Hacklahoma 2025 Project

A web application built for Hacklahoma 2025 using React frontend and Python/LangGraph backend using GenAI.

Project Structure

project/
├── frontend/                 # React frontend
│   ├── public/
│   ├── src/
│   │   ├── components/      # Reusable UI components
│   │   ├── pages/          # Page components
│   │   ├── services/       # API services
│   │   └── App.tsx
│   └── package.json
│
├── backend/                 # Python backend
│   ├── src/
│   │   ├── config/         # Configuration files
│   │   ├── graphs/         # LangGraph flows
│   │   │   ├── nodes/     # Individual graph nodes
│   │   │   └── flows/     # Graph flow definitions
│   │   ├── models/         # Data models
│   │   ├── routes/         # API routes
│   │   ├── utils/          # Utility functions
│   │   └── api/           # API endpoints
│   ├── tests/              # Test files
│   │   ├── test_nodes.py  # Node unit tests
│   │   ├── test_flow.py   # Flow integration tests
│   │   └── test_api.py    # API endpoint tests
│   ├── .env                # Environment variables
│   └── requirements.txt
│
└── README.md

Setup & Installation

Prerequisites

• Python 3.8+
• Node.js 16+
• MongoDB installed locally or MongoDB Atlas account
• OpenAI API key
• Groq API key

Backend Setup

1. Set up Python virtual environment:

   cd backend
   python -m venv venv
   source venv/bin/activate  # On Windows: .\venv\Scripts\activate

2. Install Python dependencies:

   pip install -r requirements.txt

3. Configure environment variables:

   # Copy the example environment file
   cp .env.example .env
   
   # Edit .env with your settings
   # Particularly, add your Groq API key

   Required environment variables:

   • GROQ_API_KEY: Your Groq API key
   • MONGODB_URL: MongoDB connection string
   • DATABASE_NAME: Name of the MongoDB database
   • MODEL_NAME: Groq model to use (default: mixtral-8x7b-32768)
   • MODEL_TEMPERATURE: Model temperature (default: 0.2)
   • MAX_ITERATIONS: Maximum feedback loop iterations (default: 3)
   • LOG_LEVEL: Logging level (default: INFO)

4. Start the backend server:

   uvicorn main:app --reload

Frontend Setup

1. Install Node.js dependencies:

   cd frontend
   npm install dependencies

Running Tests

Backend Tests

cd backend
pytest tests/

Available test suites:

• test_nodes.py: Unit tests for individual LangGraph nodes
• test_flow.py: Integration tests for the graph flow
• test_api.py: API endpoint tests

Frontend Tests

cd frontend
npm test

Running the Application

Start MongoDB

1. Local MongoDB:

   mongod

   Or ensure your MongoDB Atlas cluster is running

Start Backend Server

cd backend
source venv/bin/activate  # On Windows: .\venv\Scripts\activate
uvicorn main:app --reload

Start Frontend Server

cd frontend
npm run dev

API Flow

1. Planning Node: Analyzes user input and creates integration plan
2. Supervisor Node: Divides work into coding and testing tasks
3. Parallel Execution:
   • Coder Node: Generates implementation code
   • Tester Node: Creates test cases
4. Evaluator Node: Reviews code and test results
5. Feedback Loop: Supervisor reviews and decides on next steps

Technologies Used

• Frontend:
  • React
  • TypeScript
  • Tailwind
  • Vite
  • Axios
• Backend:
  • Python
  • FastAPI
  • LangGraph
  • LangChain
  • PyTest (Testing)

Development Guidelines

1. Run tests before committing changes
2. Check logs in backend/logs/ for debugging
3. Maximum 3 iterations for API integration feedback loop
4. Use type hints and documentation
5. Follow error handling patterns in BaseNode

Team Members

Louis, Raeed, Kyumin, and Devi

License

[Add license information]