What this category of data looks like
Cosmetics investment research data sources include the National Medical Products Administration cosmetics filing platform, official brand ingredient disclosure pages, third-party ingredient testing databases, e-commerce platform user reviews, and industry consumer research reports. Update cadence adjusts based on data source type. Filing data updates synchronously per regulatory requirements. Ingredient databases adjust alongside industry ingredient iterations. E-commerce reviews sync in real time. Each data document includes fields such as ingredient name, concentration label, filing number, release time, user review star rating, and source channel. Units include mg/g, %, ppm, and others.
What constraints these characteristics impose on conversation logging and auditing
Cosmetics investment research data is multi-source, heterogeneous, and has special field formats. Conversation logs must fully mark the source type of each data entry. This ensures traceable compliance and non-compliant data sources during audits. Specialized fields such as ingredient concentration and units require logs to verify field format consistency. This avoids unit confusion during audits. Real-time updated e-commerce review data requires logs to support indexing by precise timestamps. This matches the instant query needs of investment research scenarios. Additionally, cosmetics data has high compliance requirements. Logs must separately distinguish record markers between official filing data and third-party public data.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
log_enable | Full enable | Covers conversation and operation records across the entire investment research workflow |
log_retention_days | 180 days | Meets compliance retention periods required for financial investment research audits |
hide_chain_log | Enabled | Prevents AI thinking processes from being displayed in conversation history. Aligns with usage habits of investment research scenarios |
workflow_log_sync | Enabled | Ensures logs for plugins and sub-applications called within workflows are synchronously recorded |
api_log_include_sources | api,web,plugin | Covers all call entry points for investment research tools |
log_field_check | Enable concentration and unit field checks | Aligns with special field format requirements for cosmetics data |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Symptom: Conversation history includes unconfigured AI thinking process fragments. Cause: The
hide_chain_logconfiguration is not enabled. Chain execution logs are written to conversation records. - Symptom: Operations from sub-application or plugin calls within workflows do not appear in conversation logs. Cause: The
workflow_log_syncconfiguration is not enabled. Internal workflow calls do not synchronize logs. - Symptom: When pulling historical records via API, the
sourcefield only returnsapi. Call records from other scenarios are unavailable. Cause: Theapi_log_include_sourcesconfiguration is not set to cover all scenarios. Logs from non-API sources are filtered.
How to confirm the configuration is correct
- Initiate a cosmetics ingredient query conversation via the web interface. Confirm the conversation log panel fully records call time, user input, and AI response content.
- After configuring
workflow_log_sync, run an investment research workflow that includes plugin calls. Verify the log panel includes detailed records of plugin execution. - Pull historical conversations via API call. Check that the
sourcefield includes the configured scenario types. - View the system log panel. Confirm there are no abnormal prompts for log loss or filtering.
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.