
neosun100/kokoro-tts
Developer toolsЭта страница переведена автоматически. Технические детали смотрите в оригинале. Открыть оригинал
🎙️ All-in-One Docker image for Kokoro-82M TTS - Web UI, REST API, WebSocket, Streaming, Batch, MCP
Обзор
Web UI • REST API • WebSocket • Streaming • Batch • MCP - 🎨 - Modern interface with real-time audio playback - 🔌 - Full-featured HTTP endpoints with Swagger docs - 📡 - Real-time bidirectional TTS communication - 🌊 - Audio chunks delivered as they generate - 📦 - Process multiple texts in one request - 🤖 - AI agent integration (Claude, etc.) - 🌍 - English, Chinese, Japanese, Spanish, French, Hindi, Italian, Portuguese - 🚀 - CUDA support with automatic memory management - 📱 - Wide variety of male and female voices Open http://localhost:8300 in your browser. - Docker 20.10+ - NVIDIA GPU with CUDA support (optional, CPU fallback available) - nvidia-docker2 (for GPU support) - : http://localhost:8300/docs - : http://localhost:8300/redoc - : FastAPI, Uvicorn - : Kokoro-82M (StyleTTS 2) - : PyTorch, CUDA - : Docker, NVIDIA Container Toolkit Contributions are welcome! Please feel free to submit a Pull Request. 1. Fork the repository 2.
README
Показан фрагмент оригинального README. Открыть оригинал.
✨ Features
- 🎨 Beautiful Web UI - Modern interface with real-time audio playback
- 🔌 REST API - Full-featured HTTP endpoints with Swagger docs
- 📡 WebSocket - Real-time bidirectional TTS communication
- 🌊 Streaming - Audio chunks delivered as they generate
- 📦 Batch Processing - Process multiple texts in one request
- 🤖 MCP Server - AI agent integration (Claude, etc.)
- 🌍 Multi-language - English, Chinese, Japanese, Spanish, French, Hindi, Italian, Portuguese
- 🚀 GPU Accelerated - CUDA support with automatic memory management
- 📱 54+ Voices - Wide variety of male and female voices
🚀 Quick Start
docker run -d --name kokoro-tts --gpus all -p 8300:8300 neosun/kokoro-tts:latest
Open http://localhost:8300 in your browser.
📦 Installation
Prerequisites
- Docker 20.10+
- NVIDIA GPU with CUDA support (optional, CPU fallback available)
- nvidia-docker2 (for GPU support)
Docker Run
# With GPU
docker run -d \
--name kokoro-tts \
--gpus all \
-p 8300:8300 \
-e GPU_IDLE_TIMEOUT=600 \
--restart unless-stopped \
neosun/kokoro-tts:latest
# CPU only
docker run -d \
--name kokoro-tts \
-p 8300:8300 \
--restart unless-stopped \
neosun/kokoro-tts:latest
Docker Compose
services:
kokoro-tts:
image: neosun/kokoro-tts:latest
container_name: kokoro-tts
ports:
- "8300:8300"
environment:
- GPU_IDLE_TIMEOUT=600
- KEEP_MODEL_LOADED=true # Never release model from memory
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
restart: unless-stopped
docker-compose up -d
Verify Installation
# Health check
curl http://localhost:8300/health
# Generate speech
curl -X POST http://localhost:8300/api/tts \
-H "Content-Type: application/json" \
-d '{"text":"Hello world","voice":"af_heart"}' \
-o output.wav
⚙️ Configuration
| Variable | Default | Description |
|---|---|---|
PORT |
8300 |
Server port |
GPU_IDLE_TIMEOUT |
300 |
Seconds before GPU memory release |
Установка
docker exec -i kokoro-tts python /app/docker/server.py mcpКонфигурация
{
"mcpServers": {
"kokoro-tts": {
"command": "docker",
"args": ["exec", "-i", "kokoro-tts", "python", "/app/docker/server.py", "mcp"]
}
}
}