TL;DR: I built an end-to-end RAG application that lets you upload any PDF and chat with it. It uses FAISS for vector search, sentence-transformers for embeddings, and Llama 3.1 via Groq for free LLM inference. This article walks through the full architecture, every bug I hit, and how to build it yourself. Why I Built This I was working through a Machine Learning course final project and kept running into the same problem: I had dozens of research papers and lecture notes as PDFs, and finding specific information meant scrolling through hundreds of pages manually. So I built a solution. An AI assistant that reads your PDFs, understands them semantically, and answers your questions in plain English — with explanations, not just copied text. The result is PDF Q&A Pro : a multi-tab Streamlit app powered by a RAG pipeline.…