Q: How do I convert text to speech in Python?

Install cartesia , set CARTESIA_API_KEY in your server environment, and create a Cartesia client. Call client.tts.generate with your transcript, model, voice ID, and output format, then save the response with write_to_file . The example on this page produces speech.wav . See the Python examples for complete requests.

Q: Can I use Cartesia with async Python or FastAPI?

Yes. Use AsyncCartesia and await its API calls in an async application. The SDK's async examples show generation, file output, and streaming. Connect the returned audio to your application's response or player, and close the client when its lifecycle ends.

Question 1

How do I convert text to speech in Python?

Accepted Answer

Install cartesia, set CARTESIA_API_KEY in your server environment, and create a Cartesia client. Call client.tts.generate with your transcript, model, voice ID, and output format, then save the response with write_to_file. The example on this page produces speech.wav. See the Python examples for complete requests.

Question 2

Which Python version and SDK do I need?

Accepted Answer

The official SDK requires Python 3.9 or later. Install it with python -m pip install --upgrade cartesia. For WebSocket support, install python -m pip install "cartesia[websockets]". Check your installed package version against the SDK documentation when adapting an older example.

Question 3

Can I save generated speech as WAV or MP3?

Accepted Answer

Yes. The TTS endpoint supports WAV, MP3, and raw audio output. Choose the container and its supported settings in output_format before generating speech. Use WAV for the example on this page; choose MP3 when your application needs that format. Changing a filename extension alone does not convert the audio.

Question 4

How do I stream an LLM response into speech with Python?

Accepted Answer

Use a WebSocket when your application receives text a piece at a time. Send those text chunks through a shared generation context and consume the returned audio chunks as they arrive. Your application still needs to buffer and play that audio. The WebSocket API explains continuation and cancellation for conversational applications.

Question 5

Should I use HTTP or WebSockets for text-to-speech?

Accepted Answer

Use HTTP when the transcript is already available, such as a complete narration or notification. An HTTP response can deliver audio progressively too. Use WebSockets when you need to send text incrementally or manage a continuing conversation. Streaming input and streaming output are separate choices; saving a file is not the only way to consume an HTTP response.

Question 6

Can I use Cartesia with async Python or FastAPI?

Accepted Answer

Yes. Use AsyncCartesia and await its API calls in an async application. The SDK's async examples show generation, file output, and streaming. Connect the returned audio to your application's response or player, and close the client when its lifecycle ends.

Question 7

Where should I store my Cartesia API key?

Accepted Answer

Keep your long-lived key in a server environment variable or deployment secret manager. Do not commit it or send it to browser code. If the browser needs a direct connection, have your backend create a scoped, short-lived token through the access-token API.

Question 8

How do I choose a voice and language for Python TTS?

Accepted Answer

Preview a voice in the Playground and pass its ID in the request. Set language or locale for your transcript, but not both. Test names, numbers, and abbreviations from your own scripts. See the request reference for language and voice settings rather than assuming every voice has the same accent support.

Question 9

Which Sonic model ID should I use in production?

Accepted Answer

Choose a model from the current Sonic documentation and test it with your application. The sonic-3.6 ID receives stable snapshot updates. A published dated snapshot keeps model behavior fixed while you evaluate a newer release. Record the model ID alongside your tests so you can compare results after an upgrade.

Question 10

Why does raw PCM need special playback settings?

Accepted Answer

Raw PCM does not contain a file header describing how to play it. The player needs the sample rate and encoding used in your request. A mismatch can produce noise, silence, or speech at the wrong speed. Start with a WAV output to check the generated speech separately from your streaming player, then test the raw-audio playback path.

Question 11

What should I handle before using Python TTS in production?

Accepted Answer

Handle authentication failures, rate limits, network errors, and timeouts. Configure the SDK's retries and timeouts to fit your application. Test interrupted playback and avoid replaying queued audio after the user changes direction. Measure from text becoming available to audible speech, including your network and playback buffer.

Python text to speech API for real-time applications

Your first text-to-speech request

Install the SDK

Set your API key

Generate your first recording

Choose how audio reaches your app

Save a recording

Speak as text arrives

Stream audio from a complete script

Keep your key on the server

Your Python server

Sonic

Your application

From a script to a production service

Fit your Python stack

Test the full listening experience

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