What data for this category looks like
The typical entities in this category are cotton spinning, chemical fiber spinning, woven fabric, and knitted fabric enterprises. Daily documents include cotton blending batching lists, process setup sheets, equipment operation records, yarn inspection sheets, grey fabric inspection sheets, defect records, and similar items. Data sources include raw fiber inspection reports, ERP systems, real-time data from spinning and weaving looms, data collected by evenness testers and fabric inspectors, and order specification documents. Data update frequency changes based on raw material batches, team shifts, and fabric piece counts. Individual documents contain fields such as fiber indicators, process parameters, inspection values, and equipment numbers, with some fields having clear units of measurement.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
Data sources for this category are scattered and updated frequently, so the knowledge base retrieval system must support real-time or near-real-time incremental synchronization. Document types cover structured process parameters and unstructured inspection records, so the system must support both exact numerical matching and semantic text retrieval. The update logic differs for single raw material batches, per-shift equipment, and per-piece fabric, so knowledge base collections must be divided by update dimension to avoid data confusion. Tender document and quotation preparation requires precise matching of process parameters and inspection results. The relevance of retrieval results directly affects quotation accuracy and tender pass rate, so recall accuracy requirements are relatively high.
How to configure the system
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Process parameters and inspection data for spinning and weaving require high matching accuracy to avoid retrieving irrelevant content |
limit | Top 8–12 results | Individual documents for this category have moderate length; too many retrieved results will exceed the context window limit |
searchMode | mixedRecall | Must match both structured numerical fields and unstructured text content, covering multiple document types including cotton blending, process, and inspection records |
usingReRank | Enabled | Unstructured text such as defect records and inspection reports requires secondary ranking to improve relevance sorting accuracy |
datasetSearchUsingExtensionQuery | Enabled | Tender quotations need to link order specifications and process parameters; extended queries can cover more associated fields |
collectionIds | Bind to dedicated knowledge base collections for spinning and weaving | Isolate data from other categories to avoid mixing irrelevant documents that impact retrieval results |
Three common configuration errors
- Issue: A large number of dyeing and finishing, garment-related documents unrelated to spinning and weaving appear in retrieval results. Cause: The
collectionIdsparameter is not configured to bind the dedicated knowledge base collection, resulting in mixing datasets from other categories. - Issue: Single retrieval takes more than 10 seconds, and the interface shows loading delays. Cause: The
limitparameter is not set reasonably, and retrieving too many documents increases the time consumed by embedding calculation and reranking steps. - Issue: Structured numerical data such as imported fiber fineness and twist values cannot be retrieved accurately, and only irrelevant inspection record texts are matched. Cause: The
searchModehybrid retrieval mode is not enabled; using only semantic retrieval cannot match exact numerical fields.
How to confirm the configuration is correct
- Log in to the FastGPT v4.17.0 backend, navigate to the knowledge base configuration page, and confirm that
collectionIdspoints to the dedicated document set for spinning and weaving. - Enter a known process setup sheet parameter to initiate a retrieval, and check whether the returned results prioritize matching documents related to this parameter.
- Enter keywords from defect records, review the ranking of retrieval results, and confirm that results with higher relevance are ranked first after
usingReRankis enabled. - Initiate multiple repeated retrievals, confirm that the time consumption remains within a reasonable range with no obvious fluctuations.
The values provided here are common starting points and should be evaluated against the user's own samples.