What the data for this category looks like
Teams source internal office data for power generation equipment manufacturing primarily from equipment operation logs, maintenance records, spare parts inventory lists, process operation manuals, and equipment drawing documents. Equipment operation logs are structured data with fields including equipment ID, operating hours, rated power, fault codes, and more. These fields use hours and megawatts as units, respectively. Teams store maintenance records and process manuals as unstructured documents containing multi-page text and images. Data updates follow three frequencies: real-time for equipment operation data, daily for inventory and maintenance records, and weekly for process manual revisions.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Structured data includes many fields with dedicated units. Teams must retain context in multi-turn dialogue to connect sequential equipment query requests and avoid field confusion. Unstructured documents have substantial length. Teams must limit multi-turn dialogue context length to a reasonable range to prevent model processing overflow. Real-time equipment operation data requires prompts to dynamically call latest data. Teams must bind real-time data sources within the dialogue workflow. Spare part code uniqueness requires prompts to accurately match field rules. Teams must define field formats and value ranges clearly in the initial prompt.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Supports long document processing for power generation equipment maintenance reports and process manuals |
| Context recall limit | First 15 historical messages | Balances dialogue coherence and interface response speed |
chatId | Generate unique identifiers per conversation scenario | Isolates context data for different conversations to avoid interference |
messages | Retain the most recent 20 rounds of conversation content | Covers continuous equipment inspection and fault troubleshooting dialogue scenarios |
variables | Pass current equipment ID and maintenance work order number | Dynamically binds dedicated business data within prompts |
| Prompt template | Clearly define field units and format requirements | Adapts to the dedicated field rules for power generation equipment data |
Three Common Errors
- Phenomenon: When calling the
/api/v1/chat/completionsinterface, the returned result does not associate historical conversation content. Reason: Historical conversation messages were not passed in sequence within themessagesarray, so the model cannot access context information. - Phenomenon: The interface request returns a 400 status code, with a prompt indicating missing parameters. Reason: The
variablesparameter was not properly configured to bind business fields, so the prompt cannot call dedicated business data. - Phenomenon: Conversation data from different business scenarios interferes with each other, and returned results include content from other conversations. Reason: A unique
chatIdwas not generated for each conversation, leading to shared multi-turn context. Using a universal global key without isolating conversations causes interference.
How to Confirm Correct Configuration
- Call the
/api/v1/chat/completionsinterface, check that themessagesarray in the request body includes at least 2 rounds of historical conversation content, and confirm that context is correctly passed. - Review the interface returned result, and confirm that the returned content associates with the business data corresponding to the currently passed
variablesparameter, such as equipment ID and work order number. - Generate multiple conversations with different
chatIdvalues, send identical equipment query requests, and confirm that returned results from different conversations do not interfere with each other. - Check that the prompt template clearly marks the units and format requirements for data fields, and confirm that returned results comply with business rules.
The configuration values listed above are common starting points. They should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.