What the Data for This Category Looks Like
Data related to footwear yield rates is primarily sourced from brand distributor inventory and sales systems, e-commerce platform product detail pages, and offline retail terminal POS data. The update cadences vary: offline stall supply data updates daily, e-commerce platform terminal selling price data updates hourly, and official brand category pricing data updates weekly. Each individual data document uses a single SKU as the smallest unit, containing fields including SKU ID, brand name, product category, supply unit price, terminal selling price, listing duration, supply cycle, and other fields. All monetary fields use Chinese Yuan as the unit, cycle fields use days as the unit, and there are no additional percentage-based statistical fields.
Constraints Imposed by Data Characteristics on Model Access and Configuration
Differences in update frequencies across multiple data sources require configuring independent sync cycles for each data source, to avoid excessive resource usage or data lag caused by unified refreshes. The large number of fields per document and high volume of SKUs require adjusting chunk length to ensure each chunk covers complete core SKU information, preventing mapping failures caused by split fields. Minor differences in data formats across sources require configuring unified field extraction rules, to ensure the model can accurately identify and associate each field. Additionally, footwear SKUs have a large number of hierarchical classifications, so field association rules must be configured to ensure the model can group data by brand and category, providing accurate grouping basis for yield rate calculations.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
ragChunkSize | 800–1200 characters | Footwear SKU data includes multiple fields; each chunk must cover complete core SKU information to avoid mapping failures caused by split fields |
ragRefreshInterval | 3600 seconds | E-commerce platform footwear transaction price data updates hourly; sync refresh of the retrieval index is required to maintain data timeliness |
fieldMappingPrompt | Please extract the following fields: SKU ID, brand name, product category, supply unit price, terminal selling price, listing duration, supply cycle. Monetary unit is Chinese Yuan, cycle unit is days | Standard fields and units for footwear data are clearly defined; extraction rules must be specified to ensure accurate field assignment |
rerankTopN | Top 8–12 results | Footwear SKU volume is high; re-ranking is needed to filter irrelevant results while retaining sufficient candidate samples for yield rate calculations |
parseFileTimeout | 600 seconds | When importing footwear SKU data in batches, single files contain many SKUs; sufficient parsing time is required to avoid timeouts |
multiSourceSyncMode | Trigger in batches by data source type | Footwear data from different sources has different update frequencies; separate sync cycles must be configured to optimize resource usage |
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 internal samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: A
504 Gateway Timeouterror is returned after starting the model service, and data access cannot be completed. Cause: TheparseFileTimeoutparameter was not adjusted for bulk footwear SKU data, and the default timeout duration is insufficient, causing parsing failure. - Symptom: After enabling the re-ranking model in the application, no retrieval results are returned, but knowledge base testing operates normally. Cause: The re-ranking parameter was only configured on the knowledge base management page, and the
rerankTopNconfiguration on the application side was not updated synchronously, causing the application to not call the re-ranking model. - Symptom: The model correctly extracts price information for footwear SKUs, but cannot complete field assignment. Cause: Units and mapping rules for fields were not explicitly specified in
fieldMappingPrompt, causing the model to fail to match the preset field format.
How to Confirm Successful Configuration
- Upload a single footwear SKU data file, view the parsed chunk content, and confirm that all preset fields are fully retained without truncation or omission.
- Trigger a manual index refresh, compare the latest data from the data source with the data in retrieval results, and confirm that the update frequency matches the preset configuration range.
- After enabling the re-ranking model, enter a search term on the application test page, view the number of retrieval results, and confirm that it matches the configured parameter range.
- View the field assignment results output by the model, and confirm that all preset fields have corresponding content, with no null values or format abnormalities.
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.