VectorizableImageBinaryQuery interface

Package:

@azure/search-documents

The query parameters to use for vector search when a base 64 encoded binary of an image that needs to be vectorized is provided.

Extends

BaseVectorQuery<TModel>

Properties

binaryImage	The base64 encoded binary of an image to be vectorized to perform a vector search query.
kind	Polymorphic discriminator, which specifies the different types this object can be

Inherited Properties

exhaustive	When true, triggers an exhaustive k-nearest neighbor search across all vectors within the vector index. Useful for scenarios where exact matches are critical, such as determining ground truth values.
fields	Vector Fields of type Collection(Edm.Single) to be included in the vector searched.
filterOverride	The OData filter expression to apply to this specific vector query. If no filter expression is defined at the vector level, the expression defined in the top level filter parameter is used instead.
kNearestNeighborsCount	Number of nearest neighbors to return as top hits.
perDocumentVectorLimit	Controls how many vectors can be matched from each document in a vector search query. Setting it to 1 ensures at most one vector per document is matched, guaranteeing results come from distinct documents. Setting it to 0 (unlimited) allows multiple relevant vectors from the same document to be matched. Default is 0.
threshold	The threshold used for vector queries. Note this can only be set if all 'fields' use the same similarity metric.
weight	Relative weight of the vector query when compared to other vector query and/or the text query within the same search request. This value is used when combining the results of multiple ranking lists produced by the different vector queries and/or the results retrieved through the text query. The higher the weight, the higher the documents that matched that query will be in the final ranking. Default is 1.0 and the value needs to be a positive number larger than zero.

Property Details

binaryImage

The base64 encoded binary of an image to be vectorized to perform a vector search query.

binaryImage: string

Property Value

string

kind

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

kind: "imageBinary"

Property Value

"imageBinary"

Inherited Property Details

exhaustive

When true, triggers an exhaustive k-nearest neighbor search across all vectors within the vector index. Useful for scenarios where exact matches are critical, such as determining ground truth values.

exhaustive?: boolean

Property Value

boolean

Inherited From BaseVectorQuery.exhaustive

fields

Vector Fields of type Collection(Edm.Single) to be included in the vector searched.

fields?: SearchFieldArray<TModel>

Property Value

SearchFieldArray<TModel>

Inherited From BaseVectorQuery.fields

filterOverride

The OData filter expression to apply to this specific vector query. If no filter expression is defined at the vector level, the expression defined in the top level filter parameter is used instead.

filterOverride?: string

Property Value

string

Inherited From BaseVectorQuery.filterOverride

kNearestNeighborsCount

Number of nearest neighbors to return as top hits.

kNearestNeighborsCount?: number

Property Value

number

Inherited From BaseVectorQuery.kNearestNeighborsCount

perDocumentVectorLimit

Controls how many vectors can be matched from each document in a vector search query. Setting it to 1 ensures at most one vector per document is matched, guaranteeing results come from distinct documents. Setting it to 0 (unlimited) allows multiple relevant vectors from the same document to be matched. Default is 0.

perDocumentVectorLimit?: number

Property Value

number

Inherited From BaseVectorQuery.perDocumentVectorLimit

threshold

The threshold used for vector queries. Note this can only be set if all 'fields' use the same similarity metric.

threshold?: VectorThreshold

Property Value

VectorThreshold

Inherited From BaseVectorQuery.threshold

weight

Relative weight of the vector query when compared to other vector query and/or the text query within the same search request. This value is used when combining the results of multiple ranking lists produced by the different vector queries and/or the results retrieved through the text query. The higher the weight, the higher the documents that matched that query will be in the final ranking. Default is 1.0 and the value needs to be a positive number larger than zero.

weight?: number

Property Value

number

Inherited From BaseVectorQuery.weight