What Data for This Category Looks Like
The business data for metal material processing is primarily sourced from general industry standard manuals, internal enterprise production process cards, quality inspection reports, and metal grade performance databases. Data sources include national steel and non-ferrous industry standards, as well as enterprise research and development and production records. Updates are triggered irregularly alongside industry standard revisions and enterprise process adjustments. Most documents are structured by metal grade, with fields including composition proportion, mechanical properties, hot working temperature, cutting parameters, and defect repair solutions. Units used include professional industrial units such as MPa, mm, ℃, and %.
Constraints on Knowledge Base Retrieval and Recall
Metal material processing use cases have dense professional terminology, high parameter precision requirements, and most data fields are quantitative indicators. Semantic retrieval must accurately match professional expressions such as composition and process terms. The multi-grade document structure requires retrieval to filter and recall results by grade dimension, to avoid confusion of cross-grade parameters. Unit consistency for quantitative fields requires automatic association of unit information during retrieval, to prevent incorrect recall caused by unit mismatches. Additionally, most on-site production inquiries relate to real-time process adjustments. Retrieval response speed must align with on-site decision-making rhythms, to avoid delayed business progress from excessive waiting times.
Configuration Settings
This configuration is optimized for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets professional terminology precision requirements for metal material processing, filters low-relevance non-grade results |
limit | Top 10 entries | Covers multi-dimensional parameter needs for common process issues, while avoiding excessive results that exceed context length limits |
usingReRank | Enabled | Performs secondary sorting of initially recalled results by process relevance, correcting biases from single semantic similarity scores |
searchMode | Semantic retrieval | Adapts to semantic matching needs for professional terminology, resolving the rigid matching issues of keyword retrieval |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands synonyms for process-related questions, such as expanding "quenching" to "heat treatment quenching process" to cover professional expression variants |
collectionIds | Specify the collection ID of the corresponding metal material processing knowledge base | Restricts retrieval scope to avoid mixing document data from other categories |
Three Common Misconfigurations
- The interface shows a semantic retrieval score higher than 0.9, but results include irrelevant non-metallic material parameters. This occurs because
collectionIdsis not configured to limit the retrieval set, leading to recall of document data from other categories. - After enabling the reranking model, only 1 result is retained when finally input to the large model. This occurs because the post-reranking result truncation rule is incorrectly set, failing to retain sufficient multi-dimensional reference parameters.
- Single question response waiting time exceeds 15 seconds. This occurs because batch recall quantity for retrieval is not optimized, and vector index caching for the dataset is not enabled, causing vector similarity to be recalculated for each retrieval.
How to Verify Correct Configuration
- Submit an inquiry question including a specific metal grade and process parameters, and confirm recalled results only contain document data from the metal material processing category.
- View the similarity score distribution of retrieval results, and confirm the score interval matches the configured
similaritythreshold requirement. - Test submitting the same question repeatedly three or more times, and confirm response time stays within a reasonable range.
- After enabling the reranking function, check whether sorted results prioritize matching the core process requirements of the inquiry.
These values are common starting points, and should be evaluated against the user’s own specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.