docker-compose.yml

services:
  chatterbox-tts-server:
    build:
      args:
      # Can be nvidia or cpu; Default is Nvidia
        - RUNTIME=nvidia
      context: .
      dockerfile: Dockerfile
    ports:
      - "${PORT:-8004}:8004"
    volumes:
      # Mount local config file for persistence
      - ./config.yaml:/app/config.yaml
      # Mount local directories for persistent app data
      - ./voices:/app/voices
      - ./reference_audio:/app/reference_audio
      - ./outputs:/app/outputs
      - ./logs:/app/logs
      # Named volume for Hugging Face model cache to persist across container rebuilds
      - hf_cache:/app/hf_cache
    
    # --- GPU Support (NVIDIA) ---
    # The 'deploy' key is the modern way to request GPU resources.
    # If you get a 'CDI device injection failed' error, comment out the 'deploy' section
    # and uncomment the 'runtime: nvidia' line below.
    
    # Method 1: Modern Docker Compose (Recommended)
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]

    # Method 2: Legacy Docker Compose (for older setups)
    # runtime: nvidia

    restart: unless-stopped
    environment:
      - HF_TOKEN=YOUR_TOKEN_HERE
      # Enable faster Hugging Face downloads inside the container
      - HF_HUB_ENABLE_HF_TRANSFER=1
      # Make NVIDIA GPUs visible and specify capabilities for PyTorch
      - NVIDIA_VISIBLE_DEVICES=all
      - NVIDIA_DRIVER_CAPABILITIES=compute,utility

# Define the named volume for the Hugging Face cache
volumes:
  hf_cache: