To get this project up and running on your local machine, follow the instructions below:

1. Clone the Repository

git clone https://github.com/IbraheemGanayim/flask-openai-assignment.git
cd flask-openai-assignment

2. Set Up the Environment Variables

• Create a .env file in the root directory and add the following:

  OPENAI_API_KEY=your_openai_api_key_here
  

3. Build and Run the Docker Containers

Ensure that Docker is installed and running on your machine, then run:

docker-compose up --build

This command will:

• Build the Flask application container.
• Spin up the PostgreSQL database container.
• Automatically apply any database migrations using Alembic.

4. Access the Application

• Once everything is up and running, the API will be accessible at:

  • Flask App: http://localhost:5000

  Test the /ask endpoint by sending a POST request:

  curl -X POST http://localhost:5000/ask -H "Content-Type: application/json" -d '{"question": "What is AI?"}'
  

🧪 Running Tests 🧪

To ensure everything works as expected, you can run unit tests inside the Flask container.

1. Enter the Flask container:

   docker exec -it insait-flask-app /bin/sh
   

2. Run the tests:

   pytest app_test.py
   

🔄 Database Migrations

Alembic is used to handle database migrations. You can generate and apply new migrations with the following commands:

1. Create a new migration:

   alembic revision --autogenerate -m "your migration message"
   

2. Apply the migration:

   alembic upgrade head
   

📊 Project Workflow 📊

This project follows a logical development workflow:

1. Flask App Creation: Basic Flask app setup with /ask endpoint.
2. Docker Integration: Dockerized the application for easy deployment and testing.
3. PostgreSQL Integration: Set up the PostgreSQL database with SQLAlchemy.
4. Alembic Migrations: Handled schema changes via Alembic migrations.
5. Unit Testing: Added unit tests for the API functionality to ensure correctness.
6. Dockerized Testing: Configured Docker to support running unit tests inside containers.

🛠️ API Endpoints

• POST /ask
  • Description: Submit a question and receive a real answer generated by OpenAI's GPT model.
  • Request:

    {
      "question": "What is AI?"
    }
    

  • Response:

    {
      "question": "What is AI?",
      "answer": "AI stands for Artificial Intelligence, which refers to..."
    }
    

🔍 Future Improvements

• 🔒 Authentication: Add JWT-based authentication for API access.
• 🌐 Frontend Interface: Develop a simple UI using React or another frontend framework to interact with the API.

🎉 Thank You for Checking Out the Project! 🎉

Feel free to reach out if you have any questions! 😊

🖥️ Contact

• Linkedin: Ibraheem Ganayim
• Email: Ganayim.Ibraheem@gmail.com