What the data for this category looks like
Coal mine production business process-related data mainly comes from internal dispatching systems, safety inspection systems, work order management systems, and equipment operation and maintenance platforms. Data update rhythm varies with business scenarios: work order data updates in real time, safety inspection data updates per shift or daily, and equipment operation data updates after a single inspection is completed. Document structure includes fields such as business type, processing node, responsible person, time limit requirements, associated equipment number, and safety threshold. Field units include professional units such as hours, days, alphanumeric codes, and engineering percentages.
What constraints these characteristics impose on the model integration and configuration link
Heterogeneous data formats from multiple source systems require unified field mapping rules in integration configurations, to prevent the model from confusing field meanings and units of data from different sources. Real-time updated business data require the model context window validity period to match the data update frequency, to avoid calling outdated process information. Strict specifications for professional fields require the model prompt to clearly specify the value range and units of fields, to ensure generated process guidance complies with coal mine safety regulations. In addition, transmission of sensitive business data requires configuring a dedicated identity verification mechanism for API calls, to ensure data security.
Configuration reference for FastGPT v4.17.0
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Matches the full context length of coal mine business process guidance, to avoid truncating key equipment numbers and time limit requirements |
maxTokens | 2000 token | Controls the output length of single-round business guidance, to meet the quick viewing needs of coal mine site personnel |
quoteMaxToken | 1500 token | Limits the length of referenced business data, to avoid introducing irrelevant historical work order information |
toolChoice | auto | Allows the model to automatically select whether to call business data tools, to adapt to different processing scenarios |
temperature | 0.2–0.4 | Reduces generation randomness, to ensure steps in business guidance align with coal mine safety specifications |
AIPROXY_API_ENDPOINT | Proxy address deployed internally for coal mines | Enables secure calls to internal business data, to avoid exposing sensitive information over public networks |
AIPROXY_API_TOKEN | Configured in accordance with enterprise internal key specifications | Ensures identity verification security for API calls |
Three common misconfigurations
- Symptom: The call log module on the model provider's page is empty, with no request records. Cause: FastGPT's API call log collection configuration is not enabled, or the internal proxy service does not forward log information.
- Symptom: Knowledge base retrieval tests return normal results, but the model has no response or generates incorrect guidance during the business process guidance link. **Cause
: Business tool call permission is not enabled in thetoolChoice` configuration, or the context window does not include key nodes of the business process. - Symptom: The specified model version (such as DeepSeek V3.1) does not appear in the model selection list. Cause: The latest model metadata is not synchronized in the internal proxy service, or the configured
AIPROXY_API_ENDPOINTdoes not point to the correct model repository address.
How to verify successful configuration
- Check whether the
AIPROXY_API_TOKENconfiguration matches the key set in the internal proxy service, and send a test request to verify identity verification passes. - Adjust
maxContextto a preset small value range, and test whether short-context business process data loads normally. - Set
temperatureto 0.5, generate a test business guidance, and confirm the output includes correct equipment numbers and time limit fields.
The values provided above are common starting points, and should be adjusted based on the reader's own actual samples and business requirements.
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.