What the data for this category looks like
Daily business data sources for cotton spinning, chemical fiber spinning, woven and knitted enterprises include raw fiber inspection reports, ERP systems, spinning and loom operation logs, evenness tester detection data, fabric inspection machine records, and order specification documents. Data updates trigger with business nodes: update cotton blending or batching lists when each batch of raw materials arrives, update equipment operation records for each shift’s production, and update yarn or grey fabric inspection and defect records when each bolt of fabric is produced. Daily documents include structured process setup sheets, batching lists, unstructured inspection logs, and defect descriptions. Fields cover fiber indicators, process parameters, inspection values, and more. Units vary based on indicator type.
What constraints these characteristics impose on knowledge base retrieval and recall
Frequently updated business data requires the knowledge base to support incremental indexing and incremental recall. This avoids performance loss from full scans. Documents with multiple types and sources need adapted retrieval strategies. Structured process sheets must retain all parameter fields. Unstructured defect records need precise keyword matching. Key information in inspection and audit links directly ties to product quality. Retrieved results need high semantic matching accuracy. The retrieval scope must strictly limit to spinning and weaving exclusive business data. This prevents mixing irrelevant documents from other categories.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Match the semantic accuracy needs of spinning process parameters and defect descriptions, filter low-correlation historical records |
limit | Top 10 entries | Control the number of results per retrieval, align with the context length limit of single-batch inspection and audit |
usingReRank | Enabled | Optimize ranking for short or structured text like defect records and process parameters, boost recall priority for key information |
datasetSearchUsingExtensionQuery | Enabled | Expand retrieval scope using business keywords. For example, link "yarn strength" to "cotton blending indicators" and "twist parameters" |
collectionIds | Spinning/weaving exclusive collection ID | Restrict retrieval to the current category’s knowledge base collection, avoid cross-category irrelevant document recall |
Three Common Misconfigurations
- Retrieval response time exceeds 40 seconds: Incremental indexing is not configured for the high-frequency knowledge base updated per raw material batch and shift. Full retrieval scans too many historical batch document datasets.
- Imported long text documents or QA pairs fail to store: Chunking parameters are not adjusted to match the actual length of cotton blending lists and process setup sheets. Text over the preset length cannot be imported.
- Retrieval results include dyeing and finishing documents: The retrieval scope is not limited to the spinning and weaving exclusive knowledge base collection via
collectionIds. This causes cross-category recall of irrelevant business data.
How to Confirm Proper Configuration
- Initiate a retrieval for "yarn strength unqualified". Check if returned results include matching business documents such as cotton blending lists, equipment operation records, and defect records.
- Import a process setup sheet with 1500 characters. Confirm no import errors occur and the full text is retained.
- Review retrieval logs. Confirm only the spinning and weaving exclusive knowledge base collection is scanned, with no documents from other categories included.
- Test retrieval response time. Confirm it meets the real-time retrieval performance standards for FastGPT v4.17.0.
The values provided here are common starting points and should be evaluated against the reader's own samples.