Conversation Logging and Auditing for Jewelry Yield Rates

Jewelry yield rate related data comes primarily from internal brand inventory and sales systems, offline retail POS ledgers, and third-party jewelry

What the data for this category looks like

Jewelry yield rate related data comes primarily from internal brand inventory and sales systems, offline retail POS ledgers, and third-party jewelry market trend aggregation APIs. Full data synchronization runs daily at midnight. The maximum delay for updated data on individual jewelry items is no more than 2 hours. Data uses structured JSON format. Each record includes a unique SKU identifier, jewelry name, material type, daily supply unit price, daily terminal retail price, and daily second-hand circulation reference price. The unit of price fields varies by material: precious metals use yuan/gram, non-precious metals use yuan/item. The update timestamp is an ISO 8601 formatted string.

What Constraints These Characteristics Impose on Conversation Logging and Auditing

Multiple data sources require audit logs to fully record the call chain for each data entry, eliminating data traceability blind spots. Fixed daily update schedules require logs to archive incremental data daily, supporting monthly review and compliance audits. Differentiated field units require logs to track unit information for each numeric field, preventing ambiguity in valuation methods during audits. Fine-grained SKU-level data requires logs to link to specific SKU identifiers, enabling quick location of abnormal records by individual item and avoiding issues with unfilterable massive logs. Additionally, conversation logs must fully retain broadcast request parameters and returned results to ensure yield rate broadcast content can be traced and verified.

Configuration Settings

Configuration ItemRecommended ValueRationale
WORKFLOW_LOG_ENABLEtrueEnable full logging for workflow nodes, covering every execution step of the jewelry yield rate broadcast
RECORD_DATA_SOURCE_DETAILallFully record request parameters and returned fields for third-party APIs and internal systems used to call jewelry data, adapting to audit requirements for multiple data sources
LOG_FIELD_UNIT_TRACKenabledTrack unit information for each numeric field, resolving valuation unit ambiguity between precious and non-precious metal jewelry
LOG_RETENTION_DAYS90 daysMeet compliance retention requirements for financial audits, adapting to monthly review needs for jewelry yield rate daily reports
MAX_LOG_ENTRY_PER_WORKFLOW500 entriesBalance log storage and query efficiency, adapting to scenarios where a single workflow processes data for multiple SKU jewelry items
API_HISTORY_LOG_SOURCE_ENABLEtrueRecord all conversation context passed through API calls, meeting traceability requirements for cross-system audits

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

  • Phenomenon: No interface return data is recorded in workflow logs after calling the third-party jewelry market trend API. Cause: The RECORD_DATA_SOURCE_DETAIL configuration item is not enabled, resulting in failure to write data source call details to logs.
  • Phenomenon: When querying historical conversations via the API, the source field only displays a basic call identifier, and cannot distinguish the specific call source between internal inventory and sales systems and third-party market trend APIs. Cause: The LOG_SOURCE_DETAIL parameter is not configured, only general call source types are recorded, and data source identifiers are not detailed.
  • Phenomenon: After the MCP service fails to execute in a workflow, corresponding error details cannot be found in system logs. Cause: The MCP_SERVICE_LOG_ENABLE configuration item is not enabled, resulting in failure to synchronize MCP service execution logs to the global audit log database.

How to Confirm Configuration is Correct

  • Navigate to the FastGPT workflow log management page, select the jewelry yield rate broadcast workflow, and check whether execution time, input parameters, and returned results for each node are included.
  • Call the API to trigger a jewelry yield rate broadcast, query the global audit log, and confirm that the log includes data source call identifiers and field unit information.
  • Navigate to the system log management page, filter logs related to the MCP service, and confirm that execution records for the MCP component of the corresponding workflow can be found.
  • Check the log retention days configuration item, and confirm that the current retention duration meets 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.