Python: Search vectors in index

Queries vectors using a query vector to find similar vectors.

• This is an alpha feature and may change in the future.

Parameters

• bucket_name

  (Required)

  The name of the vector bucket.

• index_name

  (Required)

  The name of the index.

• query_vector

  (Required)

  The query vector to search with.

• topK

  (Optional)

  Number of results to return.

• filter

  (Optional)

  Optional filter to apply to the query.

• return_distance

  (Optional)

  Whether to return distance scores. Defaults to `true`.

• return_metadata

  (Optional)

  Whether to return metadata. Defaults to `true`.

Examples

Query vectors

response = supabase.storage.vectors().from_("vectors-bucket").index("my-index").query(
    query_vector={"float32": [0.1, 0.2, 0.3]},
    topK=10
)