2026-06-24 03:11:48 [scrapy.utils.log] INFO: Scrapy 2.12.0 started (bot: ZomatoReviewData)
2026-06-24 03:11:48 [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
2026-06-24 03:11:48 [scrapy.addons] INFO: Enabled addons:
[]
2026-06-24 03:11:48 [asyncio] DEBUG: Using selector: EpollSelector
2026-06-24 03:11:48 [scrapy.utils.log] DEBUG: Using reactor: twisted.internet.asyncioreactor.AsyncioSelectorReactor
2026-06-24 03:11:48 [scrapy.utils.log] DEBUG: Using asyncio event loop: asyncio.unix_events._UnixSelectorEventLoop
2026-06-24 03:11:48 [scrapy.utils.log] DEBUG: Using reactor: twisted.internet.asyncioreactor.AsyncioSelectorReactor
2026-06-24 03:11:48 [scrapy.utils.log] DEBUG: Using asyncio event loop: asyncio.unix_events._UnixSelectorEventLoop
2026-06-24 03:11:48 [scrapy.extensions.telnet] INFO: Telnet Password: b2682cf5eb6cb494
2026-06-24 03:11:48 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.corestats.CoreStats',
 'scrapy.extensions.telnet.TelnetConsole',
 'scrapy.extensions.memusage.MemoryUsage',
 'scrapy.extensions.logstats.LogStats']
2026-06-24 03:11:48 [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_dining_review_data/6d6ce0cb6f7a11f1997e0aab37b1cebd.log',
 'NEWSPIDER_MODULE': 'ZomatoReviewData.spiders',
 'SPIDER_MODULES': ['ZomatoReviewData.spiders'],
 'TWISTED_REACTOR': 'twisted.internet.asyncioreactor.AsyncioSelectorReactor'}
2026-06-24 03:11:48 [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']
2026-06-24 03:11:48 [scrapy.middleware] INFO: Enabled spider middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
 'scrapy.spidermiddlewares.referer.RefererMiddleware',
 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
 'scrapy.spidermiddlewares.depth.DepthMiddleware']
2026-06-24 03:11:48 [scrapy.middleware] INFO: Enabled item pipelines:
['ZomatoReviewData.pipelines.ZomatoreviewdataPipeline']
2026-06-24 03:11:48 [scrapy.core.engine] INFO: Spider opened
2026-06-24 03:11:48 [scrapy.extensions.logstats] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2026-06-24 03:11:48 [scrapy.extensions.telnet] INFO: Telnet console listening on 127.0.0.1:6024
2026-06-24 03:11:48 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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.

2026-06-24 03:11:51 [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)
2026-06-24 03:11:51 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:51 [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)
2026-06-24 03:11:51 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:52 [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)
2026-06-24 03:11:52 [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)
2026-06-24 03:11:52 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:52 [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)
2026-06-24 03:11:52 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:52 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:53 [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)
2026-06-24 03:11:53 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:53 [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)
2026-06-24 03:11:53 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:53 [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)
2026-06-24 03:11:53 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:53 [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)
2026-06-24 03:11:53 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:53 [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)
2026-06-24 03:11:53 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:54 [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)
2026-06-24 03:11:54 [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)
2026-06-24 03:11:54 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:54 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:54 [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)
2026-06-24 03:11:54 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:54 [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)
2026-06-24 03:11:54 [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)
2026-06-24 03:11:54 [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)
2026-06-24 03:11:55 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:55 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:55 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:56 [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)
2026-06-24 03:11:56 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:57 [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)
2026-06-24 03:11:57 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:57 [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)
2026-06-24 03:11:57 [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)
2026-06-24 03:11:57 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:57 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:57 [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)
2026-06-24 03:11:57 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:57 [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)
2026-06-24 03:11:58 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:58 [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)
2026-06-24 03:11:58 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:58 [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)
2026-06-24 03:11:58 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:11:59 [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)
2026-06-24 03:11:59 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:00 [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)
2026-06-24 03:12:00 [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)
2026-06-24 03:12:01 [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)
2026-06-24 03:12:01 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:01 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:01 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:01 [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)
2026-06-24 03:12:01 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:01 [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)
2026-06-24 03:12:01 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:01 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:02 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:02 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:02 [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)
2026-06-24 03:12:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:03 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:06 [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)
2026-06-24 03:12:06 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:12:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:10 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:14 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:15 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:16 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:17 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:19 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:19 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:19 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:19 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:20 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:20 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:20 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:23 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:23 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:25 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:25 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:26 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:26 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:26 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:27 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:27 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:32 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:32 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:33 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:33 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:33 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:34 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:34 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:35 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:37 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:38 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:39 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:40 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:41 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:41 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:41 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:46 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:46 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:48 [scrapy.extensions.logstats] INFO: Crawled 162 pages (at 162 pages/min), scraped 0 items (at 0 items/min)
2026-06-24 03:12:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:49 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:49 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:49 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:49 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:50 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:50 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:52 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:52 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:53 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:53 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:54 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:54 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:54 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:54 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:57 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:57 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:58 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:58 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:58 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:58 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:58 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:59 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:59 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:12:59 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:00 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:00 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:01 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:01 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:01 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:01 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:02 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:03 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:04 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:05 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:07 [scrapy.core.downloader.handlers.http11] WARNING: Got data loss in https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite. If you want to process broken responses set the setting DOWNLOAD_FAIL_ON_DATALOSS = False -- This message won't be shown in further requests
2026-06-24 03:13:07 [scrapy.downloadermiddlewares.retry] DEBUG: Retrying <GET https://api.zomato.com/merchant-gw/web/restaurant/get-all-minimal-lite> (failed 1 times): [<twisted.python.failure.Failure twisted.internet.error.ConnectionLost: Connection to the other side was lost in a non-clean fashion: Connection lost.>, <twisted.python.failure.Failure twisted.web.http._DataLoss: Chunked decoder in 'CHUNK_LENGTH' state, still expecting more data to get to 'FINISHED' state.>]
2026-06-24 03:13:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:16 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:16 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:19 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:20 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:20 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:20 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:20 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:21 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:21 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:21 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:23 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:26 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:26 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:27 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:27 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:27 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:34 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:34 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:40 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:40 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:40 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:41 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:41 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:41 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:42 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:42 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:42 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:47 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:47 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:48 [scrapy.extensions.logstats] INFO: Crawled 322 pages (at 160 pages/min), scraped 0 items (at 0 items/min)
2026-06-24 03:13:48 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:50 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:50 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:51 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:51 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:51 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:51 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:52 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:52 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:53 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:53 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:53 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:54 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:54 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:54 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:55 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:55 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:55 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:55 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:56 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:56 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:56 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:57 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:57 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:57 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:59 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:59 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:59 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:13:59 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:01 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:02 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:02 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:04 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:04 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:05 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:05 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:05 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:05 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:06 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:06 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:07 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:08 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:09 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:09 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:10 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:10 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:10 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:11 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:12 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:13 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:14 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:14 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:14 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:15 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:15 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:16 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:16 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:17 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:18 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:19 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:19 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:19 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=474931768> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:19 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=474931768>
None
2026-06-24 03:14:20 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=475050554> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:20 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=35658&review_id=475050554>
None
2026-06-24 03:14:20 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=475052734> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=475052734>
None
2026-06-24 03:14:21 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:21 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=474771291> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:21 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=48924&review_id=474771291>
None
2026-06-24 03:14:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:22 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18670791&review_id=463108730> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:22 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=18670791&review_id=463108730>
None
2026-06-24 03:14:22 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=474654887> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=474654887>
None
2026-06-24 03:14:23 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=474656564> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:23 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:23 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20583150&review_id=474656564>
None
2026-06-24 03:14:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:24 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:25 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:25 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21389292&review_id=474776399> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:25 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21389292&review_id=474776399>
None
2026-06-24 03:14:26 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=474873994> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:26 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20823682&review_id=474873994>
None
2026-06-24 03:14:26 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:27 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20631505&review_id=475031649> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:27 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21019923&review_id=474979249> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20631505&review_id=475031649>
None
2026-06-24 03:14:27 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21019923&review_id=474979249>
None
2026-06-24 03:14:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:28 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:29 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:29 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:31 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:32 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:33 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:34 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:35 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:36 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:37 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:38 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:39 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:40 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:41 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:41 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:41 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:41 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:42 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:43 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:45 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:46 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:46 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:48 [scrapy.extensions.logstats] INFO: Crawled 492 pages (at 170 pages/min), scraped 11 items (at 11 items/min)
2026-06-24 03:14:49 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:50 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:51 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:52 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:52 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=475084116> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:52 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=475084116>
None
2026-06-24 03:14:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=475084268> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=475084268>
None
2026-06-24 03:14:53 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474813856> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:53 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474813856>
None
2026-06-24 03:14:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474832465> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474832465>
None
2026-06-24 03:14:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474816770> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474816770>
None
2026-06-24 03:14:54 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474874490> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:54 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20627254&review_id=474874490>
None
2026-06-24 03:14:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:55 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=475081181> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:55 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21196973&review_id=475081181>
None
2026-06-24 03:14:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:55 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:56 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:56 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:57 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:57 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:57 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:58 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:14:59 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:00 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:01 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:01 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:01 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:02 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:02 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:03 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:04 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:04 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:05 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:06 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:07 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:08 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:09 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:10 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:11 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:12 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:13 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:14 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19310144&review_id=474780356> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:14 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19310144&review_id=474780356>
None
2026-06-24 03:15:14 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:15 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:16 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:16 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19129110&review_id=475065416> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:16 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=19129110&review_id=475065416>
None
2026-06-24 03:15:17 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:18 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:18 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:18 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:18 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:19 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:19 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:19 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:20 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:20 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:21 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:22 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:23 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:23 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:23 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:24 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:25 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:25 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:25 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:26 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:26 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:27 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:27 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:28 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:29 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:29 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20918603&review_id=474991944> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:29 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20918603&review_id=474991944>
None
2026-06-24 03:15:29 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:29 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:30 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20400105&review_id=474865519> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20400105&review_id=474865519>
None
2026-06-24 03:15:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20379354&review_id=475020604> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:31 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20379354&review_id=475020604>
None
2026-06-24 03:15:31 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474796525> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474796525>
None
2026-06-24 03:15:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474780025> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:32 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474792435> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474780025>
None
2026-06-24 03:15:32 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474792435>
None
2026-06-24 03:15:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20918660&review_id=475012826> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20918660&review_id=475012826>
None
2026-06-24 03:15:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20379354&review_id=475038955> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20379354&review_id=475038955>
None
2026-06-24 03:15:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20297585&review_id=474925174> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:33 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474961435> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20297585&review_id=474925174>
None
2026-06-24 03:15:33 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21155912&review_id=474961435>
None
2026-06-24 03:15:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=474865309> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474796947> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=474865309>
None
2026-06-24 03:15:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474796947>
None
2026-06-24 03:15:34 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=474994993> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:34 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=474994993>
None
2026-06-24 03:15:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=475004422> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:35 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20281056&review_id=475004422>
None
2026-06-24 03:15:35 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474843842> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474843842>
None
2026-06-24 03:15:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474849758> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=474849758>
None
2026-06-24 03:15:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20454622&review_id=475021659> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20454622&review_id=475021659>
None
2026-06-24 03:15:36 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=475012808> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:36 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121242&review_id=475012808>
None
2026-06-24 03:15:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=474814862> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:37 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20916935&review_id=474721058> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=474814862>
None
2026-06-24 03:15:37 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20916935&review_id=474721058>
None
2026-06-24 03:15:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20132118&review_id=474976135> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20132118&review_id=474976135>
None
2026-06-24 03:15:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=474879393> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=474879393>
None
2026-06-24 03:15:38 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20337226&review_id=474809605> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:38 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20337226&review_id=474809605>
None
2026-06-24 03:15:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121262&review_id=475021374> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:39 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475001443> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121262&review_id=475021374>
None
2026-06-24 03:15:39 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475001443>
None
2026-06-24 03:15:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121262&review_id=474960077> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=21121262&review_id=474960077>
None
2026-06-24 03:15:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243603&review_id=474957945> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243603&review_id=474957945>
None
2026-06-24 03:15:40 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243603&review_id=474947285> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:40 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243603&review_id=474947285>
None
2026-06-24 03:15:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475046839> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475050169> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475046839>
None
2026-06-24 03:15:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22243456&review_id=475050169>
None
2026-06-24 03:15:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20132118&review_id=475042432> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:41 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20132118&review_id=475042432>
None
2026-06-24 03:15:41 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=474818595> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=474818595>
None
2026-06-24 03:15:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20400105&review_id=475019606> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:42 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20400105&review_id=475019606>
None
2026-06-24 03:15:42 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=475032785> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:43 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=20356956&review_id=475032785>
None
2026-06-24 03:15:43 [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)
2026-06-24 03:15:43 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:15:44 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:44 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:45 [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)
2026-06-24 03:15:45 [py.warnings] WARNING: /home/ubuntu/eggs/ZomatoReviewData/1777988462.egg/ZomatoReviewData/spiders/ZomatoDiningReviewData.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)

2026-06-24 03:15:45 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:46 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:46 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:47 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:48 [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=dining&offset=0&start_date=2026-06-24&end_date=2026-06-24> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:48 [scrapy.extensions.logstats] INFO: Crawled 652 pages (at 160 pages/min), scraped 54 items (at 43 items/min)
2026-06-24 03:15:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:49 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:50 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:50 [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=dining&offset=0&start_date=2026-06-23&end_date=2026-06-23> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:51 [scrapy.core.engine] DEBUG: Crawled (200) <GET https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22286044&review_id=474972056> (referer: https://www.zomato.com/partners/login)
2026-06-24 03:15:51 [scrapy.core.scraper] DEBUG: Scraped from <200 https://api.zomato.com/merchant-gw/web/reviews/get/details?res_id=22286044&review_id=474972056>
None
2026-06-24 03:15:51 [scrapy.core.engine] INFO: Closing spider (finished)
2026-06-24 03:15:52 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-aa13910c-2e96-4249-b322-2a03f8089c48', '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                            anish sir was great at service \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:15:52 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:15:52 [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
2026-06-24 03:15:52 [httpcore.connection] DEBUG: connect_tcp.complete return_value=<httpcore._backends.sync.SyncStream object at 0x7b1aee3f3590>
2026-06-24 03:15:52 [httpcore.connection] DEBUG: start_tls.started ssl_context=<ssl.SSLContext object at 0x7b1aee6cc350> server_hostname='bedrock-mantle.ap-south-1.api.aws' timeout=5.0
2026-06-24 03:15:52 [httpcore.connection] DEBUG: start_tls.complete return_value=<httpcore._backends.sync.SyncStream object at 0x7b1aee4a3ad0>
2026-06-24 03:15:52 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:15:52 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:15:52 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:15:52 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:15:52 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:15:53 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:15:53 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2629'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ltbg64ri7rab6znniilwrdt4nvh4qi76mehe7wffhsf2ja55bwoa'), (b'x-request-id', b'req_ltbg64ri7rab6znniilwrdt4nvh4qi76mehe7wffhsf2ja55bwoa'), (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')])
2026-06-24 03:15:53 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:15:53 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:15:53 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:15:53 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:15:53 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:15:53 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:15:53 GMT', 'content-type': 'application/json', 'content-length': '2629', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ltbg64ri7rab6znniilwrdt4nvh4qi76mehe7wffhsf2ja55bwoa', 'x-request-id': 'req_ltbg64ri7rab6znniilwrdt4nvh4qi76mehe7wffhsf2ja55bwoa', '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'})
2026-06-24 03:15:53 [openai._base_client] DEBUG: request_id: req_ltbg64ri7rab6znniilwrdt4nvh4qi76mehe7wffhsf2ja55bwoa
2026-06-24 03:15:53 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fd1112f7-d3cf-4345-9c89-4b682ec1e978', '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                            Captain Rajesh Mondal was very helpful and through out our experience in Gurukripa from the time we entered till the time we left he was on his toes and ever ready to provide us with excellent and delightful service experience. Kudos to him and cheers.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:15:53 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:15:53 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:15:53 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:15:53 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:15:53 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:15:53 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:15:56 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:15:56 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3853'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_5ipoqv6yj6exph4wqcito6ao2nfpafsc2fbosmvwhkytqt5ijcbq'), (b'x-request-id', b'req_5ipoqv6yj6exph4wqcito6ao2nfpafsc2fbosmvwhkytqt5ijcbq'), (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')])
2026-06-24 03:15:56 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:15:56 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:15:56 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:15:56 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:15:56 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:15:56 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:15:56 GMT', 'content-type': 'application/json', 'content-length': '3853', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_5ipoqv6yj6exph4wqcito6ao2nfpafsc2fbosmvwhkytqt5ijcbq', 'x-request-id': 'req_5ipoqv6yj6exph4wqcito6ao2nfpafsc2fbosmvwhkytqt5ijcbq', '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'})
2026-06-24 03:15:56 [openai._base_client] DEBUG: request_id: req_5ipoqv6yj6exph4wqcito6ao2nfpafsc2fbosmvwhkytqt5ijcbq
2026-06-24 03:15:56 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-912db2fa-8b00-4f6a-9399-3113a2fa5d90', '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                            Excellent service by Kartik and Zeeshan!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:15:56 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:15:56 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:15:56 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:15:56 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:15:56 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:15:56 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:15:57 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:15:57 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2265'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_hp2qeaoahn2yxciozfhbhbgplbg7hxstmw3p74a4bhtdfnl6kp4a'), (b'x-request-id', b'req_hp2qeaoahn2yxciozfhbhbgplbg7hxstmw3p74a4bhtdfnl6kp4a'), (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')])
2026-06-24 03:15:57 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:15:57 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:15:57 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:15:57 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:15:57 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:15:57 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:15:57 GMT', 'content-type': 'application/json', 'content-length': '2265', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_hp2qeaoahn2yxciozfhbhbgplbg7hxstmw3p74a4bhtdfnl6kp4a', 'x-request-id': 'req_hp2qeaoahn2yxciozfhbhbgplbg7hxstmw3p74a4bhtdfnl6kp4a', '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'})
2026-06-24 03:15:57 [openai._base_client] DEBUG: request_id: req_hp2qeaoahn2yxciozfhbhbgplbg7hxstmw3p74a4bhtdfnl6kp4a
2026-06-24 03:15:57 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-4f9f5ba0-26fc-44ab-a713-b8e11507e8ba', '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                            Jasim, Karthik and Shakeel were very good and they helped us decide the menu and suggested good food\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:15:57 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:15:57 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:15:57 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:15:57 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:15:57 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:15:57 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:15:59 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:15:59 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3793'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_g4bzfjlci7oqlcttussq7h5jbpst5ll67if6amg4kr6tryfozcsq'), (b'x-request-id', b'req_g4bzfjlci7oqlcttussq7h5jbpst5ll67if6amg4kr6tryfozcsq'), (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')])
2026-06-24 03:15:59 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:15:59 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:15:59 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:15:59 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:15:59 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:15:59 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:15:59 GMT', 'content-type': 'application/json', 'content-length': '3793', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_g4bzfjlci7oqlcttussq7h5jbpst5ll67if6amg4kr6tryfozcsq', 'x-request-id': 'req_g4bzfjlci7oqlcttussq7h5jbpst5ll67if6amg4kr6tryfozcsq', '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'})
2026-06-24 03:15:59 [openai._base_client] DEBUG: request_id: req_g4bzfjlci7oqlcttussq7h5jbpst5ll67if6amg4kr6tryfozcsq
2026-06-24 03:15:59 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b17771f9-8cd7-43a3-a42b-0811ddc73ae6', '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 had the Mushroom Chilli and Veg Hakka Noodles. The Mushroom Chilli was good, and the noodles were light and easy to eat, though they could have been\n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:15:59 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:15:59 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:15:59 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:15:59 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:15:59 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:15:59 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4440'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ucffyx2kg4snkh2f5ih7bq53ukwaibt6rqkcrmt4u6ordfeuom7q'), (b'x-request-id', b'req_ucffyx2kg4snkh2f5ih7bq53ukwaibt6rqkcrmt4u6ordfeuom7q'), (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')])
2026-06-24 03:16:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:02 GMT', 'content-type': 'application/json', 'content-length': '4440', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ucffyx2kg4snkh2f5ih7bq53ukwaibt6rqkcrmt4u6ordfeuom7q', 'x-request-id': 'req_ucffyx2kg4snkh2f5ih7bq53ukwaibt6rqkcrmt4u6ordfeuom7q', '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'})
2026-06-24 03:16:02 [openai._base_client] DEBUG: request_id: req_ucffyx2kg4snkh2f5ih7bq53ukwaibt6rqkcrmt4u6ordfeuom7q
2026-06-24 03:16:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-cf7a582e-8b59-4fd3-839e-1c9419443dd3', '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                            sarfraz the outstanding person I meet at Shalimar kurla branch the food is great \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:03 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:03 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2508'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_okxlbg33wn66rujiarolan7bomo6z4devvg5berojviqoysvyozq'), (b'x-request-id', b'req_okxlbg33wn66rujiarolan7bomo6z4devvg5berojviqoysvyozq'), (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')])
2026-06-24 03:16:03 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:03 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:03 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:03 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:03 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:03 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:03 GMT', 'content-type': 'application/json', 'content-length': '2508', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_okxlbg33wn66rujiarolan7bomo6z4devvg5berojviqoysvyozq', 'x-request-id': 'req_okxlbg33wn66rujiarolan7bomo6z4devvg5berojviqoysvyozq', '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'})
2026-06-24 03:16:03 [openai._base_client] DEBUG: request_id: req_okxlbg33wn66rujiarolan7bomo6z4devvg5berojviqoysvyozq
2026-06-24 03:16:03 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-90736caf-13b6-4fb7-8c62-218d850e504c', '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                            Food was as delicious as always but the polite service and awesome food recommendations by Sarfaraaz deserve a special mention here\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:03 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:03 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:03 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:03 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:03 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:03 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:05 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:05 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3119'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rupzwrr3udmaiod4x7m3ka6crhbpklpvdjpiz3d5uu7nrbjwhria'), (b'x-request-id', b'req_rupzwrr3udmaiod4x7m3ka6crhbpklpvdjpiz3d5uu7nrbjwhria'), (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')])
2026-06-24 03:16:05 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:05 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:05 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:05 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:05 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:05 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:05 GMT', 'content-type': 'application/json', 'content-length': '3119', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rupzwrr3udmaiod4x7m3ka6crhbpklpvdjpiz3d5uu7nrbjwhria', 'x-request-id': 'req_rupzwrr3udmaiod4x7m3ka6crhbpklpvdjpiz3d5uu7nrbjwhria', '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'})
2026-06-24 03:16:05 [openai._base_client] DEBUG: request_id: req_rupzwrr3udmaiod4x7m3ka6crhbpklpvdjpiz3d5uu7nrbjwhria
2026-06-24 03:16:05 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-eebc1e6d-ed5c-4329-ad00-9f662fdb4482', '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                            Finally visited Blabber All Day in Thane, and honestly, this café is every aesthetic lover\'s dream! From the cute teddy-themed interiors to the cozy vibe, the place instantly feels warm and inviting.\n\nWe tried a bunch of dishes, and everything looked absolutely stunning on the table. The drinks were super refreshing and definitely Instagram-worthy. The starters and mains were equally satisfying, with good portions and flavours that didn\'t disappoint.\n\nBut the real highlight of our visit had to be the Deconstructed Brownie. It was rich, indulgent, and easily one of the best desserts we\'ve had in a while. Trust me, this is one dish you simply cannot skip!\n\nApart from the food, the ambience is what truly stands out. Whether you\'re planning a brunch date, catching up with friends, or spending some quality time with family, this place fits every occasion perfectly.\n\nOverall, Blabber All Day offers a great mix of good food, beautiful aesthetics, and a cozy atmosphere. Definitely a café worth visiting if you\'re in Thane!\n\n\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:05 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:05 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:05 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:05 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:05 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:05 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:10 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:10 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'8222'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_uxa27vrny3q3tngentlosytcws2vny4jgi53x3bd5p2fs4jeh7sa'), (b'x-request-id', b'req_uxa27vrny3q3tngentlosytcws2vny4jgi53x3bd5p2fs4jeh7sa'), (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')])
2026-06-24 03:16:10 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:10 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:10 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:10 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:10 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:10 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:10 GMT', 'content-type': 'application/json', 'content-length': '8222', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_uxa27vrny3q3tngentlosytcws2vny4jgi53x3bd5p2fs4jeh7sa', 'x-request-id': 'req_uxa27vrny3q3tngentlosytcws2vny4jgi53x3bd5p2fs4jeh7sa', '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'})
2026-06-24 03:16:10 [openai._base_client] DEBUG: request_id: req_uxa27vrny3q3tngentlosytcws2vny4jgi53x3bd5p2fs4jeh7sa
2026-06-24 03:16:10 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f0ca633c-cdbb-4d8a-a425-92caf8caed0a', '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                            All good\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:10 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:10 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:10 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:10 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:10 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:10 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1602'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_w3xe6vtnyfizwllb7v2faprpxkmkk2z2hff4pfgqjvzn2u6hziba'), (b'x-request-id', b'req_w3xe6vtnyfizwllb7v2faprpxkmkk2z2hff4pfgqjvzn2u6hziba'), (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')])
2026-06-24 03:16:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:11 GMT', 'content-type': 'application/json', 'content-length': '1602', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_w3xe6vtnyfizwllb7v2faprpxkmkk2z2hff4pfgqjvzn2u6hziba', 'x-request-id': 'req_w3xe6vtnyfizwllb7v2faprpxkmkk2z2hff4pfgqjvzn2u6hziba', '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'})
2026-06-24 03:16:11 [openai._base_client] DEBUG: request_id: req_w3xe6vtnyfizwllb7v2faprpxkmkk2z2hff4pfgqjvzn2u6hziba
2026-06-24 03:16:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6c0f6a9b-c4b9-4c28-89f8-3c02b6396868', '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                            Visited here on 2 occasions and the waiter interrupted us 10 times on both the occasions..also asked us whether we were done even when we had food on our place on the pretext that others were waiting when there was literally no one waiting..seems like they have been trained to make sure the guests eat fast and leave..one should make them understand that people come to restaurants to eat and also have a good time with their company..not eat in a rush and leave.. do not visit this place\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:15 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:15 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4590'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_cs5fo3xjzuhto5eaxppodrmwtimgtj24tpiu4nsosgdzuk2lrkhq'), (b'x-request-id', b'req_cs5fo3xjzuhto5eaxppodrmwtimgtj24tpiu4nsosgdzuk2lrkhq'), (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')])
2026-06-24 03:16:15 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:15 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:15 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:15 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:15 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:15 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:15 GMT', 'content-type': 'application/json', 'content-length': '4590', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_cs5fo3xjzuhto5eaxppodrmwtimgtj24tpiu4nsosgdzuk2lrkhq', 'x-request-id': 'req_cs5fo3xjzuhto5eaxppodrmwtimgtj24tpiu4nsosgdzuk2lrkhq', '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'})
2026-06-24 03:16:15 [openai._base_client] DEBUG: request_id: req_cs5fo3xjzuhto5eaxppodrmwtimgtj24tpiu4nsosgdzuk2lrkhq
2026-06-24 03:16:15 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-4f9b26db-48a7-4201-a8ca-7cb496fa1d22', '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                            Ambience, food and staff service. \n— Krishna Pal (good service)\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:15 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:15 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:15 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:15 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:15 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:15 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:18 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:18 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4995'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_qi4whqjbltf55cygpgduteg3gjwpmzd2nxsomkuk2gedo33oxoaa'), (b'x-request-id', b'req_qi4whqjbltf55cygpgduteg3gjwpmzd2nxsomkuk2gedo33oxoaa'), (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')])
2026-06-24 03:16:18 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:18 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:18 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:18 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:18 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:18 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:18 GMT', 'content-type': 'application/json', 'content-length': '4995', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_qi4whqjbltf55cygpgduteg3gjwpmzd2nxsomkuk2gedo33oxoaa', 'x-request-id': 'req_qi4whqjbltf55cygpgduteg3gjwpmzd2nxsomkuk2gedo33oxoaa', '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'})
2026-06-24 03:16:18 [openai._base_client] DEBUG: request_id: req_qi4whqjbltf55cygpgduteg3gjwpmzd2nxsomkuk2gedo33oxoaa
2026-06-24 03:16:18 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-10b30fcc-1fc5-41f9-b411-ef866fe5f642', '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                            Had a great experience at Cravekraft, Andheri East. The food was delicious, fresh, and beautifully presented. The ambiance is cozy, modern, and perfect for a casual outing or date night. The drinks were refreshing, and the desserts were a perfect way to end the meal. Friendly service and a lovely overall vibe. Definitely worth a visit! 😊🍽️✨\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:18 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:18 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:18 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:18 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:18 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:18 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:21 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:21 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6149'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2phnu72tyrmsrlpeyzypbshoycyb7dks5r4f4cjlqp35ppcn33hq'), (b'x-request-id', b'req_2phnu72tyrmsrlpeyzypbshoycyb7dks5r4f4cjlqp35ppcn33hq'), (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')])
2026-06-24 03:16:21 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:21 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:21 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:21 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:21 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:21 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:21 GMT', 'content-type': 'application/json', 'content-length': '6149', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2phnu72tyrmsrlpeyzypbshoycyb7dks5r4f4cjlqp35ppcn33hq', 'x-request-id': 'req_2phnu72tyrmsrlpeyzypbshoycyb7dks5r4f4cjlqp35ppcn33hq', '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'})
2026-06-24 03:16:21 [openai._base_client] DEBUG: request_id: req_2phnu72tyrmsrlpeyzypbshoycyb7dks5r4f4cjlqp35ppcn33hq
2026-06-24 03:16:21 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-24db69bc-dd60-47f0-a74d-71cca8ec5c61', '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                            Absolutely loved my visit to Cravekraft! The food was flavorful, the presentation was impressive, and the ambiance was warm and inviting. Every dish felt thoughtfully prepared, and the drinks complemented the meal perfectly. A great place to relax, enjoy good food, and spend quality time. Will definitely be visiting again! ✨🍴💕\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:21 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:21 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:21 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:21 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:21 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:21 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:24 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:24 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4624'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_b53zewzk6zpewtrjurp3m5gqiwi6lmvq4zyu6xt2rvycteg6onxa'), (b'x-request-id', b'req_b53zewzk6zpewtrjurp3m5gqiwi6lmvq4zyu6xt2rvycteg6onxa'), (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')])
2026-06-24 03:16:24 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:24 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:24 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:24 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:24 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:24 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:24 GMT', 'content-type': 'application/json', 'content-length': '4624', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_b53zewzk6zpewtrjurp3m5gqiwi6lmvq4zyu6xt2rvycteg6onxa', 'x-request-id': 'req_b53zewzk6zpewtrjurp3m5gqiwi6lmvq4zyu6xt2rvycteg6onxa', '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'})
2026-06-24 03:16:24 [openai._base_client] DEBUG: request_id: req_b53zewzk6zpewtrjurp3m5gqiwi6lmvq4zyu6xt2rvycteg6onxa
2026-06-24 03:16:24 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-835b04e6-ef22-45f0-9c35-115bd90abbe5', '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                            Visited Cray Craft recently and absolutely loved the experience. The ambience is classy yet comfortable, the food was packed with flavor, and every dish looked as good as it tasted. The staff was attentive and made sure everything was perfect. Definitely a place I\'d visit again with friends and family.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:24 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:24 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:24 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:24 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:24 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:24 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:26 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:26 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4228'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_mt5kj2qhzjzfushpglvwudaagx63w37gjg4lhjkglnkwupq7342a'), (b'x-request-id', b'req_mt5kj2qhzjzfushpglvwudaagx63w37gjg4lhjkglnkwupq7342a'), (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')])
2026-06-24 03:16:26 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:26 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:26 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:26 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:26 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:26 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:26 GMT', 'content-type': 'application/json', 'content-length': '4228', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_mt5kj2qhzjzfushpglvwudaagx63w37gjg4lhjkglnkwupq7342a', 'x-request-id': 'req_mt5kj2qhzjzfushpglvwudaagx63w37gjg4lhjkglnkwupq7342a', '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'})
2026-06-24 03:16:26 [openai._base_client] DEBUG: request_id: req_mt5kj2qhzjzfushpglvwudaagx63w37gjg4lhjkglnkwupq7342a
2026-06-24 03:16:26 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-1975f509-1453-4f44-bfb3-092a4b73805c', '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                            Recently came here after seeing so much on instagram, the hype was real and worth it. So many options and all SOOO YUMMY, aesthetically also super pleasing. Def comin back for the burrata papdi chat!!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:26 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:26 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:26 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:26 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:26 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:26 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:28 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:28 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3001'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_orajlxafrzm7jzbyyu4smd7l62gvrfq7zsvkorkjpruuffregvga'), (b'x-request-id', b'req_orajlxafrzm7jzbyyu4smd7l62gvrfq7zsvkorkjpruuffregvga'), (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')])
2026-06-24 03:16:28 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:28 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:28 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:28 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:28 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:28 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:28 GMT', 'content-type': 'application/json', 'content-length': '3001', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_orajlxafrzm7jzbyyu4smd7l62gvrfq7zsvkorkjpruuffregvga', 'x-request-id': 'req_orajlxafrzm7jzbyyu4smd7l62gvrfq7zsvkorkjpruuffregvga', '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'})
2026-06-24 03:16:28 [openai._base_client] DEBUG: request_id: req_orajlxafrzm7jzbyyu4smd7l62gvrfq7zsvkorkjpruuffregvga
2026-06-24 03:16:28 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6b09a8f6-eedd-4a04-822b-0e18060d9b3e', '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                            Cray Craft is one of those places that gets everything right—great food, amazing vibes, and excellent service. The presentation of the dishes was impressive and the overall atmosphere made the dining experience even better. Highly recommended for a casual outing or a special occasion.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:28 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:28 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:28 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:28 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:28 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:28 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:31 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:31 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4071'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kodgww5ybtnvywy2zp247im33zhoo5bjky5p3ectagbgftwryh3a'), (b'x-request-id', b'req_kodgww5ybtnvywy2zp247im33zhoo5bjky5p3ectagbgftwryh3a'), (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')])
2026-06-24 03:16:31 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:31 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:31 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:31 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:31 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:31 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:31 GMT', 'content-type': 'application/json', 'content-length': '4071', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kodgww5ybtnvywy2zp247im33zhoo5bjky5p3ectagbgftwryh3a', 'x-request-id': 'req_kodgww5ybtnvywy2zp247im33zhoo5bjky5p3ectagbgftwryh3a', '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'})
2026-06-24 03:16:31 [openai._base_client] DEBUG: request_id: req_kodgww5ybtnvywy2zp247im33zhoo5bjky5p3ectagbgftwryh3a
2026-06-24 03:16:31 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-2af30a1d-e293-4af7-a32a-610c05001abf', '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. There were a lot of crazy vegetarian fusion options. The bao buns were extremely good, and the sushi was amazing. I was pretty impressed by the large veg options. The burrata papdi chat is definitely a musttt have!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:31 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:31 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:31 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:31 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:31 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:31 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:35 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:35 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5800'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ghf3xzyjstwbd7o6qfbrnwaemtqmluob6othjek2ji7yiq6cvb6q'), (b'x-request-id', b'req_ghf3xzyjstwbd7o6qfbrnwaemtqmluob6othjek2ji7yiq6cvb6q'), (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')])
2026-06-24 03:16:35 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:35 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:35 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:35 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:35 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:35 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:35 GMT', 'content-type': 'application/json', 'content-length': '5800', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ghf3xzyjstwbd7o6qfbrnwaemtqmluob6othjek2ji7yiq6cvb6q', 'x-request-id': 'req_ghf3xzyjstwbd7o6qfbrnwaemtqmluob6othjek2ji7yiq6cvb6q', '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'})
2026-06-24 03:16:35 [openai._base_client] DEBUG: request_id: req_ghf3xzyjstwbd7o6qfbrnwaemtqmluob6othjek2ji7yiq6cvb6q
2026-06-24 03:16:35 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-d18e5b1f-3585-4160-babe-c06dcef32d13', '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 had a bad delivery experience with the restaurant where I had ordered a non veg platter plus mutton kebabs from this restaurant & they sent spoilt kebabs & stale & unfresh chicken tikkas... the same issue was reported to zomato & representative made sure that a call was done with the restaurant to discuss this matter at 1 am in the night... sad part is that a worker from the restaurant first understood the issue from the zomato representative then from me & then said that he will get the manager on the call to understand the same... basically wasted the representative\'s and my time in the night & then came back on the call in less then a minute & mentioned that the manager has gone out for some work & to share my contact no. so that he can call the next day but unfortunately did not receive any call even after 24hrs of reporting the issue to the restaurant... this shows how unprofessional the team is & how they don\'t care about a customer\'s experience & expectations... the ratings of the restaurant doesn\'t justify the food quality standards \n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:35 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:35 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:35 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:35 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:35 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:35 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:40 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:40 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6858'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_xlubduqxacte5wz53lc6pgmyceqklxuuux5djueoil3a5xte6rhq'), (b'x-request-id', b'req_xlubduqxacte5wz53lc6pgmyceqklxuuux5djueoil3a5xte6rhq'), (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')])
2026-06-24 03:16:40 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:40 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:40 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:40 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:40 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:40 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:40 GMT', 'content-type': 'application/json', 'content-length': '6858', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_xlubduqxacte5wz53lc6pgmyceqklxuuux5djueoil3a5xte6rhq', 'x-request-id': 'req_xlubduqxacte5wz53lc6pgmyceqklxuuux5djueoil3a5xte6rhq', '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'})
2026-06-24 03:16:40 [openai._base_client] DEBUG: request_id: req_xlubduqxacte5wz53lc6pgmyceqklxuuux5djueoil3a5xte6rhq
2026-06-24 03:16:40 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-bb3a6da6-ec81-4f5a-ab21-3ce775beaeb1', '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                            Delicious food with amazing live music\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:40 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:40 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:40 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:40 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:40 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:40 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:42 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3343'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_qkoyzxrrnl3vo6vuqlfpsf7vbdyn4lombqs6szhykdrurctw2pua'), (b'x-request-id', b'req_qkoyzxrrnl3vo6vuqlfpsf7vbdyn4lombqs6szhykdrurctw2pua'), (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')])
2026-06-24 03:16:42 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:42 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:42 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:42 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:42 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:42 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:42 GMT', 'content-type': 'application/json', 'content-length': '3343', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_qkoyzxrrnl3vo6vuqlfpsf7vbdyn4lombqs6szhykdrurctw2pua', 'x-request-id': 'req_qkoyzxrrnl3vo6vuqlfpsf7vbdyn4lombqs6szhykdrurctw2pua', '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'})
2026-06-24 03:16:42 [openai._base_client] DEBUG: request_id: req_qkoyzxrrnl3vo6vuqlfpsf7vbdyn4lombqs6szhykdrurctw2pua
2026-06-24 03:16:42 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f319943d-477f-4b7e-bb1b-4e03a93fadc2', '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                            Some places serve great food. Some leave you with a feeling you carry back home. 🫶🏻\n\nAt Ishaara, the experience begins much before the food arrives. Built with a beautiful purpose, the team welcomes you with warmth, kindness and the sweetest smiles. They talk with their hands and listen with their eyes, making every interaction feel incredibly special. 🤌🏻\n\nWe started with their comforting Broccoli & Truffle Soup, followed by the delicious Paneer Dori Kebab. 😍\n\nThen came the Exotic Farmhouse Pizza 🍕 and the star of the meal, the flavourful Gucchi Kashmiri Dum Biryani. 🥹🫰🏻\n\nTo sip alongside, we had the refreshing Virgin Mojito and Ishaara Lemonade. 🍋🍹\n\nAnd because every memorable meal deserves a sweet ending, we finished with their Pistachio Baklava. ❣️\n\nWhat stayed with us long after the meal wasn\'t just the food, but the hospitality, warmth and genuine care of the team. A wholesome experience that reminds you how powerful kindness can be. 🤝\n\nSome meals fill your stomach. Places like Ishaara fill your heart. 🥹🫶🏻 Cheers! 🥂\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:42 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:42 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:42 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:42 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:42 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:42 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:47 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:47 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'7413'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_r4e6d37skrxgau6nzuadlfdnl5v3k33s4hgscrls4hgwajk4broq'), (b'x-request-id', b'req_r4e6d37skrxgau6nzuadlfdnl5v3k33s4hgscrls4hgwajk4broq'), (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')])
2026-06-24 03:16:47 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:47 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:47 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:47 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:47 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:47 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:47 GMT', 'content-type': 'application/json', 'content-length': '7413', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_r4e6d37skrxgau6nzuadlfdnl5v3k33s4hgscrls4hgwajk4broq', 'x-request-id': 'req_r4e6d37skrxgau6nzuadlfdnl5v3k33s4hgscrls4hgwajk4broq', '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'})
2026-06-24 03:16:47 [openai._base_client] DEBUG: request_id: req_r4e6d37skrxgau6nzuadlfdnl5v3k33s4hgscrls4hgwajk4broq
2026-06-24 03:16:47 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-14f83741-acbb-4c1f-8b4e-efe6ff25bdc0', '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'}}
2026-06-24 03:16:47 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:47 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:47 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:47 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:47 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:47 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:49 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:49 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2724'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_v5ykrvrlwjcvh5c3vadwohflbnxaobiqvzyrr4rvfeim63llpurq'), (b'x-request-id', b'req_v5ykrvrlwjcvh5c3vadwohflbnxaobiqvzyrr4rvfeim63llpurq'), (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')])
2026-06-24 03:16:49 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:49 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:49 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:49 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:49 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:49 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:49 GMT', 'content-type': 'application/json', 'content-length': '2724', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_v5ykrvrlwjcvh5c3vadwohflbnxaobiqvzyrr4rvfeim63llpurq', 'x-request-id': 'req_v5ykrvrlwjcvh5c3vadwohflbnxaobiqvzyrr4rvfeim63llpurq', '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'})
2026-06-24 03:16:49 [openai._base_client] DEBUG: request_id: req_v5ykrvrlwjcvh5c3vadwohflbnxaobiqvzyrr4rvfeim63llpurq
2026-06-24 03:16:49 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-bc78b5b2-4c5c-46e0-91f5-ba63f789929b', '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                            Divyashree - thank you for keeping it very light in dine in experiences\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:49 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:49 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:49 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:49 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:49 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:49 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:51 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:51 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3166'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_z5pmp2nkqcp4sdjdrxut2ztbpfpxqi72ccspp2rpp4xjtll2wtnq'), (b'x-request-id', b'req_z5pmp2nkqcp4sdjdrxut2ztbpfpxqi72ccspp2rpp4xjtll2wtnq'), (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')])
2026-06-24 03:16:51 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:51 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:51 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:51 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:51 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:51 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:51 GMT', 'content-type': 'application/json', 'content-length': '3166', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_z5pmp2nkqcp4sdjdrxut2ztbpfpxqi72ccspp2rpp4xjtll2wtnq', 'x-request-id': 'req_z5pmp2nkqcp4sdjdrxut2ztbpfpxqi72ccspp2rpp4xjtll2wtnq', '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'})
2026-06-24 03:16:51 [openai._base_client] DEBUG: request_id: req_z5pmp2nkqcp4sdjdrxut2ztbpfpxqi72ccspp2rpp4xjtll2wtnq
2026-06-24 03:16:51 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-05e8532d-8f58-49d8-8b96-57602a84a6bf', '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 ambience, good food, very polite staff 🫶🏻\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:51 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:51 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:51 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:51 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:51 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:51 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:53 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:53 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4012'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_nsm62vj2nj4nsnmkg3oydynuktmx7hvnck7y6raoqwec3lkn3nuq'), (b'x-request-id', b'req_nsm62vj2nj4nsnmkg3oydynuktmx7hvnck7y6raoqwec3lkn3nuq'), (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')])
2026-06-24 03:16:53 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:53 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:53 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:53 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:53 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:53 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:53 GMT', 'content-type': 'application/json', 'content-length': '4012', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_nsm62vj2nj4nsnmkg3oydynuktmx7hvnck7y6raoqwec3lkn3nuq', 'x-request-id': 'req_nsm62vj2nj4nsnmkg3oydynuktmx7hvnck7y6raoqwec3lkn3nuq', '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'})
2026-06-24 03:16:53 [openai._base_client] DEBUG: request_id: req_nsm62vj2nj4nsnmkg3oydynuktmx7hvnck7y6raoqwec3lkn3nuq
2026-06-24 03:16:53 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f33d2994-4d90-4bc7-933d-58c6b96c107b', '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                            mr sachin and mr vijay offered a very good service. everything went very well. the food was also very delicious \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:53 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:53 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:53 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:53 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:53 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:53 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:55 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:55 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2953'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_kvxpcrnmmcbql4dqpq4dz3qjwephi7gtvizkyatwadp22dbyqkda'), (b'x-request-id', b'req_kvxpcrnmmcbql4dqpq4dz3qjwephi7gtvizkyatwadp22dbyqkda'), (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')])
2026-06-24 03:16:55 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:55 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:55 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:55 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:55 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:55 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:55 GMT', 'content-type': 'application/json', 'content-length': '2953', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_kvxpcrnmmcbql4dqpq4dz3qjwephi7gtvizkyatwadp22dbyqkda', 'x-request-id': 'req_kvxpcrnmmcbql4dqpq4dz3qjwephi7gtvizkyatwadp22dbyqkda', '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'})
2026-06-24 03:16:55 [openai._base_client] DEBUG: request_id: req_kvxpcrnmmcbql4dqpq4dz3qjwephi7gtvizkyatwadp22dbyqkda
2026-06-24 03:16:55 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-89a31abb-295a-4bcc-8170-9e6e8ac58876', '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 average. Expectations were a little high. All the dishes we ordered had the same flavour of the sauces. Cannot recommend it to anyone.\n                            Customer Rating:\n                            3 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:55 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:55 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:55 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:55 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:55 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:55 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:16:57 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:16:57 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3447'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_izji7grlxgcvuhqiolwxelkpautc2jzjohatt3jfuh67ynyfn3na'), (b'x-request-id', b'req_izji7grlxgcvuhqiolwxelkpautc2jzjohatt3jfuh67ynyfn3na'), (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')])
2026-06-24 03:16:57 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:16:57 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:16:57 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:16:57 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:16:57 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:16:57 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:16:57 GMT', 'content-type': 'application/json', 'content-length': '3447', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_izji7grlxgcvuhqiolwxelkpautc2jzjohatt3jfuh67ynyfn3na', 'x-request-id': 'req_izji7grlxgcvuhqiolwxelkpautc2jzjohatt3jfuh67ynyfn3na', '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'})
2026-06-24 03:16:57 [openai._base_client] DEBUG: request_id: req_izji7grlxgcvuhqiolwxelkpautc2jzjohatt3jfuh67ynyfn3na
2026-06-24 03:16:57 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-b17cdc73-f112-4bb4-92fd-0de2496735bd', '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 and best series \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:16:57 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:16:57 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:16:57 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:16:57 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:16:57 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:16:57 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:00 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3771'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_54fi4pf22hjf35s4dhkbszf2kwuoyx2we5gdlwpqvuwuxvcch33a'), (b'x-request-id', b'req_54fi4pf22hjf35s4dhkbszf2kwuoyx2we5gdlwpqvuwuxvcch33a'), (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')])
2026-06-24 03:17:00 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:00 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:00 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:00 GMT', 'content-type': 'application/json', 'content-length': '3771', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_54fi4pf22hjf35s4dhkbszf2kwuoyx2we5gdlwpqvuwuxvcch33a', 'x-request-id': 'req_54fi4pf22hjf35s4dhkbszf2kwuoyx2we5gdlwpqvuwuxvcch33a', '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'})
2026-06-24 03:17:00 [openai._base_client] DEBUG: request_id: req_54fi4pf22hjf35s4dhkbszf2kwuoyx2we5gdlwpqvuwuxvcch33a
2026-06-24 03:17:00 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-33d1fb92-fc64-4897-aa4c-a59f14185afc', '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                            Such an amazing place.  \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:00 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:00 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1566'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_txgzhjrruaueeqynmmm5nab7wce6iy5upxfmx4xatbnpxqut3w2a'), (b'x-request-id', b'req_txgzhjrruaueeqynmmm5nab7wce6iy5upxfmx4xatbnpxqut3w2a'), (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')])
2026-06-24 03:17:00 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:00 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:00 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:00 GMT', 'content-type': 'application/json', 'content-length': '1566', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_txgzhjrruaueeqynmmm5nab7wce6iy5upxfmx4xatbnpxqut3w2a', 'x-request-id': 'req_txgzhjrruaueeqynmmm5nab7wce6iy5upxfmx4xatbnpxqut3w2a', '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'})
2026-06-24 03:17:00 [openai._base_client] DEBUG: request_id: req_txgzhjrruaueeqynmmm5nab7wce6iy5upxfmx4xatbnpxqut3w2a
2026-06-24 03:17:00 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-4a811a12-c546-4981-af7f-6c7041876dc4', '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 thank you for Vaibhav \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:00 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:00 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:00 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:01 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:01 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2167'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_km2inln66a6ewl2n4sx2npqoriluwzz5yfcfzvtmdzyu5syehw6a'), (b'x-request-id', b'req_km2inln66a6ewl2n4sx2npqoriluwzz5yfcfzvtmdzyu5syehw6a'), (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')])
2026-06-24 03:17:01 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:01 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:01 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:01 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:01 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:01 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:01 GMT', 'content-type': 'application/json', 'content-length': '2167', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_km2inln66a6ewl2n4sx2npqoriluwzz5yfcfzvtmdzyu5syehw6a', 'x-request-id': 'req_km2inln66a6ewl2n4sx2npqoriluwzz5yfcfzvtmdzyu5syehw6a', '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'})
2026-06-24 03:17:01 [openai._base_client] DEBUG: request_id: req_km2inln66a6ewl2n4sx2npqoriluwzz5yfcfzvtmdzyu5syehw6a
2026-06-24 03:17:01 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-6b573767-0a9e-4653-9ecd-564ffdc9ac86', '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'}}
2026-06-24 03:17:01 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:01 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:01 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:01 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:01 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:01 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:03 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:03 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2554'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_lp3njnyqc6obm4hdmvuoxxkcbguglp6idg3xtqbuqlt2sly4kl7q'), (b'x-request-id', b'req_lp3njnyqc6obm4hdmvuoxxkcbguglp6idg3xtqbuqlt2sly4kl7q'), (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')])
2026-06-24 03:17:03 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:03 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:03 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:03 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:03 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:03 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:03 GMT', 'content-type': 'application/json', 'content-length': '2554', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_lp3njnyqc6obm4hdmvuoxxkcbguglp6idg3xtqbuqlt2sly4kl7q', 'x-request-id': 'req_lp3njnyqc6obm4hdmvuoxxkcbguglp6idg3xtqbuqlt2sly4kl7q', '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'})
2026-06-24 03:17:03 [openai._base_client] DEBUG: request_id: req_lp3njnyqc6obm4hdmvuoxxkcbguglp6idg3xtqbuqlt2sly4kl7q
2026-06-24 03:17:03 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-257096a3-8abc-463c-8020-3f0ab86aa99c', '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 nice good we just love it 🥰\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:03 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:03 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:03 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:03 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:03 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:03 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:04 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:04 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1582'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_2qltytnbuqdkomg3b6gh4nhqla4wee6iabf6rv5oelu4nult5u3q'), (b'x-request-id', b'req_2qltytnbuqdkomg3b6gh4nhqla4wee6iabf6rv5oelu4nult5u3q'), (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')])
2026-06-24 03:17:04 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:04 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:04 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:04 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:04 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:04 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:04 GMT', 'content-type': 'application/json', 'content-length': '1582', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_2qltytnbuqdkomg3b6gh4nhqla4wee6iabf6rv5oelu4nult5u3q', 'x-request-id': 'req_2qltytnbuqdkomg3b6gh4nhqla4wee6iabf6rv5oelu4nult5u3q', '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'})
2026-06-24 03:17:04 [openai._base_client] DEBUG: request_id: req_2qltytnbuqdkomg3b6gh4nhqla4wee6iabf6rv5oelu4nult5u3q
2026-06-24 03:17:04 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-32c6cd9f-17f8-4c1d-9aef-dda0a6730746', '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                            Mr Sachin and Mr Vijay offered a very nice service. The food was good and so does the ambience. Really had a good time.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:04 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:04 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:04 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:04 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:04 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:04 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:08 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:08 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5844'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_pa2aon5y5fxl56ihg4n26uynywgepfbwmptqqbzodemuvfvdik2q'), (b'x-request-id', b'req_pa2aon5y5fxl56ihg4n26uynywgepfbwmptqqbzodemuvfvdik2q'), (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')])
2026-06-24 03:17:08 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:08 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:08 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:08 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:08 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:08 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:08 GMT', 'content-type': 'application/json', 'content-length': '5844', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_pa2aon5y5fxl56ihg4n26uynywgepfbwmptqqbzodemuvfvdik2q', 'x-request-id': 'req_pa2aon5y5fxl56ihg4n26uynywgepfbwmptqqbzodemuvfvdik2q', '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'})
2026-06-24 03:17:08 [openai._base_client] DEBUG: request_id: req_pa2aon5y5fxl56ihg4n26uynywgepfbwmptqqbzodemuvfvdik2q
2026-06-24 03:17:08 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ea913c34-569f-4e7e-84ac-fe0cf3edaac1', '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 service  and Steve did a wonderful job\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:08 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:08 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:08 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:08 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:08 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:08 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:10 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:10 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3292'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_glp47qnygo6sdbm7qw3eqjlehs7dotgcbgppc5extfukziaeocvq'), (b'x-request-id', b'req_glp47qnygo6sdbm7qw3eqjlehs7dotgcbgppc5extfukziaeocvq'), (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')])
2026-06-24 03:17:10 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:10 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:10 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:10 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:10 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:10 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:10 GMT', 'content-type': 'application/json', 'content-length': '3292', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_glp47qnygo6sdbm7qw3eqjlehs7dotgcbgppc5extfukziaeocvq', 'x-request-id': 'req_glp47qnygo6sdbm7qw3eqjlehs7dotgcbgppc5extfukziaeocvq', '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'})
2026-06-24 03:17:10 [openai._base_client] DEBUG: request_id: req_glp47qnygo6sdbm7qw3eqjlehs7dotgcbgppc5extfukziaeocvq
2026-06-24 03:17:10 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-ba59f7aa-6ca2-474c-967e-227e688c9510', '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'}}
2026-06-24 03:17:10 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:10 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:10 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:10 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:10 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:10 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:11 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:11 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2284'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_e7zw6qzwyw4gravpjmkxyc7bsxienpgypb67aasbjwyae5oc7l2q'), (b'x-request-id', b'req_e7zw6qzwyw4gravpjmkxyc7bsxienpgypb67aasbjwyae5oc7l2q'), (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')])
2026-06-24 03:17:11 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:11 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:11 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:11 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:11 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:11 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:11 GMT', 'content-type': 'application/json', 'content-length': '2284', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_e7zw6qzwyw4gravpjmkxyc7bsxienpgypb67aasbjwyae5oc7l2q', 'x-request-id': 'req_e7zw6qzwyw4gravpjmkxyc7bsxienpgypb67aasbjwyae5oc7l2q', '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'})
2026-06-24 03:17:11 [openai._base_client] DEBUG: request_id: req_e7zw6qzwyw4gravpjmkxyc7bsxienpgypb67aasbjwyae5oc7l2q
2026-06-24 03:17:11 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c1223276-9300-43d5-9498-9b485c5bb56f', '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                            Sachin was an excellent waiter\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:11 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:11 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:11 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:11 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:11 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:11 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:12 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:12 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'1846'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_dgn6l7w3jp3ioqfwalih7rv7jmszq5wgznlryknw3aedu6vwkjpa'), (b'x-request-id', b'req_dgn6l7w3jp3ioqfwalih7rv7jmszq5wgznlryknw3aedu6vwkjpa'), (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')])
2026-06-24 03:17:12 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:12 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:12 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:12 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:12 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:12 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:12 GMT', 'content-type': 'application/json', 'content-length': '1846', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_dgn6l7w3jp3ioqfwalih7rv7jmszq5wgznlryknw3aedu6vwkjpa', 'x-request-id': 'req_dgn6l7w3jp3ioqfwalih7rv7jmszq5wgznlryknw3aedu6vwkjpa', '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'})
2026-06-24 03:17:12 [openai._base_client] DEBUG: request_id: req_dgn6l7w3jp3ioqfwalih7rv7jmszq5wgznlryknw3aedu6vwkjpa
2026-06-24 03:17:12 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-38a4cfe7-10f4-4f00-9317-05fe6e51bf14', '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 nice food vikas\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:12 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:12 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:12 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:12 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:12 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:12 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:13 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:13 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2374'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_f7hk5qswnwxk7dypvz56o3yfywg3zxutk7cwcupdzhtwnv6ldx2q'), (b'x-request-id', b'req_f7hk5qswnwxk7dypvz56o3yfywg3zxutk7cwcupdzhtwnv6ldx2q'), (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')])
2026-06-24 03:17:13 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:13 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:13 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:13 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:13 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:13 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:13 GMT', 'content-type': 'application/json', 'content-length': '2374', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_f7hk5qswnwxk7dypvz56o3yfywg3zxutk7cwcupdzhtwnv6ldx2q', 'x-request-id': 'req_f7hk5qswnwxk7dypvz56o3yfywg3zxutk7cwcupdzhtwnv6ldx2q', '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'})
2026-06-24 03:17:13 [openai._base_client] DEBUG: request_id: req_f7hk5qswnwxk7dypvz56o3yfywg3zxutk7cwcupdzhtwnv6ldx2q
2026-06-24 03:17:13 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-84633e77-cb51-4597-b1eb-4fe3308c001d', '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                            Food was awesome,Staff was soo kind and polite.The best part was the ambience.One of the best restaurant I have tried.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:13 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:13 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:13 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:13 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:13 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:13 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:18 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:18 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5674'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_zaa2whg6b2idwpdu7cgzma3nzkaoyhtei56v4d6bbuydrwvsfsuq'), (b'x-request-id', b'req_zaa2whg6b2idwpdu7cgzma3nzkaoyhtei56v4d6bbuydrwvsfsuq'), (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')])
2026-06-24 03:17:18 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:18 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:18 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:18 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:18 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:18 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:18 GMT', 'content-type': 'application/json', 'content-length': '5674', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_zaa2whg6b2idwpdu7cgzma3nzkaoyhtei56v4d6bbuydrwvsfsuq', 'x-request-id': 'req_zaa2whg6b2idwpdu7cgzma3nzkaoyhtei56v4d6bbuydrwvsfsuq', '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'})
2026-06-24 03:17:18 [openai._base_client] DEBUG: request_id: req_zaa2whg6b2idwpdu7cgzma3nzkaoyhtei56v4d6bbuydrwvsfsuq
2026-06-24 03:17:18 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-bd2d35d6-a854-413d-9a9d-6fd25933e430', '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                            Nitesh was great , the food was amazing\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:18 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:18 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:18 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:18 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:18 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:18 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:19 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:19 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2616'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_qjn66ki7lw4wctuy7wj6ffaiknwy5zktpa5p2p2tnkw6s5q4l4fq'), (b'x-request-id', b'req_qjn66ki7lw4wctuy7wj6ffaiknwy5zktpa5p2p2tnkw6s5q4l4fq'), (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')])
2026-06-24 03:17:19 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:19 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:19 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:19 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:19 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:19 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:19 GMT', 'content-type': 'application/json', 'content-length': '2616', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_qjn66ki7lw4wctuy7wj6ffaiknwy5zktpa5p2p2tnkw6s5q4l4fq', 'x-request-id': 'req_qjn66ki7lw4wctuy7wj6ffaiknwy5zktpa5p2p2tnkw6s5q4l4fq', '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'})
2026-06-24 03:17:19 [openai._base_client] DEBUG: request_id: req_qjn66ki7lw4wctuy7wj6ffaiknwy5zktpa5p2p2tnkw6s5q4l4fq
2026-06-24 03:17:19 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-d41daa35-2041-4447-a1d5-b7d94a04b8ae', '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                            Amazing food ❤️\nGood service by Sohail\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:19 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:19 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:19 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:19 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:19 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:19 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:21 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:21 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2278'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_mg5sx7huxkkzmi3jg2tmt5lgnsrj4i7cplmbkmdhp6pwmfntynjq'), (b'x-request-id', b'req_mg5sx7huxkkzmi3jg2tmt5lgnsrj4i7cplmbkmdhp6pwmfntynjq'), (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')])
2026-06-24 03:17:21 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:21 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:21 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:21 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:21 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:21 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:21 GMT', 'content-type': 'application/json', 'content-length': '2278', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_mg5sx7huxkkzmi3jg2tmt5lgnsrj4i7cplmbkmdhp6pwmfntynjq', 'x-request-id': 'req_mg5sx7huxkkzmi3jg2tmt5lgnsrj4i7cplmbkmdhp6pwmfntynjq', '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'})
2026-06-24 03:17:21 [openai._base_client] DEBUG: request_id: req_mg5sx7huxkkzmi3jg2tmt5lgnsrj4i7cplmbkmdhp6pwmfntynjq
2026-06-24 03:17:21 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-bffe3d2d-9ce0-43cb-a1dc-017dff61ff23', '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                            Have a nice day with the resturant and the service and ambience for very neat and clean. We have really enjoyed the taste of the food which we were ordered and service provided by Mr. Kumar was very nice , he was very polite and his behaviour also very nice...\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:21 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:21 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:21 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:21 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:21 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:21 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:23 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:23 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4786'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_paekyza5pxxwbhxeroyn4kocmdxuihhlcn5zqc42whln76jfjukq'), (b'x-request-id', b'req_paekyza5pxxwbhxeroyn4kocmdxuihhlcn5zqc42whln76jfjukq'), (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')])
2026-06-24 03:17:23 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:23 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:23 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:23 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:23 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:23 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:23 GMT', 'content-type': 'application/json', 'content-length': '4786', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_paekyza5pxxwbhxeroyn4kocmdxuihhlcn5zqc42whln76jfjukq', 'x-request-id': 'req_paekyza5pxxwbhxeroyn4kocmdxuihhlcn5zqc42whln76jfjukq', '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'})
2026-06-24 03:17:23 [openai._base_client] DEBUG: request_id: req_paekyza5pxxwbhxeroyn4kocmdxuihhlcn5zqc42whln76jfjukq
2026-06-24 03:17:23 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-24cc4ad6-34bb-4b25-94da-fcec9966f040', '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 ambience is good and the taste is perfect. Our host Seltun was really nice and did recommend some really nice dishes. Had a great time.!!\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:23 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:23 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:23 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:23 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:23 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:23 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:25 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:25 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4651'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_6divm6aa3ac3pxkswtaxq5czolpiskni5ixqoecray4xnynv6ova'), (b'x-request-id', b'req_6divm6aa3ac3pxkswtaxq5czolpiskni5ixqoecray4xnynv6ova'), (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')])
2026-06-24 03:17:25 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:25 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:25 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:25 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:25 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:25 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:25 GMT', 'content-type': 'application/json', 'content-length': '4651', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_6divm6aa3ac3pxkswtaxq5czolpiskni5ixqoecray4xnynv6ova', 'x-request-id': 'req_6divm6aa3ac3pxkswtaxq5czolpiskni5ixqoecray4xnynv6ova', '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'})
2026-06-24 03:17:25 [openai._base_client] DEBUG: request_id: req_6divm6aa3ac3pxkswtaxq5czolpiskni5ixqoecray4xnynv6ova
2026-06-24 03:17:25 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-97721e4d-d0ba-4f93-a81f-cb0dab8dfc46', '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 service for from vishal\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:25 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:25 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:25 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:25 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:25 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:25 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:27 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:27 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2774'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_z2s5ndhwfytm4oybyhjkubp3zxwql33jj6kfqap6nyupc3kakz7q'), (b'x-request-id', b'req_z2s5ndhwfytm4oybyhjkubp3zxwql33jj6kfqap6nyupc3kakz7q'), (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')])
2026-06-24 03:17:27 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:27 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:27 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:27 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:27 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:27 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:27 GMT', 'content-type': 'application/json', 'content-length': '2774', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_z2s5ndhwfytm4oybyhjkubp3zxwql33jj6kfqap6nyupc3kakz7q', 'x-request-id': 'req_z2s5ndhwfytm4oybyhjkubp3zxwql33jj6kfqap6nyupc3kakz7q', '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'})
2026-06-24 03:17:27 [openai._base_client] DEBUG: request_id: req_z2s5ndhwfytm4oybyhjkubp3zxwql33jj6kfqap6nyupc3kakz7q
2026-06-24 03:17:27 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-235605be-24f0-47ac-b4a0-61360f5a1cd5', '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                            Either they are very understaffed or their Service needs massive improvement. \n\n1. We weren\'t offered even water as basic courtesy. Later when we called for it, water was served in a disposable cup. They didn\'t even bother to fill the cup. \n\n2. Plates weren\'t replaced after each course. For some items, they didn\'t even bother to get us the plates. We had to eat from the serving bowl / plate itself. \n\n3. The wait staff weren\'t knowledgeable about their menu. They didn\'t know the difference between 2 similar items. So, we avoided ordering that anyways. \n\n4. They didn\'t bother or thought of giving us oregano & chilli flakes for the Pizza, which was anyways a disaster (Paneer tikka). No plates were given for this. \n\n5. The only saving grace is that this is a pure veg place with Jain options. So, gave it an additional star. \n\n6. The dahi puri was alright, loaded nachos recommended \n                            Customer Rating:\n                            2 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:27 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:27 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:27 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:27 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:27 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:27 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:32 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:32 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'8630'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_rsrds6khaenkzozhdjoqdtvryinvtmgpfpfjjxqnhqpndfik6goq'), (b'x-request-id', b'req_rsrds6khaenkzozhdjoqdtvryinvtmgpfpfjjxqnhqpndfik6goq'), (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')])
2026-06-24 03:17:32 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:32 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:32 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:32 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:32 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:32 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:32 GMT', 'content-type': 'application/json', 'content-length': '8630', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_rsrds6khaenkzozhdjoqdtvryinvtmgpfpfjjxqnhqpndfik6goq', 'x-request-id': 'req_rsrds6khaenkzozhdjoqdtvryinvtmgpfpfjjxqnhqpndfik6goq', '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'})
2026-06-24 03:17:32 [openai._base_client] DEBUG: request_id: req_rsrds6khaenkzozhdjoqdtvryinvtmgpfpfjjxqnhqpndfik6goq
2026-06-24 03:17:32 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-714bd3cc-0905-4b8a-867e-decf6f4e51e0', '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                            Nirmal provided excellent service !\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:32 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:32 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:32 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:32 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:32 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:32 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:34 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:34 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3665'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_264vlwz7xb24yqvs2nehyvsgjz6orddmtbezxrai4gjuj2rzdexq'), (b'x-request-id', b'req_264vlwz7xb24yqvs2nehyvsgjz6orddmtbezxrai4gjuj2rzdexq'), (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')])
2026-06-24 03:17:34 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:34 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:34 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:34 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:34 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:34 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:34 GMT', 'content-type': 'application/json', 'content-length': '3665', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_264vlwz7xb24yqvs2nehyvsgjz6orddmtbezxrai4gjuj2rzdexq', 'x-request-id': 'req_264vlwz7xb24yqvs2nehyvsgjz6orddmtbezxrai4gjuj2rzdexq', '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'})
2026-06-24 03:17:34 [openai._base_client] DEBUG: request_id: req_264vlwz7xb24yqvs2nehyvsgjz6orddmtbezxrai4gjuj2rzdexq
2026-06-24 03:17:34 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-cf385e3a-c2b9-4ab3-a8cf-1c7de5d9c428', '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                            Debasish Monda took care of our table and helped us get delicious food we thank him a lot\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:34 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:34 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:34 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:34 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:34 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:34 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:36 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:36 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3657'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_6r7uqxoaotxmm5xbn5y3ckutmwzbgjwhrm5keosertbpmqjc62ca'), (b'x-request-id', b'req_6r7uqxoaotxmm5xbn5y3ckutmwzbgjwhrm5keosertbpmqjc62ca'), (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')])
2026-06-24 03:17:36 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:36 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:36 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:36 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:36 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:36 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:36 GMT', 'content-type': 'application/json', 'content-length': '3657', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_6r7uqxoaotxmm5xbn5y3ckutmwzbgjwhrm5keosertbpmqjc62ca', 'x-request-id': 'req_6r7uqxoaotxmm5xbn5y3ckutmwzbgjwhrm5keosertbpmqjc62ca', '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'})
2026-06-24 03:17:36 [openai._base_client] DEBUG: request_id: req_6r7uqxoaotxmm5xbn5y3ckutmwzbgjwhrm5keosertbpmqjc62ca
2026-06-24 03:17:36 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-20109294-67f7-4d6d-884a-373cd664b212', '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 from Nirmal\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:36 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:36 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:36 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:36 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:36 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:36 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:37 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:37 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2223'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_q26hv7ijorjvgfmk7hjovh5oj4ykdfqcalgdm7q4es4ulzmr4umq'), (b'x-request-id', b'req_q26hv7ijorjvgfmk7hjovh5oj4ykdfqcalgdm7q4es4ulzmr4umq'), (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')])
2026-06-24 03:17:37 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:37 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:37 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:37 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:37 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:37 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:37 GMT', 'content-type': 'application/json', 'content-length': '2223', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_q26hv7ijorjvgfmk7hjovh5oj4ykdfqcalgdm7q4es4ulzmr4umq', 'x-request-id': 'req_q26hv7ijorjvgfmk7hjovh5oj4ykdfqcalgdm7q4es4ulzmr4umq', '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'})
2026-06-24 03:17:37 [openai._base_client] DEBUG: request_id: req_q26hv7ijorjvgfmk7hjovh5oj4ykdfqcalgdm7q4es4ulzmr4umq
2026-06-24 03:17:37 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f287a4a2-f2c7-4fe9-a896-919b8b17bdd9', '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                            Anjali was very friendly and profeasional. loved the food and service.\nawesome taste\ngood diacount too\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:37 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:37 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:37 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:37 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:37 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:37 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:39 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:39 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4546'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_muscasxeln2x6qxe5qqhgz6x6zvh72v3sbocpi4vybk4kgrgrapq'), (b'x-request-id', b'req_muscasxeln2x6qxe5qqhgz6x6zvh72v3sbocpi4vybk4kgrgrapq'), (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')])
2026-06-24 03:17:39 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:39 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:39 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:39 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:39 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:39 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:39 GMT', 'content-type': 'application/json', 'content-length': '4546', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_muscasxeln2x6qxe5qqhgz6x6zvh72v3sbocpi4vybk4kgrgrapq', 'x-request-id': 'req_muscasxeln2x6qxe5qqhgz6x6zvh72v3sbocpi4vybk4kgrgrapq', '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'})
2026-06-24 03:17:39 [openai._base_client] DEBUG: request_id: req_muscasxeln2x6qxe5qqhgz6x6zvh72v3sbocpi4vybk4kgrgrapq
2026-06-24 03:17:39 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-fd1fc448-9cc1-4982-98cf-b1efa352ea10', '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                            Kum Kum provided exceptional service\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:39 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:39 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:39 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:39 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:39 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:39 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:41 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:41 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2405'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_ksxu2iven4axdwpaeg72s4tyab2bduvtprbmx6cf3h4mhuhum5ea'), (b'x-request-id', b'req_ksxu2iven4axdwpaeg72s4tyab2bduvtprbmx6cf3h4mhuhum5ea'), (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')])
2026-06-24 03:17:41 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:41 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:41 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:41 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:41 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:41 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:41 GMT', 'content-type': 'application/json', 'content-length': '2405', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_ksxu2iven4axdwpaeg72s4tyab2bduvtprbmx6cf3h4mhuhum5ea', 'x-request-id': 'req_ksxu2iven4axdwpaeg72s4tyab2bduvtprbmx6cf3h4mhuhum5ea', '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'})
2026-06-24 03:17:41 [openai._base_client] DEBUG: request_id: req_ksxu2iven4axdwpaeg72s4tyab2bduvtprbmx6cf3h4mhuhum5ea
2026-06-24 03:17:41 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9d79e58f-647b-463d-9ec9-a81780c09f90', '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 and food suggestions from Vishal.\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:41 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:41 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:41 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:41 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:41 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:41 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:42 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:42 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'2938'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_44gn5k23wbqll4pil5xawk4rjwp3b7bkecosndi4wzyebxgq2jxa'), (b'x-request-id', b'req_44gn5k23wbqll4pil5xawk4rjwp3b7bkecosndi4wzyebxgq2jxa'), (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')])
2026-06-24 03:17:42 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:42 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:42 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:42 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:42 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:42 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:42 GMT', 'content-type': 'application/json', 'content-length': '2938', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_44gn5k23wbqll4pil5xawk4rjwp3b7bkecosndi4wzyebxgq2jxa', 'x-request-id': 'req_44gn5k23wbqll4pil5xawk4rjwp3b7bkecosndi4wzyebxgq2jxa', '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'})
2026-06-24 03:17:42 [openai._base_client] DEBUG: request_id: req_44gn5k23wbqll4pil5xawk4rjwp3b7bkecosndi4wzyebxgq2jxa
2026-06-24 03:17:42 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-c19724a7-54e2-401b-a8d4-98b3a40d2ed9', '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                            Ranjan was amazing at the service. food was tooo good. pav bhaji is a must try. \n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:42 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:42 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:42 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:42 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:42 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:42 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:49 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:49 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'5962'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_vn4pobhwgbhgj4jk6m225f7uhzabo3ca2r643ccp6i6ttlqgn63a'), (b'x-request-id', b'req_vn4pobhwgbhgj4jk6m225f7uhzabo3ca2r643ccp6i6ttlqgn63a'), (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')])
2026-06-24 03:17:49 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:49 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:49 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:49 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:49 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:49 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:49 GMT', 'content-type': 'application/json', 'content-length': '5962', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_vn4pobhwgbhgj4jk6m225f7uhzabo3ca2r643ccp6i6ttlqgn63a', 'x-request-id': 'req_vn4pobhwgbhgj4jk6m225f7uhzabo3ca2r643ccp6i6ttlqgn63a', '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'})
2026-06-24 03:17:49 [openai._base_client] DEBUG: request_id: req_vn4pobhwgbhgj4jk6m225f7uhzabo3ca2r643ccp6i6ttlqgn63a
2026-06-24 03:17:49 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-9e831fff-1041-4de3-8b3f-11b9b958e812', '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                            Seltun is a very nice person , extremely well behaved . Thanks for making us dinner memorable\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:49 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:49 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:49 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:49 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:49 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:49 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:52 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:52 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3429'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_iczauihijae25z43ru7dsp2sqnso5u2dkmek6ohglxxtndlulsoa'), (b'x-request-id', b'req_iczauihijae25z43ru7dsp2sqnso5u2dkmek6ohglxxtndlulsoa'), (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')])
2026-06-24 03:17:52 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:52 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:52 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:52 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:52 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:52 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:52 GMT', 'content-type': 'application/json', 'content-length': '3429', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_iczauihijae25z43ru7dsp2sqnso5u2dkmek6ohglxxtndlulsoa', 'x-request-id': 'req_iczauihijae25z43ru7dsp2sqnso5u2dkmek6ohglxxtndlulsoa', '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'})
2026-06-24 03:17:52 [openai._base_client] DEBUG: request_id: req_iczauihijae25z43ru7dsp2sqnso5u2dkmek6ohglxxtndlulsoa
2026-06-24 03:17:52 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-f65944d7-64be-4d40-848f-6e07b8c7b7b5', '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 have taken unlimited shushi.  for my son but there was one jalapeno sushi which was so damn spicy that he could not have more. first time same sushi came was good and tasty but after few serving that same sushi became so spicy that it was unreal to eat. kid had to drink so much water that he can\'t have much sushi. I feel cheated. I told them to give something sweet as he was feeling terrible hot. they gave one pastry to eat\n                            Customer Rating:\n                            1 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:52 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:52 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:52 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:52 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:52 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:52 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:55 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:55 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'4574'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_u5kel4a5nnvl42bfiyaqcjylp33sp5q3qi6xrbht25afluxltkla'), (b'x-request-id', b'req_u5kel4a5nnvl42bfiyaqcjylp33sp5q3qi6xrbht25afluxltkla'), (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')])
2026-06-24 03:17:55 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:55 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:55 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:55 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:55 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:55 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:55 GMT', 'content-type': 'application/json', 'content-length': '4574', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_u5kel4a5nnvl42bfiyaqcjylp33sp5q3qi6xrbht25afluxltkla', 'x-request-id': 'req_u5kel4a5nnvl42bfiyaqcjylp33sp5q3qi6xrbht25afluxltkla', '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'})
2026-06-24 03:17:55 [openai._base_client] DEBUG: request_id: req_u5kel4a5nnvl42bfiyaqcjylp33sp5q3qi6xrbht25afluxltkla
2026-06-24 03:17:55 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5db946a8-c0b4-4de6-b7a3-78acbc63fa62', '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                            bappa was great\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:55 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:55 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:55 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:55 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:55 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:55 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:17:58 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:17:58 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3571'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_daodkramd5nchsr3o3vsvukxyteckbtq3nxpkn5gwk5vlplt4fwq'), (b'x-request-id', b'req_daodkramd5nchsr3o3vsvukxyteckbtq3nxpkn5gwk5vlplt4fwq'), (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')])
2026-06-24 03:17:58 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:17:58 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:17:58 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:17:58 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:17:58 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:17:58 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:17:58 GMT', 'content-type': 'application/json', 'content-length': '3571', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_daodkramd5nchsr3o3vsvukxyteckbtq3nxpkn5gwk5vlplt4fwq', 'x-request-id': 'req_daodkramd5nchsr3o3vsvukxyteckbtq3nxpkn5gwk5vlplt4fwq', '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'})
2026-06-24 03:17:58 [openai._base_client] DEBUG: request_id: req_daodkramd5nchsr3o3vsvukxyteckbtq3nxpkn5gwk5vlplt4fwq
2026-06-24 03:17:58 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-5f1788f7-02f7-4393-8c59-a49095970e76', '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                            Eight at Palladium is honestly such a vibe if you’re into Asian food and aesthetic dining. The entire place has this warm, dim-lit ambience with a very calming oriental feel that instantly sets the mood.\n\nWe tried a mix of dishes and everything looked as good as it tasted. The sushi was fresh and beautifully plated, the dumplings were perfectly crisp with that lace texture, and the ramen was super comforting and flavourful. Even the appetizers had that perfect balance of spice and crunch.\n\nThe drinks were refreshing and complemented the food really well.\n\nOverall, it’s a great spot for a chill dinner, date night or even just to enjoy good Asian food in a beautiful setting. Definitely a place I’d come back to 🤍\n                            Customer Rating:\n                            4 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:17:58 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:17:58 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:17:58 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:17:58 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:17:58 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:17:58 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:18:02 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:18:02 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'6559'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_u72mmup3fow4d7ykcfpg3rwvdjsqvm2zroaoflfdo4lzi7htdnga'), (b'x-request-id', b'req_u72mmup3fow4d7ykcfpg3rwvdjsqvm2zroaoflfdo4lzi7htdnga'), (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')])
2026-06-24 03:18:02 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:18:02 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:18:02 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:18:02 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:18:02 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:18:02 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:18:02 GMT', 'content-type': 'application/json', 'content-length': '6559', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_u72mmup3fow4d7ykcfpg3rwvdjsqvm2zroaoflfdo4lzi7htdnga', 'x-request-id': 'req_u72mmup3fow4d7ykcfpg3rwvdjsqvm2zroaoflfdo4lzi7htdnga', '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'})
2026-06-24 03:18:02 [openai._base_client] DEBUG: request_id: req_u72mmup3fow4d7ykcfpg3rwvdjsqvm2zroaoflfdo4lzi7htdnga
2026-06-24 03:18:02 [openai._base_client] DEBUG: Request options: {'method': 'post', 'url': '/responses', 'files': None, 'idempotency_key': 'stainless-python-retry-36348fd5-50f0-4869-a936-362ed32cd304', '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                            yummy food preparation was too good❤️\n                            Customer Rating:\n                            5 ', 'model': 'openai.gpt-oss-120b'}}
2026-06-24 03:18:02 [openai._base_client] DEBUG: Sending HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses
2026-06-24 03:18:02 [httpcore.http11] DEBUG: send_request_headers.started request=<Request [b'POST']>
2026-06-24 03:18:02 [httpcore.http11] DEBUG: send_request_headers.complete
2026-06-24 03:18:02 [httpcore.http11] DEBUG: send_request_body.started request=<Request [b'POST']>
2026-06-24 03:18:02 [httpcore.http11] DEBUG: send_request_body.complete
2026-06-24 03:18:02 [httpcore.http11] DEBUG: receive_response_headers.started request=<Request [b'POST']>
2026-06-24 03:18:04 [httpcore.http11] DEBUG: receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Wed, 24 Jun 2026 03:18:04 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'3093'), (b'Connection', b'keep-alive'), (b'x-amzn-requestid', b'req_53ylnh2xy2xtqe4iqdmfbbmonbl3nprj7f7l27oflk7du66qndja'), (b'x-request-id', b'req_53ylnh2xy2xtqe4iqdmfbbmonbl3nprj7f7l27oflk7du66qndja'), (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')])
2026-06-24 03:18:04 [httpx] INFO: HTTP Request: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "HTTP/1.1 200 OK"
2026-06-24 03:18:04 [httpcore.http11] DEBUG: receive_response_body.started request=<Request [b'POST']>
2026-06-24 03:18:04 [httpcore.http11] DEBUG: receive_response_body.complete
2026-06-24 03:18:04 [httpcore.http11] DEBUG: response_closed.started
2026-06-24 03:18:04 [httpcore.http11] DEBUG: response_closed.complete
2026-06-24 03:18:04 [openai._base_client] DEBUG: HTTP Response: POST https://bedrock-mantle.ap-south-1.api.aws/v1/responses "200 OK" Headers({'date': 'Wed, 24 Jun 2026 03:18:04 GMT', 'content-type': 'application/json', 'content-length': '3093', 'connection': 'keep-alive', 'x-amzn-requestid': 'req_53ylnh2xy2xtqe4iqdmfbbmonbl3nprj7f7l27oflk7du66qndja', 'x-request-id': 'req_53ylnh2xy2xtqe4iqdmfbbmonbl3nprj7f7l27oflk7du66qndja', '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'})
2026-06-24 03:18:04 [openai._base_client] DEBUG: request_id: req_53ylnh2xy2xtqe4iqdmfbbmonbl3nprj7f7l27oflk7du66qndja
2026-06-24 03:18:04 [scrapy.statscollectors] INFO: Dumping Scrapy stats:
{'downloader/exception_count': 1,
 'downloader/exception_type_count/twisted.web._newclient.ResponseFailed': 1,
 'downloader/request_bytes': 3474590,
 'downloader/request_count': 660,
 'downloader/request_method_count/GET': 660,
 'downloader/response_bytes': 3515340,
 'downloader/response_count': 659,
 'downloader/response_status_count/200': 659,
 'elapsed_time_seconds': 375.622107,
 'finish_reason': 'finished',
 'finish_time': datetime.datetime(2026, 6, 24, 3, 18, 4, 385886, tzinfo=datetime.timezone.utc),
 'item_scraped_count': 55,
 'items_per_minute': None,
 'log_count/DEBUG': 1480,
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 'log_count/WARNING': 36,
 'memusage/max': 161501184,
 'memusage/startup': 145752064,
 'request_depth_max': 2,
 'response_received_count': 659,
 'responses_per_minute': None,
 'retry/count': 1,
 'retry/reason_count/twisted.web._newclient.ResponseFailed': 1,
 'scheduler/dequeued': 660,
 'scheduler/dequeued/memory': 660,
 'scheduler/enqueued': 660,
 'scheduler/enqueued/memory': 660,
 'start_time': datetime.datetime(2026, 6, 24, 3, 11, 48, 763779, tzinfo=datetime.timezone.utc)}
2026-06-24 03:18:04 [scrapy.core.engine] INFO: Spider closed (finished)
2026-06-24 03:18:05 [httpcore.connection] DEBUG: close.started
2026-06-24 03:18:05 [httpcore.connection] DEBUG: close.complete