Understanding RAG by Building a ChatPDF App with NumPy (Part 1)
๐ง Building a Chat with PDF App (From Scratch using NumPy) โ Part 1 Turning a simple PDF into a conversational AI system using local LLMs ๐ ๐ Introduction Have you ever wanted to chat with your P...

Source: DEV Community
๐ง Building a Chat with PDF App (From Scratch using NumPy) โ Part 1 Turning a simple PDF into a conversational AI system using local LLMs ๐ ๐ Introduction Have you ever wanted to chat with your PDF documents like you chat with ChatGPT? In this series, Iโll walk you through building a ChatPDF application from scratch, starting from the absolute basics and gradually improving it into a production-ready system. ๐ In this first part, weโll build a naive RAG (Retrieval-Augmented Generation) system using only NumPy โ no FAISS, no vector databases, just pure fundamentals. ๐ฏ What Weโll Build By the end of this article, youโll have: ๐ A system that reads a PDF โ๏ธ Splits it into meaningful chunks ๐ข Converts text into embeddings using a local model ๐ Searches relevant content using vector similarity ๐ฌ Generates answers using an LLM โ๏ธ Tech Stack pdfplumber โ Extract text from PDFs numpy โ Perform vector similarity search ollama โ Run local embedding + LLM models ๐งฉ How It Works (High Leve