Reference only; verify against the target FastGPT release and deployment documentation.
What does the data for this category look like?
Data for this category primarily comes from health supervision information systems, medical institution electronic registration systems, complaint reporting platforms, and law enforcement inspection records. Daily processed documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Data updates occur on a monthly basis. Core fields include institution qualification number, inspection time, rectification requirements, penalty results, and other relevant fields. The original field format of corresponding documents must be matched.
What constraints do these characteristics impose on conversation logs and auditing?
Data sources for this category are scattered and linked to multiple types of compliance documents. Conversation logs must link to unique identifiers such as institution qualification numbers and inspection record numbers, to ensure traceability to original law enforcement or regulatory data during audits. The monthly update frequency requires log retention periods to align with regulatory filing requirements. Logs must support filtering by law enforcement batches and rectification cycles. Field differences across document types are significant. Logs must mark the document category involved in the conversation, to avoid confusion between records from different business segments during audits. Errors in law enforcement and rectification links directly relate to institutional practice risks. Audits must fully record the complete conversation context and operation nodes.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind law enforcement inspection record number and institution qualification number | Ensure logs can be traced to specific regulatory business, matching the association needs of multi-source data for this category |
responseChatItemId | Link rectification notice number or penalty case file number | Precisely locate the regulatory document corresponding to a single conversation, facilitating verification of rectification closure during audits |
detail | Enable full field recording, including user questions, AI responses, and called document fragments | Cover audit requirements for multiple types of documents in this category, meeting complete traceability demands for compliance checks |
| Log retention period | 12 months | Align with the general filing cycle requirements of health regulatory systems |
| Log auto-archive trigger | Triggered after law enforcement batch completion | This category of data updates by law enforcement batch, facilitating organization of audit data by regulatory cycle |
| Log export format | Support CSV and PDF formats | Adapt to general submission requirements for regulatory reports in this category |
Three Common Configuration Mistakes
- Symptom: After configuring logs to save to a file, log files are not generated or have missing content. Cause: Incorrect read/write permissions for the log output path, or failure to enable the full recording switch.
- Symptom: The annotation field in conversation logs cannot link to the corresponding regulatory document number. Cause: Failure to bind
chatIdto the law enforcement inspection record number or institution qualification number, causing logs to be disconnected from business data. - Symptom: Stuttering occurs when loading the party building learning Q&A knowledge base, and associated logs show batch processing-related errors. Cause: Failure to adjust conversation context loading parameters based on the average length of documents in this category, leading to excessive loaded document fragments in a single session exceeding system limits.
How to Verify Successful Configuration
- Initiate a party building learning Q&A conversation about medical institution practice licenses. Check if the bound law enforcement inspection record number appears on the conversation details page.
- Export a conversation log, and verify that the log content includes user questions, AI responses, and called document fragments.
- Check the log output path, and confirm that log files for the specified period have been properly generated and contain complete records.
- Trigger auto-archive after a law enforcement batch is completed, and confirm that logs have been organized by batch and saved to the specified location.
The values provided here are common starting points, and should be evaluated against the user’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.