NornicDB/docker-compose.amd64.yml at main · orneryd/NornicDB · GitHub

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services:
  nornicdb:
    image: timothyswt/nornicdb-amd64-cuda-embed-bge-m3:latest
    container_name: nornicdb
    ports:
      - "7474:7474"  # HTTP API & Browser UI
      - "7687:7687"  # Bolt protocol (Neo4j compatible)
    volumes:
      - ./data/nornicdb:/data
      - ./data/nornicdb/export:/data/export # For loading data exports
    environment:
      - NORNICDB_DATA_DIR=/data
      - NORNICDB_HTTP_PORT=7474
      - NORNICDB_BOLT_PORT=7687
      # Embedding configuration - llama.cpp OpenAI-compatible API
      - NORNICDB_EMBEDDING_PROVIDER=local
      # - NORNICDB_EMBEDDING_API_URL=http://llama-server:8080
      # - NORNICDB_EMBEDDING_API_KEY=not-needed
      # - NORNICDB_EMBEDDING_MODEL=bge-m3
      # - NORNICDB_MODELS_DIR=/data/models
      # # Authentication (disabled by default for dev)
      - NORNICDB_NO_AUTH=${NORNICDB_NO_AUTH:-true}
      - NORNICDB_TOPOLOGY_AUTO_INTEGRATION_ENABLED=true
      # Load export data on startup (disabled - starting fresh)
      - NORNICDB_LOAD_EXPORT=
      # Badger memory tuning (reduce memory footprint)
      - GOGC=50
      - NORNICDB_GPU_ENABLED=${NORNICDB_GPU_ENABLED:-true}
      - NORNICDB_GPU_DEVICE_ID=${NORNICDB_GPU_DEVICE_ID:-0}
      - NORNICDB_EMBEDDING_CACHE_SIZE=0
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "wget --spider -q http://localhost:7474/health || exit 1"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    networks:
      - mcp_network
    deploy:
      resources:
        limits:
          memory: 2GB
        reservations:
          memory: 1GB
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu, compute, utility]

networks:
  mcp_network:
    driver: bridge