langchain/vectorstores/faiss.py/FAISS/similarity_search_with_score
class FAISS:    def similarity_search_with_score(
        self, query: str, k: int = 4
    ) -> List[Tuple[Document, float]]:
        """Return docs most similar to query.

        Args:
            query: Text to look up documents similar to.
            k: Number of Documents to return. Defaults to 4.

        Returns:
            List of Documents most similar to the query and score for each
        """
        embedding = self.embedding_function(query)
        docs = self.similarity_search_with_score_by_vector(embedding, k)
        return docs