to be used during the hybrid search portion.
                Example - hybrid_search_kwargs={"vector": [0.1, 0.2, 0.3, ...]}
            https://weaviate.io/developers/weaviate/search/hybrid#with-a-custom-vector
            4) Use Fusion ranking method
                Example - from weaviate.gql.get import HybridFusion
                hybrid_search_kwargs={"fusion": fusion_type=HybridFusion.RELATIVE_SCORE}
            https://weaviate.io/developers/weaviate/search/hybrid#fusion-ranking-method
        """
        query_obj = self.client.query.get(self.index_name, self.attributes)
        if where_filter:
            query_obj = query_obj.with_where(where_filter)
        if score:
            query_obj = query_obj.with_additional(["score", "explainScore"])
        if hybrid_search_kwargs is None:
            hybrid_search_kwargs = {}
        result = (
            query_obj.with_hybrid(query, alpha=self.alpha, **hybrid_search_kwargs)
            .with_limit(self.k)
            .do()
        )
        if "errors" in result:
            raise ValueError(f"Error during query: {result['errors']}")
        docs = []
        for res in result["data"]["Get"][self.index_name]:
            text = res.pop(self.text_key)
            docs.append(Document(page_content=text, metadata=res))
        return docs