# Ragas **Category:** Model Evaluation & Benchmarking **Website:** https://docs.ragas.io **GitHub:** https://github.com/explodinggradients/ragas **Pricing:** Open Source **Listing status:** verified **Canonical:** https://aicompliance.ai/tools/ragas ## Summary Open-source evaluation framework purpose-built for retrieval-augmented generation pipelines. ## TL;DR - Ragas — Open-source evaluation framework purpose-built for retrieval-augmented generation pipelines. - Category: Model Evaluation & Benchmarking. - Pricing model: Open Source. - Open-source code available on GitHub. ## Description Ragas is the reference open-source toolkit for RAG evaluation: faithfulness, answer relevancy, context precision, and context recall metrics that quantify whether a pipeline retrieves the right evidence and stays grounded in it. Lightweight and notebook-friendly, it is often the first eval a RAG team adopts. - RAG-specific metric suite - Testset generation from documents - LangChain and LlamaIndex integrations - Works with any LLM as judge ## Core features - RAG-specific metric suite - Testset generation from documents - LangChain and LlamaIndex integrations - Works with any LLM as judge ## FAQ ### What is Ragas? Ragas is the reference open-source toolkit for RAG evaluation: faithfulness, answer relevancy, context precision, and context recall metrics that quantify whether a pipeline retrieves the right evidence and stays grounded in it. Lightweight and notebook-friendly, it is often the first eval a RAG team adopts. ### Does Ragas have compliance certifications? Ragas does not publicly list specific compliance frameworks in our directory. Confirm the latest posture directly with the vendor at https://docs.ragas.io. ### How much does Ragas cost? Ragas is open source, so you can self-host it for free. Managed/cloud tiers may be offered separately. ### Who is Ragas for? Teams working on model evaluation & benchmarking — particularly those that need to evidence AI compliance and security controls. ### Is Ragas open source? Yes — the source code is available on GitHub at https://github.com/explodinggradients/ragas. --- Canonical HTML page: https://aicompliance.ai/tools/ragas Source: AI Compliance Index (https://aicompliance.ai)