What this category of data looks like
This category of data comes from multiple types of business systems and equipment of cotton spinning, chemical fiber spinning, weaving and knitting enterprises. It includes documents such as cotton blending formulas, process setting sheets, equipment operation records, yarn inspection reports, grey fabric inspection ledgers, and defect handling records. Data sources cover raw fiber inspection results, ERP systems, real-time collected data from spinning and weaving machines, evenness testers, output information from fabric inspection machines, and order specification documents. Updates synchronize with each batch of raw material feeding, each shift’s production progress, and each piece of fabric produced. The documents include core fields such as fiber indicators, process parameters, equipment operating status, defect types and corresponding repair solutions.
What constraints these characteristics bring to the knowledge base retrieval and recall link
Multi-source heterogeneous business and equipment data require retrieval and recall to balance structured parameter matching and unstructured text retrieval, adapting to document content in different formats. Frequently updated real-time data need to support incremental synchronization mechanisms to avoid retrieving expired process parameters or equipment records. Exclusive parameters for a single batch of raw materials or a single piece of fabric require that recall results be associated with the corresponding order specification fields to avoid mixing parameters across batches. The strong association between defect records and handling solutions requires prioritizing the recall of historical handling results for the same type of defect, improving the targeting of retrieval matching.
How to set the configurations
The following configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Matches the precision requirements for defect records and process parameters. Avoids introducing irrelevant results if set too low, and missing valid historical records if set too high |
limit | Top 8 entries | Adapts to the context length limit of equipment inspection and maintenance Q&A, while covering multiple sets of handling solutions for the same type of defect |
searchMode | mixedRecall | Balances the retrieval needs of structured equipment parameters and unstructured defect text, adapting to the characteristics of multi-source data |
usingReRank | Enabled | Re-ranks initial recall results, prioritizing process parameters and defect types for the current production batch |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands retrieval terms for related process parameters and equipment models based on user questions, covering high-frequency business scenarios such as batching and twist setting |
collectionIds | Bind to the exclusive knowledge base collection for spinning and weaving | Isolates knowledge base data from other categories, avoiding retrieving unrelated dyeing or general mechanical processing documents |
Three common mistakes
- Phenomenon: The recall results work normally during knowledge base debugging, but no knowledge base reference content is returned during formal conversation. Cause: The corresponding spinning and weaving knowledge base collection is not bound in the conversation workflow, or the context injection configuration for retrieval results is not enabled.
- Phenomenon: The number of retrieval results does not match the configured
limitparameter, with too many or too few recalled entries. Cause: Thesimilaritythreshold is not set correctly, or the weight allocation between structured and unstructured data is unbalanced in hybrid retrieval mode. - Phenomenon: Retrieval results include dyeing or other category equipment documents. Cause: The exclusive knowledge base collection is not isolated, or the
collectionIdsconfiguration incorrectly introduces cross-category data.
How to confirm the configuration is correct
- Upload a single spinning process setting sheet, submit a question related to a corresponding defect, and check whether the recall results include relevant fields from this document.
- Adjust the
similarityparameter range, observe changes in the matching degree of recall results, and confirm that the threshold takes effect. - Check the retrieval node in the workflow, confirm that the specified spinning and weaving knowledge base collection is bound, and no other unrelated collections are associated.
- Submit a composite question including equipment model and defect type, verify whether
usingReRankre-ranks the results and prioritizes content with higher matching degrees.
The values provided here are common starting points and should be evaluated against the reader’s own samples.