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
compression |
The name to associate with this particular configuration. |
default |
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. |
rerank |
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