What data for this category looks like
Data for this category comes from wood pulp and waste paper batch ledgers, DCS and QCS systems, paper machine online measurement equipment, laboratory test results, and energy and water treatment systems. Data update cycles cover real-time, per-shift, and per-roll production milestones. Daily documents include pulp preparation sheets, beating records, paper machine operation logs, online quality curves, laboratory test reports, and sheet break and product change records. Record fields include slurry solid content, beating degree, sheet grammage, moisture value, thickness, sheet break duration, and more. Units include degrees, grams per square meter, millimeters, and others.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The data sources for this category are scattered, and update cycles vary widely. The multi-turn dialogue link needs to associate cross-system ledgers, operation logs, and test data. Prompts must clearly specify the range of data sources to call. Daily document formats are diverse, including tables, curves, and plain text records. Multi-turn dialogue needs to gradually guide users to clarify the type of document to be parsed. Prompts must adapt to field extraction rules for different formats. The update logic for real-time data and historical batch data differs. Prompts must distinguish between dynamic real-time indicators and static historical records. In multi-turn dialogue, the context length must be limited to avoid overload affecting response speed.
How to set up the configuration
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current roll or batch | Used to associate historical records such as pulp preparation and beating for the corresponding batch, ensuring multi-turn dialogue context matches the current production task |
messages | Retain the first 10 dialogues and associated system data records | Adapt to the traceability requirements of multiple pulp and paper production links, avoid context overload |
variables | Inject the current paper machine model, pulp batch number, and test standard number | Allow prompts to call site-specific parameters, improving result accuracy |
| Maximum context length | 800–1200 characters | Matches the core data volume of a single roll of paper production process, avoids response timeout |
| Prompt template | Confirm the current production link first, then extract corresponding fields | Adapt to multi-link inspection and review requirements, guide users to gradually clarify the query scope |
| Context refresh interval | 60 seconds | Adapt to the update cycle of real-time data, ensure the latest online measurement data is called during dialogue |
Three common mistakes
- Symptom: Dialogue response results do not match expectations, and prompt configuration shows no effect. Cause: The prompt is not bound to the corresponding
variablesvariable, or the prompt template does not include clear instructions for field extraction. - Symptom: The dialogue interface loads slowly, and timeout errors occur. Cause: The number of dialogues retained in
messagesis not limited, and the context length exceeds the system's carrying capacity. - Symptom: Key production data is missing from exported dialogue records. Cause: The ledger ID of the corresponding batch is not injected into
variables, causing the system to fail to associate complete inspection and process records.
How to confirm the configuration is correct
- Initiate a query that includes the current roll batch number, confirm that the dialogue can automatically associate the pulp preparation sheet and beating records for the corresponding batch.
- Adjust the number of dialogues retained in
messages, test the response speed and context integrity under different values. - Enter a test prompt, confirm that the output results include the specified paper machine operation parameters and test indicators.
- Trigger dialogue record export, confirm that the exported file includes complete multi-round interaction content and associated production data.
The values provided here are common starting points and should be evaluated against the reader's own samples.