What this category of data looks like
Business data for this category comes from daily operation outputs and regulatory docking sources from manufacturing enterprise EHS departments and production maintenance teams. It includes risk identification records, hot work/permit-required confined space/lifting operation tickets, gas monitoring records, hazardous waste ledgers, emission monitoring data, and accident and hidden danger rectification reports. Data sources cover industry regulatory standards, online environmental monitoring systems, portable gas detectors, operator qualification files, equipment isolation lists, and local regulatory platforms. Data is updated immediately upon completion of a single operation, or updated per monitoring cycles and regular inspection requirements. Each document contains fields such as operation scenario, risk level, compliance basis, and responsible person. There is no unified fixed unit, and matching corresponding measurement standards based on data type.
What constraints do these characteristics impose on tool calling and plugins workflows
Data sources for this category are scattered, covering multiple types including online monitoring systems, portable devices, and qualification files. Tool calling must adapt to multi-type data access and support cross-source data aggregation. Data is updated in real time alongside operations, so tool calling must meet real-time response requirements and handle concurrent request scenarios. Single operation documents have complex fields, so tool calling must accurately extract core fields such as risk level and compliance basis, and verify data consistency. Operation compliance requirements are strict, so tool calling results must match regulations and operation scenarios. An additional post-processing link can correct unstable tool calling output, and support multi-row database queries to aggregate multi-dimensional operation data.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | This category requires flexible calling of multiple tools such as compliance verification and data extraction. Automatic mode can adapt to different operation scenarios |
| Workflow/API function-call configuration | Limit call quantity | The number of operation-related tools is controllable. Limiting calls can reduce context redundancy |
| Tool call timeout | 600 seconds | Some compliance verification requires accessing cross-source data, which takes a long time |
| Database query row limit | 2–5 rows | Single operation-related queries do not require too many results, to avoid context overload |
| Tool call post-processing | Enabled | Tool call results have fluctuations. Post-processing can correct extraction deviations |
Three common misconfigurations
- Issue: SQL syntax error prompt is returned when calling database plugins. Cause: Multi-line query statements are not split, and insert and select statements are submitted together, exceeding the single-execution statement limit of the plugin.
- Issue: Tool call returns empty results or missing core fields. Cause:
toolChoiceis not set to automatic mode, so the model cannot automatically match tools for the corresponding operation scenario, resulting in invalid tool calls. - Issue: Timeout or request discarding occurs during concurrent requests. Cause: The concurrent request threshold configuration is not adjusted, exceeding the default concurrent load limit of FastGPT v4.17.0.
How to confirm the configuration is correct
- Initiate a single operation data extraction request, and verify whether the tool call return result includes core fields such as risk level and operation type.
- Submit multi-line database query statements, and confirm that the plugin can execute normally and return expected results.
- Initiate multiple concurrent requests, confirm that the system has no obvious timeouts or errors, and adjust the concurrent threshold to match business load requirements.
- Enable tool call post-processing, and verify whether the output result completes field extraction and correction.
Note: The configuration values listed here are common starting points. Adjust them based on respective specific samples and business needs.