What This Category of Data Looks Like
Data for this category comes from the road transport administration system, the national public service platform for dynamic information of road transport vehicles, and the vehicle and practitioner database. It is updated daily. Daily documents include business license application documents, vehicle technical files, driver qualification materials, work safety management systems, and road transport business license documents. Document fields include vehicle identification number, practitioner qualification number, business scope description, site condition description, and more. The character count of individual documents varies widely, ranging from several hundred-word application forms to tens of thousands-word safety management systems.
Constraints Imposed on Tool Calling and Plugins
The daily update feature of the data requires tool calls to synchronize the latest data from specified systems in real time. This avoids using expired vehicle or practitioner qualification information. The wide character count range of documents requires tool calls to support adaptive-length content extraction. This meets processing needs from short forms to long system documents. The multi-source data and professional field features require plugins to interface with specified system APIs. Call parameters must match road transport-specific fields to avoid information matching deviations caused by generic parameters. The time consumption requirement of the core verification link requires tool calls to automatically pull associated data. This reduces manual entry and verification steps.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Tool Call Mode | Auto Mode | Adapts to the diverse drafting needs of road transport documents, no need to manually specify tools |
| Single Tool Call Timeout | 600 seconds | Covers the time requirements of long document parsing and multi-system data pulling |
| Number of Tool Call Results | Top 3 | Focuses on core associated data, avoiding redundant information interfering with document drafting |
toolChoice | auto | Allows the AI to independently judge the tools required for the current scenario, adapting to document processing for different licensing links |
functionCall | Triggered per licensing link | Matches the dedicated data requirements of different scenarios such as business license application, modification, and annual inspection |
| Context Window Size | 8000–12000 token | Adapts to the integration needs of long documents and multi-source data, calibrated based on actual testing |
Three Common Configuration Mistakes
- Symptom: Raw system data returned by tool calls is directly included in the final reply. Cause: No filtering rules for tool call results are configured. This leads to internal call data being leaked to end users.
- Symptom: Road transport professional data obtained via tool calls cannot be correctly processed by downstream models. Cause: Tool call results are not formatted as specified before being passed to the target model. This causes data format mismatches.
- Symptom: Tool call APIs are triggered by meaningless scheduled tasks. Cause: No trigger node for document drafting is bound. Scheduled tasks are directly bound to tool calls, resulting in invalid calls.
How to Verify Proper Configuration
- Trigger a draft test for a road transport business license application document. Check whether tool calls automatically pull corresponding vehicle, personnel, and safety system data.
- View tool call logs. Confirm that only specified plugin APIs related to road transport business licensing are called, with no unrelated requests.
- Review the final generated document content. Confirm that professional fields returned by tools are correctly embedded in corresponding positions, with no omissions or errors.
- Adjust
toolChoicetoautoand trigger a test. Confirm that the AI can independently select appropriate tools to complete data retrieval.
The configuration values listed above are common starting points, and should be evaluated 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.