Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Data sources include administrative law enforcement case handling systems, law enforcement recorder footage, the National Enterprise Credit Information Publicity System, and departmental supervision databases. Updates occur daily. Daily processed documents include on-site inspection records, interrogation transcripts, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, and service receipts. Data fields cover law enforcement subject information, illegal fact descriptions, discretionary benchmark application records, penalty decision content, and document delivery status. The core builds a traceable evidence chain around illegal facts and penalty decisions.
Constraints on the tool calling and plugins workflow
Data sources include structured case handling system data and unstructured footage and documents. Use the toolChoice configuration to automatically select tools, while supporting structured parameter parsing and unstructured content extraction. Daily updated law enforcement data requires tool calling frequency to match business rhythms, to avoid invalid calls or delays. Fixed document types require tool call outputs to strictly align with statutory document fields, to ensure generated content complies with case file specifications. Law enforcement recorder footage is unstructured data, so plugins must support parsing of corresponding formats. Cross-source data integration requires plugins to adapt to multi-database pull logic.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to scenarios requiring combined multi-tool calls for administrative penalty case file handling, automatically selects appropriate tools to process structured and unstructured data |
| Single tool call timeout | 600 seconds | Covers execution durations of time-consuming operations such as law enforcement footage parsing and cross-database pulls |
| Tool call result cache duration | 24 hours | Matches the daily data update frequency, prevents use of expired law enforcement information |
| Number of results returned per tool call | Top 10 | Covers law enforcement information required for daily case files, avoids redundant data |
| Multimodal content parsing plugin | Set based on actual testing | Adapts to base64 format parsing requirements for law enforcement recorder footage |
functionCall | Enable mandatory parameter validation | Prevents passing invalid parameters that do not comply with law enforcement specifications when calling tools |
Three Common Misconfigurations
- A call to the law enforcement footage parsing tool returns
{"object":"error","message":"Only allowed now"}. This happens when model call permission parameters are not correctly configured, causing tool calls to exceed the current allowed scope. - After configuring HTTP tool calls, parameter parsing works normally but actual execution does not trigger. This happens when the execution permission for the corresponding tool is not bound, or the trigger timing does not match the business node.
- Tool call return result fields do not match statutory documents. This happens when parameter validation rules are not set, causing tool output content to not align with the field structure required by case files.
How to Verify Configurations
- Simulate generating a standard administrative penalty case file, trigger tool calls, and check if returned results include required law enforcement data fields.
- Review tool call logs to confirm trigger timing matches the case file generation node, and that call durations do not exceed preset timeout thresholds.
- Upload a base64 format file of law enforcement recorder footage, verify that the tool can correctly parse and extract relevant information.
- Check that parameter validation rules are enabled, ensuring parameters passed during tool calls comply with statutory document format requirements.
The values provided 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.