What the data for this category looks like
Data for this category is generated around the unique VIN code of a single vehicle. Sources include ERP/MES systems, VIN and vehicle configuration systems, workshop tightening tools, End-of-Line (EOL) off-line inspection lines, and quality traceability systems. Daily documents cover production orders, assembly work instructions, tightening torque data, off-line inspection reports, repair records, and consistency release documents. Data updates are performed per single vehicle. Key tightening and inspection data is synchronized in real time. Batch configuration and release documents are updated per shift. Document fields include unique VIN identifiers, part batch numbers, torque parameter values, inspection qualification status, and other fields. Some fields have clear unit requirements.
What constraints these characteristics impose on model access and configuration
Real-time production data for single vehicles requires model access to support low-latency calls, to avoid disrupting workshop production cycles. Multi-source heterogeneous production documents require the model to adapt to input content in different formats. Accurate data matching based on the unique VIN code is required to avoid configuration mismatches in mixed-line production. Batch documents updated per shift require the model to support batch processing workflows, and retain data timestamps and traceability identifiers. Exception report drafting needs to associate unit-bearing fields such as tightening torque and inspection results from specific workstations. The model must accurately associate business scenarios with corresponding data to ensure report content matches actual production status.
How to set the configuration
This configuration is based on FastGPT v4.17.0. Specific parameters can be adjusted based on actual workshop network and data scale:
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Accommodates multi-source production documents and historical repair records for a single vehicle, avoids missing critical information due to context truncation |
maxTokens | 2000–3000 token | Covers the full output length of a single process document or exception report, adapts to interface return limits of workshop systems |
temperature | 0.1–0.3 | Maintains professional and rigorous wording for process documents and exception reports, avoids generating irrelevant or off-topic content |
| Workflow/API tool selection | auto | Automatically selects whether to call tools for data extraction and matching based on input data type, adapts to multi-source heterogeneous production documents |
quoteMaxToken | 1500–2000 token | Retains sufficient knowledge base reference content, supports compliance of process documents and traceability of exception reports |
AIPROXY_API_ENDPOINT | Fill in the proxy address deployed within the enterprise | Adapts to access restrictions of the workshop intranet, ensures security of production data transmission |
Three common configuration errors
- Phenomenon: When calling the model to generate process documents, redundant numbers with no source appear in the output (such as extra 0s). Cause: The
maxContextparameter is not configured correctly, leading to residual redundant data from old requests after context truncation, or thetemperatureparameter is set too high, causing irrelevant content to be generated. - Phenomenon: When batch processing production documents per shift, some data associated with VIN codes is not extracted correctly. Cause: Accurate matching rules are not configured based on VIN codes, or the
quoteMaxTokenparameter is set too small, leading to failure to fully load configuration data for the corresponding vehicle. - Phenomenon: When drafting exception reports, torque data from tightening tools cannot be associated. Cause: The data source format of workshop systems is not adapted, or automatic tool calling via
toolChoiceis not enabled, leading to failure to complete data field mapping and extraction.
How to confirm the configuration is correct
- Submit the VIN code of a single vehicle and corresponding production documents, verify that the generated process document includes all required fields and has no redundant or irrelevant content.
- Simulate an exception scenario by inputting repair records and inspection data, verify that the generated exception report accurately associates parameter values and qualification status from the corresponding workstation.
- Test batch submission of production order data per shift, verify that the model can complete accurate matching and batch processing based on VIN codes.
- View interface return logs, confirm that call delay meets the cycle requirements of workshop systems, and no abnormal error messages are present.
The values provided are common starting points, and should be validated against in-house samples.