Conversation Logs and Auditing for Jewelry Investment

What the data for this category looks like

Jewelry investment research data mainly comes from official brand product pages, industry association released material standard reports, supply chain batch quality inspection documents, and real-time raw material quotation platforms. Update cycles fall into three categories: raw material quotations are updated daily, new SKUs are updated according to brand launch cycles (quarterly or monthly), and quality inspection reports are updated with each batch shipment. Document structure has a high degree of standardization, including SKU code, material (such as 925 silver, 18K gold), gram weight, design item number, terminal pricing, supply chain batch number, nickel release amount and other compliance parameters. Units include grams, yuan, ppm and others.

What constraints these characteristics impose on conversation logs and auditing

The multi-dimensional attributes and different update frequencies of jewelry data impose multiple constraints on conversation logs and auditing. First, real-time raw material prices change daily. Audits must bind the timestamp when a question is initiated to avoid traceability deviations caused by subsequent data updates. Second, SKU and batch fields are numerous and closely linked. Logs must store corresponding fields in a standardized way, otherwise it is impossible to quickly locate quality inspection and pricing information for the corresponding batch. Third, compliance-related questions (such as nickel release amount verification) must leave traces compulsorily. The audit link must support marking key nodes to meet industry regulatory requirements. Fourth, long-text quality inspection reports and supply chain documents lead to large single log volume. Performance thresholds for log storage and querying must be limited.

How to set the configurations

Config Item	Suggested Value	Rationale
`log_retention_days`	`90 days`	Jewelry investment research requires tracing the full cycle of supply chain and quotation changes, and compliance audit requirements mandate retaining records for at least one quarter
`audit_required_tags`	`["compliance check", "SKU matching", "quotation query"]`	Jewelry investment research conversations often involve three core scenarios: compliance quality inspection, SKU matching, and real-time quotation queries, which must be marked compulsorily
`max_log_query_size`	`1000 entries`	Jewelry has a large number of SKUs, returning too many logs in a single query should be avoided to prevent performance loss on audit pages
`log_field_whitelist`	`["question", "answer", "sku_code", "material", "price", "create_time"]`	Core fields of jewelry data are SKU, material, price and time, retaining only necessary fields simplifies the audit process
`annotation_enable`	`Enabled`	Jewelry compliance-related questions require marking quality inspection reports and compliance check nodes to facilitate subsequent tracing
`api_log_batch_size`	`First 50 entries`	Investment research conversations often relate to multiple sets of SKU data, limiting the number of entries during batch pulling balances query efficiency and display effect

The parameter values provided on this page are common recommendations used as 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 settings.

Three Common Mistakes

Issue: After clicking a shared non-login link to initiate a conversation, the corresponding record cannot be found in the audit logs. Cause: The share_log_enable configuration item is not enabled. Shared links do not record conversation logs by default, which prevents traceability during the audit process.
Issue: The conversation log annotation function cannot select custom fields, only preset tags can be used. Cause: The whitelist for custom fields is not configured in audit_required_tags, which limits the annotation scope.
Issue: When configuring a jewelry knowledge base in the open source version 4.8.11, ollama logs report the error try reducing the size of the batch, and the creation process gets stuck. Cause: Jewelry documents often contain long-text quality inspection reports or supply chain data. The default batch_size parameter is too large, exceeding the model loading limit, and parameters are not adjusted according to the characteristics of jewelry data.

How to Confirm the Configuration Is Correct

Initiate a jewelry investment research conversation that includes SKU code and material parameters. Check whether the corresponding fields are automatically associated in the audit logs, and confirm that the log_field_whitelist configuration takes effect.
Try adding a custom tag to a compliance-related conversation. Confirm that annotation_enable is enabled and the annotation function works properly.
Call the audit log query interface, pass in jewelry SKU parameters. Check that the number and time consumption of the returned results meet expectations, and confirm that the max_log_query_size and log_query_timeout configurations are reasonable.
Generate a non-login shared link, initiate a conversation, check whether the record is retained in the background logs, and confirm that the share_log_enable configuration is correct.

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.