What the data for this category looks like
Jewelry research report data primarily comes from industry association monthly briefings, public new product research reports from leading brands, e-commerce platform jewelry category monitoring reports, and accessory trend analysis documents from fashion media. Update schedules vary: industry association reports are updated monthly, brand research reports are updated alongside new product launches, and e-commerce monitoring data is updated daily. Most documents are in PDF or structured table format, some contain mixed text and image content. Fields include segmented categories (such as hair accessories, jewelry, accessories), single item weight, plating thickness, pricing range, traffic source classification, and more. There is no fixed unified format, and field coverage varies across documents from different sources.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
The multi-source update schedule differences for jewelry research reports require multi-turn dialogue to support dynamic differentiation of data timeliness. Prompts must clearly label the update times of data from different sources. There are many segmented categories and personalized parameter fields. Multi-turn dialogue must retain the category and parameter context specified by the user to avoid cross-category confusion. The mixed text and image document structure requires multi-turn dialogue to support precise follow-up questions about chart content. Prompts must be configured with structured extraction rules for text and image content. The differences in field coverage across documents from different sources require prompts to clearly define retrieval rules, prioritizing matching the field range corresponding to the user's question.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | First 12000 characters | Single jewelry research report documents and multi-turn context have relatively long total length. Sufficient space must be reserved to retain parameter and category information from the user's continuous follow-up questions |
recall_topk | Top 8 entries | Jewelry research reports have rich segmented categories. Enough content covering different directions must be recalled, while controlling the length of single-round input |
Similarity threshold | 0.75 | Jewelry research reports have high precision requirements for parameters such as materials and pricing. Low-similarity irrelevant research report content must be filtered out |
max_history_length | Retain the most recent 10 rounds | Multi-turn dialogue for jewelry research reports mostly consists of continuous category or parameter follow-up questions. 10 rounds can cover complete context while avoiding redundancy |
prompt_template | Prioritize recalling research reports for the segmented category specified by the user, associate historical context when asking about parameters | Jewelry research reports have multiple segmented categories and specific parameters. The context association rules for prompts must be clearly defined |
WORKFLOW_TIMEOUT | 300 seconds | Jewelry research reports require integration of multi-source data. Sufficient retrieval and integration time must be reserved when calling tools |
The parameter values provided on this page are common starting points for configuration setup. Actual values are influenced 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 Misconfigurations
- Phenomenon: Conversation logs are empty or partially missing. Cause: Persistent storage for context logs is not enabled in the Docker configuration file, or a valid retention duration for
max_history_lengthis not configured. - Phenomenon: Reply performance after tool calling does not meet expectations. Cause: The prompt fails to clearly define association rules between jewelry research report segmented categories and parameter fields, leading the model to recall irrelevant general research report content.
- Phenomenon: No conversation logs are generated on the current day after calling a workflow. Cause: The log output switch for the workflow is not configured, or the log storage path has insufficient permissions to write log files.
How to Verify the Configuration is Correctly Set
- Initiate a multi-turn dialogue that includes jewelry segmented categories and specific parameters. View the conversation history panel to confirm that context is correctly retained.
- Call the tool to retrieve jewelry research reports. Check the matching degree between the segmented categories of the recalled content and the user's question. Adjust the similarity threshold to align with business requirements.
- View the log storage-related parameters in the Docker configuration file. Confirm the log retention rules and storage path. Restart the service, then initiate a dialogue to verify that logs are generated normally.
- Test the default model configuration for tool calling. Initiate a tool calling request to confirm that the used model is the preset target model.
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.