This project is a FastAPI-based application for generating Parsons problems, which are educational programming exercises. The application uses OpenAI's GPT model to generate problems based on user-selected programming concepts and difficulty levels.

• Dynamic Front-End: A user-friendly front-end built with HTML and JavaScript, dynamically updates based on user input.
• AI-Generated Problems: Uses OpenAI's GPT model to generate Parsons problems tailored to the selected programming language, concepts, and difficulty.
• GET API Endpoint: A /generate-problems endpoint that accepts query parameters to generate problems.
• Cross-Origin Support: Configured with CORS middleware to allow requests from any origin.

pyproject.toml       # Project configuration file
README.md            # Project documentation
server.py            # Main FastAPI application
uv.lock              # Dependency lock file
static/              # Static files (e.g., CSS, JS)
templates/           # HTML templates
    index.html       # Front-end interface

1. Clone the repository:

   git clone <repository-url>
   cd <repository-folder>

2. Install dependencies using uv:

   uv pip install -r pyproject.toml

3. Set up environment variables: Create a .env file in the root directory with the following variables:

   OPENAI_API_KEY=<your-openai-api-key>
   OPENAI_API_BASE=https://api.openai.com/v1
   OPENAI_API_MODEL_NAME=gpt-4

1. Start the server in debug mode:

   uv run uvicorn server:app --reload

2. Open your browser and navigate to:

   • Front-end: http://127.0.0.1:8000/
   • API Documentation: http://127.0.0.1:8000/docs

1. Use the front-end interface to select a programming language, concepts, and the number of problems.
2. The application dynamically generates a URL for the API request.
3. Click "Preview Result" to fetch and display the generated problems.
4. Copy the generated URL to use it in other tools or applications.

Generates Parsons problems based on the provided query parameter.

• specification (string): A base64-encoded JSON string containing the problem specification. The JSON object should have the following structure:

  {
      "language": "Python",
      "concepts": {
          "Easy": {
              "Variable Assignment": true,
              "Basic Arithmetic": false
          },
          "Medium": {
              "Functions": true
          },
          "Hard": {
              "Recursion": false
          }
      },
      "num_problems": 3
  }

curl "http://127.0.0.1:8000/generate-problems?specification=eyJsYW5ndWFnZSI6ICJQeXRob24iLCAiY29uY2VwdHMiOiB7IkVhc3kiOiB7IlZhcmlhYmxlIEFzc2lnbm1lbnQiOiB0cnVlLCAiQmFzaWMgQXJpdGhtZXRpYyI6IGZhbHNlfSwgIk1lZGl1bSI6IHsiRnVuY3Rpb25zIjogdHJ1ZX0sICJIYXJkIjogeyJSZWN1cnNpb24iOiBmYWxzZX19LCAibnVtX3Byb2JsZW1zIjogM30="

The specification parameter is a base64-encoded string of the JSON object. You can use tools like btoa in JavaScript or base64 in Python to encode the JSON object.

This project is licensed under the MIT License. See the LICENSE file for details.

• Written by Adam Smith using GitHub Copilot agent mode
• Built with FastAPI
• Powered by OpenAI GPT