# =============================================================================
# StockGNN R9700 — Docker Compose Stack
# =============================================================================
# Services:
#   - dashboard   : FastAPI web frontend (http://localhost:8000)
#   - live-trading: Continuous paper/live trading engine
#   - train       : One-off model training & backtesting
#
# Requirements:
#   - Docker 20.10+ with Compose v2
#   - AMD GPU + ROCm 5.6+ drivers on host
#   - docker-compose run --rm train   # manual training
# =============================================================================

services:
  # -------------------------------------------------------------------------
  # Base image build (shared by all services)
  # -------------------------------------------------------------------------
  dashboard:
    build:
      context: .
      dockerfile: Dockerfile
    image: stockgnn:r9700
    container_name: stockgnn-dashboard
    restart: unless-stopped

    # Override default CMD for the web dashboard
    command: >
      python -m uvicorn src.web.app:app
      --host 0.0.0.0
      --port 8000
      --reload

    ports:
      - "8000:8000"

    volumes:
      # Persist data & model artefacts across restarts
      - ./data:/app/data
      - ./models:/app/models
      - ./logs:/app/logs
      # Optional: mount source for live-reload during development
      # - ./src:/app/src

    env_file:
      - .env

    environment:
      # ROCm / AMD GPU tuning
      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
      # Ensure the app knows it is inside a container
      STOCKGNN_ENV: docker

    # AMD GPU device access
    devices:
      - /dev/kfd
      - /dev/dri

    # Required groups for GPU access inside the container
    group_add:
      - video
      - render

    # Security / capability settings for ROCm
    security_opt:
      - seccomp:unconfined

    # Shared memory size for PyTorch DataLoader multiprocessing
    shm_size: "8gb"

    # Health-check for the web dashboard
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/api/dashboard/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

    networks:
      - stockgnn-net

  # -------------------------------------------------------------------------
  # Live Trading Engine (paper or live — controlled via config.py)
  # -------------------------------------------------------------------------
  live-trading:
    build:
      context: .
      dockerfile: Dockerfile
    image: stockgnn:r9700
    container_name: stockgnn-live-trading
    restart: unless-stopped

    command: >
      python live_trading.py

    volumes:
      - ./data:/app/data
      - ./models:/app/models
      - ./logs:/app/logs

    env_file:
      - .env

    environment:
      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
      STOCKGNN_ENV: docker

    devices:
      - /dev/kfd
      - /dev/dri

    group_add:
      - video
      - render

    security_opt:
      - seccomp:unconfined

    shm_size: "8gb"

    networks:
      - stockgnn-net

    # Do not auto-start live trading until the user explicitly brings it up
    profiles:
      - live

  # -------------------------------------------------------------------------
  # Model Training & Backtesting (run manually)
  # -------------------------------------------------------------------------
  # Usage:
  #   docker compose run --rm train
  # -------------------------------------------------------------------------
  train:
    build:
      context: .
      dockerfile: Dockerfile
    image: stockgnn:r9700
    container_name: stockgnn-train

    command: >
      python main.py

    volumes:
      - ./data:/app/data
      - ./models:/app/models
      - ./logs:/app/logs

    env_file:
      - .env

    environment:
      HSA_OVERRIDE_GFX_VERSION: "${HSA_OVERRIDE_GFX_VERSION:-10.3.0}"
      PYTORCH_HIP_ALLOC_CONF: "expandable_segments:True"
      STOCKGNN_ENV: docker

    devices:
      - /dev/kfd
      - /dev/dri

    group_add:
      - video
      - render

    security_opt:
      - seccomp:unconfined

    shm_size: "16gb"

    networks:
      - stockgnn-net

    profiles:
      - train

# -----------------------------------------------------------------------------
# Shared network
# -----------------------------------------------------------------------------
networks:
  stockgnn-net:
    driver: bridge