What Data for This Category Looks Like
Data related to inspection and process record audit for petroleum refining comes from DCS/APC control systems, LIMS laboratory management systems, tank farm metering systems, crude oil evaluation databases, equipment management systems, and energy management systems. Data update frequencies include three categories: real-time, per shift, and daily. Daily documents cover operating procedures, production plans, material balance sheets, distillate export quality reports, interlock ledgers, shift handover records, and change management documents. Data fields include unit load, distillation range values, tank farm liquid levels, laboratory indicator values, and others. Corresponding units include MPa, ℃, tons, ppm, and more.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
Data from multiple systems requires prompts to explicitly specify data sources, to avoid confusion between indicators from different systems. Data with different update frequencies requires distinguishing between historical archived data and real-time collected data usage scenarios during multi-turn dialogue, to ensure audit logic accuracy. Diverse document types require prompts to match corresponding documents based on task type. For example, call interlock files when verifying interlock ledgers, and retrieve production plans and metering data when calculating material balances. Complex fields and units require prompts to standardize unit conversion rules, to avoid audit errors caused by inconsistent units. The business characteristic of coupled multiple units also requires multi-turn dialogue to retain unit parameters and coordination logic from previous conversations, to support audits for cross-unit load adjustments.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 token | Covers content from multiple core documents such as shift handover records and daily material balance sheets |
variables | Include unit ID, laboratory batch number, current shift team identifier | Accurately match real-time data and historical inspection records for the corresponding petroleum refining unit |
messages | Display context grouped by data source | Distinguish process data from DCS systems and laboratory data from LIMS systems to improve audit accuracy |
| Dialogue Timeout Duration | 600 seconds | Supports the calculation time required for complex multi-unit load coordination and material balance calculations |
chatId | Bind the unique identifier of the current shift team | Retain context for multi-turn dialogue within the same shift team to ensure consistent audit logic |
| Prompt Template | Restrict calls to specified system fields and units | Standardize data formats to avoid audit errors caused by mismatched units or fields |
Three Common Misconfigurations
- A 404 Invalid URL (POST /api/chat/completions) error occurs. This is caused by an incorrectly configured FastGPT large model interface address, which prevents dialogue requests from reaching the target service.
- The workflow stops directly after the AI replies. This is caused by missing downstream process trigger parameters in the
messagesconfiguration, so the dialogue context is not passed to subsequent nodes. - Frequent dialogue timeouts occur. This is caused by an improperly set timeout duration, or too many cross-system data queries called during multi-turn dialogue, exceeding the preset response limit.
How to Confirm the Configuration Is Correct
- Check if
chatIdis bound to the unique identifier of the current shift team, to ensure that multi-turn dialogue context for the same shift team can be called consistently. - Verify that the fields included in
variablesmatch the actual data fields of the current petroleum refining unit, to ensure accurate data calls. - Test the grouping logic of
messagesto confirm that process data and laboratory data from different sources can be correctly distinguished and called. - Adjust the dialogue timeout duration to ensure that complex material balance calculations can be completed within the set time limit.
This page is compatible with FastGPT v4.17.0. The values provided are common starting points and should be evaluated against the reader's own samples.