Conversation Logs and Audit for Minor Metal Yields

Minor metal market data primarily comes from professional non-ferrous metal industry information platforms and spot trading markets, with some

What This Category’s Data Looks Like

Minor metal market data primarily comes from professional non-ferrous metal industry information platforms and spot trading markets, with some varieties using statistical data released by international industry organizations. There are two update schedules: spot quotes release full daily data after the daily market close, while actively traded intraday varieties push real-time transaction prices every hour. Each data document includes fields such as full variety name, implementation standard, origin identifier, daily average transaction price, daily price change amount, total social inventory, and more. Units uniformly use yuan/ton (domestic spot) and US dollar/ton (international quotes), while inventory data uses tons or ten thousand tons as units.

What Constraints Do These Characteristics Impose on Conversation Logs and Audit

The high-frequency update nature of minor metal market data requires conversation logs to accurately record each request’s timestamp and the corresponding data source version identifier, ensuring accurate data traceability to the relevant point in time during audits. The multi-field, multi-dimensional document structure requires logs to fully retain user request filter parameters and the full field content of returned results, avoiding missing key verification information during audits. The existence of different pricing units requires logs to simultaneously record the unit specified in the request and the actual unit of the returned data, preventing unit conversion deviations during audits. The large number of varieties and subtle differences in fields requires logs to associate and record the specific requested variety name and returned field set, ensuring audit accuracy.

How to Configure

Configuration ItemRecommended ValueRationale
chat_log_retention_days30–90 daysMinor metal market audits typically cover monthly to quarterly cycles, this retention period matches conventional audit needs
log_include_thoughtOnly record user questions and assistant replies, exclude thought processesIn minor metal market daily yield and market report scenarios, thought processes are not required for audit, reducing log storage redundancy
export_log_fields["query", "response", "timestamp", "source_version", "unit"]Must cover core audit dimensions of minor metal market queries, including request content, returned results, timestamp, data version, and pricing unit
api_source_log_enabledEnabledMinor metal market data mostly comes from third-party professional platforms, API call source identifiers must be recorded to ensure accurate data traceability
log_request_params["metal_type", "specification", "time_range"]Minor metal market queries require specifying variety, specification, and time range, these parameters must be fully retained for audit verification
chat_log_max_size_per_entry2000 charactersSingle minor metal market data document has moderate length, this value can fully record the complete content of a single round of conversation without truncation

The parameter values provided on this page are conventional recommendations used as a starting point 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 applicable samples before finalizing.

Three Common Configuration Mistakes

  • Phenomenon: After the workflow calls the minor metal market query plugin, no corresponding record appears in the conversation log list, and the workflow operation log does not display the conversation interaction synchronization step. Cause: The workflow_log_sync_enabled configuration item is not enabled, causing conversation interactions within the workflow to not synchronize to the global audit log.
  • Phenomenon: After configuring AIProxy to call a specific model, the thought process generated by the model does not display in the conversation history log. Cause: The log_include_thought configuration item is set to only retain user and assistant interaction content, or the proxy configuration does not enable log synchronization of thought processes.
  • Phenomenon: When querying conversation logs via the /chat/history interface, the source field only returns generic keywords such as api or web, and cannot identify the minor metal market-specific data source identifier. Cause: The X-Source field is not added to the API request header to specify the specific data source, and the api_source_log_enabled configuration item is not enabled to record custom source information.

How to Verify the Configuration Is Correct

  • Enter the log management module of the target application, view the conversation log of a single round of minor metal market query, and confirm that the fields included in the log match the settings of the export_log_fields configuration item.
  • Call the conversation history query interface, check whether the source field in the returned results matches the custom data source identifier, and the identifier content can be adjusted according to the actually connected data source.
  • Initiate a test conversation that includes the model's thought process, verify whether the thought process is displayed or hidden in the log according to business requirements, adjust the log_include_thought configuration item, and re-verify.
  • Perform a conversation log deletion operation, confirm that the operation permissions meet the configuration requirements, and the corresponding record will no longer be included in the log list after deletion.

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.