ElevenLabs Python Library
The official Python SDK for ElevenLabs. ElevenLabs brings the most compelling, rich and lifelike voices to creators and developers in just a few lines of code.
📖 API & Docs
Check out the HTTP API documentation.
Install
Usage
Main Models
-
Eleven v3 (
eleven_v3)- Dramatic delivery and performances
- 70+ languages supported
- Supported for natural multi-speaker dialogue
-
Eleven Multilingual v2 (
eleven_multilingual_v2)- Excels in stability, language diversity, and accent accuracy
- Supports 29 languages
- Recommended for most use cases
-
Eleven Flash v2.5 (
eleven_flash_v2_5)- Ultra-low latency
- Supports 32 languages
- Faster model, 50% lower price per character
-
Eleven Turbo v2.5 (
eleven_turbo_v2_5)- Good balance of quality and latency
- Ideal for developer use cases where speed is crucial
- Supports 32 languages
For more detailed information about these models and others, visit the ElevenLabs Models documentation.
from dotenv import load_dotenv from elevenlabs.client import ElevenLabs from elevenlabs.play import play load_dotenv() elevenlabs = ElevenLabs() audio = elevenlabs.text_to_speech.convert( text="The first move is what sets everything in motion.", voice_id="JBFqnCBsd6RMkjVDRZzb", model_id="eleven_v3", output_format="mp3_44100_128", ) play(audio)
Play
🎧 Try it out! Want to hear our voices in action? Visit the ElevenLabs Voice Lab to experiment with different voices, languages, and settings.
Voices
List all your available voices with search().
from elevenlabs.client import ElevenLabs elevenlabs = ElevenLabs( api_key="YOUR_API_KEY", ) response = elevenlabs.voices.search() print(response.voices)
For information about the structure of the voices output, please refer to the official ElevenLabs API documentation for Get Voices.
Build a voice object with custom settings to personalize the voice style, or call
elevenlabs.voices.settings.get("your-voice-id") to get the default settings for the voice.
Clone Voice
Clone your voice in an instant. Note that voice cloning requires an API key, see below.
from elevenlabs.client import ElevenLabs from elevenlabs.play import play elevenlabs = ElevenLabs( api_key="YOUR_API_KEY", ) voice = elevenlabs.voices.ivc.create( name="Alex", description="An old American male voice with a slight hoarseness in his throat. Perfect for news", # Optional files=["./sample_0.mp3", "./sample_1.mp3", "./sample_2.mp3"], )
Streaming
Stream audio in real-time, as it's being generated.
from elevenlabs import stream from elevenlabs.client import ElevenLabs elevenlabs = ElevenLabs( api_key="YOUR_API_KEY", ) audio_stream = elevenlabs.text_to_speech.stream( text="This is a test", voice_id="JBFqnCBsd6RMkjVDRZzb", model_id="eleven_multilingual_v2" ) # option 1: play the streamed audio locally stream(audio_stream) # option 2: process the audio bytes manually for chunk in audio_stream: if isinstance(chunk, bytes): print(chunk)
Async Client
Use AsyncElevenLabs if you want to make API calls asynchronously.
import asyncio from elevenlabs.client import AsyncElevenLabs elevenlabs = AsyncElevenLabs( api_key="MY_API_KEY" ) async def print_models() -> None: models = await elevenlabs.models.list() print(models) asyncio.run(print_models())
ElevenAgents
Build interactive AI agents with real-time audio capabilities using ElevenAgents.
Basic Usage
from elevenlabs.client import ElevenLabs from elevenlabs.conversational_ai.conversation import Conversation, ClientTools from elevenlabs.conversational_ai.default_audio_interface import DefaultAudioInterface elevenlabs = ElevenLabs( api_key="YOUR_API_KEY", ) # Create audio interface for real-time audio input/output audio_interface = DefaultAudioInterface() # Create conversation conversation = Conversation( client=elevenlabs, agent_id="your-agent-id", requires_auth=True, audio_interface=audio_interface, ) # Start the conversation conversation.start_session() # The conversation runs in background until you call: conversation.end_session()
Custom Event Loop Support
For advanced use cases involving context propagation, resource reuse, or specific event loop management, ClientTools supports custom asyncio event loops:
import asyncio from elevenlabs.conversational_ai.conversation import ClientTools elevenlabs = ElevenLabs( api_key="YOUR_API_KEY", ) async def main(): # Get the current event loop custom_loop = asyncio.get_running_loop() # Create ClientTools with custom loop to prevent "different event loop" errors client_tools = ClientTools(loop=custom_loop) # Register your tools async def get_weather(params): location = params.get("location", "Unknown") # Your async logic here return f"Weather in {location}: Sunny, 72°F" client_tools.register("get_weather", get_weather, is_async=True) # Use with conversation conversation = Conversation( client=elevenlabs, agent_id="your-agent-id", requires_auth=True, audio_interface=audio_interface, client_tools=client_tools ) asyncio.run(main())
Benefits of Custom Event Loop:
- Context Propagation: Maintain request-scoped state across async operations
- Resource Reuse: Share existing async resources like HTTP sessions or database pools
- Loop Management: Prevent "Task got Future attached to a different event loop" errors
- Performance: Better control over async task scheduling and execution
Important: When using a custom loop, you're responsible for its lifecycle Don't close the loop while ClientTools are still using it.
Tool Registration
Register custom tools that the AI agent can call during conversations:
client_tools = ClientTools() # Sync tool def calculate_sum(params): numbers = params.get("numbers", []) return sum(numbers) # Async tool async def fetch_data(params): url = params.get("url") # Your async HTTP request logic return {"data": "fetched"} client_tools.register("calculate_sum", calculate_sum, is_async=False) client_tools.register("fetch_data", fetch_data, is_async=True)
Languages Supported
Explore all models & languages.
Contributing
While we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!
On the other hand, contributions to the README are always very welcome!
