What the data for this category looks like
Core data sources for basic chemical continuous production include DCS/SIS systems, online analyzers, LIMS laboratory management systems, equipment condition monitoring devices, energy metering devices, and raw material tank liquid level data. Daily documents cover operating procedures, process index cards, DCS trend curves, laboratory reports, interlock bypass records, special work permits, and shift reports. Data update rhythms are divided into real-time (such as DCS pressure and temperature), per-shift (such as shift output and energy consumption), and daily (such as interlock statistics and equipment patrol records). Document fields include unit number, process parameter units (MPa, ℃, t/h), alarm thresholds, work permit numbers and other unique chemical production identifiers.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Real-time updated DCS data requires conversation contexts to pull the latest parameters synchronously to avoid relying on outdated information. Per-shift and daily updated shift reports and interlock records require prompt engineering to dynamically match the document scope of the current cycle. The business feature of strong interlock control requires multi-turn dialogue to retain the context of historical alarms and disposal records to ensure consistent disposal logic for exception reports. Unlike other process industry categories, basic chemical continuous production focuses on the reaction-separation-circulation system steady state. Prompt engineering does not need to adapt to the complex correlations of multi-component fractionation networks, and can focus on verification and exception analysis of core process parameters.
How to set the configuration
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Include fixed prefixes with unit number and current shift | Match the daily/per-shift update rhythm of shift reports and interlock records to quickly locate corresponding production data |
variables | Pass the variables field according to the API request body | Support dynamic replacement of variable content such as unit parameters, shift output, and alarm thresholds in prompt engineering |
| Context window size | 8000–12000 token | Accommodate long text content such as multiple DCS trend curves, laboratory reports, and interlock records |
| Rerank switch | Enabled | Improve the recall priority of documents related to abnormal alarms and enhance the accuracy of exception report drafting |
| Timeout threshold | 300 seconds | Adapt to the real-time data pull delay of DCS to avoid interrupting the conversation due to data acquisition timeout |
| Single recall count | Top 6 | Cover the necessary reference content of core process documents and avoid interference from redundant information |
This page configuration is based on FastGPT v4.17.0.
Three common mistakes
- No preset initial information for new conversations: The symptom is that fixed content such as unit number and shift is not displayed after starting a conversation. The cause is that the default initial message is not configured in the system conversation template.
- Prompt engineering variables do not take effect: The symptom is that preset dynamic fields are not replaced in the reply content, such as failing to substitute the pressure parameters of the current unit. The cause is that the API request body is not passed in the
variablesfield format. - Workflow interruption with no response: The symptom is that the node waiting for user input is not triggered after text extraction fails. The cause is that the user waiting link of the workflow is not configured.
How to confirm the configuration is complete
- Start a new conversation and check if the initial message includes the preset unit number and current shift information.
- Call the API and pass the test
variablesfield to verify whether the reply content correctly replaces the dynamic parameters. - Simulate an abnormal alarm input and check whether the conversation details retain historical context content.
- View the conversation details and confirm that the
chatIdfield is unique and correctly associated with the current production unit's conversation. - View the workflow log to confirm that the rerank function is enabled and the recall count meets the preset range.
The values provided are common starting points and should be evaluated against the reader's own samples.