What data for this category looks like
Data related to biologic product yield rates comes from public pharmaceutical industry databases, periodic reports of listed companies, and real-time monitoring APIs from third-party medical information platforms. Updates are released daily after market close. Data for some niche product categories may have a 1-2 business day delay. Documents use structured JSON format, with fields including product generic name, product brand name, dosage form, specification, corresponding change amplitude, market circulation volume, statistical cycle, and data update timestamp. Market circulation volume is measured in units. Statistical cycle uses natural days as the unit. Change amplitude is expressed as relative change amplitude.
What constraints do these characteristics impose on conversation logging and auditing?
The daily updated data source requires conversation logs to retain daily market snapshots. Without this, audits cannot trace the source of that day’s market data. The multi-field structured documents require the audit process to verify the completeness of each core field. Missing fields can cause audit failures. The delayed data characteristic of niche product categories requires audit logs to mark the data source’s delay status. This prevents mistaking delayed data for real-time market quotes. The relative calculation logic for change amplitude requires the audit process to verify the consistency of calculation benchmarks. This ensures change amplitudes in logs comply with industry statistical rules.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
logRetentionDays | 90 days | Complies with statutory retention period requirements for pharmaceutical industry audits |
auditFieldChecklist | ["productName", "specification", "changeAmplitude", "updateTime"] | Covers core audit fields for biologic product yield rate data, prevents omission of critical information |
dataSnapshotInterval | Daily at 23:00 | Matches the daily post-market update schedule of data sources, ensures logs retain complete daily market snapshots |
multiUserChatScope | Isolated by user ID | Meets requirements for multi-user management of historical chat records, prevents mixing of audit logs from different users |
maxRetryTimes | 3 times | Matches retry limits of data source APIs, avoids excessive requests triggering rate limiting |
apiRequestTimeout | 15 seconds | Adapts to response times of biologic product data source APIs, prevents request timeouts causing log recording failures |
The parameter values provided on this page are common starting points for configuration. 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 your own samples before finalizing settings.
Three common configuration errors
- Phenomenon: Chat history records from different users cannot be distinguished; logs only display conversation content without associating user identifiers. Cause: The
multiUserChatScopeparameter is not configured, and the function that binds logs to user IDs is not enabled. - Phenomenon: Calling the data source API returns the
Reached the max retries per request limiterror, and no retry records appear in logs. Cause: ThemaxRetryTimesparameter is not set correctly, or the parameter value is lower than the retry threshold required by the API. - Phenomenon: The specification field for some biologic products is empty in audit logs, preventing compliance audits. Cause: The specification verification rule is not configured in
auditFieldChecklist, so no exception flag is triggered when the field is missing.
How to confirm configuration is complete
- Log in to the platform's log management module, verify that historical chat records for a specific session can be filtered using a user ID, confirming that the multi-user isolation configuration is active.
- Manually trigger a data source API call, check if the system log records the number of retries matching the
maxRetryTimesconfiguration, with no limit-exceeded errors. - Export an audit log sample, check that core fields such as
productNameandspecificationare included, confirming that field verification rules are active. - View the system's scheduled task list, confirm that the daily post-market data snapshot task has executed at the configured time.
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.