What Data Looks Like for This Category
Daily documents for this category include mold design task sheets, DFM reports, part drawings, machining process cards, mold trial reports, mold modification notices, and mold history records. Data sources cover customer product models, mold flow or forming simulation files, CAD/CAM output files, machining and measurement data, and scan data of trial mold samples. Updates follow individual project cycles. New or modified documents are synced after each mold trial or modification. Individual document fields include project number, mold model, machining parameters, defect records, and more. No unified fixed units exist; units vary based on document type.
Constraints for Vector Models and Indexing
This category has diverse data sources, including binary CAD files, structured simulation results, text-based process records, and more. Vector models must support vectorization of multiple content types. Update frequencies are irregular, and single modifications cover the full cycle of an individual project. Indexes must support incremental updates to avoid the time cost of full reconstruction. Multiple document types with inconsistent fields require chunking strategies that adapt to the semantic integrity of different documents, to avoid splitting that breaks the association between machining parameters and defect descriptions. High-frequency new data generated from mold trials and modifications requires controlling index write latency to ensure timeliness of ledger summary. Unique identifiers such as mold numbers and project numbers must be indexed as metadata to enable accurate recall of all documents for a corresponding project.
Configuration Recommendations
These recommendations are based on FastGPT v4.17.0 interface parameters:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the semantic integrity of mold drawing text and mold trial report paragraphs, avoid splitting that breaks the association logic of machining parameters |
| Overlap Length | 100–150 characters | Preserve contextual association of cross-chunk mold trial defect descriptions and mold modification records, avoid semantic fragmentation |
| Similarity Threshold | 0.72–0.85 | Filter low-match irrelevant process cards and drawing fragments, reduce interference from invalid recalls on report generation |
maxToken | 4096 token | Adapt to long text vector input limits of DFM reports and mold flow simulation results, avoid truncation of long content |
| Single Recall Limit | Top 8 entries | Cover multiple types of documents for a single mold project, avoid redundant data in recall that causes redundant report generation |
| Metadata Index Toggle | Enabled | Quickly locate corresponding ledger data based on mold numbers and project numbers, improve recall accuracy |
Three Common Misconfigurations
- Symptom: When connecting an Embedding model via OneAPI, the console returns a
model not supportederror or request timeout. Cause: Call parameters for the Tongyi multi-modal vector model are not configured per OneAPI mapping rules, and the mapping relationship between model name and interface path is not set correctly. - Symptom: After enabling and configuring a reranking model, the results returned by the online recall test have the same sorting as when the reranking model is disabled, with no reordering based on relevance. Cause: The corresponding reranking model is not bound during the knowledge base indexing phase, or the single recall limit is set too high, preventing the reranking logic from triggering.
- Symptom: After selecting an open-source indexing model, when importing CAD drawing text, recall results lack structured fields such as machining parameters and defect records. Cause: Metadata indexing is not configured for structured documents; vectors are only generated for plain text content, and field association information is not retained.
How to Verify Successful Configuration
- Upload a single mold trial report, check the vector generation log, confirm that metadata fields such as mold number and mold trial times are correctly extracted and associated with the index.
- Initiate a recall test for a specific mold number, confirm that results only include documents for the corresponding project, with no cross-project redundant data.
- After enabling the reranking model, compare the sorting logic of recall results, confirm that high-relevance documents appear in expected positions.
- Test import of a long-text DFM report, confirm that no text truncation error occurs, and the vector generation process runs normally.
The values provided here are common starting points, and should be evaluated against the reader's own samples.