Also supports Script Scoring and Painless Scripting.
        Args:
            query: Text to look up documents similar to.
            k: Number of Documents to return. Defaults to 4.
        Returns:
            List of dict with its scores most similar to the query.
        Optional Args:
            same as `similarity_search`
        """
        embedding = self.embedding_function.embed_query(query)
        search_type = _get_kwargs_value(kwargs, "search_type", "approximate_search")
        vector_field = _get_kwargs_value(kwargs, "vector_field", "vector_field")
        index_name = _get_kwargs_value(kwargs, "index_name", self.index_name)
        filter = _get_kwargs_value(kwargs, "filter", {})
        if (
            self.is_aoss
            and search_type != "approximate_search"
            and search_type != SCRIPT_SCORING_SEARCH
        ):
            raise ValueError(
                "Amazon OpenSearch Service Serverless only "
                "supports `approximate_search` and `script_scoring`"
            )
        if search_type == "approximate_search":
            boolean_filter = _get_kwargs_value(kwargs, "boolean_filter", {})
            subquery_clause = _get_kwargs_value(kwargs, "subquery_clause", "must")
            efficient_filter = _get_kwargs_value(kwargs, "efficient_filter", {})
            # `lucene_filter` is deprecated, added for Backwards Compatibility
            lucene_filter = _get_kwargs_value(kwargs, "lucene_filter", {})
            if boolean_filter != {} and efficient_filter != {}:
                raise ValueError(
                    "Both `boolean_filter` and `efficient_filter` are provided which "
                    "is invalid"
                )
            if lucene_filter != {} and efficient_filter != {}:
                raise ValueError(