DocuMind: Build Your Own RAG-Powered Chatbot for Project Knowledge
Part 2 of our Agentic AI Series Ever wished you had your own Jarvis — a chatbot that could instantly understand your project files, code, and notes? With Retrieval-Augmented Generation (RAG), you can build just that. In this post, we’ll walk through how to create a CLI-based chatbot that can learn from your local Markdown, TXT, and CSV files using open-source tools like Hugging Face Transformers and ChromaDB . 🔍 What is RAG (Retrieval-Augmented Generation)? Imagine a student trying to write an essay using just memory (LLM-only) vs. a student who Googles relevant material first and then writes the essay (RAG). RAG combines the reasoning power of an LLM with factual grounding from external knowledge sources. Core Components: Retriever: Finds relevant data chunks from a knowledge base Reader/Generator: Generates responses based on retrieved context 💡 Use Case: A Chatbot That Knows Your Codebase In large teams or solo projects, context is scattered a...
