VectorSearch

Defines a search operation using a query vector.

JSON representation
 { 
 "searchField" 
 : 
 string 
 , 
 "filter" 
 : 
 { 
 object 
 } 
 , 
 "outputFields" 
 : 
 { 
 object (  OutputFields 
 
) 
 } 
 , 
 "searchHint" 
 : 
 { 
 object (  SearchHint 
 
) 
 } 
 , 
 "distanceMetric" 
 : 
 enum (  DistanceMetric 
 
) 
 , 
 // Union field vector_type 
can be only one of the following: 
 "vector" 
 : 
 { 
 object (  DenseVector 
 
) 
 } 
 , 
 "sparseVector" 
 : 
 { 
 object (  SparseVector 
 
) 
 } 
 // End of list of possible types for union field vector_type 
. 
 "topK" 
 : 
 integer 
 } 
Fields
searchField

string

Required. The vector field to search.

filter

object ( Struct format)

Optional. A JSON filter expression, e.g. {"genre": {"$eq": "sci-fi"}}, represented as a google.protobuf.Struct.

outputFields

object ( OutputFields )

Optional. Mask specifying which fields to return.

searchHint

object ( SearchHint )

Optional. Sets the search hint. If no strategy is specified, the service will use an index if one is available, and fall back to the default KNN search otherwise.

distanceMetric

enum ( DistanceMetric )

Optional. The distance metric to use for the KNN search. If not specified, DOT_PRODUCT will be used as the default.

Union field vector_type .

vector_type can be only one of the following:

vector

object ( DenseVector )

A dense vector for the query.

sparseVector

object ( SparseVector )

A sparse vector for the query.

topK

integer

Optional. The number of nearest neighbors to return.

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