Tool Calling and Plugins for Hotel and Catering Research

What the data for this category looks like

This page describes data for hotel and catering research reports. Data sources include industry association public monitoring reports, third-party catering consulting agency monthly surveys, public investor call transcripts of listed catering enterprises, and offline store sampling data. Three update rhythm categories apply: industry overall reports update monthly, key brand dynamics update weekly, and annual trend reports release annually. Document structures usually include overall industry scale, segmented format performance, regional market distribution, core operating data, and policy impact analysis. Core fields include 坪效 (unit: yuan/square meter/month), daily average customer traffic per store (unit: people/day), customer unit price (unit: yuan/person), average food procurement price (unit: yuan/kg), and the ratio of store rent to revenue.

Constraints imposed by these characteristics on tool calling and plugins

Tools handling multi-source data access must support different format parsing rules. Format differences between public reports and survey data may cause field extraction failures, so this setup avoids those errors. Data sources with different update frequencies require configurable recall refresh cycles. Fixed cycles cannot cover all data types. Operating fields with clear units require unified unit alignment during tool calls. Unit differences across data sources may cause retrieval deviations, so this setup prevents those issues. Documents with wide length ranges require flexible configurable segmentation rules. Splitting that breaks the complete logic of single-format analysis must be avoided.

How to set configurations

Configuration Item	Recommended Value	Setting Basis
`recall_chunk_size`	800–1200 characters	Core analysis paragraphs of hotel and catering research reports are mostly 800-1200 characters. This segmentation length preserves the complete logic of single-format analysis and avoids semantic damage from splitting
`data_refresh_interval`	7200 seconds	Balances the needs of monthly updated industry overall reports and weekly updated key brand dynamics. Avoids data obsolescence from overly long refresh cycles, or increased call costs from overly short cycles
`plugin_filter_fields`	["坪效", "单店日均客流量", "客单价"]	Core decision-making fields of hotel and catering research reports are store operating data. Filtering improves retrieval accuracy and reduces invalid results occupying context space
`max_context_window`	16000–24000 characters	A single in-depth research report can reach 15000 characters. This range reserves sufficient context for logical integration and result generation during tool calls
`api_chat_id_persistence`	Enabled	Hotel and catering research report retrieval often requires cross-session tracking of users' format query needs. Persisting chatId preserves session context and ensures the continuity of tool calls

The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.

Three common configuration mistakes

Phenomenon: The calling interface returns 400 Bad Request with the prompt chatId invalid. Cause: The api_chat_id_persistence configuration is not enabled. The session ID fails to persist across requests, so tool calls cannot associate historical research report retrieval records.
Phenomenon: The number of research report results returned by tool calls does not match the configured recall_top_k value. The actual number of returned results is insufficient. Cause: The plugin_filter_fields configuration is not set for the structured fields of hotel and catering research reports. Invalid non-operating data is recalled, which crowds out valid result positions.
Phenomenon: No internal execution records for tool calls appear in the application conversation's view details page. Cause: The debug_log switch is not enabled in the plugin configuration. Internal execution details during tool calls are not captured, so plugin running status cannot be traced.

How to confirm the configuration is complete

Initiate a research report retrieval for the chain fast food format. Check whether the correct chatId parameter appears in the tool calling log, and confirm that the session context is retained.
Call a custom Python plugin to run a test script. Check whether the plugin return result includes complete execution logs, and confirm that the debug switch is enabled.
Adjust the recall_chunk_size configuration, then re-analyze a single in-depth research report. Check whether the segmented document retains the complete logic of single-format analysis.
Call the interface to initiate batch research report retrieval. Check whether the returned result fields include the operating data specified in the configured plugin_filter_fields, and confirm that the filtering rules take effect.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.