What data for this category looks like
Personal care product profit margin-related data primarily comes from brand inventory and sales systems, mainstream e-commerce platform transaction backends, and sampled data from third-party retail monitoring agencies. E-commerce channel data updates daily. Offline counter retail data updates every 7 days. Each structured data entry includes fields such as SKU code, category name, units sold, revenue amount, purchase-sales spread amount, average daily visitors, customer unit price amount, collection time, data source type, and more. Data is stored in CSV or structured JSON format. Each record corresponds to the business performance of a single SKU within one collection cycle.
What constraints do these characteristics impose on the conversation logs and auditing link
Personal care product data has multiple sources and inconsistent update rhythms, which impose multiple constraints on the conversation logs and auditing link. First, clearly mark the collection time and data source type of each data entry in logs. This avoids confusion between business data from different cycles and ensures traceability of data authenticity during audits. Second, since each data entry contains multiple SKU-related fields, the auditing link must strictly verify the format and value range of each field. This prevents dirty data from entering conversation responses. Third, since data source update frequencies differ, distinguish the data source scope covered by user queries in conversation logs. This avoids audit deviations caused by mixing cross-cycle data.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
logRetentionDays | 90 days | Meets audit compliance requirements for financial and wealth management scenarios, retains sufficient duration of conversation and data logs for traceability |
auditFieldWhitelist | SKU Code, Sales Quantity, Revenue Amount, Collection Time, Data Source Type | Only core business fields are required for personal care product profit margin audits. Filtering non-essential fields simplifies the audit verification process |
maxContext | Last 6 conversations | Personal care has a large number of SKU categories. Excessive context increases information complexity during audits, while ensuring coherence of conversation context |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Data source files for personal care categories may contain massive SKU data. Sufficient parsing time must be reserved to avoid timeout interruptions |
auditAlertThreshold | Calibrated based on actual testing | Audit rules vary significantly across enterprises. Adjust thresholds based on applicable compliance requirements and data volume |
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 specific analysis. It is recommended to test on your own samples before finalizing values.
Three common mistakes
- Symptom: Empty response after calling profit margin query, with
invalid data fielderror displayed in logs. Cause: Using the legacy audit filtering rules from the open-source 4.8.17 version, which does not support the multi-SKU field format for personal care categories, resulting in data verification failure. - Symptom:
nullvalue fields appear in audit logs, with empty results returned when looping through SKU data statistics. Cause: No reasonable duration set forPARSE_FILE_TIMEOUT_SECONDS, resulting in incomplete parsing of large-volume personal care SKU data and leftover null fields. - Symptom: Conversation history includes execution records of specified reply plugins, making it impossible to distinguish user real queries from plugin calls during audits. Cause: No filtering rule configured for
maxContext, and intermediate logs from plugin execution are not ignored, resulting in invalid content being mixed into audit logs.
How to confirm configurations are set correctly
- Log in to the log management page of the system backend, confirm that conversation and data audit records from the past 90 days can be queried, matching the
logRetentionDaysconfiguration value. - Import a test personal care SKU data file, initiate a profit margin query, and verify that the generated audit logs only include fields within the whitelist, with no additional irrelevant content.
- Initiate a test conversation that includes plugin calls, confirm that the audit logs only retain the user's original query and model responses, and do not include intermediate steps of plugin execution.
- Import a large-volume personal care SKU data file, confirm that the parsing process does not trigger timeout errors, and all fields are properly loaded into the conversation context.
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.