What this category of data looks like
Data sources for defense equipment investment research include publicly available technical standard documents from the national defense and military industry, regular research reports disclosed by military industry groups, public test reports of weapons and equipment, and equipment dynamic information released by industry associations. Update frequency is adjusted alongside new equipment finalization, equipment fielding plans, and quarterly industry dynamic releases. Document structure typically includes four sections: equipment model description, core technical parameters, supporting system list, and fielding application cases. Core fields include equipment model, maximum range (kilometers), rate of fire (rounds per minute), fielding time, supporting ammunition model, and others. All fields have clear physical or industry standard units.
Constraints Imposed on Dialogue Logging and Auditing
The multi-source and decentralized nature of defense equipment investment research data requires dialogue logs to record the original data source path of each retrieval, to avoid unclear traceability. The irregular update frequency requires audit logs to associate knowledge base update times with dialogue context timestamps, ensuring dialogue content matches the current knowledge base version. The complex document structure and unit-attached fields require logs to record the specific location of recalled paragraphs and field units, making it easy to verify the accuracy of data referenced in dialogues. Additionally, compliance requirements for investment research scenarios require full retention of full-link call information for dialogues, including user identity, query keywords, and returned results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 90 days | The audit traceability cycle for defense equipment investment research typically covers quarterly to annual investment research analysis cycles. 90 days meets standard compliance requirements |
AUDIT_LOG_ENABLE | Enabled | Investment research scenarios require full traceability of data sources and call links for each dialogue, meeting industry compliance review needs |
MAX_CONTEXT_HISTORY | Previous 20 dialogues | Defense equipment investment research dialogues often involve multi-round iterations of technical parameters. Retaining 20 dialogues covers complete analysis context while avoiding log redundancy |
RECALL_SOURCE_SHOW | Enabled | Dialogue logs must record the source of each recalled document to ensure audits can trace back to original data |
LOG_EXPORT_FORMAT | CSV format | CSV format facilitates subsequent compliance audits and bulk data statistical analysis |
ERROR_LOG_SAMPLING_RATE | 100% | Error logs for investment research scenarios must be fully retained to facilitate troubleshooting of knowledge base matching anomalies or permission configuration issues |
The parameter values provided on this page are conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: An error message reading "Insufficient permissions to operate this dialogue record" appears in dialogue logs. Cause: The
USER_PERMISSION_BINDparameter is not correctly configured, and the custom UID is not bound to the permission rules for dialogue records. - Symptom: Reference identifiers are forcibly appended to the end of paragraphs answered by the knowledge base, and cannot be hidden via the interface. Cause: The
RECALL_SOURCE_SHOWparameter is set to permanently enabled, and no rules allowing dynamic control of reference display are configured. - Symptom: Dialogue log temporary files accumulate continuously without being cleaned up in Docker-deployed FastGPT instances. Cause: The
TEMP_FILE_CLEANUP_INTERVALparameter is not configured, and the automatic cleanup mechanism for temporary log files is not enabled.
How to Verify Proper Configuration
- Access the FastGPT system configuration page and verify that the set value of
LOG_RETENTION_DAYSmatches the preset configuration. - Initiate a dialogue querying defense equipment technical parameters. In the log panel of the dialogue details page, confirm that the source path and call timestamp of the recalled document are displayed.
- Initiate two rounds of dialogue using a custom UID, verify that the history page only displays dialogue content associated with that UID, with no cross-user data access issues.
- Trigger an incorrect knowledge base query, confirm that the error log is fully recorded, including complete link information such as user UID, query keywords, and returned results.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.