Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The primary data sources for coal chemical industry internal office and employee services include equipment operation and maintenance logs, production operation reports, safety operation procedures, employee attendance and scheduling records, salary calculation documents, and more. Equipment operation and maintenance logs are organized per individual device, with fields including device ID, fault type, processing time, replacement spare part ID, and others, with units of MPa, ℃, and hours. Production operation reports are generated per shift, containing timestamp, post ID, key operation parameters, and other content. Safety operation procedures are updated by post category and revised every quarter. Attendance and salary documents are updated monthly, with fields including employee ID, post, number of attendance days, and others. Most single document records range from 800 to 1200 characters; some long documents require splitting.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Coal chemical industry data contains many specialized terms and closely linked fields. Multi-turn dialogue must accurately bind devices and conversation context to avoid mixing up operation records of different devices. Real-time production data and periodically updated procedure documents need to have their call priorities distinguished; prompts should guide prioritizing the latest safety and operation data. Single documents are relatively long, so the context window for multi-turn dialogue must be limited to prevent response delays caused by loading overly long data. The association logic of fields such as device ID and timestamp must be clearly defined in prompts to ensure accurate recall of historical records for the corresponding device during dialogue.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the single record length of coal chemical production reports and operation and maintenance logs, to avoid truncating key parameters |
| Overlap Length | 150–200 characters | Covers associated fields such as device ID and timestamp across chunks, ensuring complete context recall |
| Maximum Context | 10–15 conversation turns | Adapts to the standard multi-turn process for coal chemical fault troubleshooting, preventing slowed responses caused by overloaded context |
chatId | Bind device ID and conversation session | Ensures accurate association of multi-turn dialogue context for the same device, avoiding mixing up operation records of different devices |
variables | Bind post and device type | Filters out document content not for the target post, improving response accuracy in coal chemical employee service scenarios |
| Prompt Template | Include "Prioritize the latest safety procedures and equipment operation and maintenance logs" | Adapts to the batch update feature of coal chemical industry documents, guiding calls to the latest available knowledge base content |
Three common mistakes
- Phenomenon: Inconsistent results returned when calling the dialogue application via API compared to platform testing. Cause: The coal chemical-specific knowledge base was not bound during the call, and the general knowledge base was called by default, leading to responses deviating from the business scenario.
- Phenomenon: Operation records of different devices are mixed up during multi-turn dialogue. Cause: Device ID and conversation were not bound via
chatId, leading to cross-device context association and recall of incorrect historical records. - Phenomenon: Uploaded coal chemical operation and maintenance log files fail to parse. Cause: Industrial log format parsing configuration was not enabled; the default setting only supports general document formats and cannot recognize coal chemical-specific fields such as device ID and pressure parameters.
How to confirm the configuration is correct
- Initiate a single-turn dialogue test, input an operation and maintenance question for a specified device, and check whether the returned result contains the device’s exclusive parameters to verify that context binding is effective.
- Carry the
messagesparameter when calling the API to pass multi-turn historical dialogue, and check whether the returned result is associated with the historical context to verify that the multi-turn dialogue logic works properly. - Upload coal chemical-specific documents to the knowledge base, initiate a dialogue to ask about professional clauses in the documents, and check whether the returned content matches the latest updated document version.
- Check the chunk length and overlap length in the configuration items, confirm that the value range meets the single record length requirements of coal chemical industry documents, and verify that the document splitting logic is correct.
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.