RAGAS - A Framework for Evaluating Retrieval Augmented Generation Systems

Explore a comprehensive technical video that delves into RAGAS, a groundbreaking framework for evaluating Retrieval-Augmented Generation (RAG) systems. Learn about the challenges of RAG evaluation and discover how RAGAS addresses these through three key criteria: faithfulness, answer relevance, and context relevance. Understand the fundamentals of RAG systems, examine practical examples using the arXiv Dive Bot, and investigate the WikiEval dataset. Master the intricacies of each evaluation criterion while gaining hands-on experience with Oxen AI's dataset versioning capabilities. Connect with the community through Discord, access supplementary materials including the original research paper, and leverage provided datasets to enhance your understanding of RAG evaluation methodologies.