What the data for this category looks like
Data for this category primarily comes from production links of power transmission and distribution equipment, transformer, and switchgear manufacturing enterprises. Daily documents include winding and core assembly records, vacuum drying records, insulating oil reports, partial discharge and withstand voltage test reports, and nameplate parameter tables. Data sources include design BOM, silicon steel sheet and insulating material procurement data, vacuum drying equipment logs, oil test reports, and test station inspection records. Updates are synchronized after each product or batch of raw materials is completed. Single product ledgers include associated fields such as process parameters, test values, and material traceability. Fields are tightly bound to production links, with high data correlation.
What constraints these characteristics impose on the model access and configuration link
Multi-source associated ledger data for this category includes multiple document types such as process records and test reports. Fields are closely linked and updated in real time with each product or batch of raw materials. This requires model access to support long context processing, to avoid losing cross-field process and test association information after splitting. Test detection values have strong professional attributes. Configuration must support accurate recognition of industry terms to avoid parameter confusion. Additionally, the traceability requirement for single products demands precise matching of batches and process nodes when the knowledge base is referenced, to prevent cross-product data misuse that would reduce the accuracy of ledger summary.
How to set the configuration
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
maxContext | 8000–12000 token | The ledger for a single transformer includes multiple associated documents such as winding, drying, and test records, with a high total token count. Full associated data must be covered to avoid information loss |
quoteMaxToken | 2000–3000 token | Sufficient core details such as insulating oil parameters and partial discharge test values must be retained for summary, while redundant information that would interfere with report generation logic must be avoided |
maxTokens | 4000–6000 token | Production ledger summary reports must cover full single-product process records or multi-product batch comparisons, requiring sufficient response length to carry complete content |
temperature | 0.1–0.3 | Production ledgers and reports must accurately restore process and test data. Excessive divergence must be avoided, and output rigor must be maintained |
AIPROXY_API_ENDPOINT | Enterprise intranet compliant proxy address | FastGPT v4.17.0 supports this configuration, which meets intranet access and security compliance requirements for production data |
| Workflow/API tool selection | auto | Can automatically call information extraction tools based on ledger document types, adapting to processing needs for multiple document types such as winding records and test reports |
Three common mistakes
- The final output of workflow testing always appends a specified identifier text at the end, and this text does not appear in the configured knowledge base content. The cause is that the default additional content of the system prompt is not disabled in the model configuration. FastGPT v4.17.0 adds this identifier to the end of outputs by default.
- When configuring
maxContextorquoteMaxToken, values outside the reasonable range lead to truncated model output, failure to load complete ledger data, or response timeout. The cause is that parameters are not adjusted based on the actual data volume of a single product. Too small a value causes information truncation, while too large a value exceeds the model context limit or increases response time. - Model calls fail, returning connection timeout or permission denied errors. The cause is confusion between the configuration locations of custom request addresses and proxy addresses, or the proxy address is not configured with intranet access permissions, making it impossible to connect to the model service.
How to confirm the configuration is correctly set
- Import the complete ledger documents of a single product, run workflow testing, and verify that the output report covers all preset core fields and associated information, with no obvious truncation or omissions.
- Adjust the value ranges of configuration items, run multiple sets of comparative tests, and confirm that the rigor of the output results matches the business requirements of production ledgers, with no divergent content that violates professional logic.
- View the model call log, confirm that the request address and proxy configuration parameters are correct, with no error prompts such as connection timeout or permission denial.
- Import similar ledger data from different batches, run the test, and confirm that the knowledge base reference does not have cross-batch or cross-product data misuse.
The values provided are common starting points and should be measured against the reader's own samples.