Zonos API

⚠️ WARNING: UNSTABLE API - INITIAL RELEASE ⚠️

This API is currently in its initial release phase (v1.0.0) and is considered unstable. Breaking changes may occur without notice. Use in production at your own risk. For development and testing purposes only.

A production-grade FastAPI implementation of the Zonos Text-to-Speech model.

Credits

This API is built on top of the Zonos-v0.1-hybrid and Zonos-v0.1-transformer models created by Zyphra. The models feature:

• Zero-shot TTS with voice cloning capabilities
• Support for multiple languages (100+ languages via eSpeak-ng)
• High-quality 44kHz audio output
• Fine-grained control over speaking rate, pitch, audio quality, and emotions
• Real-time performance (~2x real-time on RTX 4090)

For more information, visit the model cards on Hugging Face: Hybrid | Transformer.

Features

• FastAPI-based REST API for Zonos Text-to-Speech model
• Support for both Transformer and Hybrid model variants
• Docker and docker-compose support with NVIDIA GPU acceleration
• Production-ready with Gunicorn workers and optimizations
• Prometheus and Grafana monitoring integration
• Health checks and comprehensive logging
• CORS support and Swagger documentation
• Voice cloning and audio continuation support
• Fine-grained emotion and audio quality control

Quick Start

Using Pre-built Image

The fastest way to get started is using our pre-built Docker image:

docker pull ghcr.io/manascb1344/zonos-api-gpu:v1.0.0
docker run -d \
  --name zonos-api-gpu \
  --gpus all \
  -p 8000:8000 \
  -e CUDA_VISIBLE_DEVICES=0 \
  zonos-api-gpu

Manual Installation

1. Clone the repository with submodules:

git clone --recursive https://github.com/manascb1344/zonos-api
cd zonos-api

The API will be available at http://localhost:8000

Running with Docker

1. Build the container:

docker build -t zonos-api .

2. Run the container:

docker run -d \
  --name zonos-api \
  --gpus all \
  -p 8000:8000 \
  -e CUDA_VISIBLE_DEVICES=0 \
  zonos-api

Environment Variables

• CUDA_VISIBLE_DEVICES: Specify which GPU(s) to use (default: 0)
• USE_GPU: Enable/disable GPU usage (default: true)

Requirements

• Docker with NVIDIA Container Toolkit installed
• NVIDIA GPU with CUDA support
• At least 8GB of GPU memory recommended

Verifying the Installation

Check if the API is running:

curl http://localhost:8000/health

API Endpoints

GET /

Root endpoint that returns basic API information

GET /models

Returns a list of available TTS models

GET /languages

Returns a list of supported languages

GET /model/{model_name}/conditioners

Returns available conditioners for a specific model

POST /synthesize

Generate speech from text. Example request:

{
  "model_choice": "Zyphra/Zonos-v0.1-transformer",
  "text": "Hello, this is a test.",
  "language": "en-us",
  "emotion_values": [1.0, 0.05, 0.05, 0.05, 0.05, 0.05, 0.1, 0.2],
  "vq_score": 0.78,
  "cfg_scale": 2.0,
  "min_p": 0.15
}

Environment Variables

• USE_GPU: Set to "true" to enable GPU acceleration (default: true)
• PYTHONPATH: Set to the application root directory

GPU Support

The API uses NVIDIA GPU acceleration by default. Make sure you have:

1. NVIDIA GPU with CUDA support
2. NVIDIA drivers installed
3. NVIDIA Container Toolkit installed and configured

Development

Prerequisites

• Python 3.10+
• NVIDIA GPU with CUDA support (recommended)
• Docker and docker-compose (for containerized deployment)

Local Development

# Start in development mode
uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

# Or with docker-compose
docker-compose up --build

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.