AI-Tutor is a modular educational assistant that leverages advanced LLMs and agentic AI workflows to help students learn science and technology. It integrates LangChain for LLM orchestration, LangGraph for agent execution, LangSmith for monitoring and analytics, FAISS for vector-based retrieval, and Gradio for a user-friendly web interface. Student

🧑‍🏫 AI Tutor (Nemo)

📖 Project Overview

AI Tutor (Nemo) is an intelligent, interactive tutor built for science and technology students. It combines Large Language Models (LLMs) with agentic workflows to provide two core capabilities:

• 💬 PDF Tutoring (RAG): Answers questions from uploaded textbooks/notes (retrieval mode).
• 🎥 Video Summarization: Transcribes and summarizes uploaded video files or YouTube links.

This system is designed to simulate a personalized AI tutor: patient, accurate, and adapted to a student’s multi-modal learning materials.

🎥 Demo Video Summarizer(New feature)

https://github.com/user-attachments/assets/4e5c3307-2cc4-4eee-8eae-d26be04b7322

🎥 Demo PDF Tutor(old feature)

https://github.com/user-attachments/assets/87b4eacf-5509-4cf5-afe1-36eec3fa2b2b

⚡ Key Features

PDF Tutoring (RAG)

• 🤖 LLM-powered tutoring using Google Generative AI (Gemini).
• 🧠 Context-aware agents with LangChain and LangGraph to manage reasoning steps.
• 📄 PDF knowledge ingestion: Extracts content, splits it, and stores embeddings in FAISS for retrieval.
• 📐 Math rendering with LaTeX: All formulas are displayed cleanly in Mark