riggpt/docker-compose.yml at main · afitnacode/riggpt · GitHub

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# ─────────────────────────────────────────────────────────────
# RigGPT — Docker Compose
#
# HARDWARE REQUIREMENTS:
#   - Icom IC-7610 (or CI-V compatible) connected via USB
#   - USB serial port (typically /dev/ttyUSB0 or /dev/ttyIC7610)
#   - USB audio device (ALSA, typically plughw:0,0 or plughw:1,0)
#
# QUICK START:
#   docker compose up -d
#   open http://localhost:5000
#
# FIRST RUN:
#   1. Check serial port:  ls /dev/ttyUSB*
#   2. Check audio device: aplay -l
#   3. Update 'devices' below to match your hardware
#   4. docker compose up -d
#   5. Connect to radio in the UI
#
# PERSISTENT DATA:
#   ./data/config/   → app_settings.json, api_keys.json, canon/
#   ./data/sounds/   → clip WAV/MP3 files
#   ./data/wav_cache/ → transmission log WAV cache
# ─────────────────────────────────────────────────────────────

services:
  riggpt:
    build: .
    image: riggpt:latest
    container_name: riggpt
    restart: unless-stopped

    ports:
      - "5000:5000"

    # ── Hardware passthrough ───────────────────────────────────
    devices:
      # Serial port — CI-V control
      # Change to match your radio's USB serial device.
      # Run 'ls /dev/ttyUSB*' on the host to find it.
      # If you have a udev rule creating /dev/ttyIC7610, use that.
      - /dev/ttyUSB0:/dev/ttyUSB0

      # ALSA sound devices — required for audio playback/capture
      - /dev/snd:/dev/snd

    # ── Volumes ────────────────────────────────────────────────
    volumes:
      # Persistent config (settings, API keys, canon files)
      - ./data/config:/home/riggpt

      # Sound clips directory
      - ./data/sounds:/sounds

      # WAV cache (transmission log audio)
      - ./data/wav_cache:/opt/riggpt/wav_cache

      # Piper TTS voices (optional — mount host directory if installed)
      # - /usr/share/piper-voices:/usr/share/piper-voices:ro

      # Gong file (optional — or place in ./data/sounds/)
      # - /opt/taco_bell_gong.wav:/opt/taco_bell_gong.wav:ro

    # ── Environment ────────────────────────────────────────────
    environment:
      # Override auto-detected audio device if needed
      # RIGGPT_AUDIO_DEVICE: "plughw:1,0"

      # Ollama host (if running on the host or another container)
      # RIGGPT_OLLAMA_HOST: "http://host.docker.internal:11434"
      TZ: ${TZ:-America/New_York}

    # ── Networking ─────────────────────────────────────────────
    # host network gives direct access to serial ports and avoids
    # NAT issues with Ollama/Qdrant on localhost. Use bridge mode
    # if you prefer isolation (but update Ollama host to use
    # host.docker.internal or the host's IP).
    network_mode: host
    # If using bridge mode instead, comment out network_mode above
    # and uncomment the ports section.


  # ── Optional: Ollama (local LLM) ────────────────────────────
  # Uncomment to run Ollama alongside RigGPT.
  # Pull a model after starting: docker exec ollama ollama pull llama3
  #
  # ollama:
  #   image: ollama/ollama:latest
  #   container_name: ollama
  #   restart: unless-stopped
  #   ports:
  #     - "11434:11434"
  #   volumes:
  #     - ollama_data:/root/.ollama
  #   # For GPU passthrough (NVIDIA):
  #   # deploy:
  #   #   resources:
  #   #     reservations:
  #   #       devices:
  #   #         - capabilities: [gpu]


  # ── Optional: Qdrant (vector database for community memory) ──
  # Uncomment to run Qdrant for Discord community memory.
  #
  # qdrant:
  #   image: qdrant/qdrant:latest
  #   container_name: qdrant
  #   restart: unless-stopped
  #   ports:
  #     - "6333:6333"
  #   volumes:
  #     - qdrant_data:/qdrant/storage


# volumes:
#   ollama_data:
#   qdrant_data: