What Data for This Category Looks Like
Data for this category originates from steel coil labels and quality certificates, press and feeder operation logs, mold management systems, MES systems, and coordinate measuring machine or fixture inspection reports. Daily documents include stamping work instructions, material utilization rate sheets, mold inspection logs, first and last piece records, dimensional inspection reports, and mold change records. Data updates trigger with each steel coil, each production batch, and each mold change. Document fields cover material grade, mold number, production batch, dimensional deviation values, blank holder force parameters, and additional relevant fields. Supported units include millimeters, newtons, square meters, and other relevant industrial units.
Constraints Imposed on Retrieval and Recall by This Category’s Data Characteristics
This category’s data characteristics create multiple constraints for the retrieval and recall workflow. Multi-source, heterogeneous data sources require the retrieval system to support unified vector mapping across systems, to avoid recall failure from field mismatches. High-frequency, decentralized update cycles demand incremental synchronization mechanisms, to ensure new data from each mold change or production batch is included in the retrieval scope in a timely manner. Diverse specialized document types and dedicated fields require optimized chunking and vector modeling for stamping-specific terminology such as drawbeads and springback, to improve recall accuracy for specialized content. Offline deployment requirements in production scenarios also demand that the retrieval link does not rely on external public services.
Configuration Settings
The following configuration guidance is written for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
similarity | 0.75–0.85 | Stamping scenarios have many specialized terms, so this range filters low-relevance results while balancing recall coverage and accuracy |
limit | Top 8–12 results | The number of documents associated with a single production batch falls within this range. Too many results increase context load, while too few risk missing critical parameters |
searchMode | mixedRecall | Balances semantic matching for specialized terms and exact matching for structured fields, to accommodate the multi-type content of stamping documents |
usingReRank | Enabled | Stamping scenarios have many similar terms such as cracking and cracks, so re-ranking can further filter low-quality recall results |
datasetSearchUsingExtensionQuery | Enabled | User defect descriptions such as “fender cracking” can be expanded to include specialized queries for mold numbers and material grades, improving recall accuracy |
collectionIds | Bind to the dedicated knowledge base collection for the stamping workshop | Isolates document data across production workshops, to avoid interference from unrelated cross-workshop content during retrieval |
Three Common Misconfiguration Issues
- Observation: When deployed offline, uploaded knowledge base files remain in a loading state indefinitely. The upload process resumes normally only after connecting to the internet. Cause: Some FastGPT dependency packages must be pulled from public code repositories. Offline environments lack pre-provisioned dependencies, causing initialization blocking.
- Observation: Semantic retrieval fails to return specialized documents, while full-text retrieval returns matching results normally. Cause: Custom extended queries for stamping-specific terminology are not enabled, so the semantic model is not adapted to industry-specific vocabulary.
- Observation: The number of retrieval results does not match the configured parameters, with empty results or results exceeding the preset limit. Cause: The dedicated knowledge base collection ID is not correctly bound, so the retrieval scope covers unrelated collections, leading to abnormal behavior.
How to Verify Correct Configuration
- A single stamping work instruction may be uploaded to trigger a retrieval test, and returned results can be verified for inclusion of specialized parameters and process descriptions from the document.
- An offline deployment environment may be simulated, a test document uploaded, and confirmation obtained that the retrieval link operates normally without accessing external public services.
- The similarity parameter range may be adjusted, the number of recall results compared across different ranges, and alignment confirmed with the accuracy requirements of the business scenario.
- After binding the dedicated collection ID, a retrieval query including a mold number may be run, and confirmation obtained that only mold management documents from the corresponding workshop are returned.
The values provided here are common starting points, and should be evaluated against applicable production samples.