What This Category of Data Looks Like
This category of data originates primarily from risk control systems, audit records, user behavior logs, and report evidence. Daily documents include ban records, appeal materials, reconsideration opinions, and user notifications. Data update cycles are mostly daily or real-time. Fields cover account unique identifiers, ban trigger times, appeal submission content, audit disposition results, associated report vouchers, and more. Units are mostly timestamps, character counts, and account ID identifiers; there is no unified fixed statistical standard.
What Constraints These Characteristics Impose on Conversation Logs and Auditing
Decentralized data sources require conversation log auditing to use cross-system aggregation rules to integrate multi-source data such as risk control, audit, and behavior logs. Real-time updated business data requires the auditing link to support low-latency queries and real-time alerts. Multi-type business document structures require log field mapping to adapt to different form formats including ban records and appeal materials. Account-level associated data must be aggregated by account ID dimension to prevent cross-account data confusion. Audit trail requirements mandate configuring a read-only storage policy for audit logs to ensure data cannot be altered.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId grouping rule | Group by all chatId associated with the account | Matches the account-level auditing requirements for account ban and appeal reconsideration, making it easy to trace all interactive logs for a single account |
responseChatItemId binding rule | Bind the responseChatItemId of the user's appeal conversation | Accurately associates the contextual conversation during appeal, making it easy to verify appeal reasons and historical interaction content |
detail field extraction | Extract violation evidence, appeal content, and audit opinions from the detail field | Covers core audit material fields required for business documents |
| Log retention period | 180–365 days | Meets basic retention requirements for compliance audits, and adapts to traceability needs for platform governance |
| Cross-source synchronization interval | 60 seconds | Adapts to real-time or daily business data update cycles, balancing synchronization efficiency and resource usage |
| Query result limit | Top 500 sessions | Balances query performance and audit coverage, calibrated based on actual testing |
Three Common Misconfigurations
- Workflow conversations display failures, but the model backend has response logs. The cause is that no exception capture rule for the
detailfield is configured, so audit-related abnormal interaction data is not synchronized to conversation logs. - No results return when counting tokens by application dimension. The cause is that the association mapping between
chatIdand application dimension is not enabled, so log aggregation dimensions do not match statistical requirements. - No call log entry appears on the model provider page. The cause is that the global configuration switch for conversation auditing is not enabled, so the log collection function is not activated, and no displayable call logs are generated.
How to Verify Correct Configuration
- Log in to the FastGPT v4.17.0 backend, access the dedicated workflow for account ban and appeal reconsideration, enter a test account ID, retrieve the associated
chatId, and confirm that all historical conversations for the account can be pulled. - Submit a simulated appeal conversation, check whether the
responseChatItemIdis correctly bound to the appeal ticket, and whether thedetailfield includes appeal content and violation evidence. - View the log storage directory, confirm that audit logs from the past 7 days have been written normally per the configured retention period, with no empty logs or missing fields.
- Trigger a simulated model call exception, check whether the corresponding
detailfield exception record is captured in the audit logs.
The values provided are common starting points and should be evaluated 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.