What this category of data entails
The core thread of this category of data is individual vehicle VINs. Daily documents include production orders, VIN lists, assembly work instructions, tightening data, offline inspection reports, repair records, and consistency release documents. Data sources cover ERP/MES systems, VIN and configuration systems, tightening tools, EOL inspection lines, and quality traceability systems. Updates are generated in real time per vehicle and synced in batches per shift. Fields include VIN codes, part batch numbers, tightening torque values, inspection results, and some fields have dedicated units such as newton meters (N·m).
Constraints imposed on tool calling and plugin workflows
The mixed-line production model centered on individual vehicle VINs requires tool calling to use VIN as the sole retrieval identifier. This ensures accurate matching of assembly work instructions and technical standards for the corresponding vehicle, and prevents cross-vehicle configuration confusion. Real-time updated tightening data and offline inspection reports require plugin calls to support high-frequency, low-latency interface requests, to align with batch synchronization rhythms per shift. Structured fields with dedicated units such as tightening torque (N·m) require tool calling to include parameter verification and unit matching, to ensure the accuracy of Q&A results. Multi-station parallel operation scenarios require plugins to handle concurrent retrieval of multiple VINs, to avoid disrupting production cycles.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Workflow/API tool selection | Set to auto | Adapt to automatic tool triggering requirements across multiple scenarios in mixed-line production, no manual tool specification needed |
| Workflow/API function-call configuration | Enabled | Ensure the AI can generate properly formatted tool call requests, suitable for structured process data retrieval |
| Tool call timeout period | 60–120 seconds | Match the operation cycle of a single work station, prevent timeouts from disrupting production workflows |
| Retrieval result limit | Top 3 entries | Control the number of process documents matched per VIN, avoid context overload that slows response speed |
| Parameter verification switch | Enabled | Ensure formatted compliance for fields with units such as VIN codes and torque values (N·m) |
| Plugin concurrency limit | Calibrated to the number of work stations | Adapt to multi-station parallel retrieval production scenarios, do not exceed on-site equipment load |
Three common configuration errors
- Symptom: Tool selection fails, and the AI returns only natural language responses without triggering tool calls. Cause: The
functionCallconfiguration is not enabled correctly, ortoolChoiceis set tonone, preventing the AI from recognizing tool calling rules. - Symptom: Empty results are returned when calling a SQL Server type database plugin. Cause: VIN codes are not configured as retrieval parameters, or the structured field formats for tightening data and inspection reports are not adapted, so matching corresponding data fails.
- Symptom: Tool call requests time out, and the interface returns a timeout status code. Cause: The timeout period is set too short, not matching the operation cycle of a single work station, or the plugin concurrency limit is too high, exceeding system load.
How to confirm successful configuration
- A test question containing a VIN code may be submitted, and the AI’s tool call triggering and return of corresponding process specification content may be verified.
- FastGPT v4.17.0 tool call logs may be reviewed, to confirm that the request format generated by
functionCallfollows preset rules, and parameters include required fields such as VIN codes. - Concurrent requests for multiple VINs may be simulated, to check whether the plugin’s response status matches the concurrency limit settings.
- The tool call timeout period may be adjusted, to verify that the timeout trigger logic behaves as expected.
The values provided here are common starting points, and should be evaluated against the specific samples relevant to the deployment environment.