What the Data for This Category Looks Like
Industrial metals investment research data is sourced primarily from official market APIs of the London Metal Exchange (LME) and Shanghai Futures Exchange (SHFE), supply and demand analysis reports from industry associations, and daily spot trader quotes. Update frequencies vary by dimension: futures market data updates in real time during trading sessions, industry supply and demand reports are released weekly and monthly, and spot quotes update daily. Document structures include fields such as contract identifier, delivery standards, benchmark quote, settlement price, total inventory, and warehouse receipt quantity. Common units are yuan per ton, ton, and number of trading lots.
Constraints for Conversation Logs and Auditing Workflows
The high-frequency updates, multi-source origins, and strict field specifications of industrial metals data create multiple constraints for conversation logs and auditing workflows. First, real-time market data updates rapidly, so audits must retain snapshots of data sources taken at the time of query. This prevents investment research conclusions from becoming untraceable due to subsequent data changes. Second, multi-cycle document updates require audits to record the version and release time of documents referenced in conversations. This ensures that only valid data matching the investment research time point is used. Finally, unified field and unit requirements mandate that the auditing workflow automatically validate the legality of fields referenced in conversations. This prevents investment research judgments from being skewed by unit errors or field confusion.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
ENABLE_CHAT_LOG | Enabled | Industrial metals investment research conversations involve high-frequency market queries, and full interaction records must be retained for auditing |
LOG_DATA_SNAPSHOT_ENABLE | Enabled | Industrial metals market data updates frequently, so snapshots of data sources at query time must be saved to avoid data version inconsistencies during audits |
LOG_RETENTION_DAYS | 180 days | Meets the standard retrospective cycle for compliance auditing in the investment research industry, covering quarterly and semi-annual investment research review needs |
AUDIT_FIELD_CHECK | Enabled | Industrial metals data has strict field and unit specifications; automatically validate the legality of fields referenced in conversations |
LOG_QUERY_FILTER_FIELDS | Contract Code, Quote Time, Inventory Data | Industrial metals investment research conversations often involve a large number of irrelevant fields; configuring filtering rules reduces log redundancy and allows audits to focus on core content |
CHAT_LOG_EXPORT_FORMAT | CSV + JSON dual format | CSV format facilitates manual auditing, while JSON format facilitates automated script processing of audit data |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Issue: Conversation logs include excessive irrelevant fields, requiring extensive time to filter core content during audits. Cause: The
LOG_QUERY_FILTER_FIELDSparameter is not configured, and log field filtering is not enabled, leading to high log redundancy. - Issue: Conversation log detail pages do not show data source snapshots, making it impossible to trace the market version at the time of query during audits. Cause: The
LOG_DATA_SNAPSHOT_ENABLEconfiguration item is not enabled, and only conversation text is retained without saving snapshot information for the corresponding data source. - Issue: Multi-user conversation logs cannot be filtered by user ID, with all users’ chat records displayed together. Cause: The
MULTI_USER_LOG_SEPARATEparameter is not configured, and multi-user log isolation functionality is not enabled, preventing accurate location of individual user interaction records during audits.
How to Verify Correct Configuration
- Navigate to the Log Management page in FastGPT system settings, check the chat log switch status, and confirm the
ENABLE_CHAT_LOGconfiguration item is enabled. - Initiate an industrial metals market query, then check the conversation log detail page for data source snapshots, query timestamps, and field validation results. Confirm that
LOG_DATA_SNAPSHOT_ENABLEandAUDIT_FIELD_CHECKconfigurations are active. - Attempt to filter conversation logs by user ID, confirming the multi-user log isolation functionality works properly and can accurately locate specified user interaction records.
- Export conversation logs for a specified time period, check that the export format matches the configured requirements, and confirm the export process has no timeout errors.
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.