An AI-powered analytics dashboard built for the UIDAI Hackathon — visualizing Aadhaar enrolment trends across India with state & district level insights.
🔗 Live Demo: https://uidai-hackathon-phi.vercel.app/ 📦 Repository: https://github.com/sweetylearner-max/UIDAI-Hackathon
- 🗺️ Interactive India Map — click any state or district to drill down
- 📊 Enrolment statistics by state, district & pincode
- 👥 Age distribution charts (enrolment vs population)
- 🤖 AI-generated insights using LangGraph + Groq LLM
- 🌐 Web search-enriched regional context
- 📡 Real-time streaming AI overview (SSE)
- 🔍 Low & high enrolment district detection
| Technology | Usage |
|---|---|
| Next.js 16 | Framework |
| React 19 | UI |
| Tailwind CSS v4 | Styling |
| React Leaflet | India Map |
| Lucide React | Icons |
| React Markdown | AI output rendering |
| Technology | Usage |
|---|---|
| FastAPI | API Server |
| Pandas | Data processing |
| LangGraph | AI Agent |
| LangChain + Groq | LLM Integration |
| Uvicorn | ASGI Server |
- Python 3.11+
- Node.js 18+
-
Clone the repository:
git clone https://github.com/sweetylearner-max/UIDAI-Hackathon.git cd UIDAI-Hackathon -
Setup environment variables:
cp .env.example .env
-
Install & run Backend:
cd backend pip install -r requirements.txt uvicorn app.main:app --reload -
Install & run Frontend:
cd frontend npm install npm run dev
UIDAI-Hackathon/
├── backend/
│ ├── AI_backend/ # LangGraph AI agent
│ │ ├── overview_agent.py
│ │ └── web_tool.py
│ ├── app/
│ │ ├── main.py # FastAPI entry point
│ │ ├── data_loader.py # CSV data loading
│ │ ├── filters.py # Region filters
│ │ ├── stats.py # Statistics
│ │ └── insights.py # Insights logic
│ ├── data/ # Aadhaar CSV datasets
│ └── requirements.txt
├── frontend/
│ ├── app/ # Next.js pages
│ ├── components/ # UI components
│ └── lib/ # API & utilities
└── .env.example
- Akanksha Bursu
- Ayaansh
- Likitha
- Prem Kumar
- Ajith
- Saanvika
Built with ❤️ by Team UIDAI Hackathon