name: jira-llm-stack
services:
  # Service for the Ollama server
  ollama:
    image: ollama/ollama:latest
    # Map port 11434 from the container to the host machine
    # This allows you to access Ollama directly from your host if needed (e.g., via curl http://localhost:11434)
    ports:
      - "11434:11434"
    # Mount a volume to persist Ollama models and data
    # This prevents redownloading models every time the container restarts
    volumes:
      - ollama_data:/root/.ollama

    # CORRECTED COMMAND:
    # We explicitly tell Docker to use 'bash -c' to execute the string.
    # This ensures that 'ollama pull' and 'ollama serve' are run sequentially.
    entrypoint: ["sh"]
    command: ["-c", "ollama serve && ollama pull phi4-mini:latest"]
    
    # Restart the container if it exits unexpectedly
    restart: unless-stopped

  # Service for your FastAPI application
  app:
    # Build the Docker image for your app from the current directory (where Dockerfile is located)
    build: .
    # Map port 8000 from the container to the host machine
    # This allows you to access your FastAPI app at http://localhost:8000
    ports:
      - "8000:8000"
    # Define environment variables for your FastAPI application
    # These will be read by pydantic-settings in your app
    environment:
      # Set the LLM mode to 'ollama'
      LLM_MODE: ollama
      # Point to the Ollama service within the Docker Compose network
      # 'ollama' is the service name, which acts as a hostname within the network
      OLLAMA_BASE_URL: http://192.168.0.122:11434
      # Specify the model to use
      OLLAMA_MODEL: gemma3:1b
      # If you have an OpenAI API key in your settings, but want to ensure it's not used
      # when LLM_MODE is ollama, you can explicitly set it to empty or omit it.
      # OPENAI_API_KEY: ""
      # OPENAI_MODEL: ""
    # Ensure the Ollama service starts and is healthy before starting the app
    depends_on:
      - ollama
    # Restart the container if it exits unexpectedly
    restart: unless-stopped
    # Mount your current project directory into the container
    # This is useful for development, as changes to your code will be reflected
    # without rebuilding the image (if you're using a hot-reloading server like uvicorn --reload)
    # For production, you might remove this and rely solely on the Dockerfile copy.
    volumes:
      - .:/app
    # Command to run your FastAPI application using Uvicorn
    # --host 0.0.0.0 is crucial for the app to be accessible from outside the container
    # --reload is good for development; remove for production
    command: uvicorn jira-webhook-llm:app --host 0.0.0.0 --port 8000 --reload

# Define named volumes for persistent data
volumes:
  ollama_data:
    driver: local