An AI-powered search engine integrating Google, YouTube, Reddit, and Google Scholar with real-time AI insights, sentiment analysis, and intelligent summaries.

• 🌍 Multi-Platform Search – Google, YouTube, Reddit, Google Scholar
• 🧠 AI-Powered Summaries – Smart summaries for retrieved results
• 💬 Real-Time Sentiment Analysis – Instant sentiment scoring
• ✅ Source Credibility Verification – Domain-based trust scoring
• 🎨 Retro-Inspired UI – Modern interactions with a vintage aesthetic
• 🌙 Dark Mode Support – Seamless experience in any lighting condition
• ⚡ Performance Optimizations – Caching, virtualized lists, lazy loading

• Frontend: React + Vite, Tailwind CSS, Framer Motion
• Backend: FastAPI (Python)
• AI Services: Hugging Face Models
• Caching: Custom Implementation
• Deployment: Vercel (Frontend), Railway + Gunicorn (Backend)

graph TD;
  User --> Frontend;
  Frontend --> |REST API| Backend;
  Backend --> |Search| Google/YouTube/Reddit/Scholar;
  Backend --> |AI Processing| HuggingFace_Models;
  Backend --> |Caching| Redis;

git clone https://github.com/Nischaya008/NeuraSeekNG.git
cd NeuraSeekNG

cd frontend
npm install

cd backend
pip install -r requirements.txt

uvicorn main:app --reload

npm run dev

• Summarizer: facebook/bart-large-cnn
• Sentiment Analysis: SamLowe/roberta-base-go_emotions
• Overall Sentiment: cardiffnlp/twitter-roberta-base-sentiment

The backend processes search results through AI pipelines for enhanced insights and credibility scoring.

• Custom Caching System – Reduces redundant requests
• Virtualized Lists – Smooth scrolling for large datasets
• Lazy Loading – Faster page loads and reduced bandwidth
• Debounced Search – Prevents excessive API calls

gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app

Deploy with one command:

vercel --prod

• CORS Configuration – Prevents unauthorized access
• API Key Management – Secure storage and usage
• Environment Variables – Keeps credentials safe

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

We welcome contributions! If you'd like to enhance NeuraSeekNG, feel free to:

1. Fork the repo
2. Create a feature branch (git checkout -b feature-name)
3. Commit your changes (git commit -m 'Add new feature')
4. Push to the branch (git push origin feature-name)
5. Open a PR

• 🔎 Personalized Search Ranking using Reinforcement Learning
• 🗂️ Search History & User Preferences
• 📈 Advanced Data Analytics Dashboard

For any inquiries or feedback, reach out via:

• 📧 Email: [email protected]
• 🐦 Twitter: @Nischaya008
• 💼 LinkedIn: Nischaya Garg

Stay Innovated, Keep Coding, Think BIG! 🚀