langchain/vectorstores/supabase.py/SupabaseVectorStore/similarity_search_by_vector_with_relevance_scores
class SupabaseVectorStore:    def similarity_search_by_vector_with_relevance_scores(
        self, query: List[float], k: int
    ) -> List[Tuple[Document, float]]:
        match_documents_params = dict(query_embedding=query, match_count=k)
        res = self._client.rpc(self.query_name, match_documents_params).execute()

        match_result = [
            (
                Document(
                    metadata=search.get("metadata", {}),  # type: ignore
                    page_content=search.get("content", ""),
                ),
                search.get("similarity", 0.0),
            )
            for search in res.data
            if search.get("content")
        ]

        return match_result