test_similarity_search() — langchain Function Reference

Source Code

libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_search.py lines 18–36

def test_similarity_search(
    location: str,
    vector_name: str,
    retrieval_mode: RetrievalMode,
    batch_size: int,
) -> None:
    """Test end to end construction and search."""
    texts = ["foo", "bar", "baz"]
    docsearch = QdrantVectorStore.from_texts(
        texts,
        ConsistentFakeEmbeddings(),
        location=location,
        batch_size=batch_size,
        vector_name=vector_name,
        retrieval_mode=retrieval_mode,
        sparse_embedding=ConsistentFakeSparseEmbeddings(),
    )
    output = docsearch.similarity_search("foo", k=1)
    assert_documents_equals(actual=output, expected=[Document(page_content="foo")])