What the data for this category looks like
Footwear intelligent due diligence reports draw their data primarily from brand production management systems, third-party quality inspection institution reports, e-commerce compliance filing documents, and supply chain ledger records. Update cycles follow two patterns: full batch updates completed before new product launches, and incremental updates triggered during daily quality inspection rectification or inventory changes. Each individual report uses a structured format. It includes basic fields such as SKU code, shoe model name, and production batch number. It also includes quality inspection fields such as last inner length, sole wear resistance test count, and upper fabric gram weight. Some fields have clear associated units.
Constraints on deployment and upgrade from these characteristics
Footwear due diligence data includes structured basic fields and quality inspection indicators with units. During deployment, field format validation rules must be configured to block imports of values with non-standard units. The combined full and incremental update cycle requires deployment to support differentiated synchronization trigger logic, distinguishing between new product launch and daily rectification scenarios. Multi-source document formats require compatible configuration for PDF structured parsing and CSV bulk import. Specific quality inspection indicator fields require the knowledge base to prioritize matching core test items during retrieval, to avoid irrelevant fields interfering with results.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Footwear due diligence reports often contain multiple pages of quality inspection data and supply chain traceability content, resulting in long parsing times |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single bulk-imported SKU ledger CSV or multi-page PDF due diligence reports have relatively large file sizes |
maxContext | 800–1200 characters | Core fields of footwear due diligence reports are concentrated; overly long contexts will dilute critical quality inspection and supply chain information |
retrieval count | top 8 entries | Footwear due diligence requires matching three core types of information: SKU code, quality inspection results, and supply chain entities. Excessive retrieval will add redundancy |
similarity threshold | 0.75–0.85 | Footwear SKU codes are unique, so precise matching must be ensured to avoid cross-category confusion |
incremental sync trigger interval | every 1 hour | Update frequency for daily quality inspection rectification and inventory changes is relatively stable; high-frequency synchronization ensures data timeliness |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three easy-to-make mistakes
- Issue: A
408 Request Timeouterror occurs when parsing footwear due diligence reports. Cause: ThePARSE_FILE_TIMEOUT_SECONDSconfiguration is not set to a duration adapted to footwear document parsing requirements. The default duration is insufficient to handle multi-page quality inspection and traceability content. - Issue: MCP MySQL query service fails when calling a locally privately deployed model, while online models function normally. Cause: The API access whitelist for the local model is not configured, or the local port for the MCP service is not correctly mapped, preventing the model from accessing the database service.
- Issue: The number of footwear due diligence report results retrieved from the knowledge base is abnormally low. Cause: The similarity threshold is set too high, filtering out some eligible SKU matching results, or no targeted retrieval rules are configured for footwear SKU code fields.
How to confirm the configuration is properly set
- Upload a single footwear due diligence PDF containing complete quality inspection items, check that the parsed fields include preset quality inspection and basic fields, to confirm that the parsing rules adapt to the category's data structure.
- Trigger an incremental synchronization task, verify that the number of new SKUs in the knowledge base after synchronization matches the number of incremental updates from the local data source, to confirm that the synchronization logic matches the update cycle.
- Enter SKU code keywords to initiate retrieval, verify the matching accuracy of retrieval results, adjust the similarity threshold to a range that meets requirements, to confirm that the retrieval rules adapt to the category's core fields.
- Call the locally deployed model to test the MCP MySQL query function, confirm that the interface returns results normally, with no port or whitelist configuration errors.
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.