RAGAS
RAG evaluation framework
0 case studies
Data Dev Framework RAG evaluation framework
Ragas is used to evaluate RAG pipeline quality with metrics like faithfulness, answer relevancy, context precision, and context recall. It provides automated evaluation without needing human annotations by using LLMs as judges, and generates synthetic test datasets from your documents for comprehensive pipeline testing.
Install with `pip install ragas` and set your OPENAI_API_KEY for the evaluator LLM. Prepare a dataset with questions, ground truth answers, retrieved contexts, and generated answers. Run `evaluate()` with your chosen metrics to get scores between 0 and 1 for each dimension of RAG quality.
$ pip install ragas` and set your OPENAI_API_KEY for the evaluator LLM Be the first to share a RAGAS case study and get discovered by clients.
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