What this category of data looks like
Coal-electric integration ledger data is sourced from real-time collection systems at coal mine production ends and power plant operation ends, daily dispatch logs, and monthly settlement reports. Data update frequencies fall into three categories: production parameters such as excavation progress and coal fed to the furnace are updated in real time; equipment operation and maintenance ledgers are updated daily; monthly energy consumption and revenue ledgers are updated periodically.
The document structure is split into coal mine sub-ledgers (excavation, transportation, coal washing links) and power plant sub-ledgers (boiler, steam turbine, desulfurization and denitrification links). Fields include raw coal output (unit: ton), heating value of coal fed to the furnace (unit: MJ/kg), power generation load (unit: MW), unit coal consumption (unit: g/kWh), and more. Some ledgers include equipment site photos and process drawings, stored in the knowledge base in URL format.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Cross-end data source structures require multi-turn dialogue to clearly distinguish scenario boundaries between coal mines and power plants, to prevent context confusion. Differences in update frequencies require prompt engineering to specify data time range parameters, ensuring that the aggregated ledger cycle matches requirements. Specific fields and units require prompt engineering to include built-in validation rules, enforcing unified output formats to prevent report errors caused by unit confusion. Attached image-based ledger data requires the dialogue flow to support parsing and display of URL-format images, with clear image call rules specified in the prompt engineering.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window length | 8000–12000 token | High correlation exists between coal and power ledger data; sufficient context preserves logical coherence of cross-link dialogue |
| Maximum dialogue turns | First 8 turns | Ledger aggregation typically revolves around fixed cycles; excessive turns may introduce irrelevant historical data that interferes with results |
| Prompt template variables | Calibrated based on actual testing | Adapt to exclusive field prefixes of different coal mines or power plants, avoiding confusion of ledger data across entities |
| Knowledge base recall count | First 6 entries | Ledger data entries are concentrated and highly correlated; a small number of recalls can cover core aggregation requirements |
| Image processing toggle | Enabled | Equipment ledgers often include site photos and process drawings; support for displaying URL-format images is required |
| Timeout duration | 120 seconds | Cross-system ledger aggregation requires retrieving data from multiple sources; sufficient response time should be reserved |
Three common misconfigurations
- Images from the knowledge base cannot be displayed during dialogue: The image processing toggle is not enabled, or image URLs in knowledge base documents do not follow standard format requirements.
- Empty ledger aggregation results are returned by API calls: Historical dialogue context is not passed in the
messagesparameter, or the exclusive ledger field prefix for the current scenario is not passed viavariables. - Ledger data output in multi-turn dialogue has inconsistent units: The prompt engineering does not explicitly require unified field units, and does not associate the current dialogue with the corresponding coal mine or power plant entity.
How to verify correct configuration
- Upload a coal-electric ledger document containing equipment image URLs, initiate a dialogue requesting image display, and confirm that images display normally.
- Initiate a cross-link multi-turn dialogue: first query the coal mine monthly ledger, then query the power plant associated energy consumption data, and confirm that the dialogue context is correctly retained.
- Pass the
chatIdparameter when calling the dialogue API, initiate two consecutive ledger query requests, and confirm that both results belong to the same dialogue context. - Initiate a test dialogue involving multi-source data retrieval, confirm that no timeout error occurs, and that the output ledger data uses consistent units.
The values provided here 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.