# Quick Start Choose a quick-start path based on your TTS provider preference. ## Option 1: Cloud TTS (Easiest) No Docker required. Use OpenAI, AWS Polly, or Google Cloud TTS. ### 1. Install Audify ```bash pip install audify-cli ``` ### 2. Configure credentials Create a `.keys` file in your working directory: ```bash # OpenAI TTS (simplest cloud option) OPENAI_API_KEY=sk-your-openai-api-key TTS_PROVIDER=openai ``` ### 3. Convert a book ```bash audify book.epub --task direct --tts-provider openai ``` ## Option 2: Kokoro TTS (Local, Free) Requires Docker and a CUDA GPU. Fast and low-latency synthesis. ### 1. Clone and start services ```bash git clone https://github.com/garciadias/audify.git cd audify docker compose --profile kokoro --profile ollama up -d # Wait ~2-3 minutes for services to start ``` ### 2. Pull an Ollama model ```bash docker compose exec ollama ollama pull qwen3:30b ``` ### 3. Convert a book ```bash uv sync audify book.epub --task direct ``` ## Option 3: Qwen-TTS (Local, Free) Requires a local Qwen-TTS-compatible API and typically a GPU. ### Option 3A: Docker Compose Profile (Recommended) Run the provided qwen-tts service in this repository: 1. Start Qwen-TTS and Ollama: ```bash docker compose --profile qwen up -d qwen-tts ollama ``` 2. Confirm Qwen-TTS health: ```bash curl http://localhost:8890/health ``` 3. Use Qwen in Audify: ```bash # Direct TTS audify book.epub --task direct --tts-provider qwen # Audiobook generation with Ollama LLM + Qwen-TTS audify book.epub --task audiobook --tts-provider qwen -m gemma4:31b ``` ### Option 3B: Local API Wrapper Script 1. Install dependencies: ```bash pip install qwen-tts fastapi uvicorn soundfile numpy torch ``` 2. Run the wrapper: ```bash python scripts/qwen_tts_api.py ``` 3. Configure Audify: ```bash TTS_PROVIDER=qwen QWEN_API_URL=http://localhost:8890 QWEN_TTS_VOICE=Vivian ``` ### Equivalent commands ```bash audify book.epub --task direct --tts-provider qwen audify book.epub --task audiobook --tts-provider qwen --llm-model gemma4:31b ``` ## Next Steps - Learn about all [usage options](usage.md) including translation - Explore the [task system](tasks.md) for LLM-powered audio generation - Set up [cloud LLM APIs](commercial-apis.md) for advanced audiobook creation