# 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.composite_retrieval_mode import CompositeRetrievalMode from ...types.composite_retrieval_result import CompositeRetrievalResult from ...types.http_validation_error import HttpValidationError from ...types.re_rank_config import ReRankConfig from ...types.retriever import Retriever from ...types.retriever_create import RetrieverCreate from ...types.retriever_pipeline import RetrieverPipeline 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 RetrieversClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._client_wrapper = client_wrapper def list_retrievers( self, *, name: typing.Optional[str] = None, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, ) -> typing.List[Retriever]: """ List Retrievers for a project. Parameters: - name: typing.Optional[str]. - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.list_retrievers() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"name": name, "project_id": project_id, "organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[Retriever], _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 create_retriever( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, request: RetrieverCreate, ) -> Retriever: """ Create a new Retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: RetrieverCreate. --- from llama_cloud import RetrieverCreate from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.create_retriever( request=RetrieverCreate( name="string", ), ) """ _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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 upsert_retriever( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, request: RetrieverCreate, ) -> Retriever: """ Upsert a new Retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: RetrieverCreate. --- from llama_cloud import RetrieverCreate from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.upsert_retriever( request=RetrieverCreate( name="string", ), ) """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever( self, retriever_id: str, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, ) -> Retriever: """ Get a Retriever by ID. Parameters: - retriever_id: str. - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.get_retriever( retriever_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever( self, retriever_id: str, *, name: typing.Optional[str] = OMIT, pipelines: typing.Optional[typing.List[RetrieverPipeline]] = OMIT, ) -> Retriever: """ Update an existing Retriever. Parameters: - retriever_id: str. - name: typing.Optional[str]. - pipelines: typing.Optional[typing.List[RetrieverPipeline]]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.update_retriever( retriever_id="string", ) """ _request: typing.Dict[str, typing.Any] = {} if name is not OMIT: _request["name"] = name if pipelines is not OMIT: _request["pipelines"] = pipelines _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}"), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever(self, retriever_id: str) -> None: """ Delete a Retriever by ID. Parameters: - retriever_id: str. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.delete_retriever( retriever_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_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 retrieve( self, retriever_id: str, *, mode: typing.Optional[CompositeRetrievalMode] = OMIT, rerank_top_n: typing.Optional[int] = OMIT, rerank_config: typing.Optional[ReRankConfig] = OMIT, query: str, ) -> CompositeRetrievalResult: """ Retrieve data using a Retriever. Parameters: - retriever_id: str. - mode: typing.Optional[CompositeRetrievalMode]. The mode of composite retrieval. - rerank_top_n: typing.Optional[int]. - rerank_config: typing.Optional[ReRankConfig]. The rerank configuration for composite retrieval. - query: str. The query to retrieve against. --- from llama_cloud import CompositeRetrievalMode, ReRankConfig, ReRankerType from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.retrieve( retriever_id="string", mode=CompositeRetrievalMode.ROUTING, rerank_config=ReRankConfig( type=ReRankerType.SYSTEM_DEFAULT, ), query="string", ) """ _request: typing.Dict[str, typing.Any] = {"query": query} if mode is not OMIT: _request["mode"] = mode if rerank_top_n is not OMIT: _request["rerank_top_n"] = rerank_top_n if rerank_config is not OMIT: _request["rerank_config"] = rerank_config _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}/retrieve" ), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(CompositeRetrievalResult, _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 direct_retrieve( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, mode: typing.Optional[CompositeRetrievalMode] = OMIT, rerank_top_n: typing.Optional[int] = OMIT, rerank_config: typing.Optional[ReRankConfig] = OMIT, query: str, pipelines: typing.Optional[typing.List[RetrieverPipeline]] = OMIT, ) -> CompositeRetrievalResult: """ Retrieve data using specified pipelines without creating a persistent retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - mode: typing.Optional[CompositeRetrievalMode]. The mode of composite retrieval. - rerank_top_n: typing.Optional[int]. - rerank_config: typing.Optional[ReRankConfig]. The rerank configuration for composite retrieval. - query: str. The query to retrieve against. - pipelines: typing.Optional[typing.List[RetrieverPipeline]]. The pipelines to use for retrieval. --- from llama_cloud import CompositeRetrievalMode, ReRankConfig, ReRankerType from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.retrievers.direct_retrieve( mode=CompositeRetrievalMode.ROUTING, rerank_config=ReRankConfig( type=ReRankerType.SYSTEM_DEFAULT, ), query="string", ) """ _request: typing.Dict[str, typing.Any] = {"query": query} if mode is not OMIT: _request["mode"] = mode if rerank_top_n is not OMIT: _request["rerank_top_n"] = rerank_top_n if rerank_config is not OMIT: _request["rerank_config"] = rerank_config if pipelines is not OMIT: _request["pipelines"] = pipelines _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers/retrieve"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(CompositeRetrievalResult, _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) class AsyncRetrieversClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._client_wrapper = client_wrapper async def list_retrievers( self, *, name: typing.Optional[str] = None, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, ) -> typing.List[Retriever]: """ List Retrievers for a project. Parameters: - name: typing.Optional[str]. - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.list_retrievers() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"name": name, "project_id": project_id, "organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[Retriever], _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 create_retriever( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, request: RetrieverCreate, ) -> Retriever: """ Create a new Retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: RetrieverCreate. --- from llama_cloud import RetrieverCreate from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.create_retriever( request=RetrieverCreate( name="string", ), ) """ _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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 upsert_retriever( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, request: RetrieverCreate, ) -> Retriever: """ Upsert a new Retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: RetrieverCreate. --- from llama_cloud import RetrieverCreate from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.upsert_retriever( request=RetrieverCreate( name="string", ), ) """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever( self, retriever_id: str, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, ) -> Retriever: """ Get a Retriever by ID. Parameters: - retriever_id: str. - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.get_retriever( retriever_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever( self, retriever_id: str, *, name: typing.Optional[str] = OMIT, pipelines: typing.Optional[typing.List[RetrieverPipeline]] = OMIT, ) -> Retriever: """ Update an existing Retriever. Parameters: - retriever_id: str. - name: typing.Optional[str]. - pipelines: typing.Optional[typing.List[RetrieverPipeline]]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.update_retriever( retriever_id="string", ) """ _request: typing.Dict[str, typing.Any] = {} if name is not OMIT: _request["name"] = name if pipelines is not OMIT: _request["pipelines"] = pipelines _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}"), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Retriever, _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_retriever(self, retriever_id: str) -> None: """ Delete a Retriever by ID. Parameters: - retriever_id: str. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.delete_retriever( retriever_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_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 retrieve( self, retriever_id: str, *, mode: typing.Optional[CompositeRetrievalMode] = OMIT, rerank_top_n: typing.Optional[int] = OMIT, rerank_config: typing.Optional[ReRankConfig] = OMIT, query: str, ) -> CompositeRetrievalResult: """ Retrieve data using a Retriever. Parameters: - retriever_id: str. - mode: typing.Optional[CompositeRetrievalMode]. The mode of composite retrieval. - rerank_top_n: typing.Optional[int]. - rerank_config: typing.Optional[ReRankConfig]. The rerank configuration for composite retrieval. - query: str. The query to retrieve against. --- from llama_cloud import CompositeRetrievalMode, ReRankConfig, ReRankerType from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.retrieve( retriever_id="string", mode=CompositeRetrievalMode.ROUTING, rerank_config=ReRankConfig( type=ReRankerType.SYSTEM_DEFAULT, ), query="string", ) """ _request: typing.Dict[str, typing.Any] = {"query": query} if mode is not OMIT: _request["mode"] = mode if rerank_top_n is not OMIT: _request["rerank_top_n"] = rerank_top_n if rerank_config is not OMIT: _request["rerank_config"] = rerank_config _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/retrievers/{retriever_id}/retrieve" ), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(CompositeRetrievalResult, _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 direct_retrieve( self, *, project_id: typing.Optional[str] = None, organization_id: typing.Optional[str] = None, mode: typing.Optional[CompositeRetrievalMode] = OMIT, rerank_top_n: typing.Optional[int] = OMIT, rerank_config: typing.Optional[ReRankConfig] = OMIT, query: str, pipelines: typing.Optional[typing.List[RetrieverPipeline]] = OMIT, ) -> CompositeRetrievalResult: """ Retrieve data using specified pipelines without creating a persistent retriever. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - mode: typing.Optional[CompositeRetrievalMode]. The mode of composite retrieval. - rerank_top_n: typing.Optional[int]. - rerank_config: typing.Optional[ReRankConfig]. The rerank configuration for composite retrieval. - query: str. The query to retrieve against. - pipelines: typing.Optional[typing.List[RetrieverPipeline]]. The pipelines to use for retrieval. --- from llama_cloud import CompositeRetrievalMode, ReRankConfig, ReRankerType from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.retrievers.direct_retrieve( mode=CompositeRetrievalMode.ROUTING, rerank_config=ReRankConfig( type=ReRankerType.SYSTEM_DEFAULT, ), query="string", ) """ _request: typing.Dict[str, typing.Any] = {"query": query} if mode is not OMIT: _request["mode"] = mode if rerank_top_n is not OMIT: _request["rerank_top_n"] = rerank_top_n if rerank_config is not OMIT: _request["rerank_config"] = rerank_config if pipelines is not OMIT: _request["pipelines"] = pipelines _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/retrievers/retrieve"), params=remove_none_from_dict({"project_id": project_id, "organization_id": organization_id}), json=jsonable_encoder(_request), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(CompositeRetrievalResult, _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)