What Data Does This Category Include
Core data for this category comes from client system interfaces, API documentation, test data, and integration logs. Daily maintenance documents typically include interface lists, integration records, field mapping tables, and issue tracking tables. Data update frequency is usually daily or aligned with integration phases. Core fields include interface call ID, request parameters, return content, field mapping relationships, and exception status codes. Data structure changes with the interface specifications of the client system. Field standards and call links vary across different clients.
What Constraints Do These Characteristics Impose on the Conversation Logs and Auditing Link
Data sources are scattered and their relationships are complex. Auditing logs must cover the full link from interface calls, AI conversations, to result returns. Every operation can be traced. Data update frequency is high. Log integrity must be verified daily or per phase to avoid missing exception records during integration. Multiple documents and field differences require the auditing process to link with corresponding interface lists and field mapping tables. Parameters in logs must match client system standards. Exception consequences are severe. Full details of all exception calls must be retained. This helps troubleshoot root causes of data desynchronization or business interruptions.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Log retention period | 30 days | Covers full verification needs across integration and acceptance phases, and aligns with FastGPT v4.17.0 log storage rules |
chatId association rule | Bind to corresponding interface call ID | Establishes one-to-one correspondence between conversation logs and interface call links to enable full-link tracing |
detail field collection switch | Enable full-field collection | Retains complete request parameters and return content to meet detail requirements for exception troubleshooting |
| Maximum single log size | 800–1200 MB | Accommodates large parameter scenarios in integration logs and prevents log truncation |
| Exception log sampling rate | 100% | Ensures all abnormal interface calls are fully recorded and avoids missing critical issues |
responseChatItemId binding rule | Link to corresponding knowledge base call node | Aligns the association between AI conversations and interface returns, and distinguishes logs from different workflow branches |
Three Common Configuration Errors
- Symptom: The
chatIdfield is empty in audit logs. Cause: ThechatIdand interface call ID association rule is not configured. This prevents establishing a correspondence between conversation logs and interface links. - Symptom: Full integration log details cannot be viewed. Cause: The
detailfield collection switch is not enabled. Only basic session summary content is retained, and critical request and return parameters are missing. - Symptom: Audit logs for multi-branch workflows cannot be distinguished by source. Cause:
responseChatItemIdis not bound to the corresponding knowledge base call node. This causes conversation logs from different branches to be mixed together.
How to Verify Successful Configuration
- Search for logs with a specified
chatIdand confirm that complete records for the corresponding interface call can be associated. - Trigger an abnormal interface call and confirm that the
detailfield contains complete request parameters and return content. - Trigger a multi-branch workflow call and confirm that
responseChatItemIdcan distinguish conversation logs from different branches. - Check the log retention settings and confirm that old logs older than 30 days can still be retrieved normally.
The values provided here are common starting points. They 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 2026-10-19.