What Data for This Category Looks Like
Data for this category primarily comes from BOMs, Gerber files, and coordinate files provided by clients, plus data from on-site MES systems, solder paste and component batch records, placement machines, SPI/AOI testing equipment, and reflow oven temperature collection systems. Daily documentation includes BOMs and coordinate files, line change sheets, stencil and furnace temperature records, first article confirmation reports, SPI/AOI testing reports, maintenance records, and traceability labels. Data is updated in real time per work order and each line change. Document fields include part numbers, reference designators, component specifications, coordinate positions, defect types, batch numbers, and other items. Some documents include units such as millimeters and degrees Celsius.
Constraints Imposed on Vector Models and Index Workflow by These Characteristics
The data characteristics of this category impose multiple constraints on the vector model and index workflow. High-frequency real-time updated work order and line change data requires indexes to support incremental synchronization, to avoid performance losses caused by full reconstruction. Multiple types of documents coexist: structured BOMs, semi-structured testing reports, and unstructured line change records. This requires vector models to adapt to text features of different formats. Document fields include unit-bearing information such as part numbers, reference designators, coordinates, and temperatures. Indexes must retain field metadata to prevent incorrect associations caused by unit confusion during matching. The volume of data associated with a single work order increases with complexity. A single retrieval must process a large number of documents, which places requirements on the recall efficiency of indexes. Incorrect associations can trigger batch material misplacement or solder joint failures. This requires the accuracy of retrieval results to meet business verification standards.
How to Set Configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Most documents for this category include structured fields and long text descriptions. Excessively long chunks will lose local associations, while excessively short chunks will damage field integrity. |
| Overlap Length | 100–200 characters | Documents such as BOMs and coordinate files have tightly linked fields. Overlapping chunks preserve cross-block field context. |
| Similarity Threshold | Calibrated via actual testing | Retrieval for this category requires matching precise fields such as part numbers and reference designators. The threshold must be adjusted in combination with business verification logic. |
| Single Search Limit | Top 10 results | The volume of documents associated with a single work order is moderate. Too many results increases re-ranking time, while too few results will miss critical information. |
| Re-ranking | Enabled | When retrieving mixed document types, re-ranking filters irrelevant results and improves matching accuracy. |
maxToken | Set to the selected embedding model/service maximum supported input tokens | maxToken is the input-token maximum supported by the selected embedding model/service; verify it in that provider configuration. See the v4.17.2 model-field reference. It is not retrieval/LLM context or a FastGPT-wide fixed cap. |
Three Common Misconfigurations
- Symptom: The interface displays a prompt that no available channels are available when configuring Qwen text-embedding-v3. Cause: Access permissions for the corresponding embedding model are not enabled in the group configuration, or the forwarding configuration does not correctly associate the model's API path.
- Symptom: Retrieval takes too long after re-ranking is enabled, and the interface shows a timeout status. Cause: The chunk length is set too long, or the single search limit is set too high, causing the re-ranking stage to process an excessive number of document fragments.
- Symptom: Matching items that confuse part numbers and coordinates appear in retrieval results. Cause: The index configuration does not retain field metadata, or the similarity threshold is set too low, causing vector matches for irrelevant fields to be incorrectly identified as valid.
How to Confirm Proper Configuration
- Import a typical document set for a single work order, run a retrieval test, and verify that the returned results include associated documents for the corresponding part numbers and reference designators.
- Check the index synchronization logs to confirm that incremental update tasks are triggered per work order and line change event, with no abnormal records of full reconstruction.
- Adjust the similarity threshold, compare retrieval results across different thresholds, and confirm that matching results meet business verification logic.
- Test the embedding model call link to confirm no interface errors or timeout prompts.
The values provided are common starting points and should be evaluated against local samples.