What the data for this category looks like
Data sources for footwear industry research reports include public reports from domestic footwear industry associations, brand quarterly financial reports, sales monitoring data for product categories from mainstream e-commerce platforms, and cross-border supply chain research documents. Update frequencies fall into three categories: Brand financial reports are updated quarterly. E-commerce monitoring data is updated daily. Industry association reports are released monthly. Documents typically include core category sales data, raw material cost proportion, online and offline channel proportion, and competitor price band distribution. Fields covered include SKU code, shipment volume, customer unit price, and gross profit margin. Units include pairs, yuan, and %, among others.
What constraints these characteristics impose on tool calling and plugins
Since daily updated e-commerce monitoring data is included, tool calling must support high-frequency data pulling and short cache cycle settings to avoid using outdated information. Since precise structured fields such as SKU code and customer unit price are included, tool calling must support parameter configuration for filtering retrieval by specified fields to improve retrieval accuracy. Since data sources include multi-format documents such as PDF financial reports and CSV sales reports, plugins must adapt to multiple file parsing rules and support data import and parsing across different formats. Since competitor dynamics for segmented product categories are updated frequently, tool calling must support real-time calls to external monitoring interfaces to supplement the latest market data.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall Count | 10–15 items | Footwear industry research reports have many data fields, and each report contains a large amount of information. Too many recalled items will exceed the context window |
Similarity Threshold | 0.72–0.78 | Footwear SKUs and competitor information have strong relevance. A threshold that is too low will introduce irrelevant data, while a threshold that is too high will miss accurately matched items |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Footwear industry research reports often contain multi-page tables and charts, which take longer to parse |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single industry research report PDF or CSV files have large file sizes, so large file uploads must be supported |
Tool Call Trigger Model | Calibrated based on actual testing | Footwear industry research report retrieval requires accurate judgment of tool call timing. The model selection must be adjusted based on actual call logs |
Plugin Cache Duration | 3600 seconds | E-commerce monitoring data is updated daily, so the cache duration should not exceed one day to avoid using outdated data |
The parameter values provided on this page are all 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 the settings.
Three common mistakes
- Phenomenon: When calling a third-party multimodal vector model, the interface returns a
Model not supportederror log. Cause: The access configuration for the corresponding model was not added, and only the parameter settings of the default model were retained. - Phenomenon: The specified tool is not automatically selected in the advanced orchestration tool call link, and a
No matching toolprompt is returned. Cause: The trigger model and optional tool range for tool calls were not specified in the configuration, causing the model to fail to recognize the call demand. - Phenomenon: When calling DALL·E3 to generate footwear style previews, the interface returns a
401 Unauthorizederror. Cause: The regional permissions and access scope of the API key were not configured correctly, resulting in interface verification failure.
How to confirm the configuration is correct
- Upload a PDF or CSV file of a footwear industry research report, check that the system parsing task status shows Completed, and there are no
Parse failedtype logs. - Initiate a footwear SKU retrieval request, check that the returned results include matching SKU codes and corresponding sales data, and the number of recalled items matches the configured
Recall Countrange. - Call the third-party multimodal vector model interface, check that the returned vector data format meets expectations, and there are no
Model not supportedtype errors. - Initiate an API request from an external browser, check that the returned status code is
200 OK, and there are no cross-domain interception prompts.
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.