SearchModelFactory.VectorSearchCompression Method
Definition
Important
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Contains configuration options specific to the compression method used during indexing or querying. Please note this is the abstract base class. The derived classes available for instantiation are: ScalarQuantizationCompression and BinaryQuantizationCompression.
public static Azure.Search.Documents.Indexes.Models.VectorSearchCompression VectorSearchCompression(string compressionName = default, Azure.Search.Documents.Indexes.Models.RescoringOptions rescoringOptions = default, int? truncationDimension = default, string kind = default);static member VectorSearchCompression : string * Azure.Search.Documents.Indexes.Models.RescoringOptions * Nullable<int> * string -> Azure.Search.Documents.Indexes.Models.VectorSearchCompressionPublic Shared Function VectorSearchCompression (Optional compressionName As String = Nothing, Optional rescoringOptions As RescoringOptions = Nothing, Optional truncationDimension As Nullable(Of Integer) = Nothing, Optional kind As String = Nothing) As VectorSearchCompressionParameters
- compressionName
- String
The name to associate with this particular configuration.
- rescoringOptions
- RescoringOptions
Contains the options for rescoring.
The number of dimensions to truncate the vectors to. Truncating the vectors reduces the size of the vectors and the amount of data that needs to be transferred during search. This can save storage cost and improve search performance at the expense of recall. It should be only used for embeddings trained with Matryoshka Representation Learning (MRL) such as OpenAI text-embedding-3-large (small). The default value is null, which means no truncation.
- kind
- String
Type of VectorSearchCompression.
Returns
A new VectorSearchCompression instance for mocking.
