What the data for this category looks like
Data for this category originates from a dedicated party building learning document library for state-owned and public enterprise equipment manufacturing sectors. It covers party constitution and regulations, industry party building policies, and party building learning materials tailored to construction machinery operation and maintenance scenarios. The system synchronizes official party building documents and industry party building updates quarterly, with no fixed upper limit on the number of documents updated per batch. Each individual document includes document identifier, publishing entity, publishing time, content category, and associated equipment model fields, stored in plain text format. Some documents include embedded fragments of party building event check-in records.
What constraints these characteristics impose on the conversation logs and auditing workflow
Conversation logs for party building learning Q&A must be associated with specific construction machinery equipment scenarios. Logs must record the equipment model and operation team information at the time a conversation is initiated, to prevent generic logs from failing to trace back to corresponding business scenarios. Since the data includes embedded party building activity record fragments, logs must also synchronize the embedded position of the original document, to ensure the specific content referenced by a conversation can be traced back during audits. Document updates follow a quarterly rhythm, so conversation logs must retain historical records for at least one full update cycle, to prevent conversations from older scenarios from failing to match latest reference materials after new documents are released. Additionally, the standardized field requirement for associated equipment models means device codes must undergo format validation when logs are stored, to avoid audit classification failures due to inconsistent coding.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Log Detail Field Switch | Enable the detail parameter | Fully record original conversation input, model responses, and associated document fragments to meet full-link traceability requirements for audits |
| Conversation Log Storage Period | 90 days | Matches the quarterly document update rhythm, ensuring traceability requirements for at least one full update cycle are covered |
| Associated Device Information Collection | Bind the chatId field | Associate equipment models with unique conversation identifiers, ensuring all conversations for a corresponding scenario can be quickly located during audits |
| Conversation Response Log Binding | Associate the responseChatItemId field | Ensure each model response corresponds to a unique conversation identifier, facilitating quick location of the full link for a single conversation during audits |
| Log Storage Upper Limit | 1000 MB | Prevent excessive log storage from occupying server storage resources, in line with state-owned and public enterprise server management rules |
| Log Field Validation Switch | Enable | Force validation of equipment model coding formats to avoid audit classification failures due to inconsistent coding |
Three Common Misconfigurations
- Symptom: The aiproxy_pg container fails to start when launching with docker-compose, with logs indicating a database connection failure. Cause: Database connection parameters for conversation log storage were not configured correctly, causing the auditing module to fail initialization.
- Symptom: Only partial content is displayed in conversation logs, and the associated equipment model field is empty. Cause: The binding rule for associated device information collection was not enabled, causing the
chatIdfield to fail to correctly associate with the device code. - Symptom: After a large model call via OneAPI fails, the corresponding error message cannot be viewed in the audit logs. Cause: The
detailparameter for full log recording was not enabled, only simplified conversation summaries were stored, and detailed call failure errors were not captured.
How to Confirm Configuration Is Complete
Initiate a party building learning Q&A conversation associated with a specific equipment model, and check whether log details include complete input and response content recorded by the detail parameter. Check whether each conversation in the log list includes the associated equipment model field, confirming that the chatId field has correctly bound the corresponding device code. Access the log storage directory to verify that archive files matching the configured storage period are automatically generated, confirming that the archiving rule has taken effect. Attempt to access logs for a specific team using an unauthorized account, to verify that the retrieval permission configuration has taken effect.
The configuration values listed above are common starting points, and should be evaluated against specific samples and operational requirements.
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.