What the data for this category looks like
Data sources for this category include ERP material master data, melting furnaces and thermometers, spectrometers, MES heat records, mold management systems, customer drawings and technical specifications. Update frequencies cover per heat, per batch, and daily. Daily documents include foundry process cards, batching lists, heat records, mold histories, first-piece inspection records, material reports, and nonconforming product review forms. Fields include heat number, alloy composition percentage, pouring temperature, mold cycle, defect type, and more. Units include professional measurement standards such as ppm, ℃, and tons.
How These Characteristics Impact Knowledge Base Retrieval and Recall
High-frequency data updates require the knowledge base to support incremental synchronization. This avoids recalling expired heat or batching records. Multi-source heterogeneous document formats and specialized fields require retrieval matching to accurately align with professional terms such as alloy proportions and defect types. This prevents invalid results from generalized matching. The business need to associate multiple ledgers with a single heat means recall results must cover multi-dimensional content like batching, temperature, and mold history. It also requires controlling context length to stay within processing limits.
How to Configure Settings
Choose a retrieval mode through representative-query testing; configure category, batch, or entity filters separately because the mode itself does not enforce those boundaries.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.85–0.92 | Matches precision requirements for foundry professional terms, avoiding irrelevant melting or mold records with low matching scores |
limit | Top 8 entries | Covers multi-dimensional records related to a single heat, while controlling total context length |
usingReRank | Enabled | Re-ranks initial recall results by professional semantics, optimizing ranking for defects like shrinkage cavities and porosity |
datasetSearchUsingExtensionQuery | Disabled | Prevents automatically expanded general semantics from interfering with precise matching of professional terms |
collectionIds | Bound to dedicated foundry knowledge base collections | Isolates documents from other categories, ensuring recall only draws from foundry ledger data |
Three Common Mistakes
- Retrieval results include documents from non-foundry categories. The cause is failure to bind the specified
collectionIds, leading the retrieval scope to cover content from other knowledge bases. - Retrieval results do not fully match the original knowledge base responses. The cause is a
similaritythreshold set too low, ordatasetSearchUsingExtensionQuerybeing enabled, leading to semantic drift. - Batching and temperature records for a single heat cannot be recalled simultaneously. The cause is a
limitvalue set too low, failing to cover retrieval results for multiple ledger types associated with a single heat.
How to Verify Proper Configuration
- Use the FastGPT v4.17.0 interface, upload a test foundry heat record, enter an accurate query term, and confirm recall results only include content from this knowledge base.
- Adjust the
similaritythreshold, verify changes in recall matching accuracy across different thresholds, and confirm alignment with business requirements. - Enable
usingReRank, compare result rankings before and after re-ranking, and confirm records related to defects and batching have improved priority. - Check the binding status of the knowledge base collection, confirm only dedicated foundry documents are included in the retrieval scope.
The values provided are common starting points and should be measured against the reader's own samples.