What this category of data looks like
Coal mining production ledger data primarily comes from underground environment sensors, fully mechanized mining equipment operation and maintenance systems, ground dispatching and command platforms, and monthly safety inspection reports. Data update cycles fall into three categories: environmental parameters refresh every 1 to 5 minutes, equipment operation data is synchronized in real time with operations, and monthly summary ledgers are archived by the 3rd day of the following month. Individual ledger documents include fields such as unique equipment number, continuous operation duration, fault trigger count, patrol inspection execution time, gas concentration value, daily coal output in tons, and more. Units include hours, times, ppm, tons, and others.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" link
The varying update rhythms of multi-source heterogeneous ledger data require that corresponding data source interfaces be called in real time during multi-turn dialogue processes, to avoid using cached expired data. The presence of specialized fields and non-standard units requires that prompts clearly define field names, statistical scopes, and units, to prevent the model from generating results that do not comply with coal mining production specifications. Scenarios involving mixed queries of cross-time dimension ledgers (real-time parameters, monthly summaries) require that multi-turn dialogue processes record the time range parameters specified by the user, to ensure each call matches the dataset with the corresponding update frequency.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the current dialogue session ID | Ensure multi-turn dialogue context is tied to the user session, to avoid cross-session data confusion |
messages | Retain the most recent 20 dialogue histories, with each piece of content not exceeding 1500 characters | Adapt to the professional text length of coal mining ledger data, to avoid context overflow |
variables | Preset two types of global variables: time range and equipment number | Match the high-frequency ledger filtering conditions used by users, to reduce repeated input |
| Maximum context | 8000–12000 token | Cover the summary text of a single batch of equipment ledgers, to support multi-turn associated queries |
| Timeout threshold | 600 seconds | Adapt to the delay of cross-system data pulling for coal mining data, to avoid request interruptions |
| Question optimization | Enabled | Automatically complete unspecified time or equipment parameters from users, in line with professional habits for coal mining ledger queries |
Three common misconfigurations
- Phenomenon: Dialogue response content takes longer than 600 seconds to return, and the interface returns a timeout error. Cause: The timeout threshold adapted for cross-system data pulling in coal mining is not configured, and the default timeout duration is insufficient.
- Phenomenon: After modifying global variables in the same dialogue, subsequent component calls do not synchronize the updated variable values. Cause: The real-time update logic for the
variablesparameter is not bound in the multi-turn dialogue process, and variables are only read during initialization. - Phenomenon: Only aggregated full context can be obtained, and individual user questions from each turn cannot be retrieved during multi-turn dialogue. Cause: The single question extraction configuration for the
messagesparameter is not enabled, and all historical contexts are incorrectly concatenated.
How to confirm configurations are correctly set
- Initiate a multi-turn query that includes equipment number and time range, and check whether each reply matches the latest ledger data from the corresponding data source.
- Manually modify the global variable values, and verify whether subsequent dialogue calls use the updated variable content.
- View the dialogue history records, and confirm that each user question is individually recorded and associated with the corresponding query request.
- Test cross-system data pulling requests, and confirm that the request duration does not exceed the preset timeout threshold.
The values provided here are common starting points, and should be evaluated 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.