Building a Simple RAG Q&A Assistant with LangChain and OpenAI

I recently explored how to combine LangChain and OpenAI’s GPT models to create an intelligent Retrieval-Augmented Generation (RAG) assistant. This project can read your local documents, store them in a searchable vector database, and answer questions based on your own text . What is RAG? RAG (Retrieval-Augmented Generation) is a powerful technique that combines informationContinue reading “Building a Simple RAG Q&A Assistant with LangChain and OpenAI”

Hello AI, Using OpenAI API with Python

Recently, I tried using OpenAI’s Python library for the first time — and I was amazed at how easy it is to create a conversational AI assistant with just a few lines of code. In this post, I’ll share my experience and a simple Python example that lets you chat directly with GPT right fromContinue reading “Hello AI, Using OpenAI API with Python”

AI for DBAs: Understanding AI Vectors

Imagine you’re building a robot librarian. Instead of organizing books by titles or authors, it groups them by meaning—romance novels near poetry, tech manuals near science fiction. This is exactly what AI vector databases do: they turn messy data (words, images, sounds) into meaningful numbers that machines can understand. Let’s break it down. 1. AI Vectors: Turning Chaos IntoContinue reading “AI for DBAs: Understanding AI Vectors”