What the data for this category looks like
This category of data typically comes from project document libraries, configuration lists, meeting minutes, and test reports. It is generated when a project phase concludes or the entire project is completed. Daily documents include completion documents, configuration manuals, training records, and acceptance certificates. These materials are archived by project number and phase classification. Fields include document name, version number, creator, archiving time, and associated project ID. The association between each document type and project progress must be consistent.
What constraints these characteristics impose on conversation logs and auditing workflows
The characteristics of this data category impose clear constraints on the conversation logs and auditing workflows. Data sources are scattered across multiple document types. Conversation logs must be associated with a specific project ID and phase identifier to accurately locate corresponding archived documents. Data updates only trigger when a project phase or the entire project is completed. Audit logs must be retained for the full project cycle and cannot be cleaned early. Documents include a version number field. Any documents referenced in conversations must have their version information recorded synchronously. This avoids troubleshooting deviations caused by subsequent version iterations. The multi-field document structure also requires logs to fully record metadata such as document name, creator, and archiving time. This facilitates compliance tracing of handover processes.
How to Configure
This guide is compatible with FastGPT v4.17.0. The following configuration items are formulated based on the data characteristics of this category:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Log associated project ID | Bind the unique identifier of the current project | Matches the project-classified archiving data characteristic of this category, enabling quick log retrieval by project |
chatId retention period | 180 days or set according to the project cycle | Covers the full cycle from project launch to handover, preventing loss of critical audit logs |
| Log recording fields | Include responseChatItemId, detail | Fully record document references and interaction details in conversations, matching the multi-field document structure of this category |
| Log trigger rules | Only trigger at document handover-related nodes | Filters invalid logs from non-archiving scenarios, reducing storage pressure |
| Exception log threshold | Calibrate based on actual testing | Adapts to the large size difference of documents in this category, avoiding false positives or false negatives |
| Log storage path | Bind a project-specific storage directory | Aligns with the project-classified data storage logic of this category, simplifying archiving management |
Three Common Configuration Errors
- Symptom: After calling the document handover workflow, the conversation logs for the corresponding
chatIdare empty. Cause: The workflow node is not bound to the project ID, and the logs are not associated with the correct project dimension, making them unmatchable during retrieval. - Symptom: In a Docker deployment environment, model testing works normally and background response logs exist, but workflow conversations show a failure. Cause: Log persistence for the
detailfield is not configured. Response logs are only retained in the model background and not synchronized to the FastGPT conversation audit library. - Symptom: No corresponding audit log is generated after an application conversation triggers an exception error. Cause: The log recording switch for exception scenarios is not enabled. Only
responseChatItemIdfor normal interactions is recorded, and details for error scenarios are omitted.
How to Confirm Correct Configuration
- Manually trigger a document handover workflow. Verify that the conversation logs under the corresponding project ID include the
chatIdanddetailinformation for this interaction - Navigate to the audit log module in FastGPT system settings. Verify that the log retention period matches the current project cycle
- Simulate an exception error scenario. Verify that an exception log entry containing
responseChatItemIdis generated - View the log storage path. Confirm that a dedicated storage directory has been created based on the project ID
The values provided are common starting points and should be measured against local deployment 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.