What the data for this category looks like
Typical entities in this category are garment OEM/ODM providers, brand supply chains, and cutting and sewing workshops. Daily generated documents include process sheets, patterns, layout plans, cutting orders, first sample seals, process quality sheets, and packaging and size matching documents. Data sources cover orders and size charts, CAD patterns, fabric and accessory inspection, hanging systems, needle detectors, and customer sample seals. Updates occur per order, per style, and per batch. This category has traits including a large number of styles, strong seasonality, irreversible fabric cut pieces, labor-intensive processes, and clear differences from the main textile fabric category.
Constraints Imposed by These Traits on Source Citation and Traceability
The category’s frequently updated order, style, and batch data require the citation and traceability link to support real-time synchronization of latest documents such as process sheets and layout plans. The traits of irreversible fabric cut pieces and labor-intensive processes require traceability to accurately bind specific batch fabric and accessory inspection records, cutting process records, and first sample seal records. This avoids traceability deviations caused by fuzzy matching. The attribute of multiple seasonal styles requires the traceability link to quickly filter related documents by order and style number. It also needs to adapt to matching logic for multiple field types including process quality sheets and packaging and size matching documents. This ensures that verification data for corresponding links can be quickly located during audits.
Configuration Settings
This configuration is based on FastGPT v4.17.0, and is adapted for the audit scenario of the garment cutting and sewing category. The following are specific configuration items and their basis:
| Configuration Item | Recommended Setting | Basis for This Setting |
|---|---|---|
quoteMaxToken | 800–1200 token | Documents for this category are mostly process sheets, layout plans, and similar materials. The length of a single cited content should not be too long, to avoid context overflow that affects audit logic |
responseData | Enabled | Associated document metadata must be returned in audit results, to facilitate verification of the match between process data submitted by suppliers and standard processes in the knowledge base |
detail | Full | This category requires traceability of data from multiple links including cutting, sewing, and inspection. Full details cover content from multiple types of documents such as process quality sheets and needle detector records |
| Single search limit | Top 6 entries | The number of documents associated with a single order in this category is moderate. Too many citations will interfere with core audit logic, while too few will fail to cover all key process data |
| Maximum context | 4000–6000 characters | It needs to carry order information, process requirements, and multi-link inspection data at the same time, to avoid loss of key information caused by context truncation |
Three Common Mistakes
- The symptom is that the cited document list is displayed on the debug page, but the cited document field is empty on the official chat page. The cause is that the
responseDataconfiguration item is not enabled, or the configuration is not associated with the conversation output module. - The symptom is that the number of returned cited documents does not meet expectations, and cannot be fixed to the specified number. The cause is that the score threshold is mistakenly used as the basis for the number limit, and the configuration is not adjusted correctly to match the document quantity characteristics of the category.
- The symptom is that the text content extraction component cannot extract content from knowledge base citations. The cause is that the output of the knowledge base citation module is not connected to the input source of the text extraction component, or the component is not adapted to the content extraction logic for multiple types of process documents.
How to Confirm the Configuration Is Correct
- Submit an audit request for a specific garment cutting process, check whether the returned results include metadata of associated documents such as process sheets and layout plans, to confirm that the configuration takes effect.
- Check the token count of returned citations, adjust the value of
quoteMaxTokento the range that matches the current document length, to ensure no content truncation. - Test queries for different orders and style numbers, confirm that related documents can be quickly filtered by order and style number, to verify that the context configuration adapts to the multi-document scenario of the category.
- Connect the text extraction component, try to extract fields such as process numbers and size requirements from the content of knowledge base citations, to confirm that the component can normally read the cited content.
The values provided are common starting points and should be evaluated against the reader's own samples.