This client provides convenient access to Cartesia's TTS models. Sonic is the fastest text-to-speech model around—it can generate a second of audio in just 650ms, and it can stream out the first audio chunk in just 135ms. Alongside Sonic, we also offer an extensive prebuilt voice library for a variety of use cases.
The JavaScript client is a thin wrapper around the Cartesia API. You can view docs for the API at docs.cartesia.ai.
# NPM
npm install @cartesia/cartesia-js
# Yarn
yarn add @cartesia/cartesia-js
# PNPM
pnpm add @cartesia/cartesia-js
# Bun
bun add @cartesia/cartesia-jsimport Cartesia from "@cartesia/cartesia-js";
const cartesia = new Cartesia({
apiKey: "your-api-key",
});
// List all voices.
const voices = await cartesia.voices.list();
console.log(voices);
// Get a voice.
const voice = await cartesia.voices.get("<voice-id>");
console.log(voice);
// Clone a voice from a file.
const clonedVoiceEmbedding = await cartesia.voices.clone({
mode: "clip",
clip: myFile, // Pass a File object or a Blob.
});
// Mix voices together.
const mixedVoiceEmbedding = await cartesia.voices.mix({
voices: [{ id: "<voice-id-1>", weight: 0.6 }, { id: "<voice-id-2>", weight: 0.4 }],
});
// Create a voice.
const newVoice = await cartesia.voices.create({
name: "Tim",
description: "A deep, resonant voice.",
embedding: Array(192).fill(1.0),
});
console.log(newVoice);import Cartesia from "@cartesia/cartesia-js";
const cartesia = new Cartesia({
apiKey: "your-api-key",
});
// Initialize the WebSocket. Make sure the output format you specify is supported.
const websocket = cartesia.tts.websocket({
container: "raw",
encoding: "pcm_f32le",
sampleRate: 44100
});
try {
await websocket.connect();
} catch (error) {
console.error(`Failed to connect to Cartesia: ${error}`);
}
// Create a stream.
const response = await websocket.send({
model_id: "sonic-english",
voice: {
mode: "id",
id: "a0e99841-438c-4a64-b679-ae501e7d6091",
},
transcript: "Hello, world!"
// The WebSocket sets output_format on your behalf.
});
// Access the raw messages from the WebSocket.
response.on("message", (message) => {
// Raw message.
console.log("Received message:", message);
});
// You can also access messages using a for-await-of loop.
for await (const message of response.events('message')) {
// Raw message.
console.log("Received message:", message);
}You can perform input streaming with contexts as described in the docs. The WebSocket's send method is just a wrapper around sending a message on the WebSocket, so the request format specified the docs can be used directly.
You should use the return from the first send call on a context to receive outputs and events for the entire context. You can ignore the return values of subsequent send calls.
To receive timestamps in responses, set the add_timestamps field in the request object to true.
const response = await websocket.send({
model_id: "sonic-english",
voice: {
mode: "id",
id: "a0e99841-438c-4a64-b679-ae501e7d6091",
},
transcript: "Hello, world!",
add_timestamps: true,
});You can then listen for timestamps on the returned response object.
response.on("timestamps", (timestamps) => {
console.log("Received timestamps for words:", timestamps.words);
console.log("Words start at:", timestamps.start);
console.log("Words end at:", timestamps.end);
});
// You can also access timestamps using a for-await-of loop.
for (await const timestamps of response.events('timestamps')) {
console.log("Received timestamps for words:", timestamps.words);
console.log("Words start at:", timestamps.start);
console.log("Words end at:", timestamps.end);
}The API has experimental support for speed and emotion controls that is not subject to semantic versioning and is subject to change without notice. You can control the speed and emotion of the synthesized speech by setting the speed and emotion fields under voice.__experimental_controls in the request object.
const response = await websocket.send({
model_id: "sonic-english",
voice: {
mode: "id",
id: "a0e99841-438c-4a64-b679-ae501e7d6091",
__experimental_controls: {
speed: "fastest",
emotion: ["sadness", "surprise:high"],
},
},
transcript: "Hello, world!",
});You can define the language of the text you want to synthesize by setting the language field in the request object. Make sure that you are using model_id: "sonic-multilingual" in the request object.
Supported languages are listed at docs.cartesia.ai.
(The WebPlayer class only supports playing audio in the browser and the raw PCM format with fp32le encoding.)
// If you're using the client in the browser, you can control audio playback using our WebPlayer:
import { WebPlayer } from "@cartesia/cartesia-js";
console.log("Playing stream...");
// Create a Player object.
const player = new WebPlayer();
// Play the audio. (`response` includes a custom Source object that the Player can play.)
// The call resolves when the audio finishes playing.
await player.play(response.source);
console.log("Done playing.");We export a React hook that simplifies the process of using the TTS API. The hook manages the WebSocket connection and provides a simple interface for buffering, playing, pausing and restarting audio.
import { useTTS } from '@cartesia/cartesia-js/react';
function TextToSpeech() {
const tts = useTTS({
apiKey: "your-api-key",
sampleRate: 44100,
})
const [text, setText] = useState("");
const handlePlay = async () => {
// Begin buffering the audio.
const response = await tts.buffer({
model_id: "sonic-english",
voice: {
mode: "id",
id: "a0e99841-438c-4a64-b679-ae501e7d6091",
},
transcript: text,
});
// Immediately play the audio. (You can also buffer in advance and play later.)
await tts.play();
}
return (
<div>
<input type="text" value={text} onChange={(event) => setText(event.target.value)} />
<button onClick={handlePlay}>Play</button>
<div>
{tts.playbackStatus} | {tts.bufferStatus} | {tts.isWaiting}
</div>
</div>
);
}