmispy2c7twrvaitayhjjhwrgn3up425c25c7shlj6r3vq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:15:56 [openai._base_client] DEBUG: request_id: req_reredfrmispy2c7twrvaitayhjjhwrgn3up425c25c7shlj6r3vq
2026-06-21 03:15:56 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9d5247c9-3d89-4c21-897c-6bff76dce87a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Veg Galouti Roll khane me bahut hi tasty aur satisfying laga. Stuffing ka texture soft tha aur uska flavor bahut rich aur delicious tha. Roll fresh tha aur sauces ne overall taste ko aur enhance kar diya. Food warm deliver hua aur packaging neatly packed aur hygienic thi. Quantity achhi thi aur quality bhi kaafi premium feel hui. Freshness aur authentic taste ne meal ko aur enjoyable bana diya. Veg Galouti Roll ne expectations se better performance diya. Will definitely order again because iska taste kaafi unique aur memorable laga.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:15:56 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:15:56 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:15:56 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:15:56 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:15:56 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:15:56 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:01 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:01 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7937'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_cvsdel2e45uoutegeszqmm4vuf5qasc73ke7pdpwgxfp6ehkyawq'), (b'x-request-id', b'req_cvsdel2e45uoutegeszqmm4vuf5qasc73ke7pdpwgxfp6ehkyawq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:01 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:01 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:01 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:01 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:01 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:01 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:01 GMT', 'content-type': 'application/json', 'content-length': '7937', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_cvsdel2e45uoutegeszqmm4vuf5qasc73ke7pdpwgxfp6ehkyawq', 'x-request-id': 'req_cvsdel2e45uoutegeszqmm4vuf5qasc73ke7pdpwgxfp6ehkyawq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:01 [openai._base_client] DEBUG: request_id: req_cvsdel2e45uoutegeszqmm4vuf5qasc73ke7pdpwgxfp6ehkyawq
2026-06-21 03:16:01 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-657e0a6c-2c09-4486-aebd-c5acfdfe7955', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Maine Charcoal Chicken Mini Biryani Bowl order kiya tha aur experience bahut hi achha raha. Chicken juicy aur perfectly cooked tha aur uska flavor bahut authentic lag raha tha. Rice fluffy aur flavorful the jo dum masalon ke saath bahut delicious combination bana rahe the. Food timely delivered hua aur warm condition me mila jis wajah se freshness bilkul maintain thi. Packaging hygienic aur professionally packaged thi jo kaafi premium feel de rahi thi. Portion size satisfying tha aur quality bhi impressive lagi. Will definitely order again because Charcoal Chicken Mini Biryani Bowl ka taste kaafi memorable tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:01 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:01 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:01 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:01 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:01 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:01 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:05 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:05 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7382'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fq3rejhf5erhqrsdvzjhewkyqbwtnmtxptkniyu5ucp3gargtbla'), (b'x-request-id', b'req_fq3rejhf5erhqrsdvzjhewkyqbwtnmtxptkniyu5ucp3gargtbla'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:05 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:05 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:05 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:05 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:05 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:05 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:05 GMT', 'content-type': 'application/json', 'content-length': '7382', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fq3rejhf5erhqrsdvzjhewkyqbwtnmtxptkniyu5ucp3gargtbla', 'x-request-id': 'req_fq3rejhf5erhqrsdvzjhewkyqbwtnmtxptkniyu5ucp3gargtbla', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:05 [openai._base_client] DEBUG: request_id: req_fq3rejhf5erhqrsdvzjhewkyqbwtnmtxptkniyu5ucp3gargtbla
2026-06-21 03:16:05 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c1e940f5-ea24-4c65-8125-9926be1cbca0', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            200 free karo khana ka free mein order\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:05 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:05 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:05 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:05 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:05 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:05 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:07 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3022'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_bgvohdtzpfl3eqo7l3iav64vcke4f4mrzdef7nqgaxruycrvwqlq'), (b'x-request-id', b'req_bgvohdtzpfl3eqo7l3iav64vcke4f4mrzdef7nqgaxruycrvwqlq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:07 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:07 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:07 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:07 GMT', 'content-type': 'application/json', 'content-length': '3022', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_bgvohdtzpfl3eqo7l3iav64vcke4f4mrzdef7nqgaxruycrvwqlq', 'x-request-id': 'req_bgvohdtzpfl3eqo7l3iav64vcke4f4mrzdef7nqgaxruycrvwqlq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:07 [openai._base_client] DEBUG: request_id: req_bgvohdtzpfl3eqo7l3iav64vcke4f4mrzdef7nqgaxruycrvwqlq
2026-06-21 03:16:07 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6d4e5cf2-118a-46fa-bae3-baf3692cc2cc', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            awesome teast \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:07 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:07 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2078'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_jatgwcjrxcahzcatp2tlrn43xa4dudva2yzzz34u5sdejpxve7aq'), (b'x-request-id', b'req_jatgwcjrxcahzcatp2tlrn43xa4dudva2yzzz34u5sdejpxve7aq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:07 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:07 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:07 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:07 GMT', 'content-type': 'application/json', 'content-length': '2078', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_jatgwcjrxcahzcatp2tlrn43xa4dudva2yzzz34u5sdejpxve7aq', 'x-request-id': 'req_jatgwcjrxcahzcatp2tlrn43xa4dudva2yzzz34u5sdejpxve7aq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:07 [openai._base_client] DEBUG: request_id: req_jatgwcjrxcahzcatp2tlrn43xa4dudva2yzzz34u5sdejpxve7aq
2026-06-21 03:16:07 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ee60b268-54f2-465d-a1c1-9b04dd0955ed', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl was one of the best protein bowls I have ordered online recently. The eggs were juicy, flavorful, and perfectly cooked with authentic spices. The rice paired beautifully with the masala which made the bowl even tastier. Food arrived fresh and hot with secure and professionally packaged wrapping. Portion size was filling and ideal for a proper meal. The freshness, hygiene, and overall quality made the Dum Spicy Egg 2X Protein Mini Bowl feel trustworthy and premium.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:07 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:07 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:07 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6038'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kyfhu3miae2rj5spcgbv4zixaozdp4bx44n25fcrfuzhr5dnmmoq'), (b'x-request-id', b'req_kyfhu3miae2rj5spcgbv4zixaozdp4bx44n25fcrfuzhr5dnmmoq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:11 GMT', 'content-type': 'application/json', 'content-length': '6038', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kyfhu3miae2rj5spcgbv4zixaozdp4bx44n25fcrfuzhr5dnmmoq', 'x-request-id': 'req_kyfhu3miae2rj5spcgbv4zixaozdp4bx44n25fcrfuzhr5dnmmoq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:11 [openai._base_client] DEBUG: request_id: req_kyfhu3miae2rj5spcgbv4zixaozdp4bx44n25fcrfuzhr5dnmmoq
2026-06-21 03:16:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-be8a3d8f-a6fc-40db-866e-768810ab8855', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            too yummy to resist \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1782'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_spd2ofabmfznqzf4l2vvlcowofsyp65n3ltlvqyjseh5rrhkbuda'), (b'x-request-id', b'req_spd2ofabmfznqzf4l2vvlcowofsyp65n3ltlvqyjseh5rrhkbuda'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:11 GMT', 'content-type': 'application/json', 'content-length': '1782', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_spd2ofabmfznqzf4l2vvlcowofsyp65n3ltlvqyjseh5rrhkbuda', 'x-request-id': 'req_spd2ofabmfznqzf4l2vvlcowofsyp65n3ltlvqyjseh5rrhkbuda', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:11 [openai._base_client] DEBUG: request_id: req_spd2ofabmfznqzf4l2vvlcowofsyp65n3ltlvqyjseh5rrhkbuda
2026-06-21 03:16:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ec10a5f1-4e02-4c88-8ecc-124a9e7ad390', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Superb Biryani Very Good Home Very big fan of your biryani Superb taste\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:13 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:13 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2566'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_djvrk6vv5yrhi645qhe5zzmzocovjzp7xbh5fab7g547i7ge4zjq'), (b'x-request-id', b'req_djvrk6vv5yrhi645qhe5zzmzocovjzp7xbh5fab7g547i7ge4zjq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:13 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:13 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:13 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:13 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:13 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:13 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:13 GMT', 'content-type': 'application/json', 'content-length': '2566', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_djvrk6vv5yrhi645qhe5zzmzocovjzp7xbh5fab7g547i7ge4zjq', 'x-request-id': 'req_djvrk6vv5yrhi645qhe5zzmzocovjzp7xbh5fab7g547i7ge4zjq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:13 [openai._base_client] DEBUG: request_id: req_djvrk6vv5yrhi645qhe5zzmzocovjzp7xbh5fab7g547i7ge4zjq
2026-06-21 03:16:13 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ca15aa04-7313-4dcb-8419-c47bf85290e5', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The biryani was top notch and more importantly the raita surprisingly was even delicious. I haven\'t eaten a tastier raita than this ever outside. Excellent it was overall \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:13 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:13 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:13 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:13 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:13 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:13 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:14 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:14 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2958'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_n4lvcnky6san5qodje7yosirf6mct4zbd7ejkcze2ldbblhjskfq'), (b'x-request-id', b'req_n4lvcnky6san5qodje7yosirf6mct4zbd7ejkcze2ldbblhjskfq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:14 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:14 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:14 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:14 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:14 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:14 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:14 GMT', 'content-type': 'application/json', 'content-length': '2958', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_n4lvcnky6san5qodje7yosirf6mct4zbd7ejkcze2ldbblhjskfq', 'x-request-id': 'req_n4lvcnky6san5qodje7yosirf6mct4zbd7ejkcze2ldbblhjskfq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:14 [openai._base_client] DEBUG: request_id: req_n4lvcnky6san5qodje7yosirf6mct4zbd7ejkcze2ldbblhjskfq
2026-06-21 03:16:14 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-04dbb914-6ebd-4ab4-97d0-475f3fe83aac', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Very bad food, if I had the chance would\'ve given 0 stars \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:14 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:14 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:14 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:14 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:14 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:14 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:16 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:16 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2989'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_t2ekhclwc3aaqulghxuu3hzyskw3hbfh6e77upzgtk3itwrzd3ia'), (b'x-request-id', b'req_t2ekhclwc3aaqulghxuu3hzyskw3hbfh6e77upzgtk3itwrzd3ia'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:16 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:16 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:16 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:16 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:16 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:16 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:16 GMT', 'content-type': 'application/json', 'content-length': '2989', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_t2ekhclwc3aaqulghxuu3hzyskw3hbfh6e77upzgtk3itwrzd3ia', 'x-request-id': 'req_t2ekhclwc3aaqulghxuu3hzyskw3hbfh6e77upzgtk3itwrzd3ia', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:16 [openai._base_client] DEBUG: request_id: req_t2ekhclwc3aaqulghxuu3hzyskw3hbfh6e77upzgtk3itwrzd3ia
2026-06-21 03:16:16 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-86d50364-c0ef-40c6-aa42-1555aee53895', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            not at all biryani test, just masala rice \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:16 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:16 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:16 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:16 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:16 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:16 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:18 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:18 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3134'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_jevyemnehj7pgzrxa7whyicaa2hv42bqw764c2sl4tvae7d6y7bq'), (b'x-request-id', b'req_jevyemnehj7pgzrxa7whyicaa2hv42bqw764c2sl4tvae7d6y7bq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:18 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:18 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:18 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:18 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:18 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:18 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:18 GMT', 'content-type': 'application/json', 'content-length': '3134', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_jevyemnehj7pgzrxa7whyicaa2hv42bqw764c2sl4tvae7d6y7bq', 'x-request-id': 'req_jevyemnehj7pgzrxa7whyicaa2hv42bqw764c2sl4tvae7d6y7bq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:18 [openai._base_client] DEBUG: request_id: req_jevyemnehj7pgzrxa7whyicaa2hv42bqw764c2sl4tvae7d6y7bq
2026-06-21 03:16:18 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-3f4a8df5-c048-452d-ac43-763ea7fe86d9', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Very late delivery\n                            Customer Rating:\n                            2 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:18 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:18 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:18 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:18 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:18 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:18 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:19 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:19 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2064'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_iecbpj63ioi7eqqppy67mgknczheaxar7vaipnmbhnhmbh46g7na'), (b'x-request-id', b'req_iecbpj63ioi7eqqppy67mgknczheaxar7vaipnmbhnhmbh46g7na'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:19 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:19 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:19 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:19 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:19 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:19 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:19 GMT', 'content-type': 'application/json', 'content-length': '2064', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_iecbpj63ioi7eqqppy67mgknczheaxar7vaipnmbhnhmbh46g7na', 'x-request-id': 'req_iecbpj63ioi7eqqppy67mgknczheaxar7vaipnmbhnhmbh46g7na', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:19 [openai._base_client] DEBUG: request_id: req_iecbpj63ioi7eqqppy67mgknczheaxar7vaipnmbhnhmbh46g7na
2026-06-21 03:16:19 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-46e5bd5c-6466-4472-b2c2-13775e021ea6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl ka taste bahut hi amazing tha aur pura bowl fresh aur flavorful laga. Eggs perfectly well cooked the aur masalon ka spicy flavor bahut tasty lag raha tha. Rice soft aur aromatic the jo bowl ko aur satisfying bana rahe the. Food came hot aur timely delivered hua jis wajah se experience aur better ho gaya. Packaging clean aur professionally packaged thi jo quality aur trust dono show kar rahi thi. Quantity bhi kaafi satisfying thi aur proper value for money feel hua.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:19 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:19 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:19 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:19 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:19 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:19 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:22 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:22 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7316'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_yolx2fb7uuuaeet4j24e664d3jkdj6wsv764blpjor36iq3dsuka'), (b'x-request-id', b'req_yolx2fb7uuuaeet4j24e664d3jkdj6wsv764blpjor36iq3dsuka'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:22 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:22 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:22 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:22 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:22 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:22 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:22 GMT', 'content-type': 'application/json', 'content-length': '7316', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_yolx2fb7uuuaeet4j24e664d3jkdj6wsv764blpjor36iq3dsuka', 'x-request-id': 'req_yolx2fb7uuuaeet4j24e664d3jkdj6wsv764blpjor36iq3dsuka', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:22 [openai._base_client] DEBUG: request_id: req_yolx2fb7uuuaeet4j24e664d3jkdj6wsv764blpjor36iq3dsuka
2026-06-21 03:16:22 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-869bf5c2-2fa7-47fa-bd55-70cb62d06a09', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I genuinely loved the Charcoal Chicken Mini Biryani Bowl because the flavor felt authentic and perfectly balanced. The chicken was soft, juicy, and cooked beautifully while the rice remained fluffy and aromatic till the last bite. Delivery was timely and the food came hot with secure hygienic packaging. The freshness of ingredients was clearly noticeable and every spoon felt satisfying. Portion size was decent and suitable for a complete meal.  Charcoal Chicken Mini Biryani Bowl exceeded expectations in quality and presentation. Will definitely order again because the taste was rich, comforting, and truly enjoyable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:22 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:22 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:22 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:22 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:22 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:22 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:26 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:26 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6730'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_oxpzz4suwdpv75pkudlow5exa3bqr6nhmzgkhtmwcux46ewwojjq'), (b'x-request-id', b'req_oxpzz4suwdpv75pkudlow5exa3bqr6nhmzgkhtmwcux46ewwojjq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:26 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:26 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:26 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:26 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:26 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:26 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:26 GMT', 'content-type': 'application/json', 'content-length': '6730', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_oxpzz4suwdpv75pkudlow5exa3bqr6nhmzgkhtmwcux46ewwojjq', 'x-request-id': 'req_oxpzz4suwdpv75pkudlow5exa3bqr6nhmzgkhtmwcux46ewwojjq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:26 [openai._base_client] DEBUG: request_id: req_oxpzz4suwdpv75pkudlow5exa3bqr6nhmzgkhtmwcux46ewwojjq
2026-06-21 03:16:26 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-97e43df3-f751-439d-b0f0-ad8eea1adb4a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            very taste by chef abhi\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:26 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:26 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:26 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:26 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:26 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:26 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:27 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:27 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2791'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zlw3eo2666cshvxvfmkbvrfzewrqq45ddxdfbeq7nqh2r7as7r5a'), (b'x-request-id', b'req_zlw3eo2666cshvxvfmkbvrfzewrqq45ddxdfbeq7nqh2r7as7r5a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:27 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:27 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:27 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:27 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:27 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:27 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:27 GMT', 'content-type': 'application/json', 'content-length': '2791', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zlw3eo2666cshvxvfmkbvrfzewrqq45ddxdfbeq7nqh2r7as7r5a', 'x-request-id': 'req_zlw3eo2666cshvxvfmkbvrfzewrqq45ddxdfbeq7nqh2r7as7r5a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:27 [openai._base_client] DEBUG: request_id: req_zlw3eo2666cshvxvfmkbvrfzewrqq45ddxdfbeq7nqh2r7as7r5a
2026-06-21 03:16:27 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-a0ad8fc7-47d3-46a4-bba8-8359a35a2dca', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            spoiled and stale rasmalai\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:27 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:27 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:27 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:27 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:27 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:27 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:31 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:31 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4023'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_d3tprbkaluekxswuagwbhhvxjcopvhep3j7u3wsvjgkgvbilqgpa'), (b'x-request-id', b'req_d3tprbkaluekxswuagwbhhvxjcopvhep3j7u3wsvjgkgvbilqgpa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:31 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:31 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:31 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:31 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:31 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:31 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:31 GMT', 'content-type': 'application/json', 'content-length': '4023', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_d3tprbkaluekxswuagwbhhvxjcopvhep3j7u3wsvjgkgvbilqgpa', 'x-request-id': 'req_d3tprbkaluekxswuagwbhhvxjcopvhep3j7u3wsvjgkgvbilqgpa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:31 [openai._base_client] DEBUG: request_id: req_d3tprbkaluekxswuagwbhhvxjcopvhep3j7u3wsvjgkgvbilqgpa
2026-06-21 03:16:31 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b029779f-1bc1-4e7a-94f3-55b87b466204', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            quantity is less\n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:31 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:31 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:31 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:31 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:31 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:31 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:32 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:32 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2576'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_4734gnygukay4asnhpy5la72rupqatq3k6mfibsu764fqqnpw2ta'), (b'x-request-id', b'req_4734gnygukay4asnhpy5la72rupqatq3k6mfibsu764fqqnpw2ta'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:32 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:32 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:32 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:32 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:32 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:32 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:32 GMT', 'content-type': 'application/json', 'content-length': '2576', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_4734gnygukay4asnhpy5la72rupqatq3k6mfibsu764fqqnpw2ta', 'x-request-id': 'req_4734gnygukay4asnhpy5la72rupqatq3k6mfibsu764fqqnpw2ta', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:32 [openai._base_client] DEBUG: request_id: req_4734gnygukay4asnhpy5la72rupqatq3k6mfibsu764fqqnpw2ta
2026-06-21 03:16:32 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f810208e-7981-47a5-a0f0-ceb523d65505', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Dum Spicy Egg 2X Protein Mini Bowl tasted fresh, spicy, and perfectly prepared. The eggs were soft and full of balanced masala flavor that gave the bowl a great taste. Packaging was faithful, neat, and professionally packaged which maintained the food quality really well. The bowl arrived hot and the freshness remained perfect till the last bite. Portion size was satisfying and worth the money. Every bite of the Dum Spicy Egg 2X Protein Mini Bowl felt flavorful, rich, and comforting.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:32 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:32 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:32 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:32 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:32 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:32 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:36 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:36 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7376'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_5oabwqdgkm6mqbyoenhkj6tabvhfuqvgwkefawrujxmuk2xptpra'), (b'x-request-id', b'req_5oabwqdgkm6mqbyoenhkj6tabvhfuqvgwkefawrujxmuk2xptpra'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:36 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:36 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:36 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:36 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:36 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:36 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:36 GMT', 'content-type': 'application/json', 'content-length': '7376', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_5oabwqdgkm6mqbyoenhkj6tabvhfuqvgwkefawrujxmuk2xptpra', 'x-request-id': 'req_5oabwqdgkm6mqbyoenhkj6tabvhfuqvgwkefawrujxmuk2xptpra', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:36 [openai._base_client] DEBUG: request_id: req_5oabwqdgkm6mqbyoenhkj6tabvhfuqvgwkefawrujxmuk2xptpra
2026-06-21 03:16:36 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ce4a3a79-af5e-4af2-a50d-3f3c06532894', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            very oily and portion was very less\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:36 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:36 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:36 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:36 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:36 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:36 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:37 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:37 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2608'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2c6fy3fsfdmtymfxks2u6izzify2vr4ublmtnt2r2qmo5rzhztcq'), (b'x-request-id', b'req_2c6fy3fsfdmtymfxks2u6izzify2vr4ublmtnt2r2qmo5rzhztcq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:37 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:37 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:37 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:37 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:37 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:37 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:37 GMT', 'content-type': 'application/json', 'content-length': '2608', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2c6fy3fsfdmtymfxks2u6izzify2vr4ublmtnt2r2qmo5rzhztcq', 'x-request-id': 'req_2c6fy3fsfdmtymfxks2u6izzify2vr4ublmtnt2r2qmo5rzhztcq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:37 [openai._base_client] DEBUG: request_id: req_2c6fy3fsfdmtymfxks2u6izzify2vr4ublmtnt2r2qmo5rzhztcq
2026-06-21 03:16:37 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9a4073a1-8e7f-445d-83e5-31123d1b6ebc', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Paneer 2X Protein Mini Bowl khane me bahut hi tasty aur satisfying laga. Paneer ka flavorful masala aur rice ka aromatic taste bahut amazing combination create kar raha tha. Extra protein quantity ki wajah se meal aur bhi filling feel hua. Food fresh tha aur overall bowl ka flavor bahut enjoyable lag raha tha. Packaging neatly packed aur hygienic thi aur delivery bhi timely hui. Quality kaafi premium feel hui aur freshness bhi impressive lagi. Will definitely order again because Dum Spicy Paneer 2X Protein Mini Bowl overall bahut delicious tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:37 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:37 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:37 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:37 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:37 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:37 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:42 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6908'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_os24g7nbilgicnryamp6gv674clsjl2mi5ywpcwg6bsciqr7g72a'), (b'x-request-id', b'req_os24g7nbilgicnryamp6gv674clsjl2mi5ywpcwg6bsciqr7g72a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:42 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:42 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:42 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:42 GMT', 'content-type': 'application/json', 'content-length': '6908', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_os24g7nbilgicnryamp6gv674clsjl2mi5ywpcwg6bsciqr7g72a', 'x-request-id': 'req_os24g7nbilgicnryamp6gv674clsjl2mi5ywpcwg6bsciqr7g72a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:42 [openai._base_client] DEBUG: request_id: req_os24g7nbilgicnryamp6gv674clsjl2mi5ywpcwg6bsciqr7g72a
2026-06-21 03:16:42 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fffc7ec0-8f77-4cc0-881d-a71b113e62c6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            great food \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:42 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:42 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2041'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_7cf6737564ew2xemndiaqzqsmsbraenxbevu2drzuvsnnxgwhlvq'), (b'x-request-id', b'req_7cf6737564ew2xemndiaqzqsmsbraenxbevu2drzuvsnnxgwhlvq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:42 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:42 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:42 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:42 GMT', 'content-type': 'application/json', 'content-length': '2041', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_7cf6737564ew2xemndiaqzqsmsbraenxbevu2drzuvsnnxgwhlvq', 'x-request-id': 'req_7cf6737564ew2xemndiaqzqsmsbraenxbevu2drzuvsnnxgwhlvq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:42 [openai._base_client] DEBUG: request_id: req_7cf6737564ew2xemndiaqzqsmsbraenxbevu2drzuvsnnxgwhlvq
2026-06-21 03:16:42 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1b53675e-1569-4d95-817f-9e01ca7e7f4c', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            chicken tikka was not cooked properly\n                            Customer Rating:\n                            2 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:42 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:42 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:44 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:44 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2675'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kehtlt3nnh23vk7az4pgfq264i42hllk5fvswsji5wgexruvhavq'), (b'x-request-id', b'req_kehtlt3nnh23vk7az4pgfq264i42hllk5fvswsji5wgexruvhavq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:44 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:44 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:44 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:44 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:44 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:44 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:44 GMT', 'content-type': 'application/json', 'content-length': '2675', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kehtlt3nnh23vk7az4pgfq264i42hllk5fvswsji5wgexruvhavq', 'x-request-id': 'req_kehtlt3nnh23vk7az4pgfq264i42hllk5fvswsji5wgexruvhavq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:44 [openai._base_client] DEBUG: request_id: req_kehtlt3nnh23vk7az4pgfq264i42hllk5fvswsji5wgexruvhavq
2026-06-21 03:16:44 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-eb20bc63-a13f-4d16-a8a7-5e3dd2e4f913', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Taste awesome, packing awesome, overall quality awesome.... too good.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:44 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:44 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:44 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:44 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:44 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:44 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:45 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:45 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3090'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_wk2umx5pen74n7whbqigsfs7gh7lbywb2f3ortorzs3vantkdgbq'), (b'x-request-id', b'req_wk2umx5pen74n7whbqigsfs7gh7lbywb2f3ortorzs3vantkdgbq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:45 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:45 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:45 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:45 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:45 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:45 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:45 GMT', 'content-type': 'application/json', 'content-length': '3090', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_wk2umx5pen74n7whbqigsfs7gh7lbywb2f3ortorzs3vantkdgbq', 'x-request-id': 'req_wk2umx5pen74n7whbqigsfs7gh7lbywb2f3ortorzs3vantkdgbq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:45 [openai._base_client] DEBUG: request_id: req_wk2umx5pen74n7whbqigsfs7gh7lbywb2f3ortorzs3vantkdgbq
2026-06-21 03:16:45 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6e23096d-23e0-4287-bed8-92299473ba52', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The taste is good but not value for money in terms of quantity \n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:45 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:45 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:45 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:45 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:45 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:45 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:47 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:47 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4217'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_36uanuaju2cq3b5m4rg4dgod72vvqbrx4nvcwwbj446cvbjhyeja'), (b'x-request-id', b'req_36uanuaju2cq3b5m4rg4dgod72vvqbrx4nvcwwbj446cvbjhyeja'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:47 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:47 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:47 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:47 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:47 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:47 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:47 GMT', 'content-type': 'application/json', 'content-length': '4217', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_36uanuaju2cq3b5m4rg4dgod72vvqbrx4nvcwwbj446cvbjhyeja', 'x-request-id': 'req_36uanuaju2cq3b5m4rg4dgod72vvqbrx4nvcwwbj446cvbjhyeja', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:47 [openai._base_client] DEBUG: request_id: req_36uanuaju2cq3b5m4rg4dgod72vvqbrx4nvcwwbj446cvbjhyeja
2026-06-21 03:16:47 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-032b71b7-5f39-4676-b596-30fb63cdae8f', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I genuinely loved the Charcoal Chicken Mini Biryani Bowl because the flavor felt authentic and perfectly balanced. The chicken was soft, juicy, and cooked beautifully while the rice remained fluffy and aromatic till the last bite. Delivery was timely and the food came hot with secure hygienic packaging. The freshness of ingredients was clearly noticeable and every spoon felt satisfying. Portion size was decent and suitable for a complete meal. Charcoal Chicken Mini Biryani Bowl exceeded expectations in quality and presentation. Will definitely order again because the taste was rich, comforting, and truly enjoyable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:47 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:47 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:47 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:47 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:47 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:47 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:51 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:51 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7137'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_wie2cwuczgczqtla5brvsavpwduxjq75lgprv5escc6rn7g3qvma'), (b'x-request-id', b'req_wie2cwuczgczqtla5brvsavpwduxjq75lgprv5escc6rn7g3qvma'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:51 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:51 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:51 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:51 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:51 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:51 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:51 GMT', 'content-type': 'application/json', 'content-length': '7137', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_wie2cwuczgczqtla5brvsavpwduxjq75lgprv5escc6rn7g3qvma', 'x-request-id': 'req_wie2cwuczgczqtla5brvsavpwduxjq75lgprv5escc6rn7g3qvma', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:51 [openai._base_client] DEBUG: request_id: req_wie2cwuczgczqtla5brvsavpwduxjq75lgprv5escc6rn7g3qvma
2026-06-21 03:16:51 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fc28407c-b04b-4875-b698-e780ef476bc1', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Maine  Charcoal Chicken Mini Biryani Bowl order kiya tha aur experience bahut hi achha raha. Chicken juicy aur perfectly cooked tha aur uska flavor bahut authentic lag raha tha. Rice fluffy aur flavorful the jo dum masalon ke saath bahut delicious combination bana rahe the. Food timely delivered hua aur warm condition me mila jis wajah se freshness bilkul maintain thi. Packaging hygienic aur professionally packaged thi jo kaafi premium feel de rahi thi. Portion size satisfying tha aur quality bhi impressive lagi. Will definitely order again because Charcoal Chicken Mini Biryani Bowl ka taste kaafi memorable tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:51 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:51 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:51 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:51 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:51 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:51 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:16:55 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:16:55 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6785'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_yivdn3icz5lrrozkfryrx4bqdzbmnw2jphgtghvy3vaaddb7xmwa'), (b'x-request-id', b'req_yivdn3icz5lrrozkfryrx4bqdzbmnw2jphgtghvy3vaaddb7xmwa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:16:55 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:16:55 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:16:55 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:16:55 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:16:55 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:16:55 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:16:55 GMT', 'content-type': 'application/json', 'content-length': '6785', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_yivdn3icz5lrrozkfryrx4bqdzbmnw2jphgtghvy3vaaddb7xmwa', 'x-request-id': 'req_yivdn3icz5lrrozkfryrx4bqdzbmnw2jphgtghvy3vaaddb7xmwa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:16:55 [openai._base_client] DEBUG: request_id: req_yivdn3icz5lrrozkfryrx4bqdzbmnw2jphgtghvy3vaaddb7xmwa
2026-06-21 03:16:55 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-e1706206-296a-44d9-bbdb-9127aa86257c', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Maine Veg Galouti Roll order kiya tha aur experience bahut achha raha. Stuffing perfectly cooked thi aur spices ka balance bahut tasty lag raha tha. Wrap fresh aur soft tha jo filling ke saath bahut achha combination bana raha tha. Food timely delivered hua aur warm condition me mila jis wajah se freshness maintain rahi. Packaging hygienic aur professionally packaged thi jo kaafi premium feel de rahi thi. Quality ingredients aur authentic flavor ne overall experience ko aur better bana diya. Veg Galouti Roll definitely value for money laga. Will definitely order again because har bite bahut satisfying thi.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:16:55 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:16:55 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:16:55 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:16:55 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:16:55 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:16:55 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5467'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_a6hp7qjufdd4ovjilfxl4cenofiiq377rov72v2ibzrtiej33ewq'), (b'x-request-id', b'req_a6hp7qjufdd4ovjilfxl4cenofiiq377rov72v2ibzrtiej33ewq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:02 GMT', 'content-type': 'application/json', 'content-length': '5467', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_a6hp7qjufdd4ovjilfxl4cenofiiq377rov72v2ibzrtiej33ewq', 'x-request-id': 'req_a6hp7qjufdd4ovjilfxl4cenofiiq377rov72v2ibzrtiej33ewq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:02 [openai._base_client] DEBUG: request_id: req_a6hp7qjufdd4ovjilfxl4cenofiiq377rov72v2ibzrtiej33ewq
2026-06-21 03:17:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fcd0cada-d044-4e58-81f5-d585a09f8aa7', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Charcoal Veg Mini  Biryani Bowl had a rich aroma and authentic flavor that made it stand out. The vegetables were perfectly cooked and blended beautifully with the aromatic rice. Food arrived hot with clean packaging that maintained hygiene and freshness very well. The ingredients tasted premium and every spoon felt comforting and satisfying. Portion size was filling and suitable for a complete meal. Charcoal Veg Mini Biryani Bowl impressed me with its freshness, great taste, and presentation. Will definitely order again because the flavor was truly memorable and enjoyable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:05 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:05 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6049'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fd4em2ntudoy34exrgwemu66a5bqfrcqown2ft2hsnatk45ppdaq'), (b'x-request-id', b'req_fd4em2ntudoy34exrgwemu66a5bqfrcqown2ft2hsnatk45ppdaq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:05 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:05 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:05 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:05 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:05 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:05 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:05 GMT', 'content-type': 'application/json', 'content-length': '6049', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fd4em2ntudoy34exrgwemu66a5bqfrcqown2ft2hsnatk45ppdaq', 'x-request-id': 'req_fd4em2ntudoy34exrgwemu66a5bqfrcqown2ft2hsnatk45ppdaq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:05 [openai._base_client] DEBUG: request_id: req_fd4em2ntudoy34exrgwemu66a5bqfrcqown2ft2hsnatk45ppdaq
2026-06-21 03:17:05 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-cc34864c-73b9-4df7-bfee-0d6602c6cc04', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Charcoal Egg Mini Biryani Bowl ka overall experience genuinely bahut achha raha. Eggs well cooked the aur unka spicy smoky flavor kaafi delicious lag raha tha. Rice soft aur aromatic the aur masala perfectly balanced tha. Packaging clean aur nicely packaged thi jo kaafi premium lagi. Delivery timely hui aur food bilkul garam deliver hua. Quantity satisfying thi aur quality kaafi value for money lagi. Har bite flavorful aur enjoyable thi.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:05 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:05 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:05 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:05 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:05 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:05 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:09 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:09 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6547'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_mgs7ijm564bgoormjp5dpe245ebjt465qjvwnjksmli7lvl6lfya'), (b'x-request-id', b'req_mgs7ijm564bgoormjp5dpe245ebjt465qjvwnjksmli7lvl6lfya'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:09 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:09 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:09 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:09 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:09 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:09 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:09 GMT', 'content-type': 'application/json', 'content-length': '6547', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_mgs7ijm564bgoormjp5dpe245ebjt465qjvwnjksmli7lvl6lfya', 'x-request-id': 'req_mgs7ijm564bgoormjp5dpe245ebjt465qjvwnjksmli7lvl6lfya', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:09 [openai._base_client] DEBUG: request_id: req_mgs7ijm564bgoormjp5dpe245ebjt465qjvwnjksmli7lvl6lfya
2026-06-21 03:17:09 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-abbaaf5b-47bd-4a97-8509-f8e5c1d571ef', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I really enjoyed the Dum Spicy Paneer 2X Protein Mini Bowl because everything from taste to packaging felt high quality. The paneer was perfectly cooked and had a rich spicy flavor that made every spoon enjoyable. The rice remained fluffy and aromatic while the masala added extra depth to the taste. Delivery was quick and the food came hot with secure hygienic packaging. Portion size was enough for a satisfying meal and the extra protein made it even better. Dum Spicy Paneer 2X Protein Mini Bowl exceeded expectations in freshness and presentation. Will definitely order again because the flavor felt authentic and memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:09 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:09 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:09 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:09 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:09 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:09 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:16 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:16 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'9220'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_3mrzmhtzwvji27xrpqf6ia25677rfowqrddh6im5eyzaqbljz7uq'), (b'x-request-id', b'req_3mrzmhtzwvji27xrpqf6ia25677rfowqrddh6im5eyzaqbljz7uq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:16 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:16 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:16 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:16 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:16 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:16 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:16 GMT', 'content-type': 'application/json', 'content-length': '9220', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_3mrzmhtzwvji27xrpqf6ia25677rfowqrddh6im5eyzaqbljz7uq', 'x-request-id': 'req_3mrzmhtzwvji27xrpqf6ia25677rfowqrddh6im5eyzaqbljz7uq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:16 [openai._base_client] DEBUG: request_id: req_3mrzmhtzwvji27xrpqf6ia25677rfowqrddh6im5eyzaqbljz7uq
2026-06-21 03:17:16 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-66888990-62f9-4b0e-a520-159b739552da', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I genuinely loved the Lucknowi Veg Mini Biryani Bowl because the freshness and quality both were noticeable from the first bite. The vegetables were perfectly seasoned and had a rich spicy flavor which made the biryani extremely tasty. The rice remained fluffy and aromatic while the masala added extra depth to every spoon. Delivery was quick and the food came hot with secure hygienic packaging. Portion size was enough for a satisfying meal and worth the money paid. Lucknowi Veg Mini Biryani Bowl exceeded expectations in taste and presentation. Will definitely order again because the flavor felt authentic and memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:16 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:16 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:16 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:16 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:16 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:16 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:19 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:19 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6497'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_cnn32lncrkv3dtq7fmhyezd3cv4tewc376sf4yevutodrzrscfeq'), (b'x-request-id', b'req_cnn32lncrkv3dtq7fmhyezd3cv4tewc376sf4yevutodrzrscfeq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:19 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:19 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:19 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:19 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:19 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:19 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:19 GMT', 'content-type': 'application/json', 'content-length': '6497', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_cnn32lncrkv3dtq7fmhyezd3cv4tewc376sf4yevutodrzrscfeq', 'x-request-id': 'req_cnn32lncrkv3dtq7fmhyezd3cv4tewc376sf4yevutodrzrscfeq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:19 [openai._base_client] DEBUG: request_id: req_cnn32lncrkv3dtq7fmhyezd3cv4tewc376sf4yevutodrzrscfeq
2026-06-21 03:17:19 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-321d025f-283f-482d-9bc4-98bd87d839b0', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Dum Spicy Paneer 2X Protein Mini Bowl had a wonderful spicy aroma and authentic flavor that felt very satisfying. The paneer was juicy, flavorful, and cooked beautifully with balanced spices. The rice stayed fluffy and fresh till the last bite which made the meal even more enjoyable. Food arrived hot with clean packaging that maintained hygiene and freshness properly. Portion size was filling and the extra protein made it ideal for a complete meal. Dum Spicy Paneer 2X Protein Mini Bowl impressed me with its freshness, great taste, and premium quality. Will definitely order again because the flavor was truly memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:19 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:19 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:19 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:19 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:19 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:19 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:29 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:29 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6806'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zqwvvxn2mszcsrzlfaf7wjdhcnzjhm53t3mtcvzyjiffhatg2gxq'), (b'x-request-id', b'req_zqwvvxn2mszcsrzlfaf7wjdhcnzjhm53t3mtcvzyjiffhatg2gxq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:29 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:29 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:29 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:29 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:29 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:29 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:29 GMT', 'content-type': 'application/json', 'content-length': '6806', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zqwvvxn2mszcsrzlfaf7wjdhcnzjhm53t3mtcvzyjiffhatg2gxq', 'x-request-id': 'req_zqwvvxn2mszcsrzlfaf7wjdhcnzjhm53t3mtcvzyjiffhatg2gxq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:29 [openai._base_client] DEBUG: request_id: req_zqwvvxn2mszcsrzlfaf7wjdhcnzjhm53t3mtcvzyjiffhatg2gxq
2026-06-21 03:17:29 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-d049a49e-5178-4c18-9bfb-5c155a210148', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Spicy Chicken Dum Mini Biryani Bowl khane me buhat hi tasty aur satisfying laga.Chicken ka spicy masala aur rice ka dum flavor buhat amazing combinations\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:29 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:29 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:29 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:29 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:29 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:29 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:30 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:30 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2633'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_u6jgcywtocb62oscqmk6xjx23fxyt35rsneys2a54o32cep6vltq'), (b'x-request-id', b'req_u6jgcywtocb62oscqmk6xjx23fxyt35rsneys2a54o32cep6vltq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:30 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:30 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:30 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:30 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:30 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:30 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:30 GMT', 'content-type': 'application/json', 'content-length': '2633', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_u6jgcywtocb62oscqmk6xjx23fxyt35rsneys2a54o32cep6vltq', 'x-request-id': 'req_u6jgcywtocb62oscqmk6xjx23fxyt35rsneys2a54o32cep6vltq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:30 [openai._base_client] DEBUG: request_id: req_u6jgcywtocb62oscqmk6xjx23fxyt35rsneys2a54o32cep6vltq
2026-06-21 03:17:30 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-59b39b53-4b74-49a9-9ff3-acb541fda5b6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Spicy Chicken Dum Mini Biryani Bowl had an incredible aroma and bold spicy flavor that felt very satisfying. The chicken pieces were juicy, flavorful, and cooked beautifully with balanced spices. The rice stayed fluffy and fresh till the last bite which made the meal even more enjoyable. Food arrived hot with clean packaging that maintained hygiene properly. Portion size was filling and ideal for a complete meal. Spicy Chicken Dum Mini Biryani Bowl impressed me with its freshness, great taste, and premium quality. Will definitely order again because the flavor was truly memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:30 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:30 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:30 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:30 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:30 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:30 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:33 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:33 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6117'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rm6w2sl4nkhc5jdpii5qrc3vg23jkheaorieo2x2epitqdfn7tia'), (b'x-request-id', b'req_rm6w2sl4nkhc5jdpii5qrc3vg23jkheaorieo2x2epitqdfn7tia'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:33 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:33 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:33 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:33 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:33 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:33 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:33 GMT', 'content-type': 'application/json', 'content-length': '6117', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rm6w2sl4nkhc5jdpii5qrc3vg23jkheaorieo2x2epitqdfn7tia', 'x-request-id': 'req_rm6w2sl4nkhc5jdpii5qrc3vg23jkheaorieo2x2epitqdfn7tia', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:33 [openai._base_client] DEBUG: request_id: req_rm6w2sl4nkhc5jdpii5qrc3vg23jkheaorieo2x2epitqdfn7tia
2026-06-21 03:17:33 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9cb9ce1a-363a-42b0-82c1-d38d7e3df45d', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl ka overall experience genuinely bahut achha raha. Eggs well cooked the aur unka spicy smoky flavor kaafi delicious lag raha tha. Rice soft aur flavorful the aur masala perfectly balanced tha. Packaging clean aur nicely packaged thi jo kaafi premium lagi. Delivery timely hui aur food bilkul garam deliver hua. Quantity satisfying thi aur quality kaafi value for money lagi. Har bite flavorful aur enjoyable thi.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:33 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:33 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:33 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:33 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:33 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:33 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:37 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:37 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6950'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_hlyjy3bw7mczdvr56as5le2w4m6i7hhvxjtmyr5kv7ybw7fil3ma'), (b'x-request-id', b'req_hlyjy3bw7mczdvr56as5le2w4m6i7hhvxjtmyr5kv7ybw7fil3ma'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:37 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:37 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:37 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:37 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:37 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:37 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:37 GMT', 'content-type': 'application/json', 'content-length': '6950', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_hlyjy3bw7mczdvr56as5le2w4m6i7hhvxjtmyr5kv7ybw7fil3ma', 'x-request-id': 'req_hlyjy3bw7mczdvr56as5le2w4m6i7hhvxjtmyr5kv7ybw7fil3ma', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:37 [openai._base_client] DEBUG: request_id: req_hlyjy3bw7mczdvr56as5le2w4m6i7hhvxjtmyr5kv7ybw7fil3ma
2026-06-21 03:17:37 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-81881b3a-1cc4-4f7f-ac0f-e9824d0b9de4', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Paneer Tikka kathi Roll was  absolutely tasty and full of smoky tikka flavors. The paneer was soft ,juicy,and well cooked with balanced spices that made every bite satisfying.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:37 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:37 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:37 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:37 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:37 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:37 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:39 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:39 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3674'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_i7ie64ldik46t3kuvitwxyfv5ooc3qm34pkxhialqa2e4v6znv5a'), (b'x-request-id', b'req_i7ie64ldik46t3kuvitwxyfv5ooc3qm34pkxhialqa2e4v6znv5a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:39 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:39 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:39 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:39 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:39 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:39 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:39 GMT', 'content-type': 'application/json', 'content-length': '3674', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_i7ie64ldik46t3kuvitwxyfv5ooc3qm34pkxhialqa2e4v6znv5a', 'x-request-id': 'req_i7ie64ldik46t3kuvitwxyfv5ooc3qm34pkxhialqa2e4v6znv5a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:39 [openai._base_client] DEBUG: request_id: req_i7ie64ldik46t3kuvitwxyfv5ooc3qm34pkxhialqa2e4v6znv5a
2026-06-21 03:17:39 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-30034226-9cd3-4758-adca-d2e77bebd18e', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Shahi Tukda had a amazing creamy aroma and rich sweet flavour. The bread pieces were soft ,juicy ,and prefectly prepared which made every bite delicious and satisfying.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:39 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:39 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:39 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:39 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:39 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:39 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:41 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:41 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3466'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_dccclxovbqqonzu3brvssp4vjc7l2n4ihvqaq4xhvlccmkv2tlha'), (b'x-request-id', b'req_dccclxovbqqonzu3brvssp4vjc7l2n4ihvqaq4xhvlccmkv2tlha'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:41 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:41 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:41 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:41 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:41 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:41 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:41 GMT', 'content-type': 'application/json', 'content-length': '3466', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_dccclxovbqqonzu3brvssp4vjc7l2n4ihvqaq4xhvlccmkv2tlha', 'x-request-id': 'req_dccclxovbqqonzu3brvssp4vjc7l2n4ihvqaq4xhvlccmkv2tlha', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:41 [openai._base_client] DEBUG: request_id: req_dccclxovbqqonzu3brvssp4vjc7l2n4ihvqaq4xhvlccmkv2tlha
2026-06-21 03:17:41 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fbaf8489-fb9b-4886-9b0d-265a1bee393a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            loved the dish prepared by Anu!!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:41 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:41 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:41 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:41 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:41 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:41 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:46 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:46 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2779'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_nhh7ocvui5ufloeigb4trif544jukj6ya47u6ll2nv5ant3txl7q'), (b'x-request-id', b'req_nhh7ocvui5ufloeigb4trif544jukj6ya47u6ll2nv5ant3txl7q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:46 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:46 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:46 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:46 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:46 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:46 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:46 GMT', 'content-type': 'application/json', 'content-length': '2779', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_nhh7ocvui5ufloeigb4trif544jukj6ya47u6ll2nv5ant3txl7q', 'x-request-id': 'req_nhh7ocvui5ufloeigb4trif544jukj6ya47u6ll2nv5ant3txl7q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:46 [openai._base_client] DEBUG: request_id: req_nhh7ocvui5ufloeigb4trif544jukj6ya47u6ll2nv5ant3txl7q
2026-06-21 03:17:46 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8d590716-5bdf-40b9-ba23-7b3b1716e1d4', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            the pathetically little quantity and high prizes have become a norm for all restuarants now it seems.\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:46 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:46 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:46 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:46 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:46 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:46 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:47 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:47 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2747'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_k455iqs5wase7we3ssrqg5ehrub46cmth7ek5ldcqi6wrovklnsa'), (b'x-request-id', b'req_k455iqs5wase7we3ssrqg5ehrub46cmth7ek5ldcqi6wrovklnsa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:47 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:47 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:47 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:47 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:47 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:47 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:47 GMT', 'content-type': 'application/json', 'content-length': '2747', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_k455iqs5wase7we3ssrqg5ehrub46cmth7ek5ldcqi6wrovklnsa', 'x-request-id': 'req_k455iqs5wase7we3ssrqg5ehrub46cmth7ek5ldcqi6wrovklnsa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:47 [openai._base_client] DEBUG: request_id: req_k455iqs5wase7we3ssrqg5ehrub46cmth7ek5ldcqi6wrovklnsa
2026-06-21 03:17:47 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5d5276dc-1129-4deb-963b-14ec9d4af5c2', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I really enjoyed the Dum Spicy Egg 2X Protein Mini Bowl because the freshness and quality both were excellent. The eggs were tender, spicy, and perfectly seasoned with rich masala. The rice was fluffy and fresh while the aroma added extra flavor to every bite. Food came hot and was professionally packaged which maintained hygiene properly. Portion size was enough for a satisfying meal and definitely felt value for money. The Dum Spicy  Egg 2X Protein Mini Bowl had an authentic restaurant style taste with premium quality ingredients.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:47 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:47 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:47 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:47 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:47 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:47 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:51 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:51 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7091'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_bn7ktmrdnec5pjo4mduj2laehx3ocr5zwkdrjzukzof3azquguwa'), (b'x-request-id', b'req_bn7ktmrdnec5pjo4mduj2laehx3ocr5zwkdrjzukzof3azquguwa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:51 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:51 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:51 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:51 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:51 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:51 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:51 GMT', 'content-type': 'application/json', 'content-length': '7091', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_bn7ktmrdnec5pjo4mduj2laehx3ocr5zwkdrjzukzof3azquguwa', 'x-request-id': 'req_bn7ktmrdnec5pjo4mduj2laehx3ocr5zwkdrjzukzof3azquguwa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:51 [openai._base_client] DEBUG: request_id: req_bn7ktmrdnec5pjo4mduj2laehx3ocr5zwkdrjzukzof3azquguwa
2026-06-21 03:17:51 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c4445e44-793a-4ec1-8de9-91a32ea47ca7', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Chicken Tikka Mini Biryani Bowl ka overall experience bahut premium laga. Chicken tikka ka flavor rich aur spicy tha aur rice ka dum aroma kaafi authentic feel ho raha tha. Har bite me freshness aur proper seasoning feel ho rahi thi jo meal ko aur enjoyable bana rahi thi. Food hot deliver hua aur packaging neat aur hygienic thi. Quantity kaafi filling thi aur quality bhi impressive lagi. Dum Chicken Tikka Mini Biryani Bowl ka smoky spicy combination bahut delicious tha. Will definitely order again because taste aur freshness dono hi outstanding the.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:51 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:51 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:51 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:51 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:51 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:51 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:56 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:56 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6220'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rfyuyqznqt3oblpydtet5swru4awd2asas7hflgazdbejntgmypa'), (b'x-request-id', b'req_rfyuyqznqt3oblpydtet5swru4awd2asas7hflgazdbejntgmypa'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:56 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:56 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:56 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:56 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:56 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:56 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:56 GMT', 'content-type': 'application/json', 'content-length': '6220', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rfyuyqznqt3oblpydtet5swru4awd2asas7hflgazdbejntgmypa', 'x-request-id': 'req_rfyuyqznqt3oblpydtet5swru4awd2asas7hflgazdbejntgmypa', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:56 [openai._base_client] DEBUG: request_id: req_rfyuyqznqt3oblpydtet5swru4awd2asas7hflgazdbejntgmypa
2026-06-21 03:17:56 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-4a0bd38a-eb8e-40ff-9950-c48d706cb269', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            great👍\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:56 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:56 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:56 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:56 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:56 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:56 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:17:57 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:17:57 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1579'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_hhoducje3ypm7brhsfzibhjfo6p5hyr6ude2xyi6kpcl5zp3r5ga'), (b'x-request-id', b'req_hhoducje3ypm7brhsfzibhjfo6p5hyr6ude2xyi6kpcl5zp3r5ga'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:17:57 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:17:57 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:17:57 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:17:57 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:17:57 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:17:57 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:17:57 GMT', 'content-type': 'application/json', 'content-length': '1579', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_hhoducje3ypm7brhsfzibhjfo6p5hyr6ude2xyi6kpcl5zp3r5ga', 'x-request-id': 'req_hhoducje3ypm7brhsfzibhjfo6p5hyr6ude2xyi6kpcl5zp3r5ga', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:17:57 [openai._base_client] DEBUG: request_id: req_hhoducje3ypm7brhsfzibhjfo6p5hyr6ude2xyi6kpcl5zp3r5ga
2026-06-21 03:17:57 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ea09b57d-7952-41a0-b175-eedb58aae2f8', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            The Dum Spicy Paneer 2X Protein Mini Bowl had a wonderful spicy aroma and authentic flavor that felt very satisfying. The paneer was juicy, flavorful, and cooked beautifully with balanced spices. The rice stayed fluffy and fresh till the last bite which made the meal even more enjoyable. Food arrived hot with clean packaging that maintained hygiene and freshness properly. Portion size was filling and the extra protein made it ideal for a complete meal. Dum Spicy Paneer 2X Protein Mini Bowl impressed me with its freshness, great taste, and premium quality. Will definitely order again because the flavor was truly memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:17:57 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:17:57 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:17:57 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:17:57 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:17:57 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:17:57 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:00 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:00 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5522'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_xhgo7l7xy2stxwz6sqqu6ee24shykmu4uwz4acxlilxu4y6fppma'), (b'x-request-id', b'req_xhgo7l7xy2stxwz6sqqu6ee24shykmu4uwz4acxlilxu4y6fppma'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:00 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:00 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:00 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:00 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:00 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:00 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:00 GMT', 'content-type': 'application/json', 'content-length': '5522', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_xhgo7l7xy2stxwz6sqqu6ee24shykmu4uwz4acxlilxu4y6fppma', 'x-request-id': 'req_xhgo7l7xy2stxwz6sqqu6ee24shykmu4uwz4acxlilxu4y6fppma', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:00 [openai._base_client] DEBUG: request_id: req_xhgo7l7xy2stxwz6sqqu6ee24shykmu4uwz4acxlilxu4y6fppma
2026-06-21 03:18:00 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-05303a7a-59f6-4a4e-bbe4-0823aba4db68', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            the raita is leaking and there are no spoons the overall quality I\'m receiving from 2 orders is bad\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:00 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:00 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:00 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:00 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:00 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:00 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3520'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_y7wqvcwxmzjtw4qpahhlulf4cu57mgvszgdanfca37w2rqruwybq'), (b'x-request-id', b'req_y7wqvcwxmzjtw4qpahhlulf4cu57mgvszgdanfca37w2rqruwybq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:02 GMT', 'content-type': 'application/json', 'content-length': '3520', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_y7wqvcwxmzjtw4qpahhlulf4cu57mgvszgdanfca37w2rqruwybq', 'x-request-id': 'req_y7wqvcwxmzjtw4qpahhlulf4cu57mgvszgdanfca37w2rqruwybq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:02 [openai._base_client] DEBUG: request_id: req_y7wqvcwxmzjtw4qpahhlulf4cu57mgvszgdanfca37w2rqruwybq
2026-06-21 03:18:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b8f874a0-c65b-41cd-9aa8-8141d657cf70', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            quantity felt less.. but food was good in taste! \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:03 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:03 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2618'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_mvfy4utkllx7vutr43ciggptxwwxqjepl5xf73fqx465s37qaykq'), (b'x-request-id', b'req_mvfy4utkllx7vutr43ciggptxwwxqjepl5xf73fqx465s37qaykq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:03 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:03 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:03 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:03 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:03 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:03 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:03 GMT', 'content-type': 'application/json', 'content-length': '2618', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_mvfy4utkllx7vutr43ciggptxwwxqjepl5xf73fqx465s37qaykq', 'x-request-id': 'req_mvfy4utkllx7vutr43ciggptxwwxqjepl5xf73fqx465s37qaykq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:03 [openai._base_client] DEBUG: request_id: req_mvfy4utkllx7vutr43ciggptxwwxqjepl5xf73fqx465s37qaykq
2026-06-21 03:18:03 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c4aa6c8f-6127-43c1-89cc-cbfa834debc6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            nice taste\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:03 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:03 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:03 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:03 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:03 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:03 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:04 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:04 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1752'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_3zsetdnwcorfj7s24noxamnraukdlkdql3ipvfgf6h5xffiau5da'), (b'x-request-id', b'req_3zsetdnwcorfj7s24noxamnraukdlkdql3ipvfgf6h5xffiau5da'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:04 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:04 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:04 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:04 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:04 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:04 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:04 GMT', 'content-type': 'application/json', 'content-length': '1752', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_3zsetdnwcorfj7s24noxamnraukdlkdql3ipvfgf6h5xffiau5da', 'x-request-id': 'req_3zsetdnwcorfj7s24noxamnraukdlkdql3ipvfgf6h5xffiau5da', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:04 [openai._base_client] DEBUG: request_id: req_3zsetdnwcorfj7s24noxamnraukdlkdql3ipvfgf6h5xffiau5da
2026-06-21 03:18:04 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-49a2e846-b9b0-4b61-a839-6795194ec5fe', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Not worth it and quantity wast very less please improve \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:04 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:04 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:04 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:04 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:04 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:04 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:05 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:05 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2427'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_jw3i2xssjfpikobzpyk42yni2s6klx6jex3is7o2mupeqgdnyeua'), (b'x-request-id', b'req_jw3i2xssjfpikobzpyk42yni2s6klx6jex3is7o2mupeqgdnyeua'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:05 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:05 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:05 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:05 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:05 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:05 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:05 GMT', 'content-type': 'application/json', 'content-length': '2427', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_jw3i2xssjfpikobzpyk42yni2s6klx6jex3is7o2mupeqgdnyeua', 'x-request-id': 'req_jw3i2xssjfpikobzpyk42yni2s6klx6jex3is7o2mupeqgdnyeua', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:05 [openai._base_client] DEBUG: request_id: req_jw3i2xssjfpikobzpyk42yni2s6klx6jex3is7o2mupeqgdnyeua
2026-06-21 03:18:05 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0dbaa8be-009c-4cef-a19c-3a6492aad7e6', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Stale food with bad smell\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:05 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:05 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:05 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:05 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:05 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:05 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:07 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:07 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2843'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rvopwm7rs2b5pb4tj26uve54hivhowhyot6nojlfuqpbp7jsvjda'), (b'x-request-id', b'req_rvopwm7rs2b5pb4tj26uve54hivhowhyot6nojlfuqpbp7jsvjda'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:07 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:07 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:07 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:07 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:07 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:07 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:07 GMT', 'content-type': 'application/json', 'content-length': '2843', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rvopwm7rs2b5pb4tj26uve54hivhowhyot6nojlfuqpbp7jsvjda', 'x-request-id': 'req_rvopwm7rs2b5pb4tj26uve54hivhowhyot6nojlfuqpbp7jsvjda', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:07 [openai._base_client] DEBUG: request_id: req_rvopwm7rs2b5pb4tj26uve54hivhowhyot6nojlfuqpbp7jsvjda
2026-06-21 03:18:07 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-16a764a4-9952-4e1a-8533-220a3649f737', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Awesome taste I have never been experienced like this taste.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:07 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:07 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:07 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:07 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:07 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:07 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:08 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:08 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2454'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_yxlo6d6ocy3fukrpg46xqvw45ljeihsddfgpey2oya473ojkxuiq'), (b'x-request-id', b'req_yxlo6d6ocy3fukrpg46xqvw45ljeihsddfgpey2oya473ojkxuiq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:08 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:08 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:08 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:08 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:08 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:08 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:08 GMT', 'content-type': 'application/json', 'content-length': '2454', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_yxlo6d6ocy3fukrpg46xqvw45ljeihsddfgpey2oya473ojkxuiq', 'x-request-id': 'req_yxlo6d6ocy3fukrpg46xqvw45ljeihsddfgpey2oya473ojkxuiq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:08 [openai._base_client] DEBUG: request_id: req_yxlo6d6ocy3fukrpg46xqvw45ljeihsddfgpey2oya473ojkxuiq
2026-06-21 03:18:08 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-cec697a1-dfce-4081-adaf-b1024a612378', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            love this biryani than any other restaurants Biryani I recommend it to my family and friends!!!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:08 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:08 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:08 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:08 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:08 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:08 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:12 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:12 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4010'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_nkrtuvi3hyisja2mlurpn7jalidw33biotpwgrpk32x5mv243evq'), (b'x-request-id', b'req_nkrtuvi3hyisja2mlurpn7jalidw33biotpwgrpk32x5mv243evq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:12 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:12 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:12 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:12 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:12 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:12 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:12 GMT', 'content-type': 'application/json', 'content-length': '4010', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_nkrtuvi3hyisja2mlurpn7jalidw33biotpwgrpk32x5mv243evq', 'x-request-id': 'req_nkrtuvi3hyisja2mlurpn7jalidw33biotpwgrpk32x5mv243evq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:12 [openai._base_client] DEBUG: request_id: req_nkrtuvi3hyisja2mlurpn7jalidw33biotpwgrpk32x5mv243evq
2026-06-21 03:18:12 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-01ec3e64-3c72-46de-bb03-49d9f4d6de96', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I really enjoyed the Dum Spicy Paneer 2X Protein Mini Bowl because everything from taste to packaging felt high quality. The paneer was perfectly cooked and had a rich spicy flavor that made every spoon enjoyable. The rice remained fluffy and aromatic while the masala added extra depth to the taste. Delivery was quick and the food came hot with secure hygienic packaging. Portion size was enough for a satisfying meal and the extra protein made it even better. Dum Spicy Paneer 2X Protein Mini Bowl exceeded expectations in freshness and presentation. Will definitely order again because the flavor felt authentic and memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:12 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:12 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:12 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:12 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:12 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:12 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:17 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:17 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'8345'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_svovcazfikr6soyuoglyfpbeknodauqnzqkgboyfskahiadtkyra'), (b'x-request-id', b'req_svovcazfikr6soyuoglyfpbeknodauqnzqkgboyfskahiadtkyra'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:17 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:17 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:17 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:17 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:17 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:17 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:17 GMT', 'content-type': 'application/json', 'content-length': '8345', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_svovcazfikr6soyuoglyfpbeknodauqnzqkgboyfskahiadtkyra', 'x-request-id': 'req_svovcazfikr6soyuoglyfpbeknodauqnzqkgboyfskahiadtkyra', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:17 [openai._base_client] DEBUG: request_id: req_svovcazfikr6soyuoglyfpbeknodauqnzqkgboyfskahiadtkyra
2026-06-21 03:18:17 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0988f592-0b07-4d46-86d6-a44be8678942', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            my kids love biryani from here \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:17 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:17 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:17 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:17 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:17 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:17 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:18 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:18 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2440'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_wr5wkkaz5hsfdl5oxeowzpwsr5nyuisnog6drxgehxbflcorhl6a'), (b'x-request-id', b'req_wr5wkkaz5hsfdl5oxeowzpwsr5nyuisnog6drxgehxbflcorhl6a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:18 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:18 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:18 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:18 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:18 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:18 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:18 GMT', 'content-type': 'application/json', 'content-length': '2440', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_wr5wkkaz5hsfdl5oxeowzpwsr5nyuisnog6drxgehxbflcorhl6a', 'x-request-id': 'req_wr5wkkaz5hsfdl5oxeowzpwsr5nyuisnog6drxgehxbflcorhl6a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:18 [openai._base_client] DEBUG: request_id: req_wr5wkkaz5hsfdl5oxeowzpwsr5nyuisnog6drxgehxbflcorhl6a
2026-06-21 03:18:18 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-589646cf-15c3-4c97-86fb-a9a014f15046', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Esko Veg biryani mat bolo esme vegetables kaha hai 🤔 jale hue chawal hai aur kadwa taste aa raha tha..esse accha to main ghar per bana leti hu.. totally money waste.. very very disappointing..\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:18 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:18 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:18 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:18 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:18 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:18 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:20 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:20 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4813'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_f34q7hyh7cxnzqcfufnd6nr6akbzk6af5ymj3wxydzwofit4adda'), (b'x-request-id', b'req_f34q7hyh7cxnzqcfufnd6nr6akbzk6af5ymj3wxydzwofit4adda'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:20 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:20 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:20 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:20 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:20 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:20 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:20 GMT', 'content-type': 'application/json', 'content-length': '4813', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_f34q7hyh7cxnzqcfufnd6nr6akbzk6af5ymj3wxydzwofit4adda', 'x-request-id': 'req_f34q7hyh7cxnzqcfufnd6nr6akbzk6af5ymj3wxydzwofit4adda', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:20 [openai._base_client] DEBUG: request_id: req_f34q7hyh7cxnzqcfufnd6nr6akbzk6af5ymj3wxydzwofit4adda
2026-06-21 03:18:20 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-408cdd86-93df-4603-8c56-2b147e743fb3', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Ghar pe baitha tha aur Soya Chaap Tikka Roll mangaya — bhai bilkul sahi decision tha! Chaap ka smoky tikka flavor ekdum authentic laga. Wrap fresh tha, portion bhi generous tha. Spices perfectly balanced the — na zyada teekha na pheeqa. Ekdum zabardast experience raha, 5 stars easily.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:20 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:20 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:20 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:20 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:20 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:20 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:22 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:22 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4603'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_4xbwtgrbys3gohadyl777li447tcxipwwujkcmhwqz2rkxaf4y4a'), (b'x-request-id', b'req_4xbwtgrbys3gohadyl777li447tcxipwwujkcmhwqz2rkxaf4y4a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:22 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:22 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:22 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:22 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:22 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:22 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:22 GMT', 'content-type': 'application/json', 'content-length': '4603', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_4xbwtgrbys3gohadyl777li447tcxipwwujkcmhwqz2rkxaf4y4a', 'x-request-id': 'req_4xbwtgrbys3gohadyl777li447tcxipwwujkcmhwqz2rkxaf4y4a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:22 [openai._base_client] DEBUG: request_id: req_4xbwtgrbys3gohadyl777li447tcxipwwujkcmhwqz2rkxaf4y4a
2026-06-21 03:18:22 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-e982da36-b383-4fe9-86b5-da99058d53df', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            best and fast service \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:22 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:22 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:22 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:22 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:22 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:22 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:24 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:24 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3097'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kd7oro2oftiqahw4bvypgacp67jxjuif5fhgqtmncqazyyk4hpeq'), (b'x-request-id', b'req_kd7oro2oftiqahw4bvypgacp67jxjuif5fhgqtmncqazyyk4hpeq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:24 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:24 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:24 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:24 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:24 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:24 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:24 GMT', 'content-type': 'application/json', 'content-length': '3097', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kd7oro2oftiqahw4bvypgacp67jxjuif5fhgqtmncqazyyk4hpeq', 'x-request-id': 'req_kd7oro2oftiqahw4bvypgacp67jxjuif5fhgqtmncqazyyk4hpeq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:24 [openai._base_client] DEBUG: request_id: req_kd7oro2oftiqahw4bvypgacp67jxjuif5fhgqtmncqazyyk4hpeq
2026-06-21 03:18:24 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-7ce3f7f7-921c-4aed-8a3f-b65b5d03b258', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I genuinely loved the Dum Spicy Paneer 2X Protein Mini Bowl because the flavor felt rich, balanced, and satisfying. The paneer was tender, juicy, and coated beautifully with spicy masala while the rice remained fluffy and aromatic till the last spoon. Delivery was timely and the food came hot with secure hygienic packaging. The freshness of ingredients was clearly noticeable and every bite felt enjoyable. The extra protein quantity made the bowl even more fulfilling. Dum Spicy Paneer 2X Protein Mini Bowl exceeded expectations in quality and presentation. Will definitely order again because the authentic dum flavor was truly enjoyable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:24 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:24 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:24 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:24 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:24 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:24 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:27 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:27 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6525'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_27jkupzhgoznivmom7mqi77vocsiolmq6q6fcbu4pqrrl3nagxma'), (b'x-request-id', b'req_27jkupzhgoznivmom7mqi77vocsiolmq6q6fcbu4pqrrl3nagxma'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:27 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:27 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:27 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:27 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:27 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:27 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:27 GMT', 'content-type': 'application/json', 'content-length': '6525', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_27jkupzhgoznivmom7mqi77vocsiolmq6q6fcbu4pqrrl3nagxma', 'x-request-id': 'req_27jkupzhgoznivmom7mqi77vocsiolmq6q6fcbu4pqrrl3nagxma', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:27 [openai._base_client] DEBUG: request_id: req_27jkupzhgoznivmom7mqi77vocsiolmq6q6fcbu4pqrrl3nagxma
2026-06-21 03:18:27 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-8609d8cb-5e9d-4af1-a4c4-5498d586e6c5', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Coke is missing please refund\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:27 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:27 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:27 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:27 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:27 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:27 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:28 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:28 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2191'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zl5tvxl4nsb2hwknuutxpglqv26w2mdnmdiozb7izvw4tqg3snyq'), (b'x-request-id', b'req_zl5tvxl4nsb2hwknuutxpglqv26w2mdnmdiozb7izvw4tqg3snyq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:28 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:28 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:28 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:28 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:28 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:28 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:28 GMT', 'content-type': 'application/json', 'content-length': '2191', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zl5tvxl4nsb2hwknuutxpglqv26w2mdnmdiozb7izvw4tqg3snyq', 'x-request-id': 'req_zl5tvxl4nsb2hwknuutxpglqv26w2mdnmdiozb7izvw4tqg3snyq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:28 [openai._base_client] DEBUG: request_id: req_zl5tvxl4nsb2hwknuutxpglqv26w2mdnmdiozb7izvw4tqg3snyq
2026-06-21 03:18:28 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-d899844f-f548-49d4-a64e-5fbaf7fea6f2', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            pathetic taste\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:28 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:28 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:28 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:28 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:28 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:28 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:29 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:29 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1708'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_v36pcsww53olpmjhpnk6ks4q333trhgsumhaxbztygnk2pgf4p3q'), (b'x-request-id', b'req_v36pcsww53olpmjhpnk6ks4q333trhgsumhaxbztygnk2pgf4p3q'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:29 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:29 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:29 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:29 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:29 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:29 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:29 GMT', 'content-type': 'application/json', 'content-length': '1708', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_v36pcsww53olpmjhpnk6ks4q333trhgsumhaxbztygnk2pgf4p3q', 'x-request-id': 'req_v36pcsww53olpmjhpnk6ks4q333trhgsumhaxbztygnk2pgf4p3q', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:29 [openai._base_client] DEBUG: request_id: req_v36pcsww53olpmjhpnk6ks4q333trhgsumhaxbztygnk2pgf4p3q
2026-06-21 03:18:29 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-84872e4a-026b-4c9e-8954-8a34f8c568e9', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Chicken keema roll toh ekdam gu tha\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:29 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:29 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:29 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:29 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:29 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:29 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:31 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:31 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3033'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_h3rfj54e3vqjsub4pvkeemmae434bdyjm44s2xzfu7upeo4monmq'), (b'x-request-id', b'req_h3rfj54e3vqjsub4pvkeemmae434bdyjm44s2xzfu7upeo4monmq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:31 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:31 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:31 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:31 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:31 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:31 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:31 GMT', 'content-type': 'application/json', 'content-length': '3033', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_h3rfj54e3vqjsub4pvkeemmae434bdyjm44s2xzfu7upeo4monmq', 'x-request-id': 'req_h3rfj54e3vqjsub4pvkeemmae434bdyjm44s2xzfu7upeo4monmq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:31 [openai._base_client] DEBUG: request_id: req_h3rfj54e3vqjsub4pvkeemmae434bdyjm44s2xzfu7upeo4monmq
2026-06-21 03:18:31 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b993c73d-c94c-4a27-baa9-a67c38ac0008', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            good service 💯💯\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:31 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:31 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:31 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:31 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:31 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:31 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:32 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:32 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2236'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_dmypuwna6xgg7ilj5folb6s3kjaiemxddc4habua3p3imqvuntnq'), (b'x-request-id', b'req_dmypuwna6xgg7ilj5folb6s3kjaiemxddc4habua3p3imqvuntnq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:32 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:32 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:32 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:32 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:32 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:32 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:32 GMT', 'content-type': 'application/json', 'content-length': '2236', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_dmypuwna6xgg7ilj5folb6s3kjaiemxddc4habua3p3imqvuntnq', 'x-request-id': 'req_dmypuwna6xgg7ilj5folb6s3kjaiemxddc4habua3p3imqvuntnq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:32 [openai._base_client] DEBUG: request_id: req_dmypuwna6xgg7ilj5folb6s3kjaiemxddc4habua3p3imqvuntnq
2026-06-21 03:18:32 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b7564370-bde6-4015-bd35-5812d5071595', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Lucknowi Veg Mini Biryani Bowl khane me bahut hi tasty aur satisfying laga. Vegetables ka spicy masala aur rice ka dum flavor bahut amazing combination create kar raha tha. Rice aromatic aur fresh the jo overall meal ko aur enjoyable bana rahe the. Food warm deliver hua aur packaging neatly packed aur hygienic thi. Quantity bhi achhi thi aur quality kaafi premium feel hui. Lucknowi Veg Mini Biryani Bowl ka freshness level bahut impressive laga aur har bite enjoyable thi. Will definitely order again because overall experience bahut delicious tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:32 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:32 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:32 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:32 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:32 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:32 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:34 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:34 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4794'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2inp26aqhq27heouben5b57ot364viy7b3ppnsfshssqi2xwysca'), (b'x-request-id', b'req_2inp26aqhq27heouben5b57ot364viy7b3ppnsfshssqi2xwysca'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:34 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:34 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:34 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:34 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:34 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:34 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:34 GMT', 'content-type': 'application/json', 'content-length': '4794', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2inp26aqhq27heouben5b57ot364viy7b3ppnsfshssqi2xwysca', 'x-request-id': 'req_2inp26aqhq27heouben5b57ot364viy7b3ppnsfshssqi2xwysca', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:34 [openai._base_client] DEBUG: request_id: req_2inp26aqhq27heouben5b57ot364viy7b3ppnsfshssqi2xwysca
2026-06-21 03:18:34 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0ccf16d6-4ef0-44ac-9ac7-438ec134572a', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            we want two biryani order one egg biryani and one kathar biryaani both .hair in my both biryaani \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:34 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:34 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:34 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:34 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:34 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:34 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:39 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:39 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3515'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_fzyjie4xp4fxvf34touiwepud25sdvuplk7wkxgdqjcgsbgzisdq'), (b'x-request-id', b'req_fzyjie4xp4fxvf34touiwepud25sdvuplk7wkxgdqjcgsbgzisdq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:39 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:39 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:39 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:39 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:39 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:39 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:39 GMT', 'content-type': 'application/json', 'content-length': '3515', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_fzyjie4xp4fxvf34touiwepud25sdvuplk7wkxgdqjcgsbgzisdq', 'x-request-id': 'req_fzyjie4xp4fxvf34touiwepud25sdvuplk7wkxgdqjcgsbgzisdq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:39 [openai._base_client] DEBUG: request_id: req_fzyjie4xp4fxvf34touiwepud25sdvuplk7wkxgdqjcgsbgzisdq
2026-06-21 03:18:39 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1d7eea34-9188-4ef4-9f69-f53174b1e5b2', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I genuinely loved the Spicy Veg Dum Biryani Bowl because the freshness and quality both were noticeable from the first bite. The vegetables were perfectly seasoned and had a rich spicy flavor which made the biryani extremely tasty. The rice remained fluffy and aromatic while the masala added extra depth to every spoon. Delivery was quick and the food came hot with secure hygienic packaging. Portion size was enough for a satisfying meal and worth the money paid. Spicy Veg Dum Biryani Bowl exceeded expectations in taste and presentation. Will definitely order again because the flavor felt authentic and memorable.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:39 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:39 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:39 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:39 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:39 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:39 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:44 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:44 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'8352'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_3kugki2fdltxpsqwukh6vefjfr2k7seifej7fcrvvgiwgoljdscq'), (b'x-request-id', b'req_3kugki2fdltxpsqwukh6vefjfr2k7seifej7fcrvvgiwgoljdscq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:44 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:44 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:44 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:44 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:44 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:44 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:44 GMT', 'content-type': 'application/json', 'content-length': '8352', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_3kugki2fdltxpsqwukh6vefjfr2k7seifej7fcrvvgiwgoljdscq', 'x-request-id': 'req_3kugki2fdltxpsqwukh6vefjfr2k7seifej7fcrvvgiwgoljdscq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:44 [openai._base_client] DEBUG: request_id: req_3kugki2fdltxpsqwukh6vefjfr2k7seifej7fcrvvgiwgoljdscq
2026-06-21 03:18:44 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-02316402-09cf-43ae-b0e7-7b4b5c781f04', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Gulab Jamun khane me bahut hi tasty aur satisfying laga. Jamun ka soft texture aur rich chashni ka flavor bahut amazing combination create kar raha tha. Dessert fresh tha aur overall taste bahut enjoyable feel ho raha tha. Packaging neatly packed aur hygienic thi aur delivery bhi timely hui. Quantity achhi thi aur quality kaafi premium feel hui. Freshness aur sweetness ka balance bahut impressive laga. Will definitely order again because Gulab Jamun ka overall experience bahut delicious tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:44 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:44 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:44 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:44 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:44 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:44 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:47 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:47 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6035'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kyao3axdxe3xuktogyp2l7xtba2xy27yleirjympvmrba5llvavq'), (b'x-request-id', b'req_kyao3axdxe3xuktogyp2l7xtba2xy27yleirjympvmrba5llvavq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:47 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:47 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:47 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:47 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:47 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:47 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:47 GMT', 'content-type': 'application/json', 'content-length': '6035', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kyao3axdxe3xuktogyp2l7xtba2xy27yleirjympvmrba5llvavq', 'x-request-id': 'req_kyao3axdxe3xuktogyp2l7xtba2xy27yleirjympvmrba5llvavq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:47 [openai._base_client] DEBUG: request_id: req_kyao3axdxe3xuktogyp2l7xtba2xy27yleirjympvmrba5llvavq
2026-06-21 03:18:47 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-793cd793-eeb9-42b1-8c38-18ad0a90d092', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl honestly bahut hi delicious tha aur iska flavor kaafi authentic laga. Eggs smoky, juicy, aur properly well cooked the jo rice ke saath bahut tasty combination bana rahe the. Bowl came hot and freshness properly maintain thi. Packaging clean aur plastic free type feel ho rahi thi which made the food look premium. Portion size kaafi filling tha aur quality genuinely value for money lagi. Spices aur aroma ne overall taste ko aur enhance kar diya.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:47 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:47 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:47 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:47 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:47 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:47 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:51 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:51 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6297'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ab3h3ssluoswaum4zx6v5ukbejbcwcxbj5qff4giqul6e5zsdhwq'), (b'x-request-id', b'req_ab3h3ssluoswaum4zx6v5ukbejbcwcxbj5qff4giqul6e5zsdhwq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:51 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:51 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:51 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:51 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:51 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:51 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:51 GMT', 'content-type': 'application/json', 'content-length': '6297', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ab3h3ssluoswaum4zx6v5ukbejbcwcxbj5qff4giqul6e5zsdhwq', 'x-request-id': 'req_ab3h3ssluoswaum4zx6v5ukbejbcwcxbj5qff4giqul6e5zsdhwq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:51 [openai._base_client] DEBUG: request_id: req_ab3h3ssluoswaum4zx6v5ukbejbcwcxbj5qff4giqul6e5zsdhwq
2026-06-21 03:18:51 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9e786bf8-cc91-419d-9228-9c87ae45f1cb', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            \nI really loved the Rasmalai because it tasted fresh and premium. The texture of the rasmalai pieces was soft and smooth while the milk was creamy and flavorful. Sweetness was balanced perfectly which made the dessert even more enjoyable. Delivery was quick and the Rasmalai arrived chilled with proper packaging. Dry fruits and kesar flavor enhanced the overall taste beautifully. The dessert felt authentic and high quality in every bite. Portion size was satisfying and worth the money. Overall, the Rasmalai exceeded my expectations and became one of the best desserts I have ordered online recently.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:51 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:51 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:51 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:51 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:51 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:51 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:54 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:54 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7115'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_e6bwthmudhy7rejnenf4a4yyd6bq5sqhn7ufph23xwkly7hbuyhq'), (b'x-request-id', b'req_e6bwthmudhy7rejnenf4a4yyd6bq5sqhn7ufph23xwkly7hbuyhq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:54 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:54 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:54 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:54 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:54 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:54 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:54 GMT', 'content-type': 'application/json', 'content-length': '7115', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_e6bwthmudhy7rejnenf4a4yyd6bq5sqhn7ufph23xwkly7hbuyhq', 'x-request-id': 'req_e6bwthmudhy7rejnenf4a4yyd6bq5sqhn7ufph23xwkly7hbuyhq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:54 [openai._base_client] DEBUG: request_id: req_e6bwthmudhy7rejnenf4a4yyd6bq5sqhn7ufph23xwkly7hbuyhq
2026-06-21 03:18:54 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-0dd1d9ed-fb91-442e-9ba6-dd943bcb3553', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Dum Spicy Egg 2X Protein Mini Bowl honestly bahut hi delicious tha aur iska flavor kaafi authentic laga. Eggs smoky, juicy, aur properly well cooked the jo rice ke saath bahut tasty combination bana rahe the. Bowl came hot and freshness properly maintain thi. Packaging clean aur plastic free type feel ho rahi thi which made the food look premium. Portion size kaafi filling tha aur quality genuinely value for money lagi. Spices aur aroma ne overall taste ko aur enhance kar diya.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:54 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:54 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:54 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:54 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:54 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:54 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:18:57 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:18:57 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5000'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_op74eksdj6szvnkufng4lewze3ugnjqcjoh2jlsbxcn6qm3e7p2a'), (b'x-request-id', b'req_op74eksdj6szvnkufng4lewze3ugnjqcjoh2jlsbxcn6qm3e7p2a'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:18:57 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:18:57 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:18:57 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:18:57 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:18:57 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:18:57 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:18:57 GMT', 'content-type': 'application/json', 'content-length': '5000', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_op74eksdj6szvnkufng4lewze3ugnjqcjoh2jlsbxcn6qm3e7p2a', 'x-request-id': 'req_op74eksdj6szvnkufng4lewze3ugnjqcjoh2jlsbxcn6qm3e7p2a', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:18:57 [openai._base_client] DEBUG: request_id: req_op74eksdj6szvnkufng4lewze3ugnjqcjoh2jlsbxcn6qm3e7p2a
2026-06-21 03:18:57 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-7a900f15-b0d8-4b9d-adf4-1114b38e16bc', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            Double Egg Roll honestly bahut hi delicious tha aur iska flavor kaafi authentic laga. Eggs soft aur flavorful the aur spices perfectly balanced the. Wrap fresh aur soft tha aur sauces ne overall taste ko aur enhance kar diya. Food warm deliver hua aur packaging bhi properly sealed thi. Portion size kaafi filling tha aur quality genuinely impressive lagi. Double Egg Roll ka spicy street style flavor har bite ko super tasty bana raha tha.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:18:57 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:18:57 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:18:57 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:18:57 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:18:57 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:18:57 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:19:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:19:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5927'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ykywof2yt5dgmgyhv4haxfrzp7tc3cvpeek7cp4ys7c3tf2dxviq'), (b'x-request-id', b'req_ykywof2yt5dgmgyhv4haxfrzp7tc3cvpeek7cp4ys7c3tf2dxviq'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:19:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:19:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:19:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:19:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:19:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:19:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:19:02 GMT', 'content-type': 'application/json', 'content-length': '5927', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ykywof2yt5dgmgyhv4haxfrzp7tc3cvpeek7cp4ys7c3tf2dxviq', 'x-request-id': 'req_ykywof2yt5dgmgyhv4haxfrzp7tc3cvpeek7cp4ys7c3tf2dxviq', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:19:02 [openai._base_client] DEBUG: request_id: req_ykywof2yt5dgmgyhv4haxfrzp7tc3cvpeek7cp4ys7c3tf2dxviq
2026-06-21 03:19:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-afe5b057-c04a-4c4c-8433-44348a63e644', 'content': None, 'json_data': {'input': ' You are an expert restaurant review analyst.\n                            Analyze the customer review using Aspect-Based Sentiment Analysis (ABSA).\n                            Your job is to identify every distinct aspect mentioned in the review and classify each one.\n                            Use this taxonomy of aspects and corresponding subcategories/root:\n                            Food:\n                            - Taste\n                            - Food Quality\n                            - Portion Size / Quantity\n                            - Freshness\n                            - Presentation\n                            - Food Temperature\n                            - Consistency\n                            - Menu Variety\n                            Service:\n                            - Staff Behavior\n                            - Friendliness\n                            - Attentiveness\n                            - Speed of Service\n                            - Order Accuracy\n                            - Problem Resolution\n                            Delivery:\n                            - Delivery Time\n                            - Packaging Quality\n                            - Food Spillage\n                            - Order Completeness\n                            - Food Condition on Arrival\n                            Value:\n                            - Pricing\n                            - Value for Money\n                            Hygiene:\n                            - Cleanliness\n                            - Food Safety\n                            Ambience:\n                            - Seating\n                            - Noise\n                            - Lighting\n                            - Comfort\n                            For each aspect detected, return:\n                            1. aspect\n                            2. subcategory/root cause\n                            3. sentiment (Positive, Negative, Neutral, Mixed)\n                            4. severity (Low, Medium, High)\n                            5. intent (Praise, Complaint, Suggestion, Refund Request, Churn Risk, Loyalty Signal)\n                            6. evidence (exact phrase from the review supporting the classification)\n                            Rules:\n                            - A single review may contain multiple aspects.\n                            - Extract ALL aspects mentioned.\n                            - Do not infer aspects not mentioned.\n                            - Do not infer subcategories not mentioned.\n                            - If one sentence contains both positive and negative signals for the same aspect, mark sentiment as Mixed.\n                            - Be strict and operationally useful.\n                            - Focus on actionable business insights.\n                            - Also provide an overall review sentiment (Positive, Negative, Neutral, Mixed).\n                            Return output ONLY in valid JSON using this format:\n                            {\n                            "overall_sentiment": "",\n                            "aspects": \n                                {\n                                "aspect": "",\n                                "subcategory": "",\n                                "sentiment": "",\n                                "severity": "",\n                                "intent": "",\n                                "evidence": ""\n                                }\n                            }\n\n                            Customer Review:\n                            I really enjoyed the Paneer Tikka Roll because the stuffing tasted fresh and perfectly seasoned. Paneer pieces were juicy and had a smoky texture which paired beautifully with the wrap.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-21 03:19:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-21 03:19:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-21 03:19:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-21 03:19:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-21 03:19:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-21 03:19:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-21 03:19:03 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Sun, 21 Jun 2026 03:19:03 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3012'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_w2fi35zklslpoclun6k7pntxlhcy642uae44ztwi37q3j4m7kyza'), (b'x-request-id', b'req_w2fi35zklslpoclun6k7pntxlhcy642uae44ztwi37q3j4m7kyza'), (b'vary', b'origin, access-control-request-method, access-control-request-headers'), (b'access-control-allow-origin', b'*'), (b'access-control-expose-headers', b'x-amzn-requestid,x-request-id,date')])
2026-06-21 03:19:03 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-21 03:19:03 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-21 03:19:03 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-21 03:19:03 [httpcore.http11] DEBUG: response_closed.started
2026-06-21 03:19:03 [httpcore.http11] DEBUG: response_closed.complete
2026-06-21 03:19:03 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Sun, 21 Jun 2026 03:19:03 GMT', 'content-type': 'application/json', 'content-length': '3012', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_w2fi35zklslpoclun6k7pntxlhcy642uae44ztwi37q3j4m7kyza', 'x-request-id': 'req_w2fi35zklslpoclun6k7pntxlhcy642uae44ztwi37q3j4m7kyza', 'vary': 'origin, access-control-request-method, access-control-request-headers', 'access-control-allow-origin': '*', 'access-control-expose-headers': 'x-amzn-requestid,x-request-id,date'})
2026-06-21 03:19:03 [openai._base_client] DEBUG: request_id: req_w2fi35zklslpoclun6k7pntxlhcy642uae44ztwi37q3j4m7kyza
2026-06-21 03:19:03 [urllib3.connectionpool] DEBUG: Starting new HTTP connection (1): 43.204.103.156:6800
2026-06-21 03:19:03 [urllib3.connectionpool] DEBUG: http://43.204.103.156:6800 "POST /schedule.json HTTP/1.1" 200 93
2026-06-21 03:19:03 [scrapy.statscollectors] INFO: Dumping Scrapy stats:
{'downloader/request_bytes': 9857165,
 'downloader/request_count': 1717,
 'downloader/request_method_count/GET': 1717,
 'downloader/response_bytes': 8284935,
 'downloader/response_count': 1717,
 'downloader/response_status_count/200': 1717,
 'elapsed_time_seconds': 764.98539,
 'finish_reason': 'finished',
 'finish_time': datetime.datetime(2026, 6, 21, 3, 19, 3, 830615, tzinfo=datetime.timezone.utc),
 'httpcompression/response_bytes': 3575714,
 'httpcompression/response_count': 540,
 'item_scraped_count': 540,
 'items_per_minute': None,
 'log_count/DEBUG': 4186,
 'log_count/INFO': 154,
 'log_count/WARNING': 35,
 'memusage/max': 160972800,
 'memusage/startup': 145608704,
 'request_depth_max': 5,
 'response_received_count': 1717,
 'responses_per_minute': None,
 'scheduler/dequeued': 1717,
 'scheduler/dequeued/memory': 1717,
 'scheduler/enqueued': 1717,
 'scheduler/enqueued/memory': 1717,
 'start_time': datetime.datetime(2026, 6, 21, 3, 6, 18, 845225, tzinfo=datetime.timezone.utc)}
2026-06-21 03:19:03 [scrapy.core.engine] INFO: Spider closed (finished)
2026-06-21 03:19:03 [httpcore.connection] DEBUG: close.started
2026-06-21 03:19:03 [httpcore.connection] DEBUG: close.complete