What Data for This Category Looks Like
This category processes data sourced from raw datasets, ETL operation logs, annotation platform output results, and sampling quality inspection results. Data updates follow a daily or batch task schedule. Daily deliverables include cleaning rule documents, quality inspection sampling tables, abnormal data lists, and delivery reports. Each individual data entry includes original content fields, cleaning mark fields, quality inspection status fields, and exception type fields. There are no mandatory additional units; most field values are text, boolean, or enumeration types.
What Constraints Do These Characteristics Impose on the Conversation Logs and Auditing Link
The data sources for this category cover outputs from multiple systems. The conversation logs and auditing link must support filtering by dimensions such as raw datasets, ETL logs, and annotation results to ensure cross-system operations are traceable. Given the daily or batch update rhythm of data, audit logs must be archived per update cycle to avoid redundant storage usage. Abnormal data lists and delivery reports must be bound to audit logs. Logs must record associated IDs of abnormal data and quality inspection status markers to ensure problem backtracking can match the corresponding quality inspection link. For cleaning and quality inspection workflows involving multiple roles, log fields must include operator role, operation type, and operation time to distinguish operation permissions and traces across different positions.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Log storage period | 30–90 days | Adapts to the log archiving rules of FastGPT v4.17.0, matches the daily or batch update task rhythm of this category, and ensures a complete traceability window |
Associate chatId field | Enabled | Binds the conversation context of a single batch of cleaning/quality inspection tasks, ensures one-to-one correspondence between logs and tasks, and enables retrieval by task dimension |
Enable detail logs | Enabled | Records complete operation details, including adjustments to cleaning rules, changes to quality inspection sampling parameters, and other scenarios covering core operations of this category |
| Log filtering dimensions | By data source, task batch, operation role | Matches the business characteristics of this category: multiple data sources, batch updates, and multi-role participation |
| Audit permission scope | Limited to data engineer and quality inspector roles | Distinguishes post operation permissions, prevents unauthorized personnel from viewing sensitive cleaning and quality inspection data |
| Log export format | CSV format | Adapts to the document formats of daily deliverables for this category, such as quality inspection sampling tables and abnormal data lists, to facilitate subsequent analysis |
Three Common Misconfigurations
- Phenomenon: After calling the conversation deletion interface, the corresponding audit log remains in the list. Cause: The log cleaning rule associated with
responseChatItemIdis not configured, causing the audit log to become unbound from the actual conversation record. - Phenomenon: No response when executing a cleaning task, and the server logs do not return clear error messages. Cause:
detaillog recording is not enabled, making it impossible to capture abnormal links during task execution. - Phenomenon: A proxy error is triggered when downloading the abnormal data list. Cause: The file access permission for audit logs is not configured, causing the abnormal data files associated with the logs to fail to load properly.
How to Confirm the Configuration Is Correct
- Execute a single batch of cleaning tasks, check whether the audit log list includes context records for the corresponding
chatIdto confirm that the task association relationship is working properly. - Switch accounts with different roles, verify that only audit logs within the corresponding permission range can be viewed to confirm that the role permission configuration is effective.
- Trigger an abnormal data tagging operation, check whether the
detailfield records complete operation content to confirm that detailed logging is enabled properly. - Download the audit log file, verify that the export format matches the daily deliverable document format to confirm that the export configuration is effective.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.