# 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.eval_dataset import EvalDataset from ...types.http_validation_error import HttpValidationError from ...types.local_eval import LocalEval from ...types.local_eval_results import LocalEvalResults from ...types.local_eval_sets import LocalEvalSets from ...types.project import Project from ...types.project_create import ProjectCreate from ...types.prompt_mixin_prompts import PromptMixinPrompts from ...types.usage_and_plan import UsageAndPlan 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 ProjectsClient: def __init__(self, *, client_wrapper: SyncClientWrapper): self._client_wrapper = client_wrapper def list_projects( self, *, organization_id: typing.Optional[str] = None, project_name: typing.Optional[str] = None ) -> typing.List[Project]: """ List projects or get one by name Parameters: - organization_id: typing.Optional[str]. - project_name: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.list_projects() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"organization_id": organization_id, "project_name": project_name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[Project], _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_project(self, *, organization_id: typing.Optional[str] = None, request: ProjectCreate) -> Project: """ Create a new project. Parameters: - organization_id: typing.Optional[str]. - request: ProjectCreate. --- from llama_cloud import ProjectCreate from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.create_project( request=ProjectCreate( name="string", ), ) """ _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"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(Project, _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_project(self, *, organization_id: typing.Optional[str] = None, request: ProjectCreate) -> Project: """ Upsert a project. Updates if a project with the same name already exists. Otherwise, creates a new project. Parameters: - organization_id: typing.Optional[str]. - request: ProjectCreate. --- from llama_cloud import ProjectCreate from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.upsert_project( request=ProjectCreate( name="string", ), ) """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"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(Project, _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_project(self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None) -> Project: """ Get a project by ID. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.get_project() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Project, _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_existing_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, name: str ) -> Project: """ Update an existing project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - name: str. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.update_existing_project( name="string", ) """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"name": name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Project, _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_project(self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None) -> None: """ Delete a project by ID. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.delete_project() """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_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_project_usage( self, project_id: typing.Optional[str], *, get_current_invoice_total: typing.Optional[bool] = None, organization_id: typing.Optional[str] = None, ) -> UsageAndPlan: """ Get usage for a project Parameters: - project_id: typing.Optional[str]. - get_current_invoice_total: typing.Optional[bool]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.get_project_usage() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/usage"), params=remove_none_from_dict( {"get_current_invoice_total": get_current_invoice_total, "organization_id": organization_id} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(UsageAndPlan, _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_datasets_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[EvalDataset]: """ List eval datasets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.list_datasets_for_project() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/eval/dataset" ), params=remove_none_from_dict({"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[EvalDataset], _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_eval_dataset_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, name: str ) -> EvalDataset: """ Create a new eval dataset for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - name: str. The name of the EvalDataset. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.create_eval_dataset_for_project( name="string", ) """ _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/eval/dataset" ), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"name": name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(EvalDataset, _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_local_eval_set_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, app_name: str, results: typing.Dict[str, typing.List[LocalEval]], ) -> typing.List[LocalEvalResults]: """ Create a new local eval set. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - app_name: str. The name of the app. - results: typing.Dict[str, typing.List[LocalEval]]. The eval results. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.create_local_eval_set_for_project( app_name="string", results={"string": []}, ) """ _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalset" ), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"app_name": app_name, "results": results}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[LocalEvalResults], _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_local_evals_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[LocalEvalResults]: """ List local eval results for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.list_local_evals_for_project() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localeval"), params=remove_none_from_dict({"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[LocalEvalResults], _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_local_eval_sets_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[LocalEvalSets]: """ List local eval sets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.list_local_eval_sets_for_project() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalsets" ), params=remove_none_from_dict({"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[LocalEvalSets], _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_local_eval_set( self, project_id: typing.Optional[str], local_eval_set_id: str, *, organization_id: typing.Optional[str] = None ) -> typing.Any: """ Delete a local eval set. Parameters: - project_id: typing.Optional[str]. - local_eval_set_id: str. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.delete_local_eval_set( local_eval_set_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalset/{local_eval_set_id}", ), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Any, _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_promptmixin_prompts( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[PromptMixinPrompts]: """ List PromptMixin prompt sets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.list_promptmixin_prompts() """ _response = self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts"), params=remove_none_from_dict({"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[PromptMixinPrompts], _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_prompt_mixin_prompts( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, request: PromptMixinPrompts, ) -> PromptMixinPrompts: """ Create a new PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: PromptMixinPrompts. --- from llama_cloud import PromptMixinPrompts from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.create_prompt_mixin_prompts( request=PromptMixinPrompts( project_id="string", name="string", prompts=[], ), ) """ _response = self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts"), params=remove_none_from_dict({"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(PromptMixinPrompts, _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_promptmixin_prompts( self, project_id: typing.Optional[str], prompt_set_id: str, *, organization_id: typing.Optional[str] = None, request: PromptMixinPrompts, ) -> PromptMixinPrompts: """ Update a PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - prompt_set_id: str. - organization_id: typing.Optional[str]. - request: PromptMixinPrompts. --- from llama_cloud import PromptMixinPrompts from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.update_promptmixin_prompts( prompt_set_id="string", request=PromptMixinPrompts( project_id="string", name="string", prompts=[], ), ) """ _response = self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts/{prompt_set_id}" ), params=remove_none_from_dict({"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(PromptMixinPrompts, _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_prompt_mixin_prompts( self, project_id: typing.Optional[str], prompt_set_id: str, *, organization_id: typing.Optional[str] = None ) -> typing.Any: """ Delete a PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - prompt_set_id: str. - organization_id: typing.Optional[str]. --- from llama_cloud.client import LlamaCloud client = LlamaCloud( token="YOUR_TOKEN", ) client.projects.delete_prompt_mixin_prompts( prompt_set_id="string", ) """ _response = self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts/{prompt_set_id}" ), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Any, _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 AsyncProjectsClient: def __init__(self, *, client_wrapper: AsyncClientWrapper): self._client_wrapper = client_wrapper async def list_projects( self, *, organization_id: typing.Optional[str] = None, project_name: typing.Optional[str] = None ) -> typing.List[Project]: """ List projects or get one by name Parameters: - organization_id: typing.Optional[str]. - project_name: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.list_projects() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"organization_id": organization_id, "project_name": project_name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[Project], _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_project(self, *, organization_id: typing.Optional[str] = None, request: ProjectCreate) -> Project: """ Create a new project. Parameters: - organization_id: typing.Optional[str]. - request: ProjectCreate. --- from llama_cloud import ProjectCreate from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.create_project( request=ProjectCreate( name="string", ), ) """ _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"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(Project, _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_project(self, *, organization_id: typing.Optional[str] = None, request: ProjectCreate) -> Project: """ Upsert a project. Updates if a project with the same name already exists. Otherwise, creates a new project. Parameters: - organization_id: typing.Optional[str]. - request: ProjectCreate. --- from llama_cloud import ProjectCreate from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.upsert_project( request=ProjectCreate( name="string", ), ) """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "api/v1/projects"), params=remove_none_from_dict({"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(Project, _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_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> Project: """ Get a project by ID. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.get_project() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Project, _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_existing_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, name: str ) -> Project: """ Update an existing project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - name: str. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.update_existing_project( name="string", ) """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"name": name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(Project, _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_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> None: """ Delete a project by ID. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.delete_project() """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}"), params=remove_none_from_dict({"organization_id": organization_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_project_usage( self, project_id: typing.Optional[str], *, get_current_invoice_total: typing.Optional[bool] = None, organization_id: typing.Optional[str] = None, ) -> UsageAndPlan: """ Get usage for a project Parameters: - project_id: typing.Optional[str]. - get_current_invoice_total: typing.Optional[bool]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.get_project_usage() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/usage"), params=remove_none_from_dict( {"get_current_invoice_total": get_current_invoice_total, "organization_id": organization_id} ), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(UsageAndPlan, _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_datasets_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[EvalDataset]: """ List eval datasets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.list_datasets_for_project() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/eval/dataset" ), params=remove_none_from_dict({"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[EvalDataset], _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_eval_dataset_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, name: str ) -> EvalDataset: """ Create a new eval dataset for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - name: str. The name of the EvalDataset. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.create_eval_dataset_for_project( name="string", ) """ _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/eval/dataset" ), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"name": name}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(EvalDataset, _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_local_eval_set_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, app_name: str, results: typing.Dict[str, typing.List[LocalEval]], ) -> typing.List[LocalEvalResults]: """ Create a new local eval set. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - app_name: str. The name of the app. - results: typing.Dict[str, typing.List[LocalEval]]. The eval results. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.create_local_eval_set_for_project( app_name="string", results={"string": []}, ) """ _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalset" ), params=remove_none_from_dict({"organization_id": organization_id}), json=jsonable_encoder({"app_name": app_name, "results": results}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.List[LocalEvalResults], _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_local_evals_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[LocalEvalResults]: """ List local eval results for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.list_local_evals_for_project() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localeval"), params=remove_none_from_dict({"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[LocalEvalResults], _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_local_eval_sets_for_project( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[LocalEvalSets]: """ List local eval sets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.list_local_eval_sets_for_project() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalsets" ), params=remove_none_from_dict({"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[LocalEvalSets], _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_local_eval_set( self, project_id: typing.Optional[str], local_eval_set_id: str, *, organization_id: typing.Optional[str] = None ) -> typing.Any: """ Delete a local eval set. Parameters: - project_id: typing.Optional[str]. - local_eval_set_id: str. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.delete_local_eval_set( local_eval_set_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/localevalset/{local_eval_set_id}", ), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Any, _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_promptmixin_prompts( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None ) -> typing.List[PromptMixinPrompts]: """ List PromptMixin prompt sets for a project. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.list_promptmixin_prompts() """ _response = await self._client_wrapper.httpx_client.request( "GET", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts"), params=remove_none_from_dict({"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[PromptMixinPrompts], _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_prompt_mixin_prompts( self, project_id: typing.Optional[str], *, organization_id: typing.Optional[str] = None, request: PromptMixinPrompts, ) -> PromptMixinPrompts: """ Create a new PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - organization_id: typing.Optional[str]. - request: PromptMixinPrompts. --- from llama_cloud import PromptMixinPrompts from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.create_prompt_mixin_prompts( request=PromptMixinPrompts( project_id="string", name="string", prompts=[], ), ) """ _response = await self._client_wrapper.httpx_client.request( "POST", urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts"), params=remove_none_from_dict({"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(PromptMixinPrompts, _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_promptmixin_prompts( self, project_id: typing.Optional[str], prompt_set_id: str, *, organization_id: typing.Optional[str] = None, request: PromptMixinPrompts, ) -> PromptMixinPrompts: """ Update a PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - prompt_set_id: str. - organization_id: typing.Optional[str]. - request: PromptMixinPrompts. --- from llama_cloud import PromptMixinPrompts from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.update_promptmixin_prompts( prompt_set_id="string", request=PromptMixinPrompts( project_id="string", name="string", prompts=[], ), ) """ _response = await self._client_wrapper.httpx_client.request( "PUT", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts/{prompt_set_id}" ), params=remove_none_from_dict({"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(PromptMixinPrompts, _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_prompt_mixin_prompts( self, project_id: typing.Optional[str], prompt_set_id: str, *, organization_id: typing.Optional[str] = None ) -> typing.Any: """ Delete a PromptMixin prompt set. Parameters: - project_id: typing.Optional[str]. - prompt_set_id: str. - organization_id: typing.Optional[str]. --- from llama_cloud.client import AsyncLlamaCloud client = AsyncLlamaCloud( token="YOUR_TOKEN", ) await client.projects.delete_prompt_mixin_prompts( prompt_set_id="string", ) """ _response = await self._client_wrapper.httpx_client.request( "DELETE", urllib.parse.urljoin( f"{self._client_wrapper.get_base_url()}/", f"api/v1/projects/{project_id}/prompts/{prompt_set_id}" ), params=remove_none_from_dict({"organization_id": organization_id}), headers=self._client_wrapper.get_headers(), timeout=60, ) if 200 <= _response.status_code < 300: return pydantic.parse_obj_as(typing.Any, _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)