cartesia 0.0.5

The official Python library for the Cartesia API.

Cartesia Python API Library

The official Cartesia Python library which provides convenient access to the Cartesia REST and Websocket API from any Python 3.8+ application.

Note: This API is still in alpha. Please expect breaking changes and report any issues you encounter.

Installation

pip install cartesia

# pip install in editable mode w/ dev dependencies
pip install -e '.[dev]'

Usage

from cartesia.tts import CartesiaTTS
import pyaudio
import os

client = CartesiaTTS(api_key=os.environ.get("CARTESIA_API_KEY"))
voices = client.get_voices()
voice = client.get_voice_embedding(voice_id=voices["Graham"]["id"])
transcript = "Hello! Welcome to Cartesia"
model_id = "genial-planet-1346" # (Optional) We'll specify a default if you don't have a specific model in mind

p = pyaudio.PyAudio()

stream = None

# Generate and stream audio
for output in client.generate(transcript=transcript, voice=voice, model_id=model_id, stream=True):
    buffer = output["audio"]
    rate = output["sampling_rate"]

    if not stream:
        stream = p.open(format=pyaudio.paFloat32,
                        channels=1,
                        rate=rate,
                        output=True)

    # Write the audio data to the stream
    stream.write(buffer)

stream.stop_stream()
stream.close()
p.terminate()

You can also use the async client if you want to make asynchronous API calls:

from cartesia.tts import AsyncCartesiaTTS
import asyncio
import pyaudio
import os

async def write_stream():
    client = AsyncCartesiaTTS(api_key=os.environ.get("CARTESIA_API_KEY"))
    voices = client.get_voices()
    voice = client.get_voice_embedding(voice_id=voices["Graham"]["id"])
    transcript = "Hello! Welcome to Cartesia"
    model_id = "genial-planet-1346" # (Optional) We'll specify a default if you don't have a specific model in mind

    p = pyaudio.PyAudio()

    stream = None

    # Generate and stream audio
    async for output in await client.generate(transcript=transcript, voice=voice, model_id=model_id, stream=True):
        buffer = output["audio"]
        rate = output["sampling_rate"]

        if not stream:
            stream = p.open(format=pyaudio.paFloat32,
                            channels=1,
                            rate=rate,
                            output=True)

        # Write the audio data to the stream
        stream.write(buffer)

    stream.stop_stream()
    stream.close()
    p.terminate()

asyncio.run(write_stream())

If you are using Jupyter Notebook or JupyterLab, you can use IPython.display.Audio to play the generated audio directly in the notebook. Additionally, in these notebook examples we show how to use the client as a context manager (though this is not required).

from IPython.display import Audio
import io
import os
import numpy as np

from cartesia.tts import CartesiaTTS

with CartesiaTTS(api_key=os.environ.get("CARTESIA_API_KEY")) as client:
    voices = client.get_voices()
    voice = client.get_voice_embedding(voice_id=voices["Graham"]["id"])
    transcript = "Hello! Welcome to Cartesia"

    # Create a BytesIO object to store the audio data
    audio_data = io.BytesIO()

    # Generate and stream audio
    for output in client.generate(transcript=transcript, voice=voice, stream=True):
        buffer = output["audio"]
        audio_data.write(buffer)

# Set the cursor position to the beginning of the BytesIO object
audio_data.seek(0)

# Create an Audio object from the BytesIO data
audio = Audio(np.frombuffer(audio_data.read(), dtype=np.float32), rate=output["sampling_rate"])

# Display the Audio object
display(audio)

Below is the same example using the async client:

from IPython.display import Audio
import io
import os
import numpy as np

from cartesia.tts import AsyncCartesiaTTS

async with AsyncCartesiaTTS(api_key=os.environ.get("CARTESIA_API_KEY")) as client:
    voices = client.get_voices()
    voice = client.get_voice_embedding(voice_id=voices["Graham"]["id"])
    transcript = "Hello! Welcome to Cartesia"

    # Create a BytesIO object to store the audio data
    audio_data = io.BytesIO()

    # Generate and stream audio
    async for output in await client.generate(transcript=transcript, voice=voice, stream=True):
        buffer = output["audio"]
        audio_data.write(buffer)

# Set the cursor position to the beginning of the BytesIO object
audio_data.seek(0)

# Create an Audio object from the BytesIO data
audio = Audio(np.frombuffer(audio_data.read(), dtype=np.float32), rate=output["sampling_rate"])

# Display the Audio object
display(audio)

To avoid storing your API key in the source code, we recommend doing one of the following:

1. Use python-dotenv to add CARTESIA_API_KEY="my-api-key" to your .env file.
2. Set the CARTESIA_API_KEY environment variable, preferably to a secure shell init file (e.g. ~/.zshrc, ~/.bashrc)