I Built a RAG-Based PDF Reader Web App Using Node.js, LangChain, Ollama, and Hugging Face

I Built a RAG-Based PDF Reader Web App Using Node.js, LangChain, Ollama, and Hugging Face Turn any PDF into an interactive AI knowledge base using Retrieval-Augmented Generation (RAG). If you've ever wanted to upload a PDF and chat with it like ChatGPT , this project does exactly that. I built a RAG-based PDF Reader Web App that allows users to: 📄 Upload a PDF file 🔍 Extract and process the content ✂️ Split the content into chunks 🧠 Generate embeddings locally 💾 Store them in a vector store 🎯 Retrieve relevant sections based on user questions 🤖 Generate grounded answers using a local LLM This project combines traditional web development with modern AI application design , making it a great hands-on example of how RAG works in practice. 💡 Live Idea of the Project The goal of this app is simple: Upload a PDF and ask questions about its content in natural language. Instead of manually searching through long reports, research papers, notes, books, or documentation, users can just ask: "Wha