docker-compose.yml

services:
  # Base de données pour les logs et les vecteurs (RAG)
  postgres:
    image: pgvector/pgvector:pg15
    container_name: agent_postgres
    environment:
      POSTGRES_USER: admin
      POSTGRES_PASSWORD: adminpassword
      POSTGRES_DB: agent_db
    ports:
      - "5432:5432"
    volumes:
      - postgres_data:/var/lib/postgresql/data

  # Cache et Queue
  redis:
    image: redis:alpine
    container_name: agent_redis
    ports:
      - "6379:6379"

  neo4j:
    image: neo4j:5.15.0
    container_name: agent_neo4j
    ports:
      - "7474:7474" # Interface Admin (Browser)
      - "7687:7687" # Port Bolt (Pour l'API Python)
    environment:
      NEO4J_AUTH: neo4j/password1234 # User/Pass basique
      # Plugins pour des algos avancés
      NEO4J_PLUGINS: '["apoc", "graph-data-science"]'
    volumes:
      - neo4j_data:/data

  # Notre API (Backend)
  api:
    build: ./backend
    container_name: agent_api
    command: uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
    volumes:
      - ./backend:/app
    ports:
      - "8000:8000"
    environment:
      - DATABASE_URL=postgresql://admin:adminpassword@postgres:5432/agent_db
      # Connexion Neo4j
      - NEO4J_URI=bolt://neo4j:7687
      - NEO4J_USERNAME=neo4j
      - NEO4J_PASSWORD=password1234
      # CRITIQUE : Il faut une clé Google pour construire le graphe
      - LLM_PROVIDER=${LLM_PROVIDER}
      - GROQ_API_KEY=${GROQ_API_KEY}
      - GROQ_MODEL=${GROQ_MODEL}
      - GOOGLE_API_KEY=${GOOGLE_API_KEY}
      - GOOGLE_MODEL=${GOOGLE_MODEL}
    env_file:
      - .env
    depends_on:
      - postgres
      - redis
      - neo4j

volumes:
  postgres_data:
  neo4j_data: