What data belongs to this category
Data for this category primarily originates from historical traffic data, service topology, monitoring metrics, and business growth plans. Daily produced documents include technical solutions, architecture diagrams, capacity assessment reports, and technical review minutes. Data updates occur monthly or when major requirement changes take place. Common data fields include solution version numbers, core topology node configurations, traffic thresholds, summary of review comments, and business growth expectation metrics. There are no unified mandatory units. Values must adapt to specific document scenarios.
What constraints do these characteristics impose on the conversation logs and auditing workflow
Historical traffic and monitoring data updates occur monthly or on demand. Conversation log auditing must cover full-cycle architecture solution changes and review records. It cannot rely on high-frequency real-time synchronized data. Technical review minute fields are scattered across different documents. Auditing requires associating topology and capacity data from corresponding versions. This increases cross-document association complexity. Business growth plans contain large amounts of unstructured content. Key constraint conditions must be extracted for compliance verification. Auditors must also avoid missing audit nodes after major requirement changes. The cross-service boundary nature of architecture design requires audit logs to cover change records of service call links. This ensures compliance reviews cover the full evolution path.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId binding rule | Associate with architecture solution version identifiers | Ensure full-link conversation logs for a single solution can be traced, and adapt to the versioned characteristics of category data |
responseChatItemId filtering rule | Only retain entries related to reviews and changes | Reduce the proportion of invalid logs, and adapt to the scattered field structure of multiple documents |
detail log switch | Enable on demand, enable during major changes | Avoid storing redundant data, and match the monthly update frequency characteristic |
| Audit storage period | 30–90 days | Cover complete solution review and iteration cycles, and adapt to the log storage mechanism of FastGPT v4.17.0 |
| Custom field mapping | Match fields from technical solutions and review minutes | Adapt to the non-standardized structure of category data |
| Single audit query limit | Top 20 entries | Adapt to the scattered storage characteristic of category data, and avoid query overload |
Three common misconfiguration issues
- Symptom: Conversation logs carry historical records with no effect. The interface displays empty context or context unrelated to the current solution. Cause:
chatIdand architecture solution version identifiers are not correctly bound, leading to incorrect log context association. - Symptom: Audit logs cannot be filtered by review comments or solution versions. No corresponding filtering fields are available. Cause: Custom field mapping rules are not configured, so non-standardized field structures of category data cannot be matched.
- Symptom: FastGPT container fails to start. Logs show permission denied errors. Cause: Log storage path permissions are not correctly configured, leading to failed audit log writes.
How to confirm correct configuration
- Run a conversation query for a single solution. Check if
chatIdis associated with the corresponding version of the architecture solution identifier, and verify log traceability. - Enable the
detaillog switch and trigger a technical review conversation. Check if logs contain detailed content such as review comments and topology changes. - View the audit storage directory. Confirm that log file generation cycles meet the 30–90 day configuration requirement.
- Try using solution versions or review types as filtering conditions. Verify that the
responseChatItemIdfiltering logic works as expected.
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 2026-10-19.