What this category of data looks like
Data for integrated coal and power internal office and employee services comes from production scheduling systems, equipment maintenance logs, office OA systems, employee attendance records, and safety inspection archives. Update rhythms vary. Production-related data is updated in real time or near real time. Office documents are updated in daily batches. The data includes structured device parameters, energy consumption reports, attendance ledgers, and unstructured inspection reports, meeting minutes, and training materials. Fields include device number, unit load, coal consumption, shift information, and corresponding units such as kilowatt-hour, ton, and person-time.
What constraints do these characteristics impose on model integration and configuration
The data characteristics of integrated coal and power operations impose multiple constraints on model integration and configuration. Mixed structured device parameters, energy consumption reports, and unstructured inspection reports and meeting minutes require configurations that support processing logic for multiple input types. Low-latency requirements for real-time production data require adjustments to model context window length and response timeout settings. The presence of a large number of industry-specific terms requires optimization of model generation accuracy parameters. Differences in update frequencies across data sources require configuration of distinct synchronization and invocation rules for different data.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to long documents in the coal and power industry such as maintenance reports and scheduling records |
temperature | 0.2–0.4 | Reduces generation deviation for professional terminology, and ensures the accuracy of office and maintenance content |
vision | Enabled | Supports processing image data from equipment inspections, and meets visualization requirements for internal employee services |
quoteMaxToken | 2000–3000 token | Retains sufficient context from historical office data and maintenance logs |
AIPROXY_API_ENDPOINT | Fill in the enterprise internal model proxy address | Adapts to coal and power industry-specific models deployed on internal networks, and ensures data security |
AIPROXY_API_TOKEN | Fill in the exclusive key allocated by the enterprise | Ensures permission verification and security for internal network model calls |
Three common mistakes
- Phenomenon: The interface prompts that no available channels are available after configuring
AIPROXY_API_TOKEN. Cause: The currently used group permission is not bound to the target model channel. - Phenomenon: The model creation entry identifier is not displayed in the upper right corner of the interface. Cause: The model management permission corresponding to the account is not configured, or FastGPT v4.17.0 or later is not used.
- Phenomenon: The token processing capacity per second of the locally deployed model cannot be queried. Cause: The performance monitoring interface of the local model is not associated in the model integration configuration.
How to confirm the configuration is complete
- Invoke the test interface and input coal and power industry professional documents. Check whether the model returned content includes accurate industry terminology and compliant data logic.
- Upload equipment inspection images, and verify whether the model can recognize them normally and return corresponding analysis results.
- View the model call log, and confirm that the actual usage values of
maxContextandtemperaturematch the preset configuration. - Test model call permissions under different groups, and confirm that the configured
AIPROXY_API_TOKENcan pass channel verification normally.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.