📚 Study Buddy

A simple learning project to explore AI integration and LLM implementation. This app demonstrates how to integrate local LLMs with web applications by creating a PDF analysis tool using FastAPI and Ollama.

� Learning Purpose

This project was built to understand:

• How to integrate LLMs into web applications
• Working with local AI models using Ollama
• Building API endpoints that interact with AI
• Processing documents and providing contextual AI responses
• Session management for conversational AI interfaces

⚡ What It Does

• Upload PDF documents for AI analysis
• Generate summaries, questions, flashcards, and outlines
• Ask follow-up questions about uploaded documents
• Demonstrates different prompt engineering techniques

🛠 Tech Stack

• FastAPI - Web framework
• Ollama + Llama3 - Local LLM processing
• PyMuPDF - PDF text extraction
• HTML/CSS/JS - Simple frontend

� Quick Start

1. Install Ollama and pull Llama3

   # Install from https://ollama.ai/
   ollama pull llama3

2. Install Python dependencies

   pip install fastapi uvicorn PyMuPDF ollama python-multipart

3. Run the application

   python main.py

4. Open upload_form.html in your browser

� Key Learning Areas

• LLM Integration: How to connect FastAPI with local AI models
• Prompt Engineering: Different prompts for various analysis types
• Session Management: Maintaining context across AI conversations
• Document Processing: Extracting and chunking text for AI analysis
• API Design: Building endpoints that work with AI workflows

📁 Key Files

• main.py - FastAPI app with AI integration logic
• upload_form.html - Simple frontend interface
• Sample PDFs and test scripts for experimentation