docker-compose.amd64.nornicdb.yml

services:
  nornicdb:
    build:
      context: ./nornicdb
      dockerfile: Dockerfile.cuda
      tags:
        - timothyswt/nornicdb:cuda
    image: timothyswt/nornicdb:cuda
    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 Mimir exports
    environment:
      - NORNICDB_DATA_DIR=/data
      - NORNICDB_HTTP_PORT=7474
      - NORNICDB_BOLT_PORT=7687
      # - NORNICDB_EMBEDDING_URL=http://llama-server:8080
      # - NORNICDB_EMBEDDING_MODEL=bge-m3
      # - NORNICDB_EMBEDDING_DIM=1024
      # # Authentication (disabled by default for dev)
      - NORNICDB_NO_AUTH=${NORNICDB_NO_AUTH:-true}
      - NORNICDB_ADMIN_PASSWORD=${NEO4J_PASSWORD:-password}
      # Load export data on startup (disabled - starting fresh)
      - NORNICDB_LOAD_EXPORT=
      # GPU Configuration (auto-detected, can override)
      - NORNICDB_GPU_ENABLED=${NORNICDB_GPU_ENABLED:-true}
      - NORNICDB_GPU_DEVICE_ID=${NORNICDB_GPU_DEVICE_ID:-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
    depends_on:
      llama-server:
        condition: service_healthy
    networks:
      - mcp_network
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu, compute, utility]

  copilot-api:
    image: timothyswt/copilot-api:latest
    container_name: copilot_api_server
    ports:
      - "4141:4141"  # Fixed: copilot-api listens on 4141, not 3000
    volumes:
      - ./copilot-data:/root/.local/share/copilot-api  # Persist GitHub token
    environment:
      - NODE_ENV=production
      # Remove PORT=3000, the app uses 4141 by default
    restart: unless-stopped
    healthcheck:
      # Use CMD-SHELL so shell operators (||) work and allow a proper HTTP probe
      test: ["CMD-SHELL", "wget --spider -q http://localhost:4141/ || exit 1"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 15s
    networks:
      - mcp_network

  # Ollama (Legacy - kept for reference, can be removed)
  # ollama:
  #   build:
  #     context: ./docker/ollama
  #     dockerfile: Dockerfile
  #     args:
  #       - EMBEDDING_MODEL=${MIMIR_EMBEDDINGS_MODEL:-bge-m3}
  #     tags:
  #       - mimir-ollama:${VERSION:-1.0.0}
  #       - mimir-ollama:latest
  #   image: mimir-ollama:${VERSION:-1.0.0}
  #   container_name: ollama_server
  #   ports:
  #     - "11434:11434"
  #   volumes:
  #     - type: bind
  #       source: ollama_models
  #       target: /root/.ollama
  #   environment:
  #     - OLLAMA_HOST=0.0.0.0:11434
  #     - OLLAMA_ORIGINS=*
  #   restart: unless-stopped
  #   healthcheck:
  #     test: ["CMD", "ollama", "list"]
  #     interval: 10s
  #     timeout: 5s
  #     retries: 5
  #     start_period: 30s
  #   networks:
  #     - mcp_network
  #   deploy:
  #     resources:
  #       reservations:
  #         devices:
  #           - driver: nvidia
  #             count: 1
  #             capabilities: [gpu]

  # llama.cpp server - OpenAI-compatible embeddings
  llama-server:
    image: timothyswt/llama-cpp-server-amd64-mxbai-cuda:latest
    container_name: llama_server
    ports:
      - "11434:8080"  # External 11434 -> Internal 8080 (llama.cpp default)
    # Note: Model is bundled in the image (bge-m3, 1024 dims)
    # No volumes needed unless you want to add additional models
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 30s
    networks:
      - mcp_network
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]

  # llama.cpp Vision Server - 2B model (faster, lower memory)
  # Qwen2.5-VL 2B with vision understanding and CUDA acceleration
  # Build with: npm run llama:build-qwen-2b-cuda
  # For use without cuda `image: timothyswt/llama-cpp-server-amd64-qwen-vl-2b:latest`
  # 
  # llama-vl-server-2b:
  #   image: timothyswt/llama-cpp-server-amd64-qwen-vl-2b-cuda:latest
  #   container_name: llama_server_vision_2b
  #   ports:
  #     - "8081:8080"  # Vision 2B API endpoint
  #   restart: unless-stopped
  #   healthcheck:
  #     test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"]
  #     interval: 30s
  #     timeout: 10s
  #     retries: 3
  #     start_period: 60s  # Vision models take longer to load
  #   networks:
  #     - mcp_network
  #   deploy:
  #     resources:
  #       limits:
  #         memory: 8G  # 2B model + vision projector
  #       reservations:
  #         memory: 4G
  #         devices:
  #           - driver: nvidia
  #             count: 1
  #             capabilities: [gpu]

  # llama.cpp Vision Server - 7B model (higher quality, more memory)
  # Qwen2.5-VL 7B with vision understanding and CUDA acceleration
  # Build with: npm run llama:build-qwen-7b-cuda
  # For use without cuda `image: timothyswt/llama-cpp-server-amd64-qwen-vl-7b:latest`
  #
  # llama-vl-server-7b:
  #   image: timothyswt/llama-cpp-server-amd64-qwen-vl-7b-cuda:latest
  #   container_name: llama_server_vision_7b
  #   ports:
  #     - "8082:8080"  # Vision 7B API endpoint
  #   restart: unless-stopped
  #   healthcheck:
  #     test: ["CMD-SHELL", "curl -f http://localhost:8080/health || exit 1"]
  #     interval: 30s
  #     timeout: 10s
  #     retries: 3
  #     start_period: 90s  # Larger models take even longer
  #   networks:
  #     - mcp_network
  #   deploy:
  #     resources:
  #       limits:
  #         memory: 16G  # 7B models need more RAM
  #       reservations:
  #         memory: 8G
  #         devices:
  #           - driver: nvidia
  #             count: 1
  #             capabilities: [gpu]

  mimir-server:
    build:
      context: .
      dockerfile: Dockerfile
      tags:
        - mimir-server:${VERSION:-1.0.0}
        - mimir-server:latest
    image: mimir-server:${VERSION:-1.0.0}
    container_name: mimir_server
    restart: unless-stopped
    environment:
      # Database Configuration
      - NEO4J_URI=bolt://nornicdb:7687
      - NEO4J_USER=admin
      - NEO4J_PASSWORD=${NEO4J_PASSWORD:-admin}
      
      # Server Configuration
      - NODE_ENV=production
      - PORT=3000
      # - NODE_TLS_REJECT_UNAUTHORIZED=${NODE_TLS_REJECT_UNAUTHORIZED:-1}
      
      # Workspace Configuration
      - WORKSPACE_ROOT=/workspace
      - HOST_WORKSPACE_ROOT=${HOST_WORKSPACE_ROOT}  # Pass through from host
      - HOST_HOME=${HOME}  # Host's home directory for expanding ~ in HOST_WORKSPACE_ROOT
     
      # LLM API Configuration
      - MIMIR_DEFAULT_PROVIDER=${MIMIR_DEFAULT_PROVIDER:-copilot}
      - MIMIR_LLM_API=${MIMIR_LLM_API:-http://copilot-api:4141}
      - MIMIR_LLM_API_PATH=${MIMIR_LLM_API_PATH:-/v1/chat/completions}
      - MIMIR_LLM_API_MODELS_PATH=${MIMIR_LLM_API_MODELS_PATH:-/v1/models}
      - MIMIR_LLM_API_KEY=${MIMIR_LLM_API_KEY:-dummy-key}
      
      # PCTX Integration (Code Mode for 90-98% token reduction)
      - PCTX_URL=${PCTX_URL:-http://host.docker.internal:8080}
      - PCTX_ENABLED=${PCTX_ENABLED:-false} 

      
      # Provider and Model Configuration (100% dynamic - no config file needed)
      - MIMIR_DEFAULT_MODEL=${MIMIR_DEFAULT_MODEL:-gpt-4.1}
      
      # Per-Agent Model Configuration (optional overrides)
      - MIMIR_PM_MODEL=${MIMIR_PM_MODEL:-}
      - MIMIR_WORKER_MODEL=${MIMIR_WORKER_MODEL:-}
      - MIMIR_QC_MODEL=${MIMIR_QC_MODEL:-}
      
      # Context Window Configuration
      - MIMIR_DEFAULT_CONTEXT_WINDOW=${MIMIR_DEFAULT_CONTEXT_WINDOW:-128000}
      
      
      # Embeddings API Configuration
      - MIMIR_EMBEDDINGS_PROVIDER=${MIMIR_EMBEDDINGS_PROVIDER:-openai}
      - MIMIR_EMBEDDINGS_API=${MIMIR_EMBEDDINGS_API:-http://llama-server:8080}
      - MIMIR_EMBEDDINGS_API_PATH=${MIMIR_EMBEDDINGS_API_PATH:-/v1/embeddings}
      - MIMIR_EMBEDDINGS_API_MODELS_PATH=${MIMIR_EMBEDDINGS_API_MODELS_PATH:-/v1/models}
      - MIMIR_EMBEDDINGS_API_KEY=${MIMIR_EMBEDDINGS_API_KEY:-dummy-key}
      
      # Embeddings Configuration
      - MIMIR_EMBEDDINGS_ENABLED=${MIMIR_EMBEDDINGS_ENABLED:-true}
      - MIMIR_EMBEDDINGS_MODEL=${MIMIR_EMBEDDINGS_MODEL:-bge-m3}
      - MIMIR_EMBEDDINGS_DIMENSIONS=${MIMIR_EMBEDDINGS_DIMENSIONS:-1024}
      - MIMIR_EMBEDDINGS_CHUNK_SIZE=${MIMIR_EMBEDDINGS_CHUNK_SIZE:-768}
      - MIMIR_EMBEDDINGS_CHUNK_OVERLAP=${MIMIR_EMBEDDINGS_CHUNK_OVERLAP:-100}
      - MIMIR_EMBEDDINGS_DELAY_MS=${MIMIR_EMBEDDINGS_DELAY_MS:-0}
      - MIMIR_EMBEDDINGS_MAX_RETRIES=${MIMIR_EMBEDDINGS_MAX_RETRIES:-3}
      # Image Embeddings Control (disabled by default for safety)
      - MIMIR_EMBEDDINGS_IMAGES=${MIMIR_EMBEDDINGS_IMAGES:-false}  # Default: disabled
      - MIMIR_EMBEDDINGS_IMAGES_DESCRIBE_MODE=${MIMIR_EMBEDDINGS_IMAGES_DESCRIBE_MODE:-true}  # Default: VL description mode
      # Qwen2.5-VL Configuration (for llama.cpp server)
      - MIMIR_EMBEDDINGS_VL_PROVIDER=${MIMIR_EMBEDDINGS_VL_PROVIDER:-llama.cpp}
      - MIMIR_EMBEDDINGS_VL_API=${MIMIR_EMBEDDINGS_VL_API:-http://llama-vl-server-2b:8080}
      - MIMIR_EMBEDDINGS_VL_API_PATH=${MIMIR_EMBEDDINGS_VL_API_PATH:-/v1/chat/completions}
      - MIMIR_EMBEDDINGS_VL_API_KEY=${MIMIR_EMBEDDINGS_VL_API_KEY:-dummy-key}
      - MIMIR_EMBEDDINGS_VL_MODEL=${MIMIR_EMBEDDINGS_VL_MODEL:-qwen2.5-vl}
      - MIMIR_EMBEDDINGS_VL_CONTEXT_SIZE=${MIMIR_EMBEDDINGS_VL_CONTEXT_SIZE:-131072}  # 128K tokens (7b/72b)
      - MIMIR_EMBEDDINGS_VL_MAX_TOKENS=${MIMIR_EMBEDDINGS_VL_MAX_TOKENS:-2048}  # Max description length
      - MIMIR_EMBEDDINGS_VL_TEMPERATURE=${MIMIR_EMBEDDINGS_VL_TEMPERATURE:-0.7}
      - MIMIR_EMBEDDINGS_VL_DIMENSIONS=${MIMIR_EMBEDDINGS_VL_DIMENSIONS:-768}  # Falls back to text model dims
      - MIMIR_EMBEDDINGS_VL_TIMEOUT=${MIMIR_EMBEDDINGS_VL_TIMEOUT:-180000}  # 3 minutes (VL processing is slow)
     
      # Indexing Configuration
      - MIMIR_INDEXING_THREADS=${MIMIR_INDEXING_THREADS:-1}
      
      # Feature Flags
      - MIMIR_FEATURE_PM_MODEL_SUGGESTIONS=${MIMIR_FEATURE_PM_MODEL_SUGGESTIONS:-true}
      - MIMIR_AUTO_INDEX_DOCS=${MIMIR_AUTO_INDEX_DOCS:-true}
      
      # Security Configuration
      - MIMIR_ENABLE_SECURITY=${MIMIR_ENABLE_SECURITY:-false}
      - MIMIR_DEV_USER_ADMIN=${MIMIR_DEV_USER_ADMIN}
      - MIMIR_DEV_USER_DEVELOPER=${MIMIR_DEV_USER_DEVELOPER}
      - MIMIR_DEV_USER_ANALYST=${MIMIR_DEV_USER_ANALYST}
      - MIMIR_DEV_USER_VIEWER=${MIMIR_DEV_USER_VIEWER}
      - MIMIR_JWT_SECRET=${MIMIR_JWT_SECRET}
      # OAuth Configuration (explicit endpoint URLs - provider-specific)
      - MIMIR_AUTH_PROVIDER=${MIMIR_AUTH_PROVIDER}
      - MIMIR_OAUTH_AUTHORIZATION_URL=${MIMIR_OAUTH_AUTHORIZATION_URL}  # Full authorization endpoint URL
      - MIMIR_OAUTH_TOKEN_URL=${MIMIR_OAUTH_TOKEN_URL}                  # Full token endpoint URL
      - MIMIR_OAUTH_USERINFO_URL=${MIMIR_OAUTH_USERINFO_URL}            # Full userinfo endpoint URL
      - MIMIR_OAUTH_CLIENT_ID=${MIMIR_OAUTH_CLIENT_ID}
      - MIMIR_OAUTH_CLIENT_SECRET=${MIMIR_OAUTH_CLIENT_SECRET}
      - MIMIR_OAUTH_CALLBACK_URL=${MIMIR_OAUTH_CALLBACK_URL}
      - MIMIR_OAUTH_ALLOW_HTTP=${MIMIR_OAUTH_ALLOW_HTTP}

      # Advanced Configuration
      - MIMIR_PARALLEL_EXECUTION=${MIMIR_PARALLEL_EXECUTION:-false}
      - MIMIR_INSTALL_DIR=${MIMIR_INSTALL_DIR:-/app}
      - MIMIR_AGENTS_DIR=${MIMIR_AGENTS_DIR:-/app/docs/agents}
    volumes:
      - ./data:/app/data
      - ./logs:/app/logs
      - ${HOST_WORKSPACE_ROOT:-~/src}:${WORKSPACE_ROOT:-/workspace}
    ports:
      - "9042:3000"
    healthcheck:
      test: ["CMD", "node", "-e", "require('http').get('http://localhost:3000/health', (res) => process.exit(res.statusCode === 200 ? 0 : 1)).on('error', () => process.exit(1))"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s
    depends_on:
      nornicdb:
        condition: service_healthy
      copilot-api:
        condition: service_healthy
      # llama.cpp server for embeddings
      llama-server:
        condition: service_healthy
      # llama.cpp server for image embeddings must set 
      # llama-vl-server:
        # condition: service_healthy
    networks:
      - mcp_network

networks:
  mcp_network:
    driver: bridge