What This Category of Data Looks Like
This category of data comes from the 12345 citizen hotline platform, contractor business systems, knowledge bases, and return visit evaluation data. The update frequency is daily. Daily documents include appeal registration forms, dispatch records, handling responses, return visit records, extension applications, return instructions, and knowledge base entries. Common data fields include appeal number, contracting unit, handling node, response content, evaluation results, etc. The data circulates in a closed loop around public appeals, and does not form statutory approval-type results.
Constraints Imposed by These Characteristics on the "Conversation Logs and Auditing" Link
Daily updated work order data requires log storage to support batch writing and fast retrieval. Associated data from multiple sources requires clear traceability links, and the auditing link must verify the source consistency of each field. The closed-loop document structure around appeals requires logs to fully record the full conversation process from dispatch to return visit. Non-statutory approval-type disposal results must ensure that logs can trace the full chain of public feedback, to avoid mismatches between responses and appeals. Combined with the party building learning Q&A scenario, logs must also associate interaction records of related learning content to meet compliance auditing requirements.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bound to work order number | Ensures each conversation log is uniquely linked to its corresponding work order, enabling fast traceability |
responseChatItemId | Bound to the unique identifier of the response content | Accurately locates the conversation context of a single response, meeting the precise retrieval requirements of audits |
detail | Enable full recording | Covers full conversation content during appeal verification, response generation, and return visit communication, complying with auditing requirements |
| Number of single log entries retained | First 20 entries | 12345 hotline work orders typically involve multi-round communication; retaining the first 20 entries covers the complete conversation chain, calibrated based on actual testing |
| Log write timeout | 600 seconds | Adapts to write delays from multiple data sources of the 12345 hotline, preventing log loss |
| Log export limit | 50,000 entries per request | Adapts to batch export needs of daily work order volume for the 12345 hotline, avoiding system overload |
Three Common Misconfiguration Issues
- Issue: After calling the API to start a party building learning Q&A conversation, extra historical records appear in the logs. Cause:
chatIdis not correctly bound to the work order number, causing duplicate association of conversation context. - Issue: An error of
lookup with 'pipeline' may not specify 'localField' or 'foreignField'occurs when viewing conversation logs. Cause: Both associated fields and aggregation pipelines for multi-source data are specified in the log association configuration, violating system validation rules. - Issue: When exporting full work order conversation logs, the export stops after only 50,000 entries. Cause: The log export limit configuration is not adjusted; the system default limit for single export entries is 50,000.
How to Verify Successful Configuration
- Randomly select one work order, check if the
chatIdin the conversation log matches the work order number. - Trigger a party building learning Q&A conversation, verify that the log fully records full-process content at the
detaillevel. - Attempt to export work order logs for a specified date, confirm that the number of exported entries meets the configured limit.
- Simulate an interface error scenario, confirm that the system can generate corresponding audit logs and they are retrievable.
The values provided are common starting points and 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.