RAG 101: Introduction to Retrieval-Augmented Generation with Python

In this beginner-friendly video, we’ll take a look at the fundamental concepts behind Retrieval-Augmented Generation (RAG) and why it’s quickly becoming a go-to technique for building powerful AI applications. You’ll learn what sets RAG apart from traditional language model workflows, the essential components needed (like vector databases and LLMs), and how Python and LangChain come together to make the magic happen. We’ll walk you through a simple example of indexing and querying documents so you can see RAG in action. Whether you’re a data scientist, software engineer, or just curious about cutting-edge AI, this introduction will give you a solid foundation for everything that follows in our RAG with LangChain series. By the end, you’ll understand how RAG systems empower users to tap into large collections of data in real time-leading to more accurate and context-rich answers from language models. Get ready to supercharge your AI projects with Python and RAG!