Method to perform a similarity search on the stored vectors in the Weaviate index. It returns the top k most similar documents, their similarity scores and embedding vectors.
similaritySearchVectorWithScoreAndEmbedding(
query: number[],
k: number,
filter: FilterValue
): Promise<[Document<Record<string, any>>, number, number, number[]][]>| Name | Type | Description |
|---|---|---|
query* | number[] | The query vector. |
k* | number | The number of most similar documents to return. |
filter | FilterValue | Optional filter to apply to the search. |