VectorizableTextQuery Class

Initializes a new instance of VectorizableTextQuery.

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.

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

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.

Number of nearest neighbors to return as top hits.

Oversampling factor. Minimum value is 1. It overrides the 'defaultOversampling' parameter configured in the index definition. It can be set only when 'rerankWithOriginalVectors' is true. This parameter is only permitted when a compression method is used on the underlying vector field.

Can be configured to let a generative model rewrite the query before sending it to be vectorized.

The text to be vectorized to perform a vector search query.

The threshold used for vector queries. Note this can only be set if all 'fields' use the same similarity metric. Please note VectorThreshold is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include SearchScoreThreshold and VectorSimilarityThreshold.

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.