Reference

History

client.history.get_all(...)

📝 Description

Returns metadata about all your generated audio.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.history.get_all()

⚙️ Parameters

page_size: typing.Optional[int] — How many history items to return at maximum. Can not exceed 1000, defaults to 100.

start_after_history_item_id: typing.Optional[str] — After which ID to start fetching, use this parameter to paginate across a large collection of history items. In case this parameter is not provided history items will be fetched starting from the most recently created one ordered descending by their creation date.

voice_id: typing.Optional[str] — Voice ID to be filtered for, you can use GET https://api.elevenlabs.io/v1/voices to receive a list of voices and their IDs.

search: typing.Optional[str] — search term used for filtering

source: typing.Optional[HistoryGetAllRequestSource] — Source of the generated history item

request_options: typing.Optional[RequestOptions] — Request-specific configuration.

client.history.get(...)

📝 Description

Returns information about an history item by its ID.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.history.get(
    history_item_id="HISTORY_ITEM_ID",
)

⚙️ Parameters

history_item_id: str — History item ID to be used, you can use GET https://api.elevenlabs.io/v1/history to receive a list of history items and their IDs.

request_options: typing.Optional[RequestOptions] — Request-specific configuration.

client.history.delete(...)

📝 Description

Delete a history item by its ID

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.history.delete(
    history_item_id="HISTORY_ITEM_ID",
)

⚙️ Parameters

history_item_id: str — History item ID to be used, you can use GET https://api.elevenlabs.io/v1/history to receive a list of history items and their IDs.

request_options: typing.Optional[RequestOptions] — Request-specific configuration.

client.history.get_audio(...)

📝 Description

Returns the audio of an history item.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.history.get_audio(
    history_item_id="HISTORY_ITEM_ID",
)

⚙️ Parameters

history_item_id: str — History item ID to be used, you can use GET https://api.elevenlabs.io/v1/history to receive a list of history items and their IDs.

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.

client.history.download(...)

📝 Description

Download one or more history items. If one history item ID is provided, we will return a single audio file. If more than one history item IDs are provided, we will provide the history items packed into a .zip file.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.history.download(
    history_item_ids=["HISTORY_ITEM_ID"],
)

⚙️ Parameters

history_item_ids: typing.Sequence[str] — A list of history items to download, you can get IDs of history items and other metadata using the GET https://api.elevenlabs.io/v1/history endpoint.

output_format: typing.Optional[str] — Output format to transcode the audio file, can be wav or default.

request_options: typing.Optional[RequestOptions] — Request-specific configuration.

TextToSoundEffects

client.text_to_sound_effects.convert(...)

📝 Description

Converts a text of your choice into sound

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.text_to_sound_effects.convert(
    text="Spacious braam suitable for high-impact movie trailer moments",
)

⚙️ Parameters

text: str — The text that will get converted into a sound effect.

duration_seconds: typing.Optional[float] — The duration of the sound which will be generated in seconds. Must be at least 0.5 and at most 22. If set to None we will guess the optimal duration using the prompt. Defaults to None.

prompt_influence: typing.Optional[float] — A higher prompt influence makes your generation follow the prompt more closely while also making generations less variable. Must be a value between 0 and 1. Defaults to 0.3.

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.

AudioIsolation

samples

client.samples.delete(...)

📝 Description

Removes a sample by its ID.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.samples.delete(
    voice_id="VOICE_ID",
    sample_id="SAMPLE_ID",
)

⚙️ 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, you can use GET https://api.elevenlabs.io/v1/voices/{voice_id} to list all the available samples for a voice.

request_options: typing.Optional[RequestOptions] — Request-specific configuration.

client.samples.get_audio(...)

📝 Description

Returns the audio corresponding to a sample attached to a voice.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.samples.get_audio(
    voice_id="VOICE_ID",
    sample_id="SAMPLE_ID",
)

⚙️ 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, you can use GET https://api.elevenlabs.io/v1/voices/{voice_id} to list all the available samples for a voice.

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.

TextToSpeech

client.text_to_speech.convert(...)

📝 Description

Converts text into speech using a voice of your choice and returns audio.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.text_to_speech.convert(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    output_format="mp3_44100_128",
    text="The first move is what sets everything in motion.",
    model_id="eleven_multilingual_v2",
)

⚙️ Parameters

voice_id: str — Voice ID to be used, you can use https://api.elevenlabs.io/v1/voices to list all the available voices.

text: str — The text that will get converted into speech.

enable_logging: typing.Optional[bool] — When enable_logging is set to false full privacy mode will be used for the request. This will mean history features are unavailable for this request, including request stitching. Full privacy mode may only be used by enterprise customers.

optimize_streaming_latency: typing.Optional[int]

You can turn on latency optimizations at some cost of quality. The best possible final latency varies by model. Possible values: 0 - default mode (no latency optimizations) 1 - normal latency optimizations (about 50% of possible latency improvement of option 3) 2 - strong latency optimizations (about 75% of possible latency improvement of option 3) 3 - max latency optimizations 4 - max latency optimizations, but also with text normalizer turned off for even more latency savings (best latency, but can mispronounce eg numbers and dates).

Defaults to None.

output_format: typing.Optional[OutputFormat] — The output format of the generated audio.

model_id: typing.Optional[str] — Identifier of the model that will be used, you can query them using GET /v1/models. The model needs to have support for text to speech, you can check this using the can_do_text_to_speech property.

language_code: typing.Optional[str] — Language code (ISO 639-1) used to enforce a language for the model. Currently only Turbo v2.5 supports language enforcement. For other models, an error will be returned if language code is provided.

voice_settings: typing.Optional[VoiceSettings] — Voice settings overriding stored setttings for the given voice. They are applied only on the given request.

pronunciation_dictionary_locators: typing.Optional[typing.Sequence[PronunciationDictionaryVersionLocator]] — A list of pronunciation dictionary locators (id, version_id) to be applied to the text. They will be applied in order. You may have up to 3 locators per request

seed: typing.Optional[int] — If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed. Must be integer between 0 and 4294967295.

previous_text: typing.Optional[str] — The text that came before the text of the current request. Can be used to improve the flow of prosody when concatenating together multiple generations or to influence the prosody in the current generation.

next_text: typing.Optional[str] — The text that comes after the text of the current request. Can be used to improve the flow of prosody when concatenating together multiple generations or to influence the prosody in the current generation.

previous_request_ids: typing.Optional[typing.Sequence[str]] — A list of request_id of the samples that were generated before this generation. Can be used to improve the flow of prosody when splitting up a large task into multiple requests. The results will be best when the same model is used across the generations. In case both previous_text and previous_request_ids is send, previous_text will be ignored. A maximum of 3 request_ids can be send.

next_request_ids: typing.Optional[typing.Sequence[str]] — A list of request_id of the samples that were generated before this generation. Can be used to improve the flow of prosody when splitting up a large task into multiple requests. The results will be best when the same model is used across the generations. In case both next_text and next_request_ids is send, next_text will be ignored. A maximum of 3 request_ids can be send.

use_pvc_as_ivc: typing.Optional[bool] — If true, we won't use PVC version of the voice for the generation but the IVC version. This is a temporary workaround for higher latency in PVC versions.

apply_text_normalization: typing.Optional[BodyTextToSpeechV1TextToSpeechVoiceIdPostApplyTextNormalization] — This parameter controls text normalization with three modes: 'auto', 'on', and 'off'. When set to 'auto', the system will automatically decide whether to apply text normalization (e.g., spelling out numbers). With 'on', text normalization will always be applied, while with 'off', it will be skipped. Cannot be turned on for 'eleven_turbo_v2_5' model.

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.

client.text_to_speech.convert_with_timestamps(...)

📝 Description

Converts text into speech using a voice of your choice and returns JSON containing audio as a base64 encoded string together with information on when which character was spoken.

🔌 Usage

from elevenlabs import ElevenLabs

client = ElevenLabs(
    api_key="YOUR_API_KEY",
)
client.text_to_speech.convert_with_timestamps(
    voice_id="JBFqnCBsd6RMkjVDRZzb",
    output_format="mp3_44100_128",
    text="The first move is what sets everything in motion.",
    model_id="eleven_multilingual_v2",
)