What this category of data looks like
Data supporting equipment inspection and maintenance Q&A for petroleum refining comes from DCS/APC control systems, LIMS laboratory information management systems, tank farm metering systems, crude oil evaluation reports, equipment management systems, and energy management systems. Daily documents include operating procedures, production plans, material balance sheets, distillate export quality reports, interlock ledgers, shift handover records, and change management documents. Three update frequency categories apply: real-time, per shift, and daily. Document fields include unit number, medium temperature, pressure, liquid level, equipment model, maintenance cycle, and more. Organizations use standard industrial units such as degrees Celsius, megapascals, and cubic meters for this data.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" link
Multiple continuous petroleum refining units couple via material and hydrogen networks. Raw material properties fluctuate widely. Multi-turn dialogue must track dynamic parameters such as current crude oil properties and unit load. Data source update frequencies vary. The system must distinguish between real-time collected process data and historically archived document content to avoid context confusion. Document structures include ledgers, reports, operating procedures, and more. Prompt engineering must adapt to the field formats of different documents to ensure retrieval results match the equipment inspection and maintenance business scenario. Error consequences are severe. The system must ensure accurate parameter references in dialogue, and avoid incorrect judgments caused by lost context.
How to set up the configuration
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum Context | Previous 10 turns of dialogue + 8000–12000 characters | Align with context association needs for coupled refinery units, and prevent loss of historical process fluctuation records |
| Single Search Limit | Top 6 recalled results | Match the document volume of refinery equipment ledgers and operating procedures, and filter redundant information |
| Question Optimization | Calibrated based on actual measurements | Adapt to changes in question expression caused by crude oil property fluctuations, and optimize the semantic accuracy of user questions |
chatId | Bind unit number and shift identifier | Distinguish dialogue contexts of different production units, and avoid cross-unit parameter confusion |
variables | Preset crude oil density and unit load variables | Quickly call real-time collected process parameters, and reduce the operational cost of repeated questions |
Three common configuration errors
- After adjusting the number of historical chat records, the dialogue fails to retain multi-turn context. The cause is that the
messagesparameter is not bound to recalled historical documents, resulting in context being overwritten by search results. - The login-free dialogue window returns complete non-streaming text by default. The cause is that the streaming switch parameter for dialogue output is not configured correctly.
- Clicking a custom preset question does not trigger the dialogue flow. The cause is that the preset question is not correctly associated with the event binding logic of the dialogue input box.
How to confirm successful configuration
- Initiate a multi-turn question that includes historical process parameters, and confirm that the dialogue context is correctly retained and not overwritten by new search results.
- Trigger a login-free dialogue, check whether the output is streaming text that returns real-time equipment status updates.
- Click a preset custom question, confirm that the dialogue input box automatically fills the corresponding question content and triggers the dialogue flow.
- Switch the
chatIdidentifier of different units, confirm that the dialogue contexts of different production units do not interfere with each other.
The values provided are common starting points and should be validated against samples from the specific deployment context.