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def list( self, project_id: str, chapter_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ChapterSnapshotsResponse: """ Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotsResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.chapters.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.list(project_id, chapter_id, request_options=request_options) return _response.data
Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotsResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.chapters.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", )
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
def get( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None, ) -> ChapterSnapshotExtendedResponseModel: """ Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotExtendedResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.chapters.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", chapter_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.get(project_id, chapter_id, chapter_snapshot_id, request_options=request_options) return _response.data
Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotExtendedResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.chapters.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", chapter_snapshot_id="21m00Tcm4TlvDq8ikWAM", )
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
def stream( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Iterator[bytes]: """ Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Streaming audio data """ with self._raw_client.stream( project_id, chapter_id, chapter_snapshot_id, convert_to_mpeg=convert_to_mpeg, request_options=request_options, ) as r: yield from r.data
Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Streaming audio data
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
async def list( self, project_id: str, chapter_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ChapterSnapshotsResponse: """ Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotsResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.chapters.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.list(project_id, chapter_id, request_options=request_options) return _response.data
Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotsResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.chapters.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
async def get( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None, ) -> ChapterSnapshotExtendedResponseModel: """ Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotExtendedResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.chapters.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", chapter_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.get( project_id, chapter_id, chapter_snapshot_id, request_options=request_options ) return _response.data
Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ChapterSnapshotExtendedResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.chapters.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", chapter_id="21m00Tcm4TlvDq8ikWAM", chapter_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
async def stream( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.AsyncIterator[bytes]: """ Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Streaming audio data """ async with self._raw_client.stream( project_id, chapter_id, chapter_snapshot_id, convert_to_mpeg=convert_to_mpeg, request_options=request_options, ) as r: async for _chunk in r.data: yield _chunk
Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Streaming audio data
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/client.py
MIT
def list( self, project_id: str, chapter_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[ChapterSnapshotsResponse]: """ Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ChapterSnapshotsResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ChapterSnapshotsResponse, construct_type( type_=ChapterSnapshotsResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ChapterSnapshotsResponse] Successful Response
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
def get( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[ChapterSnapshotExtendedResponseModel]: """ Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ChapterSnapshotExtendedResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots/{jsonable_encoder(chapter_snapshot_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ChapterSnapshotExtendedResponseModel, construct_type( type_=ChapterSnapshotExtendedResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ChapterSnapshotExtendedResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
def stream( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Iterator[HttpResponse[typing.Iterator[bytes]]]: """ Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Streaming audio data """ with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots/{jsonable_encoder(chapter_snapshot_id)}/stream", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "convert_to_mpeg": convert_to_mpeg, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) as _response: def _stream() -> HttpResponse[typing.Iterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return HttpResponse( response=_response, data=(_chunk for _chunk in _response.iter_bytes(chunk_size=_chunk_size)) ) _response.read() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield _stream()
Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Streaming audio data
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
async def list( self, project_id: str, chapter_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[ChapterSnapshotsResponse]: """ Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ChapterSnapshotsResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ChapterSnapshotsResponse, construct_type( type_=ChapterSnapshotsResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets information about all the snapshots of a chapter. Each snapshot can be downloaded as audio. Whenever a chapter is converted a snapshot will automatically be created. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ChapterSnapshotsResponse] Successful Response
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
async def get( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[ChapterSnapshotExtendedResponseModel]: """ Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ChapterSnapshotExtendedResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots/{jsonable_encoder(chapter_snapshot_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ChapterSnapshotExtendedResponseModel, construct_type( type_=ChapterSnapshotExtendedResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the chapter snapshot. Parameters ---------- project_id : str The ID of the Studio project. chapter_id : str The ID of the chapter. chapter_snapshot_id : str The ID of the chapter snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ChapterSnapshotExtendedResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
async def stream( self, project_id: str, chapter_id: str, chapter_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]]: """ Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Streaming audio data """ async with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/chapters/{jsonable_encoder(chapter_id)}/snapshots/{jsonable_encoder(chapter_snapshot_id)}/stream", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "convert_to_mpeg": convert_to_mpeg, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) as _response: async def _stream() -> AsyncHttpResponse[typing.AsyncIterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return AsyncHttpResponse( response=_response, data=(_chunk async for _chunk in _response.aiter_bytes(chunk_size=_chunk_size)), ) await _response.aread() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield await _stream()
Stream the audio from a chapter snapshot. Use `GET /v1/studio/projects/{project_id}/chapters/{chapter_id}/snapshots` to return the snapshots of a chapter. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. chapter_id : str The ID of the chapter to be used. You can use the [List project chapters](/docs/api-reference/studio/get-chapters) endpoint to list all the available chapters. chapter_snapshot_id : str The ID of the chapter snapshot to be used. You can use the [List project chapter snapshots](/docs/api-reference/studio/get-snapshots) endpoint to list all the available snapshots. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Streaming audio data
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/chapters/snapshots/raw_client.py
MIT
def update( self, project_id: str, *, from_url: typing.Optional[str] = OMIT, from_document: typing.Optional[core.File] = OMIT, auto_convert: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> EditProjectResponseModel: """ Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditProjectResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.content.update( project_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.update( project_id, from_url=from_url, from_document=from_document, auto_convert=auto_convert, request_options=request_options, ) return _response.data
Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditProjectResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.content.update( project_id="21m00Tcm4TlvDq8ikWAM", )
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/content/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/content/client.py
MIT
async def update( self, project_id: str, *, from_url: typing.Optional[str] = OMIT, from_document: typing.Optional[core.File] = OMIT, auto_convert: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> EditProjectResponseModel: """ Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditProjectResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.content.update( project_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.update( project_id, from_url=from_url, from_document=from_document, auto_convert=auto_convert, request_options=request_options, ) return _response.data
Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditProjectResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.content.update( project_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/content/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/content/client.py
MIT
def update( self, project_id: str, *, from_url: typing.Optional[str] = OMIT, from_document: typing.Optional[core.File] = OMIT, auto_convert: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[EditProjectResponseModel]: """ Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[EditProjectResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/content", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "from_url": from_url, "auto_convert": auto_convert, }, files={ **({"from_document": from_document} if from_document is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( EditProjectResponseModel, construct_type( type_=EditProjectResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[EditProjectResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/content/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/content/raw_client.py
MIT
async def update( self, project_id: str, *, from_url: typing.Optional[str] = OMIT, from_document: typing.Optional[core.File] = OMIT, auto_convert: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[EditProjectResponseModel]: """ Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[EditProjectResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/content", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "from_url": from_url, "auto_convert": auto_convert, }, files={ **({"from_document": from_document} if from_document is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( EditProjectResponseModel, construct_type( type_=EditProjectResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Updates Studio project content. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. from_url : typing.Optional[str] An optional URL from which we will extract content to initialize the Studio project. If this is set, 'from_url' must be null. If neither 'from_url' or 'from_document' are provided we will initialize the Studio project as blank. from_document : typing.Optional[core.File] See core.File for more documentation auto_convert : typing.Optional[bool] Whether to auto convert the Studio project to audio or not. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[EditProjectResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/content/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/content/raw_client.py
MIT
def create( self, project_id: str, *, pronunciation_dictionary_locators: typing.Sequence[PronunciationDictionaryVersionLocator], invalidate_affected_text: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> CreatePronunciationDictionaryResponseModel: """ Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"Vmd4Zor6fplcA7WrINey\",\"version_id\":\"hRPaxjlTdR7wFMhV4w0b\"}"' --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"JzWtcGQMJ6bnlWwyMo7e\",\"version_id\":\"lbmwxiLu4q6txYxgdZqn\"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreatePronunciationDictionaryResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs, PronunciationDictionaryVersionLocator client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.pronunciation_dictionaries.create( project_id="21m00Tcm4TlvDq8ikWAM", pronunciation_dictionary_locators=[ PronunciationDictionaryVersionLocator( pronunciation_dictionary_id="pronunciation_dictionary_id", ) ], ) """ _response = self._raw_client.create( project_id, pronunciation_dictionary_locators=pronunciation_dictionary_locators, invalidate_affected_text=invalidate_affected_text, request_options=request_options, ) return _response.data
Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"Vmd4Zor6fplcA7WrINey","version_id":"hRPaxjlTdR7wFMhV4w0b"}"' --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"JzWtcGQMJ6bnlWwyMo7e","version_id":"lbmwxiLu4q6txYxgdZqn"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreatePronunciationDictionaryResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs, PronunciationDictionaryVersionLocator client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.pronunciation_dictionaries.create( project_id="21m00Tcm4TlvDq8ikWAM", pronunciation_dictionary_locators=[ PronunciationDictionaryVersionLocator( pronunciation_dictionary_id="pronunciation_dictionary_id", ) ], )
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/pronunciation_dictionaries/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/pronunciation_dictionaries/client.py
MIT
async def create( self, project_id: str, *, pronunciation_dictionary_locators: typing.Sequence[PronunciationDictionaryVersionLocator], invalidate_affected_text: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> CreatePronunciationDictionaryResponseModel: """ Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"Vmd4Zor6fplcA7WrINey\",\"version_id\":\"hRPaxjlTdR7wFMhV4w0b\"}"' --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"JzWtcGQMJ6bnlWwyMo7e\",\"version_id\":\"lbmwxiLu4q6txYxgdZqn\"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreatePronunciationDictionaryResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs, PronunciationDictionaryVersionLocator client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.pronunciation_dictionaries.create( project_id="21m00Tcm4TlvDq8ikWAM", pronunciation_dictionary_locators=[ PronunciationDictionaryVersionLocator( pronunciation_dictionary_id="pronunciation_dictionary_id", ) ], ) asyncio.run(main()) """ _response = await self._raw_client.create( project_id, pronunciation_dictionary_locators=pronunciation_dictionary_locators, invalidate_affected_text=invalidate_affected_text, request_options=request_options, ) return _response.data
Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"Vmd4Zor6fplcA7WrINey","version_id":"hRPaxjlTdR7wFMhV4w0b"}"' --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"JzWtcGQMJ6bnlWwyMo7e","version_id":"lbmwxiLu4q6txYxgdZqn"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- CreatePronunciationDictionaryResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs, PronunciationDictionaryVersionLocator client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.pronunciation_dictionaries.create( project_id="21m00Tcm4TlvDq8ikWAM", pronunciation_dictionary_locators=[ PronunciationDictionaryVersionLocator( pronunciation_dictionary_id="pronunciation_dictionary_id", ) ], ) asyncio.run(main())
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/pronunciation_dictionaries/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/pronunciation_dictionaries/client.py
MIT
def create( self, project_id: str, *, pronunciation_dictionary_locators: typing.Sequence[PronunciationDictionaryVersionLocator], invalidate_affected_text: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[CreatePronunciationDictionaryResponseModel]: """ Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"Vmd4Zor6fplcA7WrINey\",\"version_id\":\"hRPaxjlTdR7wFMhV4w0b\"}"' --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"JzWtcGQMJ6bnlWwyMo7e\",\"version_id\":\"lbmwxiLu4q6txYxgdZqn\"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[CreatePronunciationDictionaryResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/pronunciation-dictionaries", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "pronunciation_dictionary_locators": convert_and_respect_annotation_metadata( object_=pronunciation_dictionary_locators, annotation=typing.Sequence[PronunciationDictionaryVersionLocator], direction="write", ), "invalidate_affected_text": invalidate_affected_text, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( CreatePronunciationDictionaryResponseModel, construct_type( type_=CreatePronunciationDictionaryResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"Vmd4Zor6fplcA7WrINey","version_id":"hRPaxjlTdR7wFMhV4w0b"}"' --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"JzWtcGQMJ6bnlWwyMo7e","version_id":"lbmwxiLu4q6txYxgdZqn"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[CreatePronunciationDictionaryResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/pronunciation_dictionaries/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/pronunciation_dictionaries/raw_client.py
MIT
async def create( self, project_id: str, *, pronunciation_dictionary_locators: typing.Sequence[PronunciationDictionaryVersionLocator], invalidate_affected_text: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[CreatePronunciationDictionaryResponseModel]: """ Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"Vmd4Zor6fplcA7WrINey\",\"version_id\":\"hRPaxjlTdR7wFMhV4w0b\"}"' --form 'pronunciation_dictionary_locators="{\"pronunciation_dictionary_id\":\"JzWtcGQMJ6bnlWwyMo7e\",\"version_id\":\"lbmwxiLu4q6txYxgdZqn\"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[CreatePronunciationDictionaryResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/pronunciation-dictionaries", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "pronunciation_dictionary_locators": convert_and_respect_annotation_metadata( object_=pronunciation_dictionary_locators, annotation=typing.Sequence[PronunciationDictionaryVersionLocator], direction="write", ), "invalidate_affected_text": invalidate_affected_text, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( CreatePronunciationDictionaryResponseModel, construct_type( type_=CreatePronunciationDictionaryResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a set of pronunciation dictionaries acting on a project. This will automatically mark text within this project as requiring reconverting where the new dictionary would apply or the old one no longer does. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. pronunciation_dictionary_locators : typing.Sequence[PronunciationDictionaryVersionLocator] A list of pronunciation dictionary locators (pronunciation_dictionary_id, version_id) encoded as a list of JSON strings for pronunciation dictionaries to be applied to the text. A list of json encoded strings is required as adding projects may occur through formData as opposed to jsonBody. To specify multiple dictionaries use multiple --form lines in your curl, such as --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"Vmd4Zor6fplcA7WrINey","version_id":"hRPaxjlTdR7wFMhV4w0b"}"' --form 'pronunciation_dictionary_locators="{"pronunciation_dictionary_id":"JzWtcGQMJ6bnlWwyMo7e","version_id":"lbmwxiLu4q6txYxgdZqn"}"'. Note that multiple dictionaries are not currently supported by our UI which will only show the first. invalidate_affected_text : typing.Optional[bool] This will automatically mark text in this project for reconversion when the new dictionary applies or the old one no longer does. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[CreatePronunciationDictionaryResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/pronunciation_dictionaries/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/pronunciation_dictionaries/raw_client.py
MIT
def list( self, project_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ProjectSnapshotsResponse: """ Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotsResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.list(project_id, request_options=request_options) return _response.data
Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotsResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", )
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
def get( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ProjectSnapshotExtendedResponseModel: """ Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotExtendedResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", project_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.get(project_id, project_snapshot_id, request_options=request_options) return _response.data
Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotExtendedResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.studio.projects.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", project_snapshot_id="21m00Tcm4TlvDq8ikWAM", )
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
def stream( self, project_id: str, project_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Iterator[bytes]: """ Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Successful Response """ with self._raw_client.stream( project_id, project_snapshot_id, convert_to_mpeg=convert_to_mpeg, request_options=request_options ) as r: yield from r.data
Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Successful Response
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
def stream_archive( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> typing.Iterator[bytes]: """ Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Streaming archive data """ with self._raw_client.stream_archive(project_id, project_snapshot_id, request_options=request_options) as r: yield from r.data
Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[bytes] Streaming archive data
stream_archive
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
async def list( self, project_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ProjectSnapshotsResponse: """ Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotsResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.list(project_id, request_options=request_options) return _response.data
Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotsResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.snapshots.list( project_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
async def get( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> ProjectSnapshotExtendedResponseModel: """ Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotExtendedResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", project_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.get(project_id, project_snapshot_id, request_options=request_options) return _response.data
Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- ProjectSnapshotExtendedResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.studio.projects.snapshots.get( project_id="21m00Tcm4TlvDq8ikWAM", project_snapshot_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
async def stream( self, project_id: str, project_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.AsyncIterator[bytes]: """ Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Successful Response """ async with self._raw_client.stream( project_id, project_snapshot_id, convert_to_mpeg=convert_to_mpeg, request_options=request_options ) as r: async for _chunk in r.data: yield _chunk
Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Successful Response
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
async def stream_archive( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> typing.AsyncIterator[bytes]: """ Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Streaming archive data """ async with self._raw_client.stream_archive( project_id, project_snapshot_id, request_options=request_options ) as r: async for _chunk in r.data: yield _chunk
Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[bytes] Streaming archive data
stream_archive
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/client.py
MIT
def list( self, project_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[ProjectSnapshotsResponse]: """ Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ProjectSnapshotsResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ProjectSnapshotsResponse, construct_type( type_=ProjectSnapshotsResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ProjectSnapshotsResponse] Successful Response
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
def get( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[ProjectSnapshotExtendedResponseModel]: """ Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ProjectSnapshotExtendedResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ProjectSnapshotExtendedResponseModel, construct_type( type_=ProjectSnapshotExtendedResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[ProjectSnapshotExtendedResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
def stream( self, project_id: str, project_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.Iterator[HttpResponse[typing.Iterator[bytes]]]: """ Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Successful Response """ with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}/stream", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "convert_to_mpeg": convert_to_mpeg, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) as _response: def _stream() -> HttpResponse[typing.Iterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return HttpResponse( response=_response, data=(_chunk for _chunk in _response.iter_bytes(chunk_size=_chunk_size)) ) _response.read() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield _stream()
Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Successful Response
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
def stream_archive( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> typing.Iterator[HttpResponse[typing.Iterator[bytes]]]: """ Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Streaming archive data """ with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}/archive", base_url=self._client_wrapper.get_environment().base, method="POST", request_options=request_options, ) as _response: def _stream() -> HttpResponse[typing.Iterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return HttpResponse( response=_response, data=(_chunk for _chunk in _response.iter_bytes(chunk_size=_chunk_size)) ) _response.read() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield _stream()
Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.Iterator[HttpResponse[typing.Iterator[bytes]]] Streaming archive data
stream_archive
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
async def list( self, project_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[ProjectSnapshotsResponse]: """ Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ProjectSnapshotsResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ProjectSnapshotsResponse, construct_type( type_=ProjectSnapshotsResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Retrieves a list of snapshots for a Studio project. Parameters ---------- project_id : str The ID of the Studio project. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ProjectSnapshotsResponse] Successful Response
list
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
async def get( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[ProjectSnapshotExtendedResponseModel]: """ Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ProjectSnapshotExtendedResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( ProjectSnapshotExtendedResponseModel, construct_type( type_=ProjectSnapshotExtendedResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the project snapshot. Parameters ---------- project_id : str The ID of the Studio project. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[ProjectSnapshotExtendedResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
async def stream( self, project_id: str, project_snapshot_id: str, *, convert_to_mpeg: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]]: """ Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Successful Response """ async with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}/stream", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "convert_to_mpeg": convert_to_mpeg, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) as _response: async def _stream() -> AsyncHttpResponse[typing.AsyncIterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return AsyncHttpResponse( response=_response, data=(_chunk async for _chunk in _response.aiter_bytes(chunk_size=_chunk_size)), ) await _response.aread() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield await _stream()
Stream the audio from a Studio project snapshot. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. convert_to_mpeg : typing.Optional[bool] Whether to convert the audio to mpeg format. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Successful Response
stream
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
async def stream_archive( self, project_id: str, project_snapshot_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]]: """ Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Streaming archive data """ async with self._client_wrapper.httpx_client.stream( f"v1/studio/projects/{jsonable_encoder(project_id)}/snapshots/{jsonable_encoder(project_snapshot_id)}/archive", base_url=self._client_wrapper.get_environment().base, method="POST", request_options=request_options, ) as _response: async def _stream() -> AsyncHttpResponse[typing.AsyncIterator[bytes]]: try: if 200 <= _response.status_code < 300: _chunk_size = request_options.get("chunk_size", 1024) if request_options is not None else 1024 return AsyncHttpResponse( response=_response, data=(_chunk async for _chunk in _response.aiter_bytes(chunk_size=_chunk_size)), ) await _response.aread() if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError( status_code=_response.status_code, headers=dict(_response.headers), body=_response.text ) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json) yield await _stream()
Returns a compressed archive of the Studio project's audio. Parameters ---------- project_id : str The ID of the project to be used. You can use the [List projects](/docs/api-reference/studio/get-projects) endpoint to list all the available projects. project_snapshot_id : str The ID of the Studio project snapshot. request_options : typing.Optional[RequestOptions] Request-specific configuration. You can pass in configuration such as `chunk_size`, and more to customize the request and response. Returns ------- typing.AsyncIterator[AsyncHttpResponse[typing.AsyncIterator[bytes]]] Streaming archive data
stream_archive
python
elevenlabs/elevenlabs-python
src/elevenlabs/studio/projects/snapshots/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/studio/projects/snapshots/raw_client.py
MIT
def create_previews( self, *, voice_description: str, output_format: typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] = None, text: typing.Optional[str] = OMIT, auto_generate_text: typing.Optional[bool] = OMIT, loudness: typing.Optional[float] = OMIT, quality: typing.Optional[float] = OMIT, seed: typing.Optional[int] = OMIT, guidance_scale: typing.Optional[float] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> VoiceDesignPreviewResponse: """ Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- VoiceDesignPreviewResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.text_to_voice.create_previews( voice_description="A sassy squeaky mouse", ) """ _response = self._raw_client.create_previews( voice_description=voice_description, output_format=output_format, text=text, auto_generate_text=auto_generate_text, loudness=loudness, quality=quality, seed=seed, guidance_scale=guidance_scale, request_options=request_options, ) return _response.data
Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- VoiceDesignPreviewResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.text_to_voice.create_previews( voice_description="A sassy squeaky mouse", )
create_previews
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/client.py
MIT
def create_voice_from_preview( self, *, voice_name: str, voice_description: str, generated_voice_id: str, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, played_not_selected_voice_ids: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> Voice: """ Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.text_to_voice.create_voice_from_preview( voice_name="Sassy squeaky mouse", voice_description="A sassy squeaky mouse", generated_voice_id="37HceQefKmEi3bGovXjL", ) """ _response = self._raw_client.create_voice_from_preview( voice_name=voice_name, voice_description=voice_description, generated_voice_id=generated_voice_id, labels=labels, played_not_selected_voice_ids=played_not_selected_voice_ids, request_options=request_options, ) return _response.data
Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.text_to_voice.create_voice_from_preview( voice_name="Sassy squeaky mouse", voice_description="A sassy squeaky mouse", generated_voice_id="37HceQefKmEi3bGovXjL", )
create_voice_from_preview
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/client.py
MIT
async def create_previews( self, *, voice_description: str, output_format: typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] = None, text: typing.Optional[str] = OMIT, auto_generate_text: typing.Optional[bool] = OMIT, loudness: typing.Optional[float] = OMIT, quality: typing.Optional[float] = OMIT, seed: typing.Optional[int] = OMIT, guidance_scale: typing.Optional[float] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> VoiceDesignPreviewResponse: """ Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- VoiceDesignPreviewResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.text_to_voice.create_previews( voice_description="A sassy squeaky mouse", ) asyncio.run(main()) """ _response = await self._raw_client.create_previews( voice_description=voice_description, output_format=output_format, text=text, auto_generate_text=auto_generate_text, loudness=loudness, quality=quality, seed=seed, guidance_scale=guidance_scale, request_options=request_options, ) return _response.data
Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- VoiceDesignPreviewResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.text_to_voice.create_previews( voice_description="A sassy squeaky mouse", ) asyncio.run(main())
create_previews
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/client.py
MIT
async def create_voice_from_preview( self, *, voice_name: str, voice_description: str, generated_voice_id: str, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, played_not_selected_voice_ids: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> Voice: """ Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.text_to_voice.create_voice_from_preview( voice_name="Sassy squeaky mouse", voice_description="A sassy squeaky mouse", generated_voice_id="37HceQefKmEi3bGovXjL", ) asyncio.run(main()) """ _response = await self._raw_client.create_voice_from_preview( voice_name=voice_name, voice_description=voice_description, generated_voice_id=generated_voice_id, labels=labels, played_not_selected_voice_ids=played_not_selected_voice_ids, request_options=request_options, ) return _response.data
Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.text_to_voice.create_voice_from_preview( voice_name="Sassy squeaky mouse", voice_description="A sassy squeaky mouse", generated_voice_id="37HceQefKmEi3bGovXjL", ) asyncio.run(main())
create_voice_from_preview
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/client.py
MIT
def create_previews( self, *, voice_description: str, output_format: typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] = None, text: typing.Optional[str] = OMIT, auto_generate_text: typing.Optional[bool] = OMIT, loudness: typing.Optional[float] = OMIT, quality: typing.Optional[float] = OMIT, seed: typing.Optional[int] = OMIT, guidance_scale: typing.Optional[float] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[VoiceDesignPreviewResponse]: """ Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[VoiceDesignPreviewResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/text-to-voice/create-previews", base_url=self._client_wrapper.get_environment().base, method="POST", params={ "output_format": output_format, }, json={ "voice_description": voice_description, "text": text, "auto_generate_text": auto_generate_text, "loudness": loudness, "quality": quality, "seed": seed, "guidance_scale": guidance_scale, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( VoiceDesignPreviewResponse, construct_type( type_=VoiceDesignPreviewResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[VoiceDesignPreviewResponse] Successful Response
create_previews
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/raw_client.py
MIT
def create_voice_from_preview( self, *, voice_name: str, voice_description: str, generated_voice_id: str, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, played_not_selected_voice_ids: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[Voice]: """ Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Voice] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/text-to-voice/create-voice-from-preview", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "voice_name": voice_name, "voice_description": voice_description, "generated_voice_id": generated_voice_id, "labels": labels, "played_not_selected_voice_ids": played_not_selected_voice_ids, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Voice, construct_type( type_=Voice, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Voice] Successful Response
create_voice_from_preview
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/raw_client.py
MIT
async def create_previews( self, *, voice_description: str, output_format: typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] = None, text: typing.Optional[str] = OMIT, auto_generate_text: typing.Optional[bool] = OMIT, loudness: typing.Optional[float] = OMIT, quality: typing.Optional[float] = OMIT, seed: typing.Optional[int] = OMIT, guidance_scale: typing.Optional[float] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[VoiceDesignPreviewResponse]: """ Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[VoiceDesignPreviewResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/text-to-voice/create-previews", base_url=self._client_wrapper.get_environment().base, method="POST", params={ "output_format": output_format, }, json={ "voice_description": voice_description, "text": text, "auto_generate_text": auto_generate_text, "loudness": loudness, "quality": quality, "seed": seed, "guidance_scale": guidance_scale, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( VoiceDesignPreviewResponse, construct_type( type_=VoiceDesignPreviewResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a voice from a text prompt. Parameters ---------- voice_description : str Description to use for the created voice. output_format : typing.Optional[TextToVoiceCreatePreviewsRequestOutputFormat] The output format of the generated audio. text : typing.Optional[str] Text to generate, text length has to be between 100 and 1000. auto_generate_text : typing.Optional[bool] Whether to automatically generate a text suitable for the voice description. loudness : typing.Optional[float] Controls the volume level of the generated voice. -1 is quietest, 1 is loudest, 0 corresponds to roughly -24 LUFS. quality : typing.Optional[float] Higher quality results in better voice output but less variety. seed : typing.Optional[int] Random number that controls the voice generation. Same seed with same inputs produces same voice. guidance_scale : typing.Optional[float] Controls how closely the AI follows the prompt. Lower numbers give the AI more freedom to be creative, while higher numbers force it to stick more to the prompt. High numbers can cause voice to sound artificial or robotic. We recommend to use longer, more detailed prompts at lower Guidance Scale. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[VoiceDesignPreviewResponse] Successful Response
create_previews
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/raw_client.py
MIT
async def create_voice_from_preview( self, *, voice_name: str, voice_description: str, generated_voice_id: str, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, played_not_selected_voice_ids: typing.Optional[typing.Sequence[str]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[Voice]: """ Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Voice] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/text-to-voice/create-voice-from-preview", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "voice_name": voice_name, "voice_description": voice_description, "generated_voice_id": generated_voice_id, "labels": labels, "played_not_selected_voice_ids": played_not_selected_voice_ids, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Voice, construct_type( type_=Voice, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Add a generated voice to the voice library. Parameters ---------- voice_name : str Name to use for the created voice. voice_description : str Description to use for the created voice. generated_voice_id : str The generated_voice_id to create, call POST /v1/text-to-voice/create-previews and fetch the generated_voice_id from the response header if don't have one yet. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Optional, metadata to add to the created voice. Defaults to None. played_not_selected_voice_ids : typing.Optional[typing.Sequence[str]] List of voice ids that the user has played but not selected. Used for RLHF. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Voice] Successful Response
create_voice_from_preview
python
elevenlabs/elevenlabs-python
src/elevenlabs/text_to_voice/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/text_to_voice/raw_client.py
MIT
def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> UsageCharactersResponseModel: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- UsageCharactersResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.usage.get( start_unix=1, end_unix=1, ) """ _response = self._raw_client.get( start_unix=start_unix, end_unix=end_unix, include_workspace_metrics=include_workspace_metrics, breakdown_type=breakdown_type, aggregation_interval=aggregation_interval, metric=metric, request_options=request_options, ) return _response.data
Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- UsageCharactersResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.usage.get( start_unix=1, end_unix=1, )
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/usage/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/usage/client.py
MIT
async def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> UsageCharactersResponseModel: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- UsageCharactersResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.usage.get( start_unix=1, end_unix=1, ) asyncio.run(main()) """ _response = await self._raw_client.get( start_unix=start_unix, end_unix=end_unix, include_workspace_metrics=include_workspace_metrics, breakdown_type=breakdown_type, aggregation_interval=aggregation_interval, metric=metric, request_options=request_options, ) return _response.data
Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- UsageCharactersResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.usage.get( start_unix=1, end_unix=1, ) asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/usage/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/usage/client.py
MIT
def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[UsageCharactersResponseModel]: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[UsageCharactersResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/usage/character-stats", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "start_unix": start_unix, "end_unix": end_unix, "include_workspace_metrics": include_workspace_metrics, "breakdown_type": breakdown_type, "aggregation_interval": aggregation_interval, "metric": metric, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( UsageCharactersResponseModel, construct_type( type_=UsageCharactersResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[UsageCharactersResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/usage/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/usage/raw_client.py
MIT
async def get( self, *, start_unix: int, end_unix: int, include_workspace_metrics: typing.Optional[bool] = None, breakdown_type: typing.Optional[BreakdownTypes] = None, aggregation_interval: typing.Optional[UsageAggregationInterval] = None, metric: typing.Optional[MetricType] = None, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[UsageCharactersResponseModel]: """ Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[UsageCharactersResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/usage/character-stats", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "start_unix": start_unix, "end_unix": end_unix, "include_workspace_metrics": include_workspace_metrics, "breakdown_type": breakdown_type, "aggregation_interval": aggregation_interval, "metric": metric, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( UsageCharactersResponseModel, construct_type( type_=UsageCharactersResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns the usage metrics for the current user or the entire workspace they are part of. The response provides a time axis based on the specified aggregation interval (default: day), with usage values for each interval along that axis. Usage is broken down by the selected breakdown type. For example, breakdown type "voice" will return the usage of each voice for each interval along the time axis. Parameters ---------- start_unix : int UTC Unix timestamp for the start of the usage window, in milliseconds. To include the first day of the window, the timestamp should be at 00:00:00 of that day. end_unix : int UTC Unix timestamp for the end of the usage window, in milliseconds. To include the last day of the window, the timestamp should be at 23:59:59 of that day. include_workspace_metrics : typing.Optional[bool] Whether or not to include the statistics of the entire workspace. breakdown_type : typing.Optional[BreakdownTypes] How to break down the information. Cannot be "user" if include_workspace_metrics is False. aggregation_interval : typing.Optional[UsageAggregationInterval] How to aggregate usage data over time. Can be "hour", "day", "week", "month", or "cumulative". metric : typing.Optional[MetricType] Which metric to aggregate. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[UsageCharactersResponseModel] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/usage/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/usage/raw_client.py
MIT
async def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> User: """ Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- User Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.user.get() asyncio.run(main()) """ _response = await self._raw_client.get(request_options=request_options) return _response.data
Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- User Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.user.get() asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/client.py
MIT
def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> HttpResponse[User]: """ Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[User] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/user", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( User, construct_type( type_=User, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[User] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/raw_client.py
MIT
async def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> AsyncHttpResponse[User]: """ Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[User] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/user", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( User, construct_type( type_=User, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets information about the user Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[User] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/raw_client.py
MIT
async def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> Subscription: """ Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Subscription Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.user.subscription.get() asyncio.run(main()) """ _response = await self._raw_client.get(request_options=request_options) return _response.data
Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Subscription Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.user.subscription.get() asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/subscription/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/subscription/client.py
MIT
def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> HttpResponse[Subscription]: """ Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Subscription] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/user/subscription", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Subscription, construct_type( type_=Subscription, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Subscription] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/subscription/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/subscription/raw_client.py
MIT
async def get(self, *, request_options: typing.Optional[RequestOptions] = None) -> AsyncHttpResponse[Subscription]: """ Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Subscription] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/user/subscription", base_url=self._client_wrapper.get_environment().base, method="GET", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Subscription, construct_type( type_=Subscription, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets extended information about the users subscription Parameters ---------- request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Subscription] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/user/subscription/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/user/subscription/raw_client.py
MIT
def get_all( self, *, show_legacy: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None ) -> GetVoicesResponse: """ Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get_all() """ _response = self._raw_client.get_all(show_legacy=show_legacy, request_options=request_options) return _response.data
Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get_all()
get_all
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def search( self, *, next_page_token: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, sort: typing.Optional[str] = None, sort_direction: typing.Optional[str] = None, voice_type: typing.Optional[str] = None, category: typing.Optional[str] = None, fine_tuning_state: typing.Optional[str] = None, collection_id: typing.Optional[str] = None, include_total_count: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetVoicesV2Response: """ Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesV2Response Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.search( include_total_count=True, ) """ _response = self._raw_client.search( next_page_token=next_page_token, page_size=page_size, search=search, sort=sort, sort_direction=sort_direction, voice_type=voice_type, category=category, fine_tuning_state=fine_tuning_state, collection_id=collection_id, include_total_count=include_total_count, request_options=request_options, ) return _response.data
Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesV2Response Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.search( include_total_count=True, )
search
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def get( self, voice_id: str, *, with_settings: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> Voice: """ Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get( voice_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.get(voice_id, with_settings=with_settings, request_options=request_options) return _response.data
Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get( voice_id="21m00Tcm4TlvDq8ikWAM", )
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def delete( self, voice_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> DeleteVoiceResponseModel: """ Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DeleteVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.delete( voice_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.delete(voice_id, request_options=request_options) return _response.data
Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DeleteVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.delete( voice_id="21m00Tcm4TlvDq8ikWAM", )
delete
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def update( self, voice_id: str, *, name: str, files: typing.Optional[typing.List[core.File]] = OMIT, remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> EditVoiceResponseModel: """ Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.update( voice_id="21m00Tcm4TlvDq8ikWAM", name="name", ) """ _response = self._raw_client.update( voice_id, name=name, files=files, remove_background_noise=remove_background_noise, description=description, labels=labels, request_options=request_options, ) return _response.data
Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.update( voice_id="21m00Tcm4TlvDq8ikWAM", name="name", )
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def get_shared( self, *, page_size: typing.Optional[int] = None, category: typing.Optional[VoicesGetSharedRequestCategory] = None, gender: typing.Optional[str] = None, age: typing.Optional[str] = None, accent: typing.Optional[str] = None, language: typing.Optional[str] = None, locale: typing.Optional[str] = None, search: typing.Optional[str] = None, use_cases: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, descriptives: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, featured: typing.Optional[bool] = None, min_notice_period_days: typing.Optional[int] = None, include_custom_rates: typing.Optional[bool] = None, include_live_moderated: typing.Optional[bool] = None, reader_app_enabled: typing.Optional[bool] = None, owner_id: typing.Optional[str] = None, sort: typing.Optional[str] = None, page: typing.Optional[int] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetLibraryVoicesResponse: """ Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get_shared( featured=True, reader_app_enabled=True, ) """ _response = self._raw_client.get_shared( page_size=page_size, category=category, gender=gender, age=age, accent=accent, language=language, locale=locale, search=search, use_cases=use_cases, descriptives=descriptives, featured=featured, min_notice_period_days=min_notice_period_days, include_custom_rates=include_custom_rates, include_live_moderated=include_live_moderated, reader_app_enabled=reader_app_enabled, owner_id=owner_id, sort=sort, page=page, request_options=request_options, ) return _response.data
Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.get_shared( featured=True, reader_app_enabled=True, )
get_shared
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def find_similar_voices( self, *, audio_file: typing.Optional[core.File] = OMIT, similarity_threshold: typing.Optional[float] = OMIT, top_k: typing.Optional[int] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> GetLibraryVoicesResponse: """ Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.find_similar_voices() """ _response = self._raw_client.find_similar_voices( audio_file=audio_file, similarity_threshold=similarity_threshold, top_k=top_k, request_options=request_options, ) return _response.data
Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.find_similar_voices()
find_similar_voices
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def get_all( self, *, show_legacy: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None ) -> GetVoicesResponse: """ Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get_all() asyncio.run(main()) """ _response = await self._raw_client.get_all(show_legacy=show_legacy, request_options=request_options) return _response.data
Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get_all() asyncio.run(main())
get_all
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def search( self, *, next_page_token: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, sort: typing.Optional[str] = None, sort_direction: typing.Optional[str] = None, voice_type: typing.Optional[str] = None, category: typing.Optional[str] = None, fine_tuning_state: typing.Optional[str] = None, collection_id: typing.Optional[str] = None, include_total_count: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetVoicesV2Response: """ Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesV2Response Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.search( include_total_count=True, ) asyncio.run(main()) """ _response = await self._raw_client.search( next_page_token=next_page_token, page_size=page_size, search=search, sort=sort, sort_direction=sort_direction, voice_type=voice_type, category=category, fine_tuning_state=fine_tuning_state, collection_id=collection_id, include_total_count=include_total_count, request_options=request_options, ) return _response.data
Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetVoicesV2Response Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.search( include_total_count=True, ) asyncio.run(main())
search
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def get( self, voice_id: str, *, with_settings: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> Voice: """ Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.get(voice_id, with_settings=with_settings, request_options=request_options) return _response.data
Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- Voice Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def delete( self, voice_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> DeleteVoiceResponseModel: """ Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DeleteVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.delete( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.delete(voice_id, request_options=request_options) return _response.data
Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DeleteVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.delete( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
delete
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def update( self, voice_id: str, *, name: str, files: typing.Optional[typing.List[core.File]] = OMIT, remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> EditVoiceResponseModel: """ Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.update( voice_id="21m00Tcm4TlvDq8ikWAM", name="name", ) asyncio.run(main()) """ _response = await self._raw_client.update( voice_id, name=name, files=files, remove_background_noise=remove_background_noise, description=description, labels=labels, request_options=request_options, ) return _response.data
Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- EditVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.update( voice_id="21m00Tcm4TlvDq8ikWAM", name="name", ) asyncio.run(main())
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def get_shared( self, *, page_size: typing.Optional[int] = None, category: typing.Optional[VoicesGetSharedRequestCategory] = None, gender: typing.Optional[str] = None, age: typing.Optional[str] = None, accent: typing.Optional[str] = None, language: typing.Optional[str] = None, locale: typing.Optional[str] = None, search: typing.Optional[str] = None, use_cases: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, descriptives: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, featured: typing.Optional[bool] = None, min_notice_period_days: typing.Optional[int] = None, include_custom_rates: typing.Optional[bool] = None, include_live_moderated: typing.Optional[bool] = None, reader_app_enabled: typing.Optional[bool] = None, owner_id: typing.Optional[str] = None, sort: typing.Optional[str] = None, page: typing.Optional[int] = None, request_options: typing.Optional[RequestOptions] = None, ) -> GetLibraryVoicesResponse: """ Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get_shared( featured=True, reader_app_enabled=True, ) asyncio.run(main()) """ _response = await self._raw_client.get_shared( page_size=page_size, category=category, gender=gender, age=age, accent=accent, language=language, locale=locale, search=search, use_cases=use_cases, descriptives=descriptives, featured=featured, min_notice_period_days=min_notice_period_days, include_custom_rates=include_custom_rates, include_live_moderated=include_live_moderated, reader_app_enabled=reader_app_enabled, owner_id=owner_id, sort=sort, page=page, request_options=request_options, ) return _response.data
Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.get_shared( featured=True, reader_app_enabled=True, ) asyncio.run(main())
get_shared
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
async def find_similar_voices( self, *, audio_file: typing.Optional[core.File] = OMIT, similarity_threshold: typing.Optional[float] = OMIT, top_k: typing.Optional[int] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> GetLibraryVoicesResponse: """ Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.find_similar_voices() asyncio.run(main()) """ _response = await self._raw_client.find_similar_voices( audio_file=audio_file, similarity_threshold=similarity_threshold, top_k=top_k, request_options=request_options, ) return _response.data
Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- GetLibraryVoicesResponse Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.find_similar_voices() asyncio.run(main())
find_similar_voices
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/client.py
MIT
def get_all( self, *, show_legacy: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[GetVoicesResponse]: """ Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetVoicesResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "show_legacy": show_legacy, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetVoicesResponse, construct_type( type_=GetVoicesResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetVoicesResponse] Successful Response
get_all
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def search( self, *, next_page_token: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, sort: typing.Optional[str] = None, sort_direction: typing.Optional[str] = None, voice_type: typing.Optional[str] = None, category: typing.Optional[str] = None, fine_tuning_state: typing.Optional[str] = None, collection_id: typing.Optional[str] = None, include_total_count: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[GetVoicesV2Response]: """ Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetVoicesV2Response] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v2/voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "next_page_token": next_page_token, "page_size": page_size, "search": search, "sort": sort, "sort_direction": sort_direction, "voice_type": voice_type, "category": category, "fine_tuning_state": fine_tuning_state, "collection_id": collection_id, "include_total_count": include_total_count, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetVoicesV2Response, construct_type( type_=GetVoicesV2Response, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetVoicesV2Response] Successful Response
search
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def get( self, voice_id: str, *, with_settings: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[Voice]: """ Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Voice] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "with_settings": with_settings, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Voice, construct_type( type_=Voice, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[Voice] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def delete( self, voice_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> HttpResponse[DeleteVoiceResponseModel]: """ Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[DeleteVoiceResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="DELETE", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( DeleteVoiceResponseModel, construct_type( type_=DeleteVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[DeleteVoiceResponseModel] Successful Response
delete
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def update( self, voice_id: str, *, name: str, files: typing.Optional[typing.List[core.File]] = OMIT, remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[EditVoiceResponseModel]: """ Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[EditVoiceResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}/edit", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "name": name, "remove_background_noise": remove_background_noise, "description": description, "labels": labels, }, files={ **({"files": files} if files is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( EditVoiceResponseModel, construct_type( type_=EditVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[EditVoiceResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def share( self, public_user_id: str, voice_id: str, *, new_name: str, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[AddVoiceResponseModel]: """ Add a shared voice to your collection of Voices Parameters ---------- public_user_id : str Public user ID used to publicly identify ElevenLabs users. voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. new_name : str The name that identifies this voice. This will be displayed in the dropdown of the website. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/add/{jsonable_encoder(public_user_id)}/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "new_name": new_name, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Add a shared voice to your collection of Voices Parameters ---------- public_user_id : str Public user ID used to publicly identify ElevenLabs users. voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. new_name : str The name that identifies this voice. This will be displayed in the dropdown of the website. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response
share
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def get_shared( self, *, page_size: typing.Optional[int] = None, category: typing.Optional[VoicesGetSharedRequestCategory] = None, gender: typing.Optional[str] = None, age: typing.Optional[str] = None, accent: typing.Optional[str] = None, language: typing.Optional[str] = None, locale: typing.Optional[str] = None, search: typing.Optional[str] = None, use_cases: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, descriptives: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, featured: typing.Optional[bool] = None, min_notice_period_days: typing.Optional[int] = None, include_custom_rates: typing.Optional[bool] = None, include_live_moderated: typing.Optional[bool] = None, reader_app_enabled: typing.Optional[bool] = None, owner_id: typing.Optional[str] = None, sort: typing.Optional[str] = None, page: typing.Optional[int] = None, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[GetLibraryVoicesResponse]: """ Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetLibraryVoicesResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/shared-voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "page_size": page_size, "category": category, "gender": gender, "age": age, "accent": accent, "language": language, "locale": locale, "search": search, "use_cases": use_cases, "descriptives": descriptives, "featured": featured, "min_notice_period_days": min_notice_period_days, "include_custom_rates": include_custom_rates, "include_live_moderated": include_live_moderated, "reader_app_enabled": reader_app_enabled, "owner_id": owner_id, "sort": sort, "page": page, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetLibraryVoicesResponse, construct_type( type_=GetLibraryVoicesResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetLibraryVoicesResponse] Successful Response
get_shared
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def find_similar_voices( self, *, audio_file: typing.Optional[core.File] = OMIT, similarity_threshold: typing.Optional[float] = OMIT, top_k: typing.Optional[int] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[GetLibraryVoicesResponse]: """ Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetLibraryVoicesResponse] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/similar-voices", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "similarity_threshold": similarity_threshold, "top_k": top_k, }, files={ **({"audio_file": audio_file} if audio_file is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetLibraryVoicesResponse, construct_type( type_=GetLibraryVoicesResponse, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[GetLibraryVoicesResponse] Successful Response
find_similar_voices
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def get_all( self, *, show_legacy: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[GetVoicesResponse]: """ Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetVoicesResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "show_legacy": show_legacy, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetVoicesResponse, construct_type( type_=GetVoicesResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns a list of all available voices for a user. Parameters ---------- show_legacy : typing.Optional[bool] If set to true, legacy premade voices will be included in responses from /v1/voices request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetVoicesResponse] Successful Response
get_all
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def search( self, *, next_page_token: typing.Optional[str] = None, page_size: typing.Optional[int] = None, search: typing.Optional[str] = None, sort: typing.Optional[str] = None, sort_direction: typing.Optional[str] = None, voice_type: typing.Optional[str] = None, category: typing.Optional[str] = None, fine_tuning_state: typing.Optional[str] = None, collection_id: typing.Optional[str] = None, include_total_count: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[GetVoicesV2Response]: """ Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetVoicesV2Response] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v2/voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "next_page_token": next_page_token, "page_size": page_size, "search": search, "sort": sort, "sort_direction": sort_direction, "voice_type": voice_type, "category": category, "fine_tuning_state": fine_tuning_state, "collection_id": collection_id, "include_total_count": include_total_count, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetVoicesV2Response, construct_type( type_=GetVoicesV2Response, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Gets a list of all available voices for a user with search, filtering and pagination. Parameters ---------- next_page_token : typing.Optional[str] The next page token to use for pagination. Returned from the previous request. page_size : typing.Optional[int] How many voices to return at maximum. Can not exceed 100, defaults to 10. Page 0 may include more voices due to default voices being included. search : typing.Optional[str] Search term to filter voices by. Searches in name, description, labels, category. sort : typing.Optional[str] Which field to sort by, one of 'created_at_unix' or 'name'. 'created_at_unix' may not be available for older voices. sort_direction : typing.Optional[str] Which direction to sort the voices in. 'asc' or 'desc'. voice_type : typing.Optional[str] Type of the voice to filter by. One of 'personal', 'community', 'default', 'workspace', 'non-default'. 'non-default' is equal to 'personal' plus 'community'. category : typing.Optional[str] Category of the voice to filter by. One of 'premade', 'cloned', 'generated', 'professional' fine_tuning_state : typing.Optional[str] State of the voice's fine tuning to filter by. Applicable only to professional voices clones. One of 'draft', 'not_verified', 'not_started', 'queued', 'fine_tuning', 'fine_tuned', 'failed', 'delayed' collection_id : typing.Optional[str] Collection ID to filter voices by. include_total_count : typing.Optional[bool] Whether to include the total count of voices found in the response. Incurs a performance cost. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetVoicesV2Response] Successful Response
search
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def get( self, voice_id: str, *, with_settings: typing.Optional[bool] = None, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[Voice]: """ Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Voice] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "with_settings": with_settings, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( Voice, construct_type( type_=Voice, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns metadata about a specific voice. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. with_settings : typing.Optional[bool] This parameter is now deprecated. It is ignored and will be removed in a future version. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[Voice] Successful Response
get
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def delete( self, voice_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> AsyncHttpResponse[DeleteVoiceResponseModel]: """ Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[DeleteVoiceResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="DELETE", request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( DeleteVoiceResponseModel, construct_type( type_=DeleteVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Deletes a voice by its ID. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[DeleteVoiceResponseModel] Successful Response
delete
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def update( self, voice_id: str, *, name: str, files: typing.Optional[typing.List[core.File]] = OMIT, remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[EditVoiceResponseModel]: """ Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[EditVoiceResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/{jsonable_encoder(voice_id)}/edit", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "name": name, "remove_background_noise": remove_background_noise, "description": description, "labels": labels, }, files={ **({"files": files} if files is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( EditVoiceResponseModel, construct_type( type_=EditVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Edit a voice created by you. Parameters ---------- voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.Optional[typing.List[core.File]] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[EditVoiceResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def share( self, public_user_id: str, voice_id: str, *, new_name: str, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[AddVoiceResponseModel]: """ Add a shared voice to your collection of Voices Parameters ---------- public_user_id : str Public user ID used to publicly identify ElevenLabs users. voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. new_name : str The name that identifies this voice. This will be displayed in the dropdown of the website. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/add/{jsonable_encoder(public_user_id)}/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "new_name": new_name, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Add a shared voice to your collection of Voices Parameters ---------- public_user_id : str Public user ID used to publicly identify ElevenLabs users. voice_id : str ID of the voice to be used. You can use the [Get voices](/docs/api-reference/voices/search) endpoint list all the available voices. new_name : str The name that identifies this voice. This will be displayed in the dropdown of the website. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response
share
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def get_shared( self, *, page_size: typing.Optional[int] = None, category: typing.Optional[VoicesGetSharedRequestCategory] = None, gender: typing.Optional[str] = None, age: typing.Optional[str] = None, accent: typing.Optional[str] = None, language: typing.Optional[str] = None, locale: typing.Optional[str] = None, search: typing.Optional[str] = None, use_cases: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, descriptives: typing.Optional[typing.Union[str, typing.Sequence[str]]] = None, featured: typing.Optional[bool] = None, min_notice_period_days: typing.Optional[int] = None, include_custom_rates: typing.Optional[bool] = None, include_live_moderated: typing.Optional[bool] = None, reader_app_enabled: typing.Optional[bool] = None, owner_id: typing.Optional[str] = None, sort: typing.Optional[str] = None, page: typing.Optional[int] = None, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[GetLibraryVoicesResponse]: """ Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetLibraryVoicesResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/shared-voices", base_url=self._client_wrapper.get_environment().base, method="GET", params={ "page_size": page_size, "category": category, "gender": gender, "age": age, "accent": accent, "language": language, "locale": locale, "search": search, "use_cases": use_cases, "descriptives": descriptives, "featured": featured, "min_notice_period_days": min_notice_period_days, "include_custom_rates": include_custom_rates, "include_live_moderated": include_live_moderated, "reader_app_enabled": reader_app_enabled, "owner_id": owner_id, "sort": sort, "page": page, }, request_options=request_options, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetLibraryVoicesResponse, construct_type( type_=GetLibraryVoicesResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Retrieves a list of shared voices. Parameters ---------- page_size : typing.Optional[int] How many shared voices to return at maximum. Can not exceed 100, defaults to 30. category : typing.Optional[VoicesGetSharedRequestCategory] Voice category used for filtering gender : typing.Optional[str] Gender used for filtering age : typing.Optional[str] Age used for filtering accent : typing.Optional[str] Accent used for filtering language : typing.Optional[str] Language used for filtering locale : typing.Optional[str] Locale used for filtering search : typing.Optional[str] Search term used for filtering use_cases : typing.Optional[typing.Union[str, typing.Sequence[str]]] Use-case used for filtering descriptives : typing.Optional[typing.Union[str, typing.Sequence[str]]] Search term used for filtering featured : typing.Optional[bool] Filter featured voices min_notice_period_days : typing.Optional[int] Filter voices with a minimum notice period of the given number of days. include_custom_rates : typing.Optional[bool] Include/exclude voices with custom rates include_live_moderated : typing.Optional[bool] Include/exclude voices that are live moderated reader_app_enabled : typing.Optional[bool] Filter voices that are enabled for the reader app owner_id : typing.Optional[str] Filter voices by public owner ID sort : typing.Optional[str] Sort criteria page : typing.Optional[int] request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetLibraryVoicesResponse] Successful Response
get_shared
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
async def find_similar_voices( self, *, audio_file: typing.Optional[core.File] = OMIT, similarity_threshold: typing.Optional[float] = OMIT, top_k: typing.Optional[int] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[GetLibraryVoicesResponse]: """ Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetLibraryVoicesResponse] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/similar-voices", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "similarity_threshold": similarity_threshold, "top_k": top_k, }, files={ **({"audio_file": audio_file} if audio_file is not None else {}), }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( GetLibraryVoicesResponse, construct_type( type_=GetLibraryVoicesResponse, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Returns a list of shared voices similar to the provided audio sample. If neither similarity_threshold nor top_k is provided, we will apply default values. Parameters ---------- audio_file : typing.Optional[core.File] See core.File for more documentation similarity_threshold : typing.Optional[float] Threshold for voice similarity between provided sample and library voices. Values range from 0 to 2. The smaller the value the more similar voices will be returned. top_k : typing.Optional[int] Number of most similar voices to return. If similarity_threshold is provided, less than this number of voices may be returned. Values range from 1 to 100. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[GetLibraryVoicesResponse] Successful Response
find_similar_voices
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/raw_client.py
MIT
def create( self, *, name: str, files: typing.List[core.File], remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AddVoiceIvcResponseModel: """ Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceIvcResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.ivc.create( name="name", ) """ _response = self._raw_client.create( name=name, files=files, remove_background_noise=remove_background_noise, description=description, labels=labels, request_options=request_options, ) return _response.data
Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceIvcResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.ivc.create( name="name", )
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/ivc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/ivc/client.py
MIT
async def create( self, *, name: str, files: typing.List[core.File], remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AddVoiceIvcResponseModel: """ Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceIvcResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.ivc.create( name="name", ) asyncio.run(main()) """ _response = await self._raw_client.create( name=name, files=files, remove_background_noise=remove_background_noise, description=description, labels=labels, request_options=request_options, ) return _response.data
Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceIvcResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.ivc.create( name="name", ) asyncio.run(main())
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/ivc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/ivc/client.py
MIT
def create( self, *, name: str, files: typing.List[core.File], remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[AddVoiceIvcResponseModel]: """ Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceIvcResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/voices/add", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "name": name, "remove_background_noise": remove_background_noise, "description": description, "labels": labels, }, files={ "files": files, }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceIvcResponseModel, construct_type( type_=AddVoiceIvcResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceIvcResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/ivc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/ivc/raw_client.py
MIT
async def create( self, *, name: str, files: typing.List[core.File], remove_background_noise: typing.Optional[bool] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[AddVoiceIvcResponseModel]: """ Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceIvcResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/voices/add", base_url=self._client_wrapper.get_environment().base, method="POST", data={ "name": name, "remove_background_noise": remove_background_noise, "description": description, "labels": labels, }, files={ "files": files, }, request_options=request_options, omit=OMIT, force_multipart=True, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceIvcResponseModel, construct_type( type_=AddVoiceIvcResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Create a voice clone and add it to your Voices Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. description : typing.Optional[str] A description of the voice. labels : typing.Optional[str] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceIvcResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/ivc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/ivc/raw_client.py
MIT
def update( self, voice_id: str, *, name: typing.Optional[str] = OMIT, language: typing.Optional[str] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AddVoiceResponseModel: """ Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.update( voice_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.update( voice_id, name=name, language=language, description=description, labels=labels, request_options=request_options, ) return _response.data
Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.update( voice_id="21m00Tcm4TlvDq8ikWAM", )
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/client.py
MIT
def train( self, voice_id: str, *, model_id: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> StartPvcVoiceTrainingResponseModel: """ Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- StartPvcVoiceTrainingResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.train( voice_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.train(voice_id, model_id=model_id, request_options=request_options) return _response.data
Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- StartPvcVoiceTrainingResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.train( voice_id="21m00Tcm4TlvDq8ikWAM", )
train
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/client.py
MIT
async def update( self, voice_id: str, *, name: typing.Optional[str] = OMIT, language: typing.Optional[str] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AddVoiceResponseModel: """ Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.pvc.update( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.update( voice_id, name=name, language=language, description=description, labels=labels, request_options=request_options, ) return _response.data
Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.pvc.update( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/client.py
MIT
async def train( self, voice_id: str, *, model_id: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> StartPvcVoiceTrainingResponseModel: """ Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- StartPvcVoiceTrainingResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.pvc.train( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main()) """ _response = await self._raw_client.train(voice_id, model_id=model_id, request_options=request_options) return _response.data
Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- StartPvcVoiceTrainingResponseModel Successful Response Examples -------- import asyncio from elevenlabs import AsyncElevenLabs client = AsyncElevenLabs( api_key="YOUR_API_KEY", ) async def main() -> None: await client.voices.pvc.train( voice_id="21m00Tcm4TlvDq8ikWAM", ) asyncio.run(main())
train
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/client.py
MIT
def create( self, *, name: str, language: str, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[AddVoiceResponseModel]: """ Creates a new PVC voice with metadata but no samples Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. language : str Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( "v1/voices/pvc", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "name": name, "language": language, "description": description, "labels": labels, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Creates a new PVC voice with metadata but no samples Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. language : str Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
def update( self, voice_id: str, *, name: typing.Optional[str] = OMIT, language: typing.Optional[str] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[AddVoiceResponseModel]: """ Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/pvc/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "name": name, "language": language, "description": description, "labels": labels, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[AddVoiceResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
def train( self, voice_id: str, *, model_id: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> HttpResponse[StartPvcVoiceTrainingResponseModel]: """ Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[StartPvcVoiceTrainingResponseModel] Successful Response """ _response = self._client_wrapper.httpx_client.request( f"v1/voices/pvc/{jsonable_encoder(voice_id)}/train", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "model_id": model_id, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( StartPvcVoiceTrainingResponseModel, construct_type( type_=StartPvcVoiceTrainingResponseModel, # type: ignore object_=_response.json(), ), ) return HttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- HttpResponse[StartPvcVoiceTrainingResponseModel] Successful Response
train
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
async def create( self, *, name: str, language: str, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[AddVoiceResponseModel]: """ Creates a new PVC voice with metadata but no samples Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. language : str Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( "v1/voices/pvc", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "name": name, "language": language, "description": description, "labels": labels, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Creates a new PVC voice with metadata but no samples Parameters ---------- name : str The name that identifies this voice. This will be displayed in the dropdown of the website. language : str Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
async def update( self, voice_id: str, *, name: typing.Optional[str] = OMIT, language: typing.Optional[str] = OMIT, description: typing.Optional[str] = OMIT, labels: typing.Optional[typing.Dict[str, typing.Optional[str]]] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[AddVoiceResponseModel]: """ Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/pvc/{jsonable_encoder(voice_id)}", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "name": name, "language": language, "description": description, "labels": labels, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( AddVoiceResponseModel, construct_type( type_=AddVoiceResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Edit PVC voice metadata Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. name : typing.Optional[str] The name that identifies this voice. This will be displayed in the dropdown of the website. language : typing.Optional[str] Language used in the samples. description : typing.Optional[str] Description to use for the created voice. labels : typing.Optional[typing.Dict[str, typing.Optional[str]]] Serialized labels dictionary for the voice. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[AddVoiceResponseModel] Successful Response
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
async def train( self, voice_id: str, *, model_id: typing.Optional[str] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AsyncHttpResponse[StartPvcVoiceTrainingResponseModel]: """ Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[StartPvcVoiceTrainingResponseModel] Successful Response """ _response = await self._client_wrapper.httpx_client.request( f"v1/voices/pvc/{jsonable_encoder(voice_id)}/train", base_url=self._client_wrapper.get_environment().base, method="POST", json={ "model_id": model_id, }, headers={ "content-type": "application/json", }, request_options=request_options, omit=OMIT, ) try: if 200 <= _response.status_code < 300: _data = typing.cast( StartPvcVoiceTrainingResponseModel, construct_type( type_=StartPvcVoiceTrainingResponseModel, # type: ignore object_=_response.json(), ), ) return AsyncHttpResponse(response=_response, data=_data) if _response.status_code == 422: raise UnprocessableEntityError( headers=dict(_response.headers), body=typing.cast( HttpValidationError, construct_type( type_=HttpValidationError, # type: ignore object_=_response.json(), ), ), ) _response_json = _response.json() except JSONDecodeError: raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response.text) raise ApiError(status_code=_response.status_code, headers=dict(_response.headers), body=_response_json)
Start PVC training process for a voice. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. model_id : typing.Optional[str] The model ID to use for the conversion. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AsyncHttpResponse[StartPvcVoiceTrainingResponseModel] Successful Response
train
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/raw_client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/raw_client.py
MIT
def create( self, voice_id: str, *, files: typing.List[core.File], remove_background_noise: typing.Optional[bool] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> typing.List[VoiceSample]: """ Add audio samples to a PVC voice Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.List[VoiceSample] Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.samples.create( voice_id="21m00Tcm4TlvDq8ikWAM", ) """ _response = self._raw_client.create( voice_id, files=files, remove_background_noise=remove_background_noise, request_options=request_options ) return _response.data
Add audio samples to a PVC voice Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. files : typing.List[core.File] See core.File for more documentation remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- typing.List[VoiceSample] Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.samples.create( voice_id="21m00Tcm4TlvDq8ikWAM", )
create
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/samples/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/samples/client.py
MIT
def update( self, voice_id: str, sample_id: str, *, remove_background_noise: typing.Optional[bool] = OMIT, selected_speaker_ids: typing.Optional[typing.Sequence[str]] = OMIT, trim_start_time: typing.Optional[int] = OMIT, trim_end_time: typing.Optional[int] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> AddVoiceResponseModel: """ Update a PVC voice sample - apply noise removal, or select speaker. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. sample_id : str Sample ID to be used remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. selected_speaker_ids : typing.Optional[typing.Sequence[str]] Speaker IDs to be used for PVC training. Make sure you send all the speaker IDs you want to use for PVC training in one request because the last request will override the previous ones. trim_start_time : typing.Optional[int] The start time of the audio to be used for PVC training. Time should be in milliseconds trim_end_time : typing.Optional[int] The end time of the audio to be used for PVC training. Time should be in milliseconds request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.samples.update( voice_id="21m00Tcm4TlvDq8ikWAM", sample_id="VW7YKqPnjY4h39yTbx2L", ) """ _response = self._raw_client.update( voice_id, sample_id, remove_background_noise=remove_background_noise, selected_speaker_ids=selected_speaker_ids, trim_start_time=trim_start_time, trim_end_time=trim_end_time, request_options=request_options, ) return _response.data
Update a PVC voice sample - apply noise removal, or select speaker. Parameters ---------- voice_id : str Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices. sample_id : str Sample ID to be used remove_background_noise : typing.Optional[bool] If set will remove background noise for voice samples using our audio isolation model. If the samples do not include background noise, it can make the quality worse. selected_speaker_ids : typing.Optional[typing.Sequence[str]] Speaker IDs to be used for PVC training. Make sure you send all the speaker IDs you want to use for PVC training in one request because the last request will override the previous ones. trim_start_time : typing.Optional[int] The start time of the audio to be used for PVC training. Time should be in milliseconds trim_end_time : typing.Optional[int] The end time of the audio to be used for PVC training. Time should be in milliseconds request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- AddVoiceResponseModel Successful Response Examples -------- from elevenlabs import ElevenLabs client = ElevenLabs( api_key="YOUR_API_KEY", ) client.voices.pvc.samples.update( voice_id="21m00Tcm4TlvDq8ikWAM", sample_id="VW7YKqPnjY4h39yTbx2L", )
update
python
elevenlabs/elevenlabs-python
src/elevenlabs/voices/pvc/samples/client.py
https://github.com/elevenlabs/elevenlabs-python/blob/master/src/elevenlabs/voices/pvc/samples/client.py
MIT