What the Data for This Category Looks Like
Core data for this category comes from coating supplier TDS/SDS documents, spray booth and oven operation data, detection data collected by colorimeters and film thickness gauges, environmental monitoring records, and workshop MES systems. Daily documents include coating process cards, coating batch sheets, paint mixing records, film thickness and color difference reports, oven curves, defect repair sheets, and VOCs logs.
Data updates are triggered by coating batches and production shifts. Some device data is collected continuously. Fields include coating batch number, viscosity parameters, film thickness values, oven temperature nodes, VOC emission concentrations, defect types, and repair plans, among others.
What Constraints These Characteristics Impose on Knowledge Base Retrieval and Recall
Data update frequency varies across this category. Some device data is generated continuously, so incremental retrieval must be supported to avoid loading redundant historical data.
Diverse document types include structured detection values and unstructured process steps. Retrieval matching accuracy must be balanced for both content types.
Most fields relate to production compliance and quality parameters. Retrieval results must first match the current batch’s coating and equipment operation parameters, while covering VOC compliance requirements.
Bidding document and quotation preparation requires precise association of process, cost, and compliance requirements. The retrieval scope must be limited to coating-specific documents to avoid mixing irrelevant data from other categories.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | When matching coating process parameters and coating batch information, ensure the semantic overlap between retrieval results and queries meets standards, and avoid mixing irrelevant defect repair records |
limit | Top 10 entries | Bidding quotations require a balance between comprehensiveness and readability. Too many results will increase the burden of document preparation, while too few may miss key process parameters |
searchMode | mixedRecall | Coating-related documents include structured data (such as film thickness values) and unstructured text (such as process card steps). Hybrid search can cover both types of content |
usingReRank | Enabled | Similar parameters in coating-related retrieval results are easily confused. Reranking can correct sorting deviations from initial recall |
datasetSearchUsingExtensionQuery | Enabled | Bidding queries often include complex requirements, such as "spraying process for a specific batch of coating + VOC requirements". Extended queries can supplement implicit associated parameters |
collectionIds | Fill in according to the bound coating-specific knowledge base ID | Avoid retrieving documents from other categories, and ensure the retrieval scope is precise |
Three Common Errors
- Symptom: Knowledge base search response times out, and logs show vector retrieval takes more than 30 seconds. Cause: Incremental synchronization is not configured for frequently updated batch data in the coating category, and too many historical documents are loaded during full retrieval.
- Symptom: Sorting does not change after enabling
usingReRank, and returned results match the initial recall order. Cause: The reranking model’s API key or quota is not configured, so the system automatically skips the reranking step. - Symptom: VOCs log entries appear before process parameters in retrieval results, which does not align with business priority. Cause: The
similaritythreshold is not adjusted, or reranking is not enabled, and the initial recall’s semantic matching weight distribution is unreasonable.
How to Verify Correct Configuration
- Upload a latest coating batch sheet and paint mixing record, initiate a query including "spraying process parameters for this batch of coating", and check whether retrieval results include the core fields of the corresponding documents.
- Check the retrieval log to confirm that there is a call record for
usingReRank, and that the returned results’ sorting differs from the initial recall results. - Test different query terms, such as "repair plan for unqualified film thickness", "oven curve parameters", and check whether retrieval results cover category-specific documents.
- Verify that the FastGPT version is v4.17.0, and confirm that the currently configured parameters are supported and take effect in this version.
The values provided here are common starting points, and should be evaluated against the sample data relevant to the specific deployment.