Ragas

Ragas is an open-source Python library designed for evaluating the quality of Retrieval-Augmented Generation (RAG) systems. It provides metrics and tools to assess RAG pipelines by measuring aspects like faithfulness, answer relevance, context relevance, and context recall. This helps developers identify weaknesses and improve the performance of their RAG applications.

Also known as: RAGAS, RAG Evaluation, RAG Assessment, RAG Metrics, RAG Quality Tool

Why learn Ragas?

Developers should learn and use Ragas when building or optimizing RAG systems, such as chatbots, question-answering tools, or document-based AI assistants, to ensure reliable and accurate outputs. It is particularly useful during development, testing, and deployment phases to benchmark performance against industry standards and iterate on improvements based on quantitative feedback.

Learning Resources

• docs: Ragas Documentation
• tutorial: Getting Started with Ragas Tutorial
• video: RAG Evaluation with Ragas - YouTube Video
• tutorial: Ragas: A Framework for Evaluating RAG Pipelines - Article