What the data for this category looks like
Investment research data for large state-owned banks comes from multiple sources. These include in-house developed investment research systems, publicly available regulatory documents from the central bank and banking and insurance regulatory authority, research reports from external authoritative financial institutions, and internal credit approval documents. Data updates follow three schedules: real-time regulatory document pushes, daily industry research report updates, and monthly credit report archiving. Each individual document includes research report number, publishing entity, publishing date, core argumentation logic, and risk reminder fields. Data field units include 100 million yuan and percentage points. Document lengths vary widely. It is recommended to conduct statistics or on-site testing using local samples before finalizing values.
What constraints do these characteristics impose on the conversation logs and auditing link?
Investment research data comes from multiple sources and updates frequently. Conversation logs must fully record the data source identifier and matched document ID associated with each call. This avoids traceability deviations. Individual documents have long lengths. Logs must support configuration for truncating ultra-long context. This prevents storage overflow. The multi-field document structure requires the auditing link to support precise filtering of log entries. Filtering uses fields such as research report number and publishing entity. Compliance requirements for large state-owned banks mandate that log retention meets regulatory standards. Log storage must support configurable retention periods and cleanup rules.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
log_retention_days | 1825 days | Meets the log retention period required by regulatory standards for large state-owned banks, covering compliance auditing needs |
max_log_context_length | 12000 characters | Adapts to the typical length of investment research documents for large state-owned banks, preventing log storage overflow |
user_history_separation | Enabled | Isolates chat history records across different users, prevents cross-user data leaks, and aligns with user management requirements |
log_search_filter_fields | Research Report Number, Publishing Entity, Call Time | Matches the core fields of investment research data, supporting precise auditing and retrieval |
log_cleanup_cron | 0 3 * * * | Configures daily log cleanup at 3 AM, preventing invalid logs from occupying storage resources |
audit_log_detail_level | Full | Records details such as data source and matched document ID for each call, meeting investment research traceability requirements |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to conduct testing using local samples before finalizing settings.
Three common configuration errors
- Symptom: Chat history from other users is visible to a test user. Returned historical data includes conversations not belonging to the current user. Cause: The
user_history_separationconfiguration item is not enabled, and user session isolation logic is not activated. - Symptom: Log storage usage continues to grow, leading to insufficient server disk space. Cause: The
log_retention_daysconfiguration is not set, or the retention period is set too long, and the scheduled cleanup task is not enabled. - Symptom: Unable to filter log results by research report number when searching logs. Cause:
研报编号is not added to thelog_search_filter_fieldsconfiguration item, and retrieval support for the corresponding field is not enabled.
How to confirm configurations are correctly set
- Initiate conversations with two different test users. Check that each user’s chat history only displays their own sessions. Verify that user session isolation configuration is active.
- Review log storage usage trends. Confirm that the scheduled cleanup task runs automatically at 3 AM daily. Verify that the scheduled cleanup configuration is correct.
- Attempt to search conversation logs using fields such as research report number, publishing entity, and call time. Confirm that corresponding entries can be filtered precisely. Verify that retrieval field configuration is complete.
- Review audit log details for a single conversation. Confirm that key information such as data source and matched document ID is included. Verify that audit log detail configuration is correct.
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.