LabNav - AI-Powered Search for Virtual Labs

📌 Overview

This project was developed as part of OLabs Hackathon 2025 (OLabsThon), a national-level technology event organized by Amrita School of Computing, ACM Student Chapter, and Amrita CREATE. The project aims to enhance OLabs, an online virtual laboratory initiative, by integrating an AI-powered search system for improved accessibility and resource discovery.

🎯 Objective

Our goal was to create an intelligent search functionality that helps students easily find and relate educational resources, experiment manuals, and relevant study materials.

Why?

• ✨ Bridging the gap: Many students in rural areas lack access to physical labs.
• ✨ Enhancing e-learning: AI-powered search improves student engagement, memory retention, and independent learning.
• ✨ Making OLabs a self-study tool: Enabling seamless access to study materials with intelligent recommendations.

🚀 Features

• ✅ AI-Powered Search: Finds and suggests relevant resources from experiment manuals and academic materials.
• ✅ PDF Processing: Extracts text from PDFs and indexes it for efficient search.
• ✅ Semantic Search with TensorFlow: Uses NLP-based embeddings for smart document retrieval.
• ✅ Scalable Web Application: Built with Next.js for a modern and responsive UI.
• ✅ Backend with Python & Flask: Manages search indexing and data retrieval.
• ✅ User-Friendly Interface: Categorized subject-wise search results.

🏗️ Tech Stack

Frontend

• Next.js (React framework) for building the user interface.
• CSS for styling.

Backend

• Flask for API development.
• Python for processing PDFs and search functionalities.
• TensorFlow for embedding-based semantic search.
• PostgreSQL for data storage.

🛠️ Setup & Installation

1️⃣ Backend Setup

cd backend
pip install -r requirements.txt
python app.py

2️⃣ Frontend Setup

cd frontend
npm install
npm run dev

3️⃣ Access the Web Application

Open http://localhost:3000 in your browser.

🔗 Future Scope

• Integration with OLabs: Embedding the AI-powered search feature into the official OLabs platform.
• Advanced AI Suggestions: Implementing GPT-based recommendations for study pathways.
• Blockchain Credentials: Secure verification of experiment completion.

👥 Team & Credits

This project was developed by a team of passionate developers during OLabsThon 2025. Special thanks to Amrita CREATE, ACM Student Chapter, and OLabs Hackathon organizers for the opportunity.