What this type of data looks like
Data related to inspection and process record audit for basic chemical continuous production comes from DCS/SIS systems, online analyzers, LIMS systems, equipment condition monitoring, energy metering devices and raw material storage tanks. Data update rhythms fall into three categories: real-time, shift-based and daily, corresponding to process parameters, shift records and periodic reports. Daily documents include operating procedures, process index cards, DCS trend charts, laboratory reports, interlock bypass records, special work permits and shift reports. Fields include process control point values, interlock trigger conditions, work approval status and other items. Corresponding units include degrees Celsius, megapascals, cubic meters per hour and more.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The characteristics of multi-source real-time and batch-updated data require limiting the context of multi-turn dialogue to a reasonable length to avoid excessive token usage. Diverse document types require prompt engineering to clearly distinguish usage scenarios. For example, use process index cards to verify current parameters, and use interlock records to audit alarm handling. Data with different update frequencies requires prompt engineering to specify retrieval of the latest shift reports and real-time DCS data. Ensure dialogue return results match the units of corresponding fields to avoid confusion of process parameters. The business characteristic of strong interlock control requires multi-turn dialogue to gradually ask for missing verification parameters to ensure audit completeness.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 800–1200 characters | Matches the total length of real-time data and shift reports for basic chemical continuous production, and adapts to the token capacity limit of FastGPT v4.17.0 |
messages context truncation rule | Retain the most recent 3 turns of dialogue and the latest 2 pieces of real-time data | Adapts to the update rhythm of real-time data, avoiding context overload that affects dialogue response speed |
variables binding rule | Bind the process unit ID of the current dialogue | Limit dialogue to only retrieve operating procedures and DCS data for the corresponding unit, narrowing the retrieval scope |
chatId association rule | Bind the session ID of the corresponding production device | Ensure that the context of multi-turn dialogue only belongs to the current inspection and audit scenario, avoiding confusion of cross-device data |
| Knowledge base recall scope | All documents generated during the current shift | Corresponds to the shift-based update frequency of the data, ensuring recall of the latest shift reports and interlock records |
Three common errors
- Phenomenon: Real-time DCS data cannot be added to the knowledge base during dialogue. Cause: The knowledge base write trigger condition is not clearly specified in the prompt engineering, and the data source tag in
variablesis not bound. - Phenomenon: SQL query results are not displayed in the AI dialogue box. Cause: The result splicing step for
messagesis not configured in the workflow, and query results are not written to the dialogue context. - Phenomenon: Markdown messages sent via the WeChat interface display original syntax symbols. Cause: Format adaptation is not enabled in the dialogue configuration, and special symbols are not standardized.
How to confirm the configuration is correct
- Initiate an inspection and audit dialogue for a specific process unit, check whether the dialogue context includes the latest DCS trend and shift report for that unit.
- Trigger a knowledge base write operation, verify whether the corresponding document is successfully added to the designated inspection and audit knowledge base.
- View the dialogue log, confirm that the parameter values of
chatId,messagesandvariablesmatch the configuration rules. - Test the dialogue result sent via the WeChat interface, confirm that the Markdown format is displayed normally with no residual original syntax symbols.
The values provided are common starting points and should be measured against the reader's own samples.