What the Data for This Category Looks Like
Data for this category mainly comes from the state-owned assets supervision and administration commission’s investment supervision system, enterprise ERP and project management systems, industry market data, audit and financial statements. Commonly involved documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset evaluation reports, and post-investment evaluation reports. The data update frequency is quarterly. Core fields include project approval number, investment scale, approval date, post-investment evaluation milestones, and others. Field units are adjusted based on the business scenario of the specific document, with no unified fixed format.
What Constraints These Characteristics Impose on Conversation Logs and Audit Processes
The multi-source data and quarterly update characteristics of this category impose multiple constraints on the conversation logs and audit process. Multi-data sources cover internal business systems and external public industry data, requiring logs to be associated with specific data sources and called document fragments to meet the traceability requirements of state-owned asset audits. The quarterly update business rhythm requires log storage periods to match the business traceability period, to avoid premature deletion of key audit materials. The multi-stakeholder investment process requires logs to be divided into access permissions by role, to prevent unauthorized viewing of confidential project information, while ensuring that logs cannot be tampered with and fully retain full-link call records.
How to Configure
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Log storage period | 90 days | Matches quarterly update frequency and state-owned asset audit traceability requirements |
| Log storage upper limit | 1000 MB | Meets capacity requirements for quarterly data storage |
chatId binding switch | Enabled | Associates full-process conversations for a single project approval, facilitating audit traceability by project |
detail field enabled | Enabled | Records specific called document fragments and parameters, complies with investment project audit standards |
responseChatItemId associated record | Enabled | Binds individual replies to specific document calls, refining audit granularity |
| Token statistics by application dimension | Enabled | Matches application statistics requirements for investment project approval and post-evaluation |
Three Common Misconfigurations
- Symptom: Conversation logs are missing, and historical call records cannot be retrieved. Cause: Log storage period is not configured, or the Docker configuration file does not correctly mount the log directory.
- Symptom: A specified agent cannot view conversation logs from other groups. Cause: Role-isolated permission settings are not enabled, or permission group configuration is incorrect.
- Symptom: Token statistics data does not match actual call volume. Cause: Token statistics by application dimension is not configured, or the statistical scope does not cover full-process calls.
How to Confirm Successful Configuration
- Navigate to the log management page in the FastGPT backend, retrieve conversations using the specified project number, and confirm that records corresponding to the target business process are returned.
- Switch test accounts with different roles, verify that only conversation logs within the authorized scope are accessible, and that unauthorized access to records from other projects is blocked.
- View the token statistics panel, confirm that the statistical dimension aligns with the business requirements of the current application, and that call data can be viewed by application dimension.
- Navigate to the detail page of a single conversation, confirm that the
detailfield contains specific called document fragments and parameter information.
The values provided are common starting points and should be validated against the specific samples used in the deployment.
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.