docker-compose.yml

services:
  db:
    image: pgvector/pgvector:pg16
    ports:
      - "5432:5432"
    environment:
      POSTGRES_USER: ${POSTGRES_USER:-rag}
      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-rag}
      POSTGRES_DB: ${POSTGRES_DB:-rag}
    volumes:
      - pgdata:/var/lib/postgresql/data
    healthcheck:
      test:
        - CMD-SHELL
        - pg_isready -U "$$POSTGRES_USER" -d "$$POSTGRES_DB"
      interval: 5s
      timeout: 3s
      retries: 12
      start_period: 5s
    restart: unless-stopped

  app:
    build:
      context: .
      dockerfile: Dockerfile
    env_file:
      - .env
    environment:
      # Override the .env DATABASE_URL host so the app talks to the
      # `db` service inside the compose network, regardless of what
      # the developer put in .env (which may point at localhost for
      # host-side tooling).
      DATABASE_URL: postgresql://${POSTGRES_USER:-rag}:${POSTGRES_PASSWORD:-rag}@db:5432/${POSTGRES_DB:-rag}
    ports:
      - "8000:8000"
    # Linux: make host.docker.internal resolve to the host so the
    # local OpenAI-API-compatible grounding judge (LM Studio / Ollama /
    # llama.cpp) is reachable from inside the container, matching the
    # macOS/Windows behavior of Docker Desktop. Feature 002 / FR-028.
    extra_hosts:
      - "host.docker.internal:host-gateway"
    volumes:
      # Mount data/ so `make ingest` (which dispatches inside the
      # container) can reach the committed sample PDF + any PDFs the
      # developer drops in, and write ingested PDFs for serving.
      - ./data:/app/data
      # Mount evals/ read-write so `make eval` can read the committed
      # question set AND write fresh results.{jsonl,md} that we then
      # commit. Feature 005 / Article III.
      - ./evals:/app/evals
    depends_on:
      db:
        condition: service_healthy
    restart: unless-stopped

volumes:
  pgdata: