feat: add HFresh vector index type support (#285)#289
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robbespo00
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Add VectorIndex.HFresh as a first-class vector index configuration type, matching feature parity with the Python client (PR weaviate-python-client#1848). HFresh is an inverted-list-based ANN index introduced in Weaviate 1.36. Vectors are distributed across posting lists (Replicas) and queries probe SearchProbe lists for candidates. Supports RQ quantization and multi-vector configurations. MaxPostingSizeKb can be left unset for server-computed sizing. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
… for HFresh Improve HFresh vector index test coverage: - Add test verifying MultiVector config survives serialize/deserialize roundtrip - Add test verifying BQ quantizer throws WeaviateClientException (only RQ supported) - Add test verifying HFresh deserialization with full named vector fields and RQ quantizer Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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dirkkul
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Summary
VectorIndex.HFreshas a first-class vector index configuration type, providing feature parity with the Python client (PR #1848)HFreshDto, bidirectionalToHFresh()/ToDto()mappings, factory dispatch, andSerializeHFresh/DeserializeHFreshhelpersPublicAPI.Unshipped.txtwith all 24 new public symbols (Roslyn RS0016 clean)HFresh Parameters
MaxPostingSizeKbmaxPostingSizeKBReplicasreplicasSearchProbesearchProbeDistancedistanceVectorDistanceenumQuantizerrqMultiVectormultivectorTest Plan
dotnet build -warnaserror— 0 errors, 0 warningsCloses #285
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