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feat: add distance scores to dense search results - #101
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Pinned toolchain version to 1.98.1 |
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| assert_eq!(results.len(), 1); | ||
| assert_eq!(results[0], ids[0]); // The first vector should be closest | ||
| assert_eq!(results[0].0, ids[0]); // The first vector should be closest |
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I think we should assert the similarity score also here
| assert_eq!(results.len(), 2); | ||
| assert_eq!(results[0], id1); // Closest | ||
| assert_eq!(results[1], id2); // Second closest | ||
| assert_eq!(results[0].0, id1); // Closest |
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should probably assert distance here as well
| assert_eq!(results[0], id1); | ||
| assert_eq!(results[1], id2); | ||
| assert_eq!(results[0].0, id1); | ||
| assert_eq!(results[1].0, id2); |
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should assert distance here as well
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Summary
Search results now return a distance score alongside each point ID (lower = closer).
Changes
VectorIndex::searchreturns(PointId, distance)pairs, updated Flat, KD-tree and HNSWsearch/batch_searchreturn(point_id, score)tuples