Provider Tts Localhost

5.3.6. TTS Localhost Provider

Run Resemble AI Chatterbox on the host with the chatterbox-tts-api server. Atlas containers reach it through host.docker.internal. Select it with TTS_PROVIDER_SOURCE=chatterbox-localhost.

Use this source for zero-shot voice cloning without an NVIDIA container. The server runs on macOS (MPS) and on Linux (CPU or CUDA).

1. When to use it

• macOS: Docker Desktop containers cannot use MPS. A host install can.
• No large GPU: the chatterbox-container-gpu source needs an NVIDIA GPU; upstream recommends 8 GB+ memory. The host server can run on the CPU, but slowly.
• Voice samples on the host: the voice library is a host directory, not a container volume.

For TTS with no host setup, use TTS_PROVIDER_SOURCE=speaches-container-cpu. Speaches provides Kokoro voices but no voice cloning.

Atlas publishes no speed figures for Chatterbox. Benchmark representative text on the deployment host.

2. Install

The chatterbox-tts-api 1.0.0 package on PyPI contains no code, so install from the repository. Its pyproject.toml requires Python 3.11.

git clone https://github.com/travisvn/chatterbox-tts-api
cd chatterbox-tts-api

# With uv (creates the virtual environment):
uv sync

# Or with pip:
python3.11 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

The chatterbox-tts model library installs from a git source, so the first install can take a few minutes.

3. Run the server

main.py is the entry point. It listens on PORT (default 4123) and HOST (default 0.0.0.0).

# 63044 is the CHATTERBOX_LOCALHOST_PORT default. It is independent of the
# container CHATTERBOX_PORT, which is 63059.
PORT=63044 uv run main.py
# or, in an activated virtual environment:
PORT=63044 python main.py

The server starts, then loads the model in the background. The first start downloads the weights from Hugging Face (about 2 GB). GET /health responds during the load and reports the initialization state.

The server has no authentication. With the default HOST=0.0.0.0, it is reachable from the local network as well as from Docker. Use the host firewall when the network is not trusted.

The device setting DEVICE=auto selects MPS on Apple Silicon. Set DEVICE=mps if detection fails, or DEVICE=cpu to force the CPU.

In another terminal, from the Atlas repository root, select the source:

./start.sh --tts-provider-source chatterbox-localhost

If the server uses another port, set it in .env. Atlas derives the URL http://host.docker.internal:${CHATTERBOX_LOCALHOST_PORT:-63044}:

CHATTERBOX_LOCALHOST_PORT=9000

4. Verify

curl http://localhost:63044/health         # expect "status": "healthy" once loaded
curl http://localhost:63044/v1/models      # expect chatterbox-tts-1 in the list
curl -X POST http://localhost:63044/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"chatterbox-tts-1","input":"hello world","voice":"alloy"}' \
  --output /tmp/test.wav
file /tmp/test.wav   # expect: RIFF (little-endian) data, WAVE audio

5. Voice cloning

Chatterbox has two voice-cloning paths. Neither uses a reference_audio JSON field.

1) Add a voice to the server's voice library, then use its name:

# Upload once (multipart). Use a short, clean speech clip.
curl -X POST http://localhost:63044/voices \
  -F "voice_name=alice" \
  -F "voice_file=@ALICE.wav"

# Use the registered name as the voice:
curl -X POST http://localhost:63044/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{"model":"chatterbox-tts-1","input":"Synthesize in this voice.","voice":"alice"}' \
  --output cloned.wav

2) Upload the reference clip with the request to the /upload route:

curl -X POST http://localhost:63044/v1/audio/speech/upload \
  -F "input=Synthesize in this voice." \
  -F "voice_file=@ALICE.wav" \
  --output cloned.wav

The upstream voice library guide covers the other voice operations.

The Chatterbox model is MIT-licensed. The chatterbox-tts-api server is AGPL-3.0.

6. Troubleshooting

MPS not detected on macOS: the server log reports the CPU device. Set DEVICE=mps. If that fails, reinstall PyTorch with MPS support, for example pip install --upgrade --force-reinstall torch torchaudio.

Port already in use: start on another port, then set it in .env:

PORT=9000 uv run main.py
# then in .env:
CHATTERBOX_LOCALHOST_PORT=9000

First requests fail after the first start: the model is still downloading or loading. Wait until /health returns "status": "healthy".

7. References

• Chatterbox upstream
• chatterbox-tts-api server
• Chatterbox model card