# This file was auto-generated by Fern from our API Definition. import typing import urllib.parse from json.decoder import JSONDecodeError from ...core.api_error import ApiError from ...core.client_wrapper import AsyncClientWrapper, SyncClientWrapper from ...core.jsonable_encoder import jsonable_encoder from ...core.remove_none_from_dict import remove_none_from_dict from ...errors.unprocessable_entity_error import UnprocessableEntityError from ...types.file_count_by_status_response import FileCountByStatusResponse from ...types.http_validation_error import HttpValidationError from ...types.managed_ingestion_status_response import ManagedIngestionStatusResponse from ...types.paginated_list_pipeline_files_response import PaginatedListPipelineFilesResponse from ...types.pipeline_file import PipelineFile from ...types.pipeline_file_create import PipelineFileCreate from .types.pipeline_file_update_custom_metadata_value import PipelineFileUpdateCustomMetadataValue try: import pydantic if pydantic.__version__.startswith("1."): raise ImportError import pydantic.v1 as pydantic # type: ignore except ImportError: import pydantic # type: ignore # this is used as the default value for optional parameters OMIT = typing.cast(typing.Any, ...) class PipelineFilesClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._client_wrapper = client_wrapper def list_pipeline_files( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, ) -> typing.List[PipelineFile]: """ Get files for a pipeline. Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.list_pipeline_files( pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files"), params=remove_none_from_dict( {"data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[PipelineFile], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def add_files_to_pipeline_api( self, pipeline_id: str, *, request: typing.List[PipelineFileCreate] ) -> typing.List[PipelineFile]: """ Add files to a pipeline. Parameters: - pipeline_id: str. - request: typing.List[PipelineFileCreate]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.add_files_to_pipeline_api( pipeline_id="string", request=[], ) """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files"), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[PipelineFile], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def get_pipeline_file_status_counts( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, ) -> FileCountByStatusResponse: """ Get files for a pipeline. Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.get_pipeline_file_status_counts( pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/status-counts" ), params=remove_none_from_dict( {"data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(FileCountByStatusResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def update_pipeline_file( self, file_id: str, pipeline_id: str, *, custom_metadata: typing.Optional[ typing.Dict[str, typing.Optional[PipelineFileUpdateCustomMetadataValue]] ] = OMIT, ) -> PipelineFile: """ Update a file for a pipeline. Parameters: - file_id: str. - pipeline_id: str. - custom_metadata: typing.Optional[typing.Dict[str, typing.Optional[PipelineFileUpdateCustomMetadataValue]]]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.update_pipeline_file( file_id="string", pipeline_id="string", ) """ _request: typing.Dict[str, typing.Any] = {} if custom_metadata is not OMIT: _request["custom_metadata"] = custom_metadata _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}" ), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(PipelineFile, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def delete_pipeline_file(self, file_id: str, pipeline_id: str) -> None: """ Delete a file from a pipeline. Parameters: - file_id: str. - pipeline_id: str. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.delete_pipeline_file( file_id="string", pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}" ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def get_pipeline_file_status(self, file_id: str, pipeline_id: str) -> ManagedIngestionStatusResponse: """ Get status of a file for a pipeline. Parameters: - file_id: str. - pipeline_id: str. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.get_pipeline_file_status( file_id="string", pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}/status" ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(ManagedIngestionStatusResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def list_pipeline_files_2( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, file_name_contains: typing.Optional[str] = None, limit: typing.Optional[int] = None, offset: typing.Optional[int] = None, order_by: typing.Optional[str] = None, ) -> PaginatedListPipelineFilesResponse: """ Get files for a pipeline. Args: pipeline_id: ID of the pipeline data_source_id: Optional filter by data source ID only_manually_uploaded: Filter for only manually uploaded files file_name_contains: Optional filter by file name (substring match) limit: Limit number of results offset: Offset for pagination order_by: Field to order by Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. - file_name_contains: typing.Optional[str]. - limit: typing.Optional[int]. - offset: typing.Optional[int]. - order_by: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.list_pipeline_files_2( pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files2"), params=remove_none_from_dict( { "data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded, "file_name_contains": file_name_contains, "limit": limit, "offset": offset, "order_by": order_by, } ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(PaginatedListPipelineFilesResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def import_pipeline_metadata(self, pipeline_id: str, *, upload_file: typing.IO) -> typing.Dict[str, str]: """ Import metadata for a pipeline. Parameters: - pipeline_id: str. - upload_file: typing.IO. """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/metadata"), data=jsonable_encoder({}), files={"upload_file": upload_file}, headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Dict[str, str], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) def delete_pipeline_files_metadata(self, pipeline_id: str) -> None: """ Delete metadata for all files in a pipeline. Parameters: - pipeline_id: str. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.pipeline_files.delete_pipeline_files_metadata( pipeline_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/metadata"), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) class AsyncPipelineFilesClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._client_wrapper = client_wrapper async def list_pipeline_files( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, ) -> typing.List[PipelineFile]: """ Get files for a pipeline. Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.list_pipeline_files( pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files"), params=remove_none_from_dict( {"data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[PipelineFile], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def add_files_to_pipeline_api( self, pipeline_id: str, *, request: typing.List[PipelineFileCreate] ) -> typing.List[PipelineFile]: """ Add files to a pipeline. Parameters: - pipeline_id: str. - request: typing.List[PipelineFileCreate]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.add_files_to_pipeline_api( pipeline_id="string", request=[], ) """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files"), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[PipelineFile], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def get_pipeline_file_status_counts( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, ) -> FileCountByStatusResponse: """ Get files for a pipeline. Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.get_pipeline_file_status_counts( pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/status-counts" ), params=remove_none_from_dict( {"data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(FileCountByStatusResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def update_pipeline_file( self, file_id: str, pipeline_id: str, *, custom_metadata: typing.Optional[ typing.Dict[str, typing.Optional[PipelineFileUpdateCustomMetadataValue]] ] = OMIT, ) -> PipelineFile: """ Update a file for a pipeline. Parameters: - file_id: str. - pipeline_id: str. - custom_metadata: typing.Optional[typing.Dict[str, typing.Optional[PipelineFileUpdateCustomMetadataValue]]]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.update_pipeline_file( file_id="string", pipeline_id="string", ) """ _request: typing.Dict[str, typing.Any] = {} if custom_metadata is not OMIT: _request["custom_metadata"] = custom_metadata _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}" ), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(PipelineFile, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def delete_pipeline_file(self, file_id: str, pipeline_id: str) -> None: """ Delete a file from a pipeline. Parameters: - file_id: str. - pipeline_id: str. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.delete_pipeline_file( file_id="string", pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}" ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def get_pipeline_file_status(self, file_id: str, pipeline_id: str) -> ManagedIngestionStatusResponse: """ Get status of a file for a pipeline. Parameters: - file_id: str. - pipeline_id: str. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.get_pipeline_file_status( file_id="string", pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files/{file_id}/status" ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(ManagedIngestionStatusResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def list_pipeline_files_2( self, pipeline_id: str, *, data_source_id: typing.Optional[str] = None, only_manually_uploaded: typing.Optional[bool] = None, file_name_contains: typing.Optional[str] = None, limit: typing.Optional[int] = None, offset: typing.Optional[int] = None, order_by: typing.Optional[str] = None, ) -> PaginatedListPipelineFilesResponse: """ Get files for a pipeline. Args: pipeline_id: ID of the pipeline data_source_id: Optional filter by data source ID only_manually_uploaded: Filter for only manually uploaded files file_name_contains: Optional filter by file name (substring match) limit: Limit number of results offset: Offset for pagination order_by: Field to order by Parameters: - pipeline_id: str. - data_source_id: typing.Optional[str]. - only_manually_uploaded: typing.Optional[bool]. - file_name_contains: typing.Optional[str]. - limit: typing.Optional[int]. - offset: typing.Optional[int]. - order_by: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.list_pipeline_files_2( pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/files2"), params=remove_none_from_dict( { "data_source_id": data_source_id, "only_manually_uploaded": only_manually_uploaded, "file_name_contains": file_name_contains, "limit": limit, "offset": offset, "order_by": order_by, } ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(PaginatedListPipelineFilesResponse, _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def import_pipeline_metadata(self, pipeline_id: str, *, upload_file: typing.IO) -> typing.Dict[str, str]: """ Import metadata for a pipeline. Parameters: - pipeline_id: str. - upload_file: typing.IO. """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/metadata"), data=jsonable_encoder({}), files={"upload_file": upload_file}, headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Dict[str, str], _response.json()) # type: ignore if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json) async def delete_pipeline_files_metadata(self, pipeline_id: str) -> None: """ Delete metadata for all files in a pipeline. Parameters: - pipeline_id: str. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.pipeline_files.delete_pipeline_files_metadata( pipeline_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/pipelines/{pipeline_id}/metadata"), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return if _response.status_code == 422: raise UnprocessableEntityError(pydantic.parse_obj_as(HttpValidationError, _response.json())) # type: ignore try: _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, body=_response.text) raise ApiError(status_code=_response.status_code, body=_response_json)