Python: Weaviate vector store #9101
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TaoChenOSU
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Oct 14, 2024
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| for vector in data_model_definition.fields.values(): | ||
| if isinstance(vector, VectorStoreRecordVectorField): | ||
| named_vectors.append( | ||
| Configure.NamedVectors.none( | ||
| name=vector.name, | ||
| vector_index_config=to_weaviate_vector_index_config(vector), | ||
| ) | ||
| ) |
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Should we return named_vectors collection from this method after we populate it with vector-related info? Based on the usage of this method vectorizer_config=data_model_definition_to_weaviate_named_vectors(self.data_model_definition) it looks like it should return something, but it doesn't have a return statement.
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| case DistanceFunction.COSINE: | ||
| return "cosine" | ||
| case DistanceFunction.DOT_PROD: | ||
| return "dot" | ||
| case DistanceFunction.EUCLIDEAN: | ||
| return "l2-squared" | ||
| case DistanceFunction.MANHATTAN: | ||
| return "manhattan" |
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There is also hamming distance function: https://weaviate.io/developers/weaviate/config-refs/distances#available-distance-metrics
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Motivation and Context
Add Weaviate DB to Semantic Kernel with the new vector store and vector collection interfaces.
Address: #6553
Description
Contribution Checklist