What data for this category looks like
The data for this category comes from enterprise ERP order and inventory systems, BOM lists, process route tables, equipment capacity ledgers, staff scheduling tables, work-in-progress ledgers, and supplier arrival records. Daily generated documents include sales orders, master production plans, material requirement plans, weekly production schedules, production work orders, material shortage lists, delivery change notices, and more. Fields include order numbers, material codes, capacity man-hours, scheduling priority, delivery dates, and others. Update frequencies are daily, weekly, or real-time when orders or exceptions occur.
Constraints imposed on model access and configuration
Data sources are scattered and have varying formats, so model access must support unified parsing of multi-source data. Document length and content complexity are high, so sufficient context processing space must be reserved to avoid truncation of core information such as scheduling and work order breakdown. Exception triggers have no fixed pattern, so model calls must support real-time responses. At the same time, production data involves core enterprise business, so access processes must comply with intranet isolation and permission control requirements to prevent sensitive data leaks.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the long context requirements of production planning documents, avoiding truncation of core information such as scheduling and work order breakdown |
maxTokens | 4000 token | Matches the output length of process documents and exception reports, covering complete process descriptions, scheduling adjustment suggestions, and other content |
temperature | 0.2–0.4 | Maintains the rigor of production documents, avoiding generation of parameters or scheduling plans that do not comply with production specifications |
AIPROXY_API_ENDPOINT | Fill in the enterprise intranet proxy address or official model access address | Adapts to the network isolation requirements of the production environment, ensuring that core production data does not flow out of the enterprise intranet |
AIPROXY_API_TOKEN | Exclusive key assigned according to business roles | Differentiates call permissions for different roles such as shop schedulers and PMC personnel, preventing unauthorized data access caused by key sharing |
Three common mistakes
- Symptom: The model test returns the error "[] is too short - 'messages'". Cause: No valid business context is passed, only empty task instructions or production data containing only placeholders are submitted.
- Symptom: After upgrading to FastGPT v4.17.0, the newly added model configuration items cannot be seen in the interface, and the issue persists after restarting the service. Cause: Model configuration parameters are not correctly written to the system configuration file, or front-end cache has not triggered an update, causing interface loading abnormalities.
- Symptom: Models accessed via a proxy cannot connect normally. Cause: The proxy address or key configuration is incorrect, or the enterprise network firewall blocks outbound requests for model calls.
How to confirm configuration is complete
- Run a model connectivity test, confirm that no errors are returned and the response time meets business expectations.
- Upload a test sales order and weekly production schedule, verify that the model can generate process document drafts that comply with the format.
- Configure user permission groups, test whether different roles can call exclusive model keys and generate documents for corresponding businesses.
- Simulate a material shortage exception scenario, upload a test material shortage list, verify that the model can generate required exception reports.
The values provided are common starting points and should be evaluated against the reader's own samples.