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

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