ScalarQuantizationCompression interface

Contains configuration options specific to the scalar quantization compression method used during indexing and querying.

Extends

Properties

kind

Polymorphic discriminator, which specifies the different types this object can be

parameters

Contains the parameters specific to Scalar Quantization.

Inherited Properties

compressionName

The name to associate with this particular configuration.

defaultOversampling

Default oversampling factor. Oversampling will internally request more documents (specified by this multiplier) in the initial search. This increases the set of results that will be reranked using recomputed similarity scores from full-precision vectors. Minimum value is 1, meaning no oversampling (1x). This parameter can only be set when rerankWithOriginalVectors is true. Higher values improve recall at the expense of latency.

rerankWithOriginalVectors

If set to true, once the ordered set of results calculated using compressed vectors are obtained, they will be reranked again by recalculating the full-precision similarity scores. This will improve recall at the expense of latency.

Property Details

kind

Polymorphic discriminator, which specifies the different types this object can be

kind: "scalarQuantization"

Property Value

"scalarQuantization"

parameters

Contains the parameters specific to Scalar Quantization.

parameters?: ScalarQuantizationParameters

Property Value

Inherited Property Details

compressionName

The name to associate with this particular configuration.

compressionName: string

Property Value

string

Inherited From BaseVectorSearchCompression.compressionName

defaultOversampling

Default oversampling factor. Oversampling will internally request more documents (specified by this multiplier) in the initial search. This increases the set of results that will be reranked using recomputed similarity scores from full-precision vectors. Minimum value is 1, meaning no oversampling (1x). This parameter can only be set when rerankWithOriginalVectors is true. Higher values improve recall at the expense of latency.

defaultOversampling?: number

Property Value

number

Inherited From BaseVectorSearchCompression.defaultOversampling

rerankWithOriginalVectors

If set to true, once the ordered set of results calculated using compressed vectors are obtained, they will be reranked again by recalculating the full-precision similarity scores. This will improve recall at the expense of latency.

rerankWithOriginalVectors?: boolean

Property Value

boolean

Inherited From BaseVectorSearchCompression.rerankWithOriginalVectors