test_qdrant_from_texts_stores_metadatas() — langchain Function Reference

Source Code

libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_from_texts.py lines 318–344

def test_qdrant_from_texts_stores_metadatas(
    location: str,
    content_payload_key: str,
    metadata_payload_key: str,
    vector_name: str,
    retrieval_mode: RetrievalMode,
    sparse_vector_name: str,
) -> None:
    """Test end to end construction and search."""
    texts = ["fabrin", "barizda"]
    metadatas = [{"page": i} for i in range(len(texts))]
    docsearch = QdrantVectorStore.from_texts(
        texts,
        ConsistentFakeEmbeddings(),
        metadatas=metadatas,
        location=location,
        content_payload_key=content_payload_key,
        metadata_payload_key=metadata_payload_key,
        vector_name=vector_name,
        retrieval_mode=retrieval_mode,
        sparse_vector_name=sparse_vector_name,
        sparse_embedding=ConsistentFakeSparseEmbeddings(),
    )
    output = docsearch.similarity_search("fabrin", k=1)
    assert_documents_equals(
        output, [Document(page_content="fabrin", metadata={"page": 0})]
    )