def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:
        """
        Perform a similarity search with the given query embedding.

        Args:
            query (VectorStoreQuery): The query object containing the query data.
            **kwargs: Additional keyword arguments.

        Returns:
            VectorStoreQueryResult: The result of the similarity search.

        Raises:
            ValueError: If the query embedding is not provided.

        """
        if query.query_embedding is None:
            raise ValueError("Query embedding must be provided.")
        return self._similarity_search_with_score(
            query.query_embedding,
            query.similarity_top_k,
            query.filters,
            **kwargs,
        )

        Perform a similarity search with the given query embedding.

        Args:
            query (VectorStoreQuery): The query object containing the query data.
            **kwargs: Additional keyword arguments.

        Returns:
            VectorStoreQueryResult: The result of the similarity search.

        Raises:
            ValueError: If the query embedding is not provided.

        
llama-index-integrations/vector_stores/llama-index-vector-stores-tidbvector/llama_index/vector_stores/tidbvector/base.py