🎓 AI Study Pal - Capstone Project Submission

Student Name: Alwin Project Title: AI Study Pal: Personalized RAG-Based Learning Assistant Date: December 2025

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🚀 Project Overview

AI Study Pal is a local-first, privacy-focused educational platform designed to help students learn faster and more effectively. Unlike generic AI chatbots, it uses Retrieval Augmented Generation (RAG) to "read" your personal notes and syllabus, ensuring that every answer is relevant to your specific curriculum.

Key Goals

1. Personalization: Adapt study plans and answers to the user's specific syllabus and files.
2. Privacy: Run AI models locally (TinyLlama) on consumer hardware without sending private data to the cloud.
3. Efficiency: Automate the creation of study schedules, quizzes, and summaries.

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✨ Features

• 🧠 Chat with Notes (RAG): Upload PDF/DOCX files and ask questions. The system references your content to answer accurately.
• 📅 Dynamic Study Planner: Generates a structured hourly schedule based on your subject, available hours, and goals.
• ❓ AI Quiz Engine: Automatically generates Multiple Choice Questions (MCQs) from your notes or any academic topic. Tracks performance over time.
• 📊 Adaptive Analytics: Visualizes your learning progress and knowledge gaps using dynamically generated charts.
• 📝 Intelligent Summarizer: Distills long documents into key themes and actionable insights.
• ⚡ Hardware-Aware Backend: "Smart Loader" detects your GPU (e.g., RTX 3050) and optimizes inference speed automatically.

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🛠️ Technology Stack

Frontend

• Framework: React + Vite (TypeScript)
• UI Library: Tailwind CSS + shadcn/ui
• Charts: Recharts

Backend

• Server: Python Flask
• AI Models: TinyLlama-1.1B (Local), Google Gemini (Cloud Fallback)
• RAG Engine: LangChain + FAISS + Sentence-Transformers
• Database: Supabase (PostgreSQL)

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📂 Submission Contents

1. Technical_Reference.md: A complete dictionary of every file in the codebase.
2. PROJECT_REPORT.md: A detailed report on architecture, challenges, and future scope.
3. SETUP_GUIDE.md: Instructions to install and run the project from scratch.

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⚡ Quick Start

1. Navigate to ai-study-pal-ui folder.
2. Run npm run dev to start the Frontend.
3. In a new terminal, run python backend/app.py to start the Backend.
4. Open http://localhost:5173.

(For full installation instructions, see SETUP_GUIDE.md)