We have discussed RAG before, but now it’s time to dive into building your own RAG solution.

What is RAG? RAG stands for Retrieval-Augmented Generation. It is a technique that combines retrieval-based methods with generative models to improve the quality and accuracy of generated text. This approach leverages relevant documents from a database to provide context and information that enhance the generative process.

In this talk, we will first explore RAG in more detail. Then, we will demonstrate how to build a simple RAG solution using Python. Our approach will utilize 100% open-source tools, including open-source Large Language Models (LLMs), to create a free and secure solution.