from langchain.vectorstores.neo4j_vector import Neo4jVector
            from langchain.embeddings.openai import OpenAIEmbeddings
            url="bolt://localhost:7687"
            username="neo4j"
            password="pleaseletmein"
            embeddings = OpenAIEmbeddings()
            vectorestore = Neo4jVector.from_documents(
                embedding=embeddings,
                documents=docs,
                url=url
                username=username,
                password=password,
            )
    """
[docs]    def __init__(
        self,
        embedding: Embeddings,
        *,
        search_type: SearchType = SearchType.VECTOR,
        username: Optional[str] = None,
        password: Optional[str] = None,
        url: Optional[str] = None,
        keyword_index_name: Optional[str] = "keyword",
        database: str = "neo4j",
        index_name: str = "vector",
        node_label: str = "Chunk",
        embedding_node_property: str = "embedding",
        text_node_property: str = "text",
        distance_strategy: DistanceStrategy = DEFAULT_DISTANCE_STRATEGY,
        logger: Optional[logging.Logger] = None,
        pre_delete_collection: bool = False,
        retrieval_query: str = "",
        relevance_score_fn: Optional[Callable[[float], float]] = None,
    ) -> None:
        try:
            import neo4j
        except ImportError:
            raise ImportError(
                "Could not import neo4j python package. "
                "Please install it with `pip install neo4j`."
            )
        # Allow only cosine and euclidean distance strategies
        if distance_strategy not in [
            DistanceStrategy.EUCLIDEAN_DISTANCE,
            DistanceStrategy.COSINE,