What this category of data looks like
Carbon steel yield data comes primarily from commodity spot market trading APIs and domestic futures exchange delivery product data sources. Full daily data updates are completed after market close each day. Hourly incremental sync is available for some high-frequency market nodes. Documents use standard JSON or CSV format. Fields include contract code, product name, daily settlement price, previous day’s settlement price, price change percentage, open interest, and more. Units are yuan/ton, percentage, and lots. Fields must match the steel industry’s standard product classification standards. This prevents cross-data source field mapping errors.
What constraints do these characteristics impose on conversation logs and auditing?
The multi-source synchronization feature of carbon steel data requires conversation logs to record both data source identifiers and update timestamps. This supports compliance tracing during audits. For high-frequency incremental sync scenarios, conversation logs must support quick filtering by contract code and time range. This prevents slow retrieval caused by large log volumes. The standardized field requirement for carbon steel data means audits must verify that market data fields called in conversations match preset standard fields. This prevents yield calculation errors from missing or mis-mapped fields. The daily full update schedule requires logs to mark the statistical cycle of the day’s data. This enables natural day reconciliation during audits.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 30–90 days | Audit cycles for carbon steel market data typically cover monthly reconciliation needs. Retaining data for 30-90 days meets regular audit and backtracking requirements |
LOG_QUERY_MAX_RESULTS | Top 1000 entries | Carbon steel market conversation logs are usually aggregated by contract or time range. A single query does not need to return too many entries, to avoid interface loading delays |
AUDIT_FIELD_VALIDATION_ENABLE | Enabled | Carbon steel data must follow industry standard field rules. Enabling this setting automatically verifies whether market data fields called in conversations meet preset standards |
LOG_DATA_SOURCE_TAG_ENABLE | Enabled | Carbon steel data relies on multi-source synchronization. Enabling this setting automatically records data source identifiers in logs, to support compliance tracing during audits |
LOG_TIMESTAMP_PATTERN | YYYY-MM-DD HH:mm:ss | Update times for carbon steel market data must match industry-standard time formats, to enable cross-system reconciliation and audit verification |
The parameter values provided on this page are general recommendations to serve as a starting point 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.
Three common configuration mistakes
- Symptom: No call token statistics data appears in conversation logs, making token consumption statistics impossible to complete by application dimension. Cause: The
TOKEN_STATISTICS_ENABLEconfiguration item is not enabled, or its value is set to disabled. - Symptom: The model provider page does not display the conversation log entry. Cause: The global log collection configuration
LOG_COLLECT_ENABLEis not enabled, or the current application is not bound to a model interface that can generate logs. - Symptom: Workflow conversation logs for the current day and previous day are empty. Cause: The time range parameter for log filtering is not configured, or the system time of the deployment environment has a time zone deviation from the update time of the market data source, causing logs to not be archived by natural day.
How to verify successful configuration
- Log in to the FastGPT backend system configuration module, check the current values of core configuration items including
LOG_RETENTION_DAYSandLOG_DATA_SOURCE_TAG_ENABLE, confirm they match preset requirements. - Initiate a carbon steel market query conversation, enter the conversation details page to view log content, confirm that data source identifiers, update timestamps and called market data fields have been recorded.
- Enter the application's log management interface, attempt to perform filtering operations by contract code and time range, confirm that the filtering function can load corresponding logs normally.
- Trigger a model call flow, check whether the log details include token consumption statistics entries, confirm that the statistics logic is working correctly.
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.