What the Data for This Category Looks Like
Jewelry research report data sources include public industry monitoring databases, brand annual and half-year public reports, and offline retail terminal sampling data. The regular update cycle is quarterly. Temporary report updates for hot new products or industry events have no fixed cycle. A single research report document structure includes macro environment analysis, segmented category performance, leading brand trends, and supply and demand forecasting modules. It also includes structured appendices and statistical notes. Fields include material type, unit price, monthly sales volume, channel type, and more. Each field has a clear statistical caliber and unit of measurement.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
The multi-source data nature of jewelry research reports requires tool calling to support both structured SQL queries and unstructured document parsing. Two types of plugins must be configured to work together. The quarterly update feature requires plugin caching strategies to match the update cycle. This prevents the return of outdated data. Clear field classification requires specifying return fields during tool calling. This prevents irrelevant data from interfering with large model analysis. Temporary updated reports require plugins to support manual cache refresh. This covers the latest data from hot events.
How to Configure Settings
| Configuration Item | Recommended Value | Basis for This Setting |
|---|---|---|
tool_call_max_retries | 2 times | Jewelry research report tool calls involve pulling data from multiple sources. Retrying 2 times covers temporary network or interface fluctuations, and avoids direct task failure. |
plugin_cache_ttl | 7776000 seconds | The regular update cycle of jewelry research reports is quarterly. Matching the cache expiration time to the update cycle ensures data timeliness of returned results. |
sql_query_selected_fields | material type, unit price, monthly sales volume, channel type | The core analysis dimensions of jewelry research reports are material, price, sales volume, and sales channels. Limiting returned fields reduces data transmission volume and improves large model processing efficiency. |
rag_recall_top_k | top 3 entries | The body of a single jewelry research report is moderately long. Too many recalled entries will cause context overflow. Recalling 3 entries covers core analysis fragments. |
rag_similarity_threshold | 0.75–0.85 | Jewelry research reports contain many professional terms. A threshold that is too low will introduce irrelevant fragments, while a threshold that is too high will miss valid content. This range balances recall precision and coverage. |
workflow_exec_timeout | 1800 seconds | When processing batch jewelry research report queries, tool calls require sufficient time to complete data pulling and parsing. 1800 seconds covers the execution duration of most batch tasks. |
The parameter values provided on this page are all common recommendations used as a starting point 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
- Phenomenon: After calling a MySQL tool to return structured data, the large model outputs only a summary conclusion without displaying original database snippets. Cause: The context mounting function for tool results is not enabled. Structured query results are not synchronized to the RAG recall link, so the large model cannot access original data snippets.
- Phenomenon: Tool calls return the
401 Unauthorizederror code. Cause: A general authentication key is used to access a dedicated jewelry research report database. Such databases are usually bound to dedicated access permissions. General keys cannot pass identity verification. - Phenomenon: When processing batch jewelry research report queries, workflow execution times out. A timeout prompt displays on the interface. Cause: The
workflow_exec_timeoutparameter is not adjusted. The default timeout duration is insufficient to cover the time required for batch data pulling and parsing.
How to Confirm Proper Configuration
- Initiate a SQL tool call for jewelry of a specific material. Check if returned result fields match the configured
sql_query_selected_fields. - Trigger a plugin call. View the cache generation time to confirm the cache expiration time matches the
plugin_cache_ttlconfiguration. - Submit a batch jewelry research report query task. Monitor execution duration, and adjust the
workflow_exec_timeoutparameter to a range that allows the task to complete normally. - Test RAG recall results under different similarity thresholds. Confirm that the relevance of recalled fragments meets analysis requirements.
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.