Ragas
RAGAS, an acronym for Retrieval Augmented Generation Assessment, is a framework specifically designed to evaluate Retrieval Augmented Generation (RAG) pipelines. RAG pipelines represent a category of Large Language Model (LLM) applications that utilize external data to enhance the context of the LLM.
Areas of application
- Machine Learning
- Data Science
- Natural Language Processing
- Question Answering Systems
- Large Language Models
Example
For example, in a question-answering system, a RAG pipeline could use a database of facts to provide more accurate and detailed answers. The RAGAS framework would then be used to assess the effectiveness of this pipeline.