What the data for this category looks like
Energy metal market data primarily comes from official APIs of global major commodity exchanges and domestic futures exchanges. There are two update frequencies: real-time quotes and post-market daily reports. Real-time quotes are pushed every 15 seconds. Post-market daily reports are updated within 1 hour after the close of each trading day.
A single daily report document includes fields such as product identifier, benchmark transaction price, daily fluctuation range, position size, and delivery standards. Units are mostly yuan per ton and lots. Some overseas products use US dollar pricing units. The data format is uniformly structured JSON, including meta fields such as timestamp and data source identifier.
Constraints on conversation logs and auditing
The high-frequency updates, multi-field structure, and multi-data-source characteristics of energy metal market data create multiple constraints for conversation logs and auditing.
Logs must accurately record the target variety of each query, request timestamp, and data return timestamp. They must align with real-time quote update windows to avoid retaining expired data.
Logs must verify the completeness of returned fields, including core professional fields such as benchmark price, fluctuation range, and delivery standards. They must also mark data sources and pricing units to prevent audit errors caused by unit confusion across different exchanges.
Logs must retain precise query condition matching information. This enables tracing of historical query records for specific varieties during audits, meeting traceability requirements for financial scenarios.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
logRetentionDays | 365 days | Meets legal retention period requirements for transaction data in financial industry audits, covering full quarterly audit needs |
logIncludeMetadata | Enabled | Energy metal market data requires recording metadata such as data source, timestamp, and unit identifier to support data legitimacy verification during audits |
maxConversationLogs | Top 800 entries | There are many energy metal varieties, and the volume of generated conversation logs is large. Limiting the number of entries prevents excessive consumption of storage resources |
auditLogFilterRule | Filter by product code and query time | Targeting the feature of numerous sub-categories, filtering logs by core dimensions improves audit troubleshooting efficiency |
logSourceCapture | Capture by exchange identifier | Matches the multi-data-source scenario for energy metals, allowing the source field to carry specific data source information instead of generic identifiers |
historyLogDisplayMode | Hide intermediate thought processes | Aligns with user scenarios for viewing historical records, only retaining core content of user questions and model responses to meet audit simplicity requirements |
The parameter values provided on this page are general recommendations used as starting points for configuration. Actual values are affected by material forms, 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 Mistakes
- Symptom: When calling a configured energy metal market query application in a workflow, no corresponding interaction record appears in the conversation logs panel. Cause: The
logWorkflowStepsconfiguration item for the workflow node was not enabled, so internal workflow calls are not included in the conversation log system. - Symptom: After configuring
historyLogDisplayModeto hide thought processes, some thought processes from returned results still appear in historical records. Cause: The model-side thought process output switch was not configured synchronously, so the original content returned by the model is not filtered. - Symptom: When calling the interface to view historical records, the
sourcefield only displays a generic call identifier and cannot identify specific energy metal data sources. Cause: The detailed identifier rule forlogSourceCapturewas not configured, so only the generic source type is captured.
How to Verify Successful Configuration
- Initiate a market query for a specified energy metal variety, view the conversation logs panel, and confirm that the record includes query information and returned data for the corresponding variety.
- Call the historical record query interface, check that the
sourcefield in the returned content carries a specific data source identifier, and adjust thelogSourceCaptureconfiguration to match requirements. - Verify the workflow call scenario, confirm that interaction steps within the workflow are included in the conversation logs, which can be achieved by enabling the corresponding configuration items.
- Check historical record display, confirm that intermediate thought processes are hidden or retained as configured, and adjust relevant switches for both the model and the platform synchronously.
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.