test_qdrant_similarity_search_with_relevance_scores() — langchain Function Reference

Source Code

libs/partners/qdrant/tests/integration_tests/test_similarity_search.py lines 262–283

def test_qdrant_similarity_search_with_relevance_scores(
    batch_size: int,
    content_payload_key: str,
    metadata_payload_key: str,
    vector_name: str | None,
) -> None:
    """Test end to end construction and search."""
    texts = ["foo", "bar", "baz"]
    docsearch = Qdrant.from_texts(
        texts,
        ConsistentFakeEmbeddings(),
        location=":memory:",
        content_payload_key=content_payload_key,
        metadata_payload_key=metadata_payload_key,
        batch_size=batch_size,
        vector_name=vector_name,
    )
    output = docsearch.similarity_search_with_relevance_scores("foo", k=3)

    assert all(
        (score <= 1 or np.isclose(score, 1)) and score >= 0 for _, score in output
    )