What this type of data looks like
Coal mine production document data primarily comes from underground operation logs, shift scheduling records, safety hazard rectification notices, acceptance inspection reports, and operation procedure documents. Data is updated upon completion of each production shift, and the volume of data per shift fluctuates with operation scale. The document structure uniformly includes fields such as operation location code, operation duration, participating work teams, hazard inspection items, and rectification closed-loop status. Most field units are common production units such as meters, tons, hours, and shifts, and some documents have associated identifiers for on-site photos.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The shift-based update feature of coal mine production documents requires that multi-turn dialogue be bound to chatId to track the context of the current operation cycle, preventing interference from cross-shift data. Specialized fields and units require that prompts pre-set standard coal mine operation terminology to avoid terminology misunderstandings. Associated photo identifiers require that the multi-turn process support unstructured data calls. Fluctuations in per-shift data volume require limiting the amount of context called in a single dialogue to prevent model processing overload. Document formats vary significantly across different operation scenarios such as tunneling, coal mining, and ventilation, so prompts need to dynamically adjust parameters based on the scenario to ensure generated content complies with the specifications of the corresponding operation.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 800–1200 characters | Matches the average length of per-shift coal mine documents, avoiding exceeding model processing limits |
chatId | Bind the unique identifier of the current operation shift | Ensures multi-turn dialogue tracks the context of the same operation cycle, preventing confusion from cross-shift data |
messages | Only retain the last 3 rounds of dialogue and content related to the current operation documents | Reduces redundant data and improves model response efficiency |
variables | Pre-set coal mine operation terminology and safety regulation keywords | Ensures prompts accurately match production-specific fields and units |
| Question optimization | Trigger pre-verification based on operation scenarios | Filters non-production document drafting requests in advance, focusing on compliant content |
| Single context call volume | Top 5 associated documents | Matches the scale of associated data for per-shift documents, avoiding overload |
Three common mistakes
- Calling the dialogue interface returns an empty conversation list. Cause: The
chatIdparameter is not passed correctly, so the system cannot identify the conversation context for the current operation. - Generated documents contain terminology deviations unrelated to coal mine production. Cause: Coal mine-specific terminology and safety regulation keywords are not pre-set in
variables, leading the model to misinterpret field meanings. - Irrelevant documents are returned during knowledge base retrieval. Cause: The retrieval scope is not limited to current shift production documents via conversation context, resulting in matching redundant data from cross-cycle periods.
How to confirm the configuration is complete
- Call the dialogue interface, pass the
chatIdbound to the current operation shift, and check if the returned conversation records include the documents for the current shift. - Submit a drafting request that includes coal mine-specific terminology, and check if the generated documents accurately use the corresponding fields and units.
- View the knowledge base retrieval results to confirm that only coal mine production documents within the current operation cycle are returned.
- Initiate two or more consecutive dialogues, and check if subsequent requests can associate previous operation parameters and context.
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.