ai-knowledge-assistant-python/docker-compose.yml at main · sabry-awad97/ai-knowledge-assistant-python · GitHub

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services:
  # PostgreSQL Database
  postgres:
    image: postgres:18-alpine
    container_name: ai-knowledge-postgres
    environment:
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres
      POSTGRES_DB: ai_knowledge_db
    ports:
      - "5432:5432"
    volumes:
      - postgres_data:/var/lib/postgresql/data
    healthcheck:
      test: [ "CMD-SHELL", "pg_isready -U postgres" ]
      interval: 10s
      timeout: 5s
      retries: 5
    networks:
      - ai-knowledge-network

  # Weaviate Vector Database
  weaviate:
    image: cr.weaviate.io/semitechnologies/weaviate:1.34.0
    container_name: ai-knowledge-weaviate
    command:
      - --host
      - 0.0.0.0
      - --port
      - '8080'
      - --scheme
      - http
    environment:
      QUERY_DEFAULTS_LIMIT: 25
      AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: 'true'
      PERSISTENCE_DATA_PATH: '/var/lib/weaviate'
      ENABLE_MODULES: 'text2vec-ollama,generative-ollama'
      CLUSTER_HOSTNAME: 'node1'
    ports:
      - "8080:8080"
      - "50051:50051"
    volumes:
      - weaviate_data:/var/lib/weaviate
    restart: on-failure:0
    healthcheck:
      test: [ "CMD", "wget", "--spider", "-q", "http://localhost:8080/v1/.well-known/ready" ]
      interval: 10s
      timeout: 5s
      retries: 5
    networks:
      - ai-knowledge-network

  # FastAPI Application
  api:
    build:
      context: .
      dockerfile: Dockerfile
    image: ai-knowledge-assistant-api:latest
    container_name: ai-knowledge-api
    models:
      - embedding-gemma
    environment:
      # Database
      POSTGRES_HOST: postgres
      POSTGRES_PORT: 5432
      POSTGRES_USER: postgres
      POSTGRES_PASSWORD: postgres
      POSTGRES_DB: ai_knowledge_db

      # Weaviate
      WEAVIATE_HOST: weaviate
      WEAVIATE_PORT: 8080
      WEAVIATE_GRPC_PORT: 50051

      # Docker AI (for embeddings)
      DOCKER_AI_URL: ${DOCKER_AI_URL:-http://host.docker.internal:12434}
      EMBEDDING_MODEL: ${EMBEDDING_MODEL:-ai/embeddinggemma}

      # Gemini API (for generation only)
      GEMINI_API_KEY: ${GEMINI_API_KEY}

      # Security
      SECRET_KEY: ${SECRET_KEY:-your-secret-key-change-in-production}

      # Logging
      LOG_LEVEL: ${LOG_LEVEL:-INFO}
    ports:
      - "8000:8000"
    volumes:
      - ./uploads:/app/uploads
      - ./src:/app/src
      - ./asgi.py:/app/asgi.py
    depends_on:
      postgres:
        condition: service_healthy
      weaviate:
        condition: service_healthy
    networks:
      - ai-knowledge-network
    command: python asgi.py

volumes:
  postgres_data:
  weaviate_data:


models:
  embedding-gemma:
    model: ${EMBEDDING_MODEL:-ai/embeddinggemma}

networks:
  ai-knowledge-network:
    driver: bridge