chatterbox-tts-api 1.0.0

REST API for ChatterboxTTS with OpenAI compatibility

Chatterbox TTS API

A Flask-based REST API for ChatterboxTTS, providing OpenAI-compatible text-to-speech endpoints with voice cloning capabilities.

Features

🚀 OpenAI-Compatible API - Drop-in replacement for OpenAI's TTS API
🎭 Voice Cloning - Use your own voice samples for personalized speech
📝 Smart Text Processing - Automatic chunking for long texts
🐳 Docker Ready - Full containerization support
⚙️ Configurable - Extensive environment variable configuration
🎛️ Parameter Control - Real-time adjustment of speech characteristics

Quick Start

1. Local Installation

# Clone the repository
git clone https://github.com/travisvn/chatterbox-tts-api
cd chatterbox-tts-api

# Setup environment — using Python 3.11
python -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Copy and customize environment variables
cp .env.example .env

# Add your voice sample (or use the provided one)
# cp your-voice.mp3 voice-sample.mp3

# Start the API
python api.py

2. Docker (Recommended)

# Clone and start with Docker Compose
git clone https://github.com/travisvn/chatterbox-tts-api
cd chatterbox-tts-api
cp .env.example .env  # Customize as needed
docker compose up -d

# If you have nvidia/CUDA, you might have better luck with this
docker compose -f docker-compose.gpu.yml up -d --build

# Watch the logs as it initializes (the first use of TTS takes the longest)
docker logs chatterbox-tts-api -f

# Test the API
curl -X POST http://localhost:5123/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{"input": "Hello from ChatterboxTTS!"}' \
  --output test.wav

API Usage

Basic Text-to-Speech

curl -X POST http://localhost:5123/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{"input": "Your text here"}' \
  --output speech.wav

With Custom Parameters

curl -X POST http://localhost:5123/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Dramatic speech!",
    "exaggeration": 1.2,
    "cfg_weight": 0.3,
    "temperature": 0.9
  }' \
  --output dramatic.wav

Python Example

import requests

response = requests.post(
    "http://localhost:5123/v1/audio/speech",
    json={
        "input": "Hello world!",
        "exaggeration": 0.8  # More expressive
    }
)

with open("output.wav", "wb") as f:
    f.write(response.content)

Configuration

Key environment variables (see .env.example for full list):

Variable	Default	Description
PORT	5123	API server port
EXAGGERATION	0.5	Emotion intensity (0.25-2.0)
CFG_WEIGHT	0.5	Pace control (0.0-1.0)
TEMPERATURE	0.8	Sampling randomness (0.05-5.0)
VOICE_SAMPLE_PATH	./voice-sample.mp3	Voice sample for cloning
DEVICE	auto	Device (auto/cuda/mps/cpu)

Voice Cloning

Replace the default voice sample:

# Replace the default voice sample
cp your-voice.mp3 voice-sample.mp3

# Or set a custom path
echo "VOICE_SAMPLE_PATH=/path/to/your/voice.mp3" >> .env

For best results:

• Use 10-30 seconds of clear speech
• Avoid background noise
• Prefer WAV or high-quality MP3

Docker Deployment

Development

docker compose up

Production

# Create production environment
cp .env.example .env
nano .env  # Set FLASK_DEBUG=false, etc.

# Deploy
docker compose -f docker-compose.yml up -d

With GPU Support

# Uncomment GPU section in docker-compose.yml
# Ensure NVIDIA Container Toolkit is installed
docker compose up -d

API Endpoints

Endpoint	Method	Description
/v1/audio/speech	POST	Generate speech from text
/health	GET	Health check and status
/config	GET	Current configuration
/v1/models	GET	Available models (OpenAI compat)

Parameters Reference

Speech Generation Parameters

Exaggeration (0.25-2.0)

• 0.3-0.4: Professional, neutral
• 0.5: Default balanced
• 0.7-0.8: More expressive
• 1.0+: Very dramatic

CFG Weight (0.0-1.0)

• 0.2-0.3: Faster speech
• 0.5: Default pace
• 0.7-0.8: Slower, deliberate

Temperature (0.05-5.0)

• 0.4-0.6: More consistent
• 0.8: Default balance
• 1.0+: More creative/random

Testing

Run the test suite:

python test_api.py

Performance

• CPU: Works but slower, reduce chunk size for better memory usage
• GPU: Recommended for production, significantly faster
• Memory: 4GB minimum, 8GB+ recommended
• Concurrency: Single request processing for stability

Troubleshooting

Common Issues

CUDA/CPU Compatibility Error

RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False

This happens because chatterbox-tts models require PyTorch with CUDA support, even when running on CPU. Solutions:

# Option 1: Use default setup (now includes CUDA-enabled PyTorch (maybe))
docker compose up -d

# Option 2: Use explicit CUDA setup
docker compose -f docker-compose.gpu.yml up -d

# Option 3: Use CPU-only setup (may have compatibility issues)
docker compose -f docker-compose.cpu.yml up -d

# Option 4: Clear model cache and retry with CUDA-enabled setup
docker volume rm chatterbox-tts-api_chatterbox-models
docker compose up -d --build

For local development, install PyTorch with CUDA support:

pip uninstall torch torchvision torchaudio
pip install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cu126
pip install chatterbox-tts

Port conflicts

# Change port
echo "PORT=5002" >> .env

GPU not detected

# Force CPU mode
echo "DEVICE=cpu" >> .env

Out of memory

# Reduce chunk size
echo "MAX_CHUNK_LENGTH=200" >> .env

Model download fails

# Clear cache and retry
rm -rf models/
python api.py

Development

Local Development

# Install in development mode
pip install -e .

# Enable debug mode
export FLASK_DEBUG=true
python api.py

Testing

# Run API tests
python test_api.py

# Test specific endpoint
curl http://localhost:5123/health

License

This API wrapper is provided under the same license terms as the underlying ChatterboxTTS model. See the ChatterboxTTS repository for details.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Related Projects

• ChatterboxTTS - The core TTS model
• Resemble AI - Production TTS services

Support

• 📖 Documentation: See API_README.md and DOCKER_README.md
• 🐛 Issues: Report bugs and feature requests via GitHub issues
• 💬 Discord: Join the ChatterboxTTS Discord or the Discord for this project

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