What the Data for This Category Looks Like
Coking coal-related market and yield data primarily comes from the Dalian Commodity Exchange futures market and domestic coal industry association spot price channels. Data update cadence differs between futures and spot: futures data updates in real time during trading sessions on trading days, while spot quotes are released at fixed times each day. Standard data documents include fields such as coking coal delivery grade, origin, pricing unit (yuan/ton), benchmark price, daily price change, trading volume, open interest, and data release time. Some extended data includes regional price spread and upstream-downstream linkage index fields.
What Constraints These Characteristics Impose on Conversation Logs and Auditing
The multi-source, time-staged update characteristics of coking coal market and yield data create multiple constraints for conversation logs and auditing. Real-time futures data updates at high frequency require logs to accurately record the exact timestamp of each data call, matching the trading session of the query. This prevents audit deviations caused by mixing data across time periods. The existence of multi-dimensional segmented fields requires logs to fully store specific called field parameters. During audits, this allows quick matching of user needs with actual called content, preventing unauthorized calls of non-necessary fields. Differences in release times across data sources require audit links to distinguish data source scenarios. Dependency relationships for extended data require logs to record complete call chains, enabling backtracking of data calculation logic.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
CHAT_LOG_STORAGE_DAYS | 90 days | Auditing cycles for coking coal industry data typically cover 3 months. This duration meets compliance auditing requirements while avoiding excessive storage space usage from long-term retention. |
LOG_INCLUDE_FIELDS | ["chatId", "queryText", "dataSource", "calledFields", "requestTime", "responseStatus"] | Coking coal data requires recording call sources, specific fields, time, and status. This fully covers key information needed for audit traceability. |
REQUIRE_CHAT_ID_ON_API | true | User conversations and log records must be bound via chatId. This prevents log association confusion in non-logged-in scenarios and resolves audit blind spots caused by lack of identifiers. |
DATA_SOURCE_VALIDATE_SWITCH | Enabled | Coking coal data has multiple sources including futures and spot channels. Enabling this validates data source legitimacy and prevents calls to unauthorized data sources. |
LOG_ERROR_DETAIL_ENABLE | Full recording | Coking coal data interfaces may experience exceptions due to market fluctuations. Full recording of error details allows quick localization of specific causes of call failures. |
CHAT_DELETE_LOG_BEHAVIOR | Retain logs | Audits require retention of complete operational records. Logs should not be deleted synchronously when a conversation is deleted, preventing missing records for compliance audits. |
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. It is recommended to test on internal samples before finalizing settings.
Three Common Misconfigurations
- Symptom: After calling the API with the
chatIdparameter, the conversation log does not record the parameter value, making it impossible to associate conversations and logs via chatId. Cause: TheREQUIRE_CHAT_ID_ON_APIconfiguration item is not enabled, so the system does not forcibly capture and store the chatId parameter. - Symptom: After a non-logged-in user deletes a conversation via a shared link, the corresponding conversation logs retained in the backend are synchronously cleared. Cause: The
CHAT_DELETE_LOG_BEHAVIORconfiguration item is set to delete with the conversation, failing to retain operational records required for audits. - Symptom: The call log page displays the "Failed to obtain data" error, with the interface returning status code 500. Cause: For open source version V4.9.7, this error may be caused by compatibility issues with the log storage module. Additionally, failure to enable
DATA_SOURCE_VALIDATE_SWITCHwill prevent interception of unauthorized data source calls, or an excessively shortCHAT_LOG_STORAGE_DAYSconfiguration will cause historical logs to be automatically cleaned up.
How to Confirm Proper Configuration
- Initiate an API call related to coking coal data, pass a clear
chatIdparameter, and check whether the conversation log fully records the parameter value. Confirm that theREQUIRE_CHAT_ID_ON_APIconfiguration is effective. - Simulate a non-logged-in user deleting a conversation record, and check whether the backend logs retain the complete call records for that conversation. Confirm that the
CHAT_DELETE_LOG_BEHAVIORconfiguration meets audit requirements. - Call an unauthorized coking coal data source, and check whether the corresponding error record is generated in the logs. Confirm that the
DATA_SOURCE_VALIDATE_SWITCHconfiguration is enabled. - View the log storage list, verify whether the log retention duration matches the
CHAT_LOG_STORAGE_DAYSconfiguration value, and confirm that the storage cycle aligns with internal audit requirements.
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.