test_qdrant_similarity_search_with_relevance_score_with_threshold() — langchain Function Reference

Source Code

libs/partners/qdrant/tests/integration_tests/async_api/test_similarity_search.py lines 166–190

async def test_qdrant_similarity_search_with_relevance_score_with_threshold(
    vector_name: str | None,
    qdrant_location: str,
) -> None:
    """Test end to end construction and search."""
    texts = ["foo", "bar", "baz"]
    metadatas = [
        {"page": i, "metadata": {"page": i + 1, "pages": [i + 2, -1]}}
        for i in range(len(texts))
    ]
    docsearch = Qdrant.from_texts(
        texts,
        ConsistentFakeEmbeddings(),
        metadatas=metadatas,
        vector_name=vector_name,
        location=qdrant_location,
    )

    score_threshold = 0.98
    kwargs = {"score_threshold": score_threshold}
    output = await docsearch.asimilarity_search_with_relevance_scores(
        "foo", k=3, **kwargs
    )
    assert len(output) == 1
    assert all(score >= score_threshold for _, score in output)