TTSFM

⚠️ Disclaimer
This project is for learning and testing purposes only. For production environments, please use OpenAI's official TTS service.

English | 中文

🌟 Project Introduction

TTSFM is a reverse-engineered API server that is fully compatible with OpenAI's Text-to-Speech (TTS) interface.

🎮 Try it now: Official Demo Site

🏗️ Project Structure

ttsfm/
├── main.py              # Application entry
├── server/              # Core services
│   ├── api.py           # OpenAI-compatible API
│   └── handlers.py      # Request handlers
├── utils/               # Utility modules
│   └── config.py        # Configuration management
├── static/              # Frontend resources
│   ├── index.html       # English interface
│   ├── index_zh.html    # Chinese interface
│   ├── script.js        # Frontend JavaScript
│   └── styles.css       # Frontend styles
├── pressure_test.py     # Stress testing script
├── Dockerfile          # Docker configuration
├── requirements.txt    # Python dependencies
└── .env.example       # Environment variables template

🚀 Quick Start

System Requirements

• Python ≥ 3.8
• Or Docker environment

🐳 Docker Run (Recommended)

Basic usage:

docker run -p 7000:7000 dbcccc/ttsfm:latest

Custom configuration using environment variables:

docker run -d \
  -p 7000:7000 \
  -e HOST=0.0.0.0 \
  -e PORT=7000 \
  -e VERIFY_SSL=true \
  -e MAX_QUEUE_SIZE=100 \
  -e RATE_LIMIT_REQUESTS=30 \
  -e RATE_LIMIT_WINDOW=60 \
  dbcccc/ttsfm:latest

Available environment variables:

• HOST: Server host (default: 0.0.0.0)
• PORT: Server port (default: 7000)
• VERIFY_SSL: Whether to verify SSL certificates (default: true)
• MAX_QUEUE_SIZE: Maximum number of tasks in queue (default: 100)
• RATE_LIMIT_REQUESTS: Maximum number of requests per time window (default: 30)
• RATE_LIMIT_WINDOW: Time window in seconds for rate limiting (default: 60)

💡 Tip
MacOS users experiencing port conflicts can use alternative ports:
docker run -p 5051:7000 dbcccc/ttsfm:latest

📦 Manual Installation

1. Download the latest release package from GitHub Releases
2. Extract and enter the directory:

tar -zxvf ttsfm-vX.X.X.tar.gz
cd ttsfm-vX.X.X

3. Install dependencies and launch:

pip install -r requirements.txt
cp .env.example .env  # Edit config as needed
python main.py

📚 Usage Guide

Web Interface

Access http://localhost:7000 to experience the interactive demo

API Endpoints

Endpoint	Method	Description
/v1/audio/speech	POST	Text-to-Speech
/api/queue-size	GET	Query task queue

🔍 Complete API documentation is available via the web interface after local deployment

🤝 Contributing

We welcome all forms of contributions! You can participate by:

• Submitting Issues to report problems
• Creating Pull Requests to improve code
• Sharing usage experiences and suggestions

📜 Project licensed under MIT License

📈 Project Activity