What data for this category includes
This category of data covers the entire law enforcement process for market supervision, ecological environment, transportation, emergency management, urban management and other law enforcement agencies. Daily documents include fixed-format legal documents such as on-site inspection records, interrogation records, evidence lists, prior administrative penalty notices, hearing notices, penalty decisions, and service receipts. Data sources include administrative law enforcement case handling systems, law enforcement recorder footage, the national enterprise credit information publicity system, and departmental supervision databases, with daily updates. The data includes both structured case handling fields and unstructured audio, video, and scanned document copies. The core focuses on forming a traceable evidence chain around illegal facts and penalty decisions.
Constraints imposed on the tool calling and plugin link by these data characteristics
The data characteristics of this category impose multiple constraints on the tool calling and plugin link. Multi-source and heterogeneous data sources require plugins to adapt to API interfaces and data formats of different systems, and integrate tools such as cross-departmental database queries and law enforcement footage analysis. Daily updated data requires tool calling to support real-time synchronization, and avoid using expired supervision data. Fixed-format document structures require tool calling to accurately extract specific fields, and cannot rely on general fuzzy matching logic. The traceability of the evidence chain requires that every operation in tool calling generates auditable logs, to ensure that the review process can be traced. The serious consequences of errors require tool calling to have a stable retry and error handling mechanism, to avoid case file review delays caused by call failures.
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to multi-tool calling scenarios for administrative penalty case file review, automatically matches document parsing and data query tools |
functionCall | Enabled | Enforces structured output, ensuring extracted fields can be directly used for case file archiving and legal review |
| Tool calling timeout | 600 seconds | Law enforcement footage analysis and cross-departmental data queries require long processing cycles |
| Tool calling retry count | 2 | Balances call success rate and platform resource consumption |
| Concurrent call limit | 5 | Matches the reasonable peak workload of grassroots law enforcement agencies |
| Result post-processing rules | Calibrated based on actual tests | Adapts to document field extraction logic for different law enforcement domains |
Three common mistakes
- Phenomenon: Connection timeout error returned when calling a locally deployed large model | Cause: The correct API address and port of the local model are not configured, or the server network policy restricts cross-domain access
- Phenomenon: Unstable tool calling results, extracted record fields are empty or have inconsistent formatting | Cause: A dedicated extraction logic for the fixed document structure of administrative penalty case files is not configured, or the
functionCallparameter for enforcing structured output is not enabled - Phenomenon: Interface rate limit error occurs during concurrent calls | Cause: The concurrent call limit configuration is not adjusted, exceeding the call threshold of the FastGPT platform
How to verify the configuration is correctly set
- Import a standard administrative penalty case file sample, trigger the tool calling process, and check whether core fields of on-site inspection records and interrogation records are automatically extracted
- View tool calling logs, confirm that the
toolChoiceparameter takes effect, and the corresponding data query and document parsing tools are automatically selected - Initiate more than 3 concurrent calls, check that no errors occur and results meet expectations
- Test the connection of the locally deployed large model, confirm that the returned tool calling results have no formatting errors
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.