What the data for this category looks like
Data for apparel and home textile market trends and yield rates comes from three sources: domestic public market databases for the textile and apparel industry, real-time quotes from fabric spot trading platforms, and brand terminal sales ledgers. There are two update schedules. Fabric raw material data updates every hour. Sales and inventory data for terminal home textile products updates daily. The data uses structured JSON format, with fields including product SKU code, raw material unit price, terminal supply price, per-unit/per-set cost, monthly revenue, and inventory surplus. The units for each field are as follows: raw material unit price: yuan/kilogram, terminal supply price: yuan/item, cost: yuan/item, revenue: yuan, inventory surplus: items.
Constraints on forms and interactions from these characteristics
This category’s data sources include high-frequency raw material data and low-frequency terminal sales data. Form interactions must support time granularity switching configuration. This adapts to data pulling from sources with different update schedules. Fields in this data use multiple unit types. The form must include built-in automatic unit matching logic. This prevents calculation errors caused by mixed units across categories. Data is split by SKU granularity. The form must support batch import of SKU codes. This accommodates multi-SKU query requirements. Document structures vary across different data sources. The interaction interface must provide a field mapping configuration entry. This matches JSON structures from different sources. Multiple industry standards exist for field naming in this category. Form interactions must support custom field mapping. This prevents extraction failures caused by inconsistent field names.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
batch_input_max_count | 50-200 items per batch | The apparel and home textile category has a large number of SKUs. Batch imports per session avoid frequent API requests and accommodate batch query needs |
unit_auto_match_switch | Enabled | This category uses multiple unit types. Automatic matching reduces manual adjustment costs and prevents calculation errors caused by mixed units |
jsonPath_extract_rule | Match by field prefix | JSON structures vary across different data sources. Prefix matching accommodates variable extraction from multiple source datasets |
request_timeout | 600 seconds | Raw material data APIs have high response latency. This duration covers the full pull cycle and prevents request timeouts |
custom_input_component_switch | Enabled | Built-in controls cannot cover the complex interaction requirements of batch SKU imports. Enable custom controls to adapt to category scenarios |
response_var_pass_mode | Map by field name | Extracted variables must be passed accurately to downstream nodes. This prevents runtime errors in downstream nodes caused by variable name conflicts |
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. Each situation requires specific analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: After an HTTP request returns data, variables received by downstream nodes are empty. Cause: No precise matching rule is configured for
jsonPath_extract_rule, or the extraction path does not match the JSON structure of the data source. Multiple industry standards exist for field naming in the apparel and home textile category, so path deviations are common. - Symptom: The number of knowledge base retrieval results is abnormally low, and no matching market trend data is returned. Cause: The maximum number of inputs per batch is not restricted. Excessively long input text exceeds the knowledge base’s context threshold, leading to failed retrieval matching.
- Symptom: The custom input component does not take effect, and the form still uses built-in controls. Cause: The
custom_input_component_switchconfiguration item is not enabled, or the interaction logic for corresponding SKU imports is not bound. This means the requirement for batch SKU entry in the apparel and home textile category cannot be met.
How to confirm correct configuration
- Initiate a test request for a single SKU. Check whether variables from returned data are correctly passed to downstream nodes. Verify whether the matching result of
jsonPath_extract_rulemeets expectations. - Import batch SKU codes. Confirm that the number of submitted requests matches the number of items imported per batch. Verify that the
batch_input_max_countconfiguration is effective. - Adjust the value of
request_timeout. Simulate a high-frequency raw material data pulling scenario. Confirm that no request timeout errors are triggered. - Enable the custom input component. Test the batch SKU entry interaction. Confirm that the component functions meet the input requirements of category data.
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.