services:
  # --- LLM Inference (CUDA + grammar support) ---
  llama-server:
    build:
      context: ./inference
      dockerfile: Dockerfile.v31
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    volumes:
      - ${ATLAS_MODELS_DIR:-./models}:/models:ro
    command: >
      /llama-server
      --model /models/${ATLAS_MODEL_FILE:-Qwen3.5-9B-Q6_K.gguf}
      --host 0.0.0.0 --port 8080
      --ctx-size ${ATLAS_CTX_SIZE:-32768}
      --n-gpu-layers 99
      --no-mmap
    ports:
      - "${ATLAS_LLAMA_PORT:-8080}:8080"
    ulimits:
      memlock: -1
      stack: 67108864
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:8080/health"]
      interval: 30s
      timeout: 10s
      retries: 10
      start_period: 120s
    networks:
      - atlas

  # --- Geometric Lens (C(x)/G(x) scoring) ---
  geometric-lens:
    build:
      context: ./geometric-lens
    environment:
      - LLAMA_URL=http://llama-server:8080
      - LLAMA_EMBED_URL=http://llama-server:8080
      - GEOMETRIC_LENS_ENABLED=true
      - PROJECT_DATA_DIR=/data/projects
    volumes:
      - lens-data:/data/projects
      - ${ATLAS_LENS_MODELS:-./geometric-lens/geometric_lens/models}:/app/geometric_lens/models:ro
    ports:
      - "${ATLAS_LENS_PORT:-8099}:8099"
    depends_on:
      llama-server:
        condition: service_healthy
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:8099/health"]
      interval: 15s
      timeout: 5s
      retries: 5
    networks:
      - atlas

  # --- V3 Pipeline Service ---
  v3-service:
    build:
      context: .
      dockerfile: v3-service/Dockerfile
    environment:
      - ATLAS_INFERENCE_URL=http://llama-server:8080
      - ATLAS_LENS_URL=http://geometric-lens:8099
      - ATLAS_SANDBOX_URL=http://sandbox:8020
      - ATLAS_MODEL_NAME=${ATLAS_MODEL_NAME:-Qwen3.5-9B-Q6_K}
    ports:
      - "${ATLAS_V3_PORT:-8070}:8070"
    depends_on:
      llama-server:
        condition: service_healthy
      geometric-lens:
        condition: service_healthy
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:8070/health"]
      interval: 15s
      timeout: 5s
      retries: 5
    networks:
      - atlas

  # --- Sandbox (isolated code execution) ---
  sandbox:
    build:
      context: ./sandbox
    tmpfs:
      - /tmp/sandbox:size=512M
    read_only: true
    security_opt:
      - no-new-privileges:true
    ports:
      - "${ATLAS_SANDBOX_PORT:-30820}:8020"
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:8020/health"]
      interval: 15s
      timeout: 5s
      retries: 3
    networks:
      - atlas

  # --- ATLAS Proxy v2 (agent loop + grammar + Aider format) ---
  # The proxy needs access to your project files for read_file, write_file, etc.
  # Set ATLAS_PROJECT_DIR to your project path, or it defaults to the current directory.
  atlas-proxy:
    build:
      context: ./atlas-proxy
    environment:
      - ATLAS_PROXY_PORT=8090
      - ATLAS_INFERENCE_URL=http://llama-server:8080
      - ATLAS_LLAMA_URL=http://llama-server:8080
      - ATLAS_LENS_URL=http://geometric-lens:8099
      - ATLAS_SANDBOX_URL=http://sandbox:8020
      - ATLAS_V3_URL=http://v3-service:8070
      - ATLAS_AGENT_LOOP=1
      - ATLAS_MODEL_NAME=${ATLAS_MODEL_NAME:-Qwen3.5-9B-Q6_K}
    volumes:
      - ${ATLAS_PROJECT_DIR:-.}:/workspace
    working_dir: /workspace
    ports:
      - "${ATLAS_PROXY_PORT:-8090}:8090"
    depends_on:
      llama-server:
        condition: service_healthy
      geometric-lens:
        condition: service_healthy
      v3-service:
        condition: service_healthy
      sandbox:
        condition: service_healthy
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:8090/health"]
      interval: 10s
      timeout: 5s
      retries: 5
    networks:
      - atlas

volumes:
  lens-data:

networks:
  atlas:
    driver: bridge