Ragas

Evaluation framework specialized for measuring and optimizing RAG pipeline quality.

Overview

Ragas provides a standardized set of metrics to evaluate retrieval-augmented generation systems, including faithfulness, answer relevance, and context precision. It works by generating reference-free evaluation datasets and scoring them against your pipeline's outputs, enabling continuous optimization of retrievers and generators.

Best for

• RAG quality measurement
• retriever optimization
• reference-free evaluation

Trade-offs

What XeroHack pre-wires

When you pick Ragas in the interview, the engine emits these files into your scaffold:

• ragas evaluate(...) with default RAG metrics
• dataset generation for few-shot evals