What this category’s data looks like
Core data for complete vehicle final assembly uses the individual vehicle’s VIN as its unique identifier. Data sources include ERP/MES systems, VIN and configuration systems, tightening tools, EOL off-line inspection lines, quality traceability systems, and supplier batch libraries. Daily produced documents include production orders, assembly work instructions, tightening torque data, off-line inspection reports, rework records, and consistency release documents. Fields include VIN, torque value (unit N·m), inspection item number, part batch number, and others. Update frequency is real-time generation per vehicle, with batch data aggregated per shift.
What constraints do these characteristics impose on the tool calling and plugins workflow
This category uses mixed-model production with VIN as the primary identifier for individual vehicles. Tool calling must dynamically match hundreds of part configurations tied to a given VIN, so plugins from different data sources must be called dynamically. Each vehicle has large data volumes with real-time updates, so a reasonable timeout must be set for tool calling to avoid workflow interruptions. Drafting abnormal reports requires associating tightening, inspection, and rework data from multiple systems, so multi-plugin linked calls must be configured. Errors may cause line stops or vehicle recalls, so permissions and parameter validity for tool calling must be strictly verified.
How to set configurations
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapts to the need for dynamic calling of plugins from different data sources in mixed-model production, no manual tool specification required |
| Workflow/API function-call configuration | Enabled | Ensures tool calling results are output in structured format, facilitating automatic splicing of subsequent abnormal reports and process documents |
| API key verification | Enabled and bound to an exclusive key | Prevents unAuthApiKey errors, and aligns with internal permission control requirements of vehicle manufacturers |
| Tool call timeout | 300–600 seconds | Adapts to the duration required for batch pulling of tightening data and off-line inspection reports |
| Context window size | 8000–12000 token | Accommodates full process configuration and inspection data for a single vehicle, avoiding context truncation |
| Global variable update trigger | After tool call completes | Synchronizes configuration parameters matched via VIN to subsequent conversation steps, ensuring data consistency |
Three common mistakes
- Phenomenon: The
chatIdparameter is passed when calling the FastGPT API, but the parameter does not appear in the conversation log. Cause: Session context binding is not enabled in platform settings, and the session identifier is not passed through the tool calling chain. - Phenomenon: Global variables updated during tool calling do not take effect in subsequent workflows. Cause: The variable update action is not bound to the tool call completion callback node, and the variable scope is limited to a single conversation loop.
- Phenomenon: Calling a tool returns the error
{"code":514,"statusText":"unAuthApiKey","message":"common:code_error.e. Cause: A valid FastGPT API key is not configured, or the permission scope bound to the key does not cover the currently called tool plugin.
How to confirm the configuration is complete
- Initiate a test call, pass a test VIN, and verify that the configuration data returned by the tool matches the assembly requirements for the corresponding VIN.
- View the conversation log, confirm that the passed
chatIdparameter is correctly recorded and used to associate session context. - Trigger the abnormal report drafting workflow, and verify that the global variables have synchronized the latest rework record data.
- Pass an invalid key when calling a tool, confirm that the
unAuthApiKeyerror is returned, and verify that the permission check is active.
The values provided here are common starting points and should be measured against the reader's own samples.