What the data for this category looks like
Footwear intelligent due diligence report data comes from three main sources: brand production ledgers, third-party quality inspection test reports, and cross-border e-commerce sales platform parameters. Update frequency fluctuates with new product launch cycles. Multiple batch updates run weekly during spring and autumn new product seasons. Daily restocks only update information for individual SKUs. Each footwear style’s due diligence document includes three modules: basic style identification, material parameters, and compliance test data. Fields include 款号, 帮面材质, 外底耐磨次数 (unit: revolutions), 鞋楦型号, and 生产批次号. Some cross-border styles also include size correspondences between EU sizes, US sizes, and Chinese sizes.
Constraints for Tool Calling and Plugins
Multi-source data access requires tool calling to support connections to multiple heterogeneous interfaces. It must adapt to authentication and return formats for different data sources. Footwear-specific fields differ from general product parameters. The parameter parsing module for tool calling must specifically map these dedicated fields. It cannot directly reuse configurations for general product categories. Update frequency varies widely. Rate limiting plugins must be configured during batch update scenarios to avoid interface overload. Compliance test data is a required item. Tool calling must verify the presence of fields such as 外底耐磨次数 and 甲醛含量. Missing fields must return clear error prompts.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PLUGIN_REQUEST_TIMEOUT | 300 seconds | Parsing footwear quality inspection reports and calling interfaces typically takes 2 to 5 minutes. 300 seconds covers most scenarios |
PARSE_FIELD_MAPPING | {"款号":"sku_code","外底耐磨次数":"wear_resistance","帮面材质":"upper_material"} | Maps footwear-specific fields to standard field names for general interfaces |
API_RATE_LIMIT | 10 requests per minute | Adapts to the interface call frequency for footwear batch updates, avoids triggering third-party interface rate limits |
REQUIRED_FIELDS_CHECK | ["款号","外底耐磨次数","生产批次号"] | Covers required compliance fields for footwear due diligence reports, ensures report completeness |
UPLOAD_FILE_MAX_SIZE | 200 MB | Single footwear quality inspection report PDF or CSV files typically do not exceed 150 MB. This value reserves reasonable buffer space |
MAX_RETRY_TIMES | 2 times | Adapts to occasional interface fluctuations for footwear data sources, avoids excessive retries that trigger rate limits |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: Calling the DeepSeek R1 plugin returns a 422 Unprocessable Entity error. Cause: Footwear-specific field mapping rules are not configured correctly. The request body carries fields not registered in the plugin allowlist.
- Symptom: Calling real-shot footwear product images with a multimodal tool returns a 400 invalid image error. Cause: Image format and resolution requirements are not verified. Unsupported WebP format images or images with insufficient resolution are submitted.
- Symptom: Running an SQL statement with a data connection tool returns empty results or a field does not exist error. Cause: The table structure for footwear data sources is not adapted. Field names from general product tables are used instead of footwear-specific field names.
How to Verify Correct Configuration
- Initiate a test call for a single footwear SKU on the plugin configuration page. Verify that the returned results include the configured mapped fields, with no missing or incorrectly mapped fields.
- Upload a footwear quality inspection report file. Verify that the fields extracted by the parsing tool fully match the preset
款号,外底耐磨次数, and other fields. - Trigger a batch update task. Review API call logs. Confirm that all request status codes are 200, with no 429 rate limit errors.
- Run a test SQL statement. Verify that the returned results include dedicated fields for footwear data sources, with no field does not exist 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.