Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Core data for this category comes from ecological environment law enforcement detachments, monitoring stations, pollutant discharge units, and third-party testing institutions. Daily documents include on-site inspection records, sampling records, monitoring reports, order for correction decisions, and administrative penalty decisions. Data sources include online monitoring platforms, automatic pollution source monitoring data, ecological environment law enforcement systems, and third-party test reports. Data is updated daily. Data fields include sampling point number, monitoring concentration value, law enforcement officer number, inspection time, rectification requirements, and more. Some fields have fixed units, such as mg/m³ or ppm for concentration values.
How data characteristics constrain tool calling and plugin workflows
Daily updated data sources require tool calling to implement a scheduled synchronization mechanism. This ensures access to the latest monitoring and law enforcement data. Variations in structure across different document types require plugins to support parsing logic for multiple formats. For example, parse point fields from sampling records and rectification requirement fields from on-site inspection records. Fields with fixed units require tool calling to verify data unit consistency. This prevents errors caused by mismatched units. Errors in law enforcement-related data directly impact regulatory effectiveness. Therefore, tool calling must include failure retry and result verification steps. This stops incorrect data from being added to ledgers and reports.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Automatically match the tool calls required for law enforcement ledger generation, no manual specification needed |
functionCall | enabled | Force generation of function call results that comply with law enforcement document formats, ensuring compliant output structure |
| Plugin trigger timing | 2:00 AM daily | Aligns with the daily update schedule of data sources, avoids calling outdated data |
| Point matching threshold | ≥80% | Ensures monitoring data called accurately corresponds to law enforcement points, reduces invalid data |
| Retry count | 3 times | Addresses temporary unavailability of data sources, improves call success rate |
| Custom prompt length | 800–1200 characters | Covers business rules and format requirements needed for law enforcement ledger generation |
Three common mistakes
- Phenomenon: The
/api/v1/chat/completionsinterface returns a "missing required function" error. Cause: The law enforcement-related tool function name is not specified in thefunctionCallconfiguration, causing interface verification to fail. - Phenomenon: Monitoring data points in the generated ledger do not match on-site law enforcement points, and the number of results is abnormal. Cause: No point matching threshold is set, so the tool calls monitoring data from unrelated areas and does not filter invalid entries.
- Phenomenon: Styles cannot be customized after embedding the FastGPT page in a frontend application. Cause: The default style injection switch is not turned off, and custom style interface parameters are not configured, causing default styles to override custom configurations.
How to confirm correct configuration
- Call the test interface, pass in a law enforcement ledger generation request, check if the returned results include the tool function structure specified by
functionCall. - Manually trigger a ledger generation task, verify that the point numbers in the returned data match the preset law enforcement monitoring points.
- Simulate temporary unavailability of data sources, check if the configured retry mechanism is triggered and retry logs are generated.
- View system logs, confirm that the daily scheduled synchronization plugin executes normally at 2:00 AM with no error messages.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.