result_ids = self._post_texts_as_inputs(batch_texts, batch_metadatas)
                input_ids.extend(result_ids)
                logger.debug(f"Input {result_ids} posted successfully.")
            except Exception as error:
                logger.warning(f"Post inputs failed: {error}")
                traceback.print_exc()
        return input_ids
[docs]    def similarity_search_with_score(
        self,
        query: str,
        k: int = 4,
        filter: Optional[dict] = None,
        namespace: Optional[str] = None,
        **kwargs: Any,
    ) -> List[Tuple[Document, float]]:
        """Run similarity search with score using Clarifai.
        Args:
            query (str): Query text to search for.
            k (int): Number of results to return. Defaults to 4.
            filter (Optional[Dict[str, str]]): Filter by metadata.
            Defaults to None.
        Returns:
            List[Document]: List of documents most similar to the query text.
        """
        try:
            from clarifai_grpc.grpc.api import resources_pb2, service_pb2
            from clarifai_grpc.grpc.api.status import status_code_pb2
            from google.protobuf import json_format  # type: ignore
            from google.protobuf.struct_pb2 import Struct  # type: ignore
        except ImportError as e:
            raise ImportError(
                "Could not import clarifai python package. "
                "Please install it with `pip install clarifai`."
            ) from e
        # Get number of docs to return
        if self._number_of_docs is not None:
            k = self._number_of_docs
        req = service_pb2.PostAnnotationsSearchesRequest(
            user_app_id=self._userDataObject,