What the data for this category looks like
Professional chain intelligent due diligence report data comes from chain headquarters ERP systems, in-store POS terminals, franchise contract ledgers, store inspection reports, and third-party business district passenger flow monitoring data. Update frequency varies by dimension: daily updates for in-store sales and passenger flow data, change-triggered updates for franchise qualification and regional layout data, weekly updates for inspection reports. Document structure centers on structured tables, with fields including store ID, business address, square meter efficiency, passenger flow, fulfillment rate, and more. Some attachments include store photos and supply chain reconciliation vouchers. Field units use standardized metrics such as yuan/square meter/month, trips/day, calendar year, and other standard measurement formats.
What constraints these characteristics impose on tool calling and plugins
The multi-source heterogeneous data structure of professional chains requires tool calling to support cross-system interface authentication and batch data pulling, and adapt to interface formats of different data sources. Daily updated sales and passenger flow data requires tool calling trigger frequency to match the data update cycle, to avoid triggering rate limits on third-party interfaces. Unstructured inspection photos and reconciliation vouchers require plugins to integrate OCR parsing and structured field extraction capabilities. Change-based data such as franchise qualifications requires tool calling to support event listening triggers, to adapt to change-triggered update requirements. Standardized field measurement requirements mean tool return fields must strictly match preset units, to avoid format deviations affecting due diligence conclusions.
How to set the configurations
| Config Item | Suggested Value | Rationale |
|---|---|---|
maxToolCallsPerRound | 8–12 | Adapts to the volume of multi-store data that needs to be pulled in a single due diligence batch for professional chains, and avoids exceeding limits in a single call |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to the parsing time of inspection photos and supply chain reconciliation vouchers, and avoids mid-call timeout interruptions |
toolCallTimeout | 600 seconds | Covers the full time required for batch pulling of multi-store POS data and cross-ERP system interface calls |
pluginOcrEnabled | Enabled | Supports parsing handwritten inspection items in photos and printed text on paper reconciliation vouchers |
fieldUnitValidation | Enabled | Verifies whether the units of returned data match preset formats such as yuan/square meter/month and trips/day |
dataSyncTrigger | Event listening + daily completion | Balances change-triggered updates for franchise qualifications and store layouts, and scheduled synchronization for daily updated sales data |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common errors
- Phenomenon: Tool calls return mixed units for data such as square meter efficiency and passenger flow, using non-preset measurement formats. Cause: The
fieldUnitValidationconfiguration is not enabled, and mandatory verification of returned field units is not performed. - Phenomenon: OCR plugin calls return empty results or missing recognized content when parsing store inspection photos. Cause:
pluginOcrEnabledis not set to Enabled, or uploaded photo formats fall outside the range supported by the plugin. - Phenomenon: No segmented streaming output data is obtained when calling the tool chain via API, or an interface error is returned when calling the current time plugin. Cause: Streaming transmission configuration is not enabled in API request parameters, or the plugin's call address and authentication parameters are not correctly configured.
How to confirm configurations are properly set
- Initiate a simulated due diligence call, check if returned structured fields include preset content such as store ID, square meter efficiency and passenger flow, and if units match business requirements.
- Upload a store inspection photo, trigger OCR plugin parsing, and confirm that text content in the photo can be extracted and converted to structured fields.
- Configure tool call trigger rules, simulate a franchise contract change event, and confirm the tool can automatically pull updated qualification data.
- View tool call logs, confirm that the number of calls per round does not exceed the configured
maxToolCallsPerRoundlimit, and that timeout settings match configured values.
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.