Ragas: Open-source library for evaluating RAG pipelines
Published:Mar 21, 2024 15:48
•1 min read
•Hacker News
Analysis
Ragas is an open-source library designed to evaluate and test Retrieval-Augmented Generation (RAG) pipelines and other Large Language Model (LLM) applications. It addresses the challenges of selecting optimal RAG components and generating test datasets efficiently. The project aims to establish an open-source standard for LLM application evaluation, drawing inspiration from traditional Machine Learning (ML) lifecycle principles. The focus is on metrics-driven development and innovation in evaluation techniques, rather than solely relying on tracing tools.
Key Takeaways
- •Open-source library for evaluating RAG and LLM applications.
- •Addresses challenges in component selection and test data generation.
- •Aims to establish an open-source standard for LLM evaluation.
- •Focuses on metrics-driven development and innovative evaluation techniques.
Reference
“How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? How do you formulate a test dataset without spending tons of money and time?”