What the Data for This Category Looks Like
The investment research data sources for multi-domain holdings cover business research reports from each group subsidiary, industry database interfaces from the group’s middle platform, and external compliance backup documents. Data update cycles differ:
- Subsidiary business data is synced daily
- Industry macro data is updated weekly
- Group consolidated research reports are updated quarterly
Document structure falls into three categories: single-subject special research reports, group consolidated analysis documents, and compliance backup files. Core fields include 发布主体, 数据周期, 关联子公司清单, 合规校验状态. Some fields have clear business measurement identifiers.
Constraints on Conversation Logging and Audit
Since data sources cover multiple entities and update cycles vary significantly, conversation logs must link the 发布主体 and 关联子公司清单 fields. This ensures specific data sources cited in individual conversations can be traced during audits. Data from different cycles must be archived and categorized by 数据周期. This prevents audit errors caused by mixed cross-cycle data. Because the 合规校验状态 field exists, the audit workflow must record change trails for compliance check results. This ensures compliance operations can be traced back. Conversations involving cross-subject related transactions must link the 文档关联ID field. This allows quick location of associated multiple documents during audits.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 180 days | Meets compliance audit retention cycle requirements for financial investment research scenarios |
LOG_INCLUDE_DOC_FIELDS | Publishing Entity, Affiliated Subsidiary List, Data Cycle | Matches core associated fields for multi-domain holdings' investment research data. Ensures complete data lineage can be traced during audits |
ERROR_LOG_SAMPLING_RATE | 100% | Retains all error logs to avoid missing compliance-related error information |
API_LOG_ENABLE_CONTEXT | Enabled | Records full conversation context for audit tracing of cross-subject investment research conversations |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing durations for large group consolidated research reports, avoids timeout interruptions |
AUDIT_TRAIL_AUTO_SYNC | Enabled | Automatically syncs audit logs to compliance storage systems, meets regulatory archiving requirements |
Three Common Configuration Mistakes
- Symptom: Calling the investment research knowledge base API returns a
500 内部服务器错误, but no specific error stack is shown in system logs. Cause: The full collection configuration forERROR_LOG_SAMPLING_RATEis not enabled. Only partial error logs are sampled, causing compliance-related errors to be missed. - Symptom: The knowledge base model referenced in a conversation does not match the configured
应用配置模型. No model switching trail is recorded in system logs. Cause: Model configuration field collection forLOG_INCLUDE_DOC_FIELDSis not enabled. This prevents confirmation of the actual called model version during audits. - Symptom: Cross-subsidiary related transaction conversation results are empty. No associated document reference records are found in logs. Cause: The
关联子公司清单field forLOG_INCLUDE_DOC_FIELDSis not configured. This means logs do not record associated multiple document IDs, making it impossible to trace back data sources.
How to Verify Correct Configuration
- Access the system log management interface, filter logs of the
投研对话type. Confirm each log contains the preset core fields. - Trigger one investment research-related error request. Check if error logs include complete error stack information to confirm the sampling configuration is active.
- Call the API interface to initiate an investment research conversation. Check if returned log parameters include full conversation context and model configuration information.
- Check synchronization tasks in the compliance storage system. Confirm audit logs are automatically synced to the specified location per the preset cycle.
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
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.