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🚦 TPLLM — Flask + React

Simple traffic prediction dashboard with a Flask backend and React (Vite) frontend.

Project Structure

  • api/ — Flask API with /predict and /health
  • public/ — Static assets (logo)
  • src/ — React components and styles
  • package.json — Vite-powered frontend scripts

Getting Started

Backend (Flask)

  1. cd api
  2. python -m venv .venv && .venv\Scripts\activate (Windows)
  3. pip install -r requirements.txt
  4. python app.py (runs on http://localhost:5000)

Frontend (React + Vite)

  1. Install Node.js 18+
  2. From project root: npm install
  3. npm run dev (runs on http://localhost:3000)

The React app calls the Flask API at http://localhost:5000/predict by default. Override with VITE_API_BASE in a .env file if needed.

Deployment Notes

  • Keep Flask and React served separately or proxy /predict during production.
  • Update CORS settings in api/app.py if you restrict origins.

License

MIT License

About

TPLLM is an AI-driven framework designed to reduce traffic congestion and optimize vehicle flow in highly populated areas. It leverages LLMs (LLaMA-GPT style models), real-time traffic streaming data, and predictive analytics to forecast traffic conditions.

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