What the data for this category looks like
The primary entities in this category are cotton spinning, chemical fiber spinning, woven, and knitted fabric enterprises. Daily documents include cotton blending lists, process setup sheets, equipment operation records, yarn and grey fabric inspection reports, and defect logs. Data sources cover raw fiber inspection data, ERP systems, real-time spinning and weaving machine data, evenness testers, fabric inspection machine test results, and order specification documents. Data updates sync with each batch of raw materials, each shift’s production, and each piece of fabric produced. Document fields include fiber indicators, process parameters, equipment operation values, inspection thresholds, defect types, and more. Units use textile-specific measurements such as yarn count, twist, centimeter, and gram weight.
Constraints imposed on knowledge base retrieval and recall by these data characteristics
The data characteristics of this category create multiple constraints for the knowledge base retrieval and recall process. Multi-source heterogeneous data sources, including offline inspection reports, real-time equipment data, and business system documents, require retrieval to support unified indexing and associated recall of cross-source data. The high-frequency update rhythm, syncing with each batch of raw materials, each shift’s production, and each piece of fabric produced, requires the retrieval pipeline to adapt to rapid incremental data synchronization, and avoid returning outdated process or inspection information. Documents contain textile-specific parameters such as yarn count, twist, and gram weight. Field precision must be preserved to prevent matching deviations caused by semantic generalization. Defect records are strongly bound to processes and equipment. Recall results must link to original data from corresponding links, and avoid returning isolated single pieces of information.
The following configurations are adapted for FastGPT v4.17.0.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.85 | This category has high parameter precision requirements. Filter low-match non-professional content, and retain highly relevant textile-specific documents |
limit | Top 8–12 results | Process parameters and defect types for a single production batch are limited. Too many results increase context redundancy and reduce audit efficiency |
searchMode | mixedRecall | Balance semantic matching of textile-specific terminology and precise field matching. Avoid missing precise parameter matching results that rely solely on vector retrieval |
usingReRank | Enabled | Recall results must be reordered by business relevance, and prioritize content directly related to processes and inspections |
datasetSearchUsingExtensionQuery | Enabled | User quality audit queries can be expanded to include process parameters, improving matching accuracy in textile professional scenarios |
collectionIds | Knowledge base collections divided by business domain | Support permission partitioning by supplier and production team, isolate audit data across different departments, and meet permission control requirements |
Three common configuration errors
- Phenomenon: Retrieval results return a large volume of non-textile professional content, such as general chemical formulas. Cause: The
similaritythreshold is not set, or the threshold is set too low, failing to filter low-match irrelevant documents. - Phenomenon: When batch uploading inspection reports in docx or pdf format, some fields such as twist and yarn count are not correctly parsed. Cause: The document structured parsing switch is not enabled, or extraction rules for textile-specific fields are not configured.
- Phenomenon: Auditors cannot retrieve historical inspection data for the corresponding supplier. Cause: Business domain knowledge bases are not divided by
collectionIds, leading to unisolated cross-domain permissions or data not linked to the corresponding supplier collection.
How to verify correct configuration
- Upload a batch of cotton blending lists and defect records, initiate a query for "process parameters corresponding to this batch of raw materials", and check whether the returned results include the corresponding fiber indicators and process setup sheet content.
- Switch
collectionIdsacross different business domains, and verify that users with different permission roles can only access knowledge base data for the corresponding supplier. - After enabling
usingReRank, compare the result order before and after reordering, and confirm that highly relevant process and inspection data is returned first. - Submit a query containing textile-specific terminology, and verify that
datasetSearchUsingExtensionQueryautomatically expands relevant parameter descriptions to expand the matching scope.
The values provided are common starting points and should be measured against the reader's own samples.