What the Data for This Category Looks Like
Internal office and employee service data for new energy development comes primarily from station operation and maintenance logs, equipment inspection ledgers, office approval flow records, employee training documents, and project meeting minutes. Three update schedules apply:
- Station operation parameters are updated hourly
- Approval flows are updated in real time after submission
- Training documents and meeting minutes are updated quarterly
Two data formats are supported: structured and unstructured. Structured data includes fields such as station ID, equipment ID, power generation volume, fault level, with units including kW, hour, and count. Unstructured data mostly consists of operation and maintenance reports or approval descriptions, with 1000–3000 characters per document.
Constraints for Multi-turn Dialogue and Prompt Engineering
The real-time requirement of station operation parameters requires multi-turn dialogue to bind to real-time interfaces to obtain the latest data. The multi-field attribute of structured data requires prompts to explicitly specify target extraction fields to avoid confusing parameters from different stations. The length of unstructured documents consumes significant context space, so the number of turns and length of dialogue history must be limited to prevent exceeding system processing limits. Continuous inquiries from different employees require retaining conversation context, so conversation identifiers must be persisted to avoid reinitializing context for each dialogue turn.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window size | 8000–12000 token | Adapts to the average length of new energy development operation and maintenance reports and approval documents, preventing context overflow |
messages history turn limit | First 10 dialogue turns | Reduces redundant context usage and optimizes multi-turn dialogue response speed |
Dynamic variables update frequency | Every 5 minutes | Matches the real-time update rhythm of station operation parameters to ensure dialogue calls use the latest data |
| Prompt field constraints | Explicitly specify station ID, fault level, and approval status | Matches the standard field structure of internal office data to improve information extraction accuracy |
chatId conversation persistence toggle | Enabled | Retains context association for multi-turn dialogue, adapting to scenarios where employees continuously inquire about station-related issues |
Three Common Misconfigurations
- Phenomenon: Multi-turn dialogue outputs empty results, or custom
outputfields have no content. Cause: Target fields for extracting internal office data are not explicitly specified in the prompt template, or dynamicvariablesare not correctly bound to station data interfaces. - Phenomenon: Continuous inquiries about operation and maintenance issues for different stations result in responses that mix up station IDs and parameters. Cause: The number of
messageshistory turns is not limited, and redundant context interferes with field matching for the current dialogue. - Phenomenon: Multi-turn dialogue responses time out. Cause: The context window is set too large, and historical data from too many stations loads at once, exceeding the system's processing limits.
How to Verify Correct Configuration
- Initiate 3 consecutive rounds of operation and maintenance inquiries for different stations, and verify that each round of responses associates with the corresponding station's parameters.
- Submit a question-and-answer request for a long document, and check whether the response has content truncation or abnormal error reports.
- Exit the system after triggering a multi-turn conversation, then re-enter the conversation to confirm whether the previous dialogue context is retained.
- View the return results of dynamic
variablesto confirm that the called data matches real-time station ledgers.
The values provided here are common starting points, and should be evaluated 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.