What this category of data looks like
Data for this category comes from dyeing, setting, laboratory and quality departments of dyeing and finishing factories. It includes dyeing formulas, chemical feeding records, dye vat operation curves, sample confirmation sheets, color difference reports, setting process sheets, sewage ledgers, and other documents. Data sources cover customer color samples, formula libraries, dye chemical batch records, dye vat control systems, colorimeters, setting machine parameters, and environmental monitoring data. Data updates occur once per vat, per batch, or per shift. Document fields include process parameters, batch numbers, test values, emission indicators, and other items. Units involve temperature, concentration, weight per unit area, pH value, and more.
Constraints on knowledge base retrieval and recall from these characteristics
High-frequency updates at the vat and batch levels require knowledge base retrieval and recall to support near-real-time incremental synchronization. This prevents the return of expired process parameters. Multiple document types cover time-series curves, numerical reports, and ledger records. Retrieval rules must adapt to different formats of text and structured data. Documents contain diverse unit fields such as temperature, concentration, pH value, and weight per unit area. Retrieval must match parameter units to avoid cross-unit matching failures. Batch number is the core associated field. Retrieval logic must bind the current production batch to ensure recalled results accurately correspond to the current task.
How to set configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Match the precision requirements for dyeing process parameters, avoid recalling irrelevant batch data |
limit | Top 8 entries | Cover core parameters of a single vat process and associated exception reports, control context length, reduce hard disk and memory consumption |
usingReRank | Enabled | Re-rank structured data such as dye vat curves and color difference reports to improve precise matching accuracy |
searchMode | mixedRecall | Balance semantic matching of process parameters and precise keyword matching of batch numbers |
datasetSearchUsingExtensionQuery | Enabled | Expand query scope to associate and match data related to customer color samples and current dyeing formulas |
collectionIds | Divided by production workshop/product line | Limit retrieval scope, reduce invalid recalls of cross-workshop data |
Three common misconfigurations
- Phenomenon: Retrieval returns dye vat curves or color difference reports from non-current batches. Cause: Failed to limit retrieval scope via
collectionIds, or set thesimilaritythreshold too low, resulting in recall of expired or irrelevant production data. - Phenomenon: Returns vague answers even when the knowledge base has no matching content. Cause: Failed to configure empty result intercept logic, or did not correctly set the
similaritythreshold to filter invalid recall results. - Phenomenon: Incomplete retrieval result content output. Cause: Failed to enable
usingReRank, set an overly highlimitvalue leading to context overflow, or did not adapt segment processing to the time-series segment rules of dye vat curves.
How to verify correct configuration
- Submit a query for a single vat dyeing process. Check whether the recalled results include the current batch's dyeing formula and chemical feeding records. Confirm whether the
collectionIdsscope matches the current production scenario. - Input an exception scenario query outside the knowledge base scope. Check whether the system only returns empty results or clearly prompts no matching content. Verify the empty result intercept configuration.
- Import a segment of dye vat time-series curve data. Check whether the recalled results include rearranged key temperature and feeding node data after retrieval. Verify the configuration effect of
usingReRank. - Submit 10 consecutive queries for the same batch. Check whether the retrieval response time is stable. Verify the rationality of the indexing and incremental synchronization strategy.
The configuration values provided are common starting points. They should be evaluated against the samples used in the specific deployment.