AudioMuse-AI (NVIDIA GPU)

# AudioMuse-AI with NVIDIA GPU acceleration for analysis + clustering
# Mirrors https://github.com/NeptuneHub/AudioMuse-AI/blob/main/deployment/docker-compose-nvidia.yaml
# Requires the NVIDIA Container Toolkit on the host and a CUDA 12.8.1+ driver.
# On a host without a GPU this stack will fail to start - use the standard
# AudioMuse-AI template instead (sources/stacks/audiomuse-ai.yml).

services:
  audiomuse-ai-flask:
    image: ghcr.io/neptunehub/audiomuse-ai:${AUDIOMUSE_TAG:-latest-nvidia}
    restart: unless-stopped
    ports:
      - "${FRONTEND_PORT:-8000}:8000"
    environment:
      SERVICE_TYPE: flask
      TZ: ${TZ:-UTC}
      POSTGRES_HOST: postgres
      POSTGRES_PORT: "5432"
      POSTGRES_USER: ${POSTGRES_USER:-audiomuse}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-audiomusepassword}
      POSTGRES_DB: audiomusedb
      REDIS_URL: redis://redis:6379/0
      TEMP_DIR: /app/temp_audio
    volumes:
      - temp-audio-flask:/app/temp_audio
      # Plugins are installed to disk (code + pip deps), so each container keeps its own copy
      - plugins-flask:/app/plugin/installed
    depends_on:
      postgres:
        condition: service_healthy
      redis:
        condition: service_healthy
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ["${NVIDIA_GPU_ID:-0}"]
              capabilities: [gpu]

  audiomuse-ai-worker:
    image: ghcr.io/neptunehub/audiomuse-ai:${AUDIOMUSE_TAG:-latest-nvidia}
    restart: unless-stopped
    environment:
      SERVICE_TYPE: worker
      TZ: ${TZ:-UTC}
      POSTGRES_HOST: postgres
      POSTGRES_PORT: "5432"
      POSTGRES_USER: ${POSTGRES_USER:-audiomuse}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-audiomusepassword}
      POSTGRES_DB: audiomusedb
      REDIS_URL: redis://redis:6379/0
      TEMP_DIR: /app/temp_audio
      NVIDIA_VISIBLE_DEVICES: ${NVIDIA_GPU_ID:-0}
      NVIDIA_DRIVER_CAPABILITIES: compute,utility
      # GPU clustering via RAPIDS cuML - falls back to CPU on error or OOM
      USE_GPU_CLUSTERING: ${USE_GPU_CLUSTERING:-true}
    volumes:
      - temp-audio-worker:/app/temp_audio
      - plugins-worker:/app/plugin/installed
    depends_on:
      postgres:
        condition: service_healthy
      redis:
        condition: service_healthy
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ["${NVIDIA_GPU_ID:-0}"]
              capabilities: [gpu]

  # AudioMuse-AI is built against PostgreSQL 15 - other majors are known to error
  postgres:
    image: postgres:15-alpine
    restart: unless-stopped
    environment:
      TZ: ${TZ:-UTC}
      POSTGRES_USER: ${POSTGRES_USER:-audiomuse}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-audiomusepassword}
      POSTGRES_DB: audiomusedb
    volumes:
      - postgres-data:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-audiomuse} -d audiomusedb"]
      interval: 10s
      timeout: 5s
      retries: 6

  # Task queue for the analysis/clustering jobs
  redis:
    image: redis:7-alpine
    restart: unless-stopped
    environment:
      TZ: ${TZ:-UTC}
    volumes:
      - redis-data:/data
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 6

volumes:
  postgres-data:
  redis-data:
  temp-audio-flask:
  temp-audio-worker:
  plugins-flask:
  plugins-worker:

git clone https://github.com/lissy93/portainer-templates
cd portainer-templates
docker compose -f sources/stacks/audiomuse-ai-nvidia.yml up -d