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Ragas

Ragas is an open-source framework designed for evaluating Retrieval Augmented Generation (RAG) systems. It provides metrics to measure aspects such as faithfulness, answer relevance, and context recall within RAG pipelines and other LLM applications. The framework offers fine-grained control over evaluation metrics, requiring technical setup for implementation. This tool is specialized for RAG-based AI agents, offering domain-specific metrics for programmatic evaluation of LLM outputs. It provides a deep evaluation of LLM outputs, particularly for RAG systems, allowing users to assess the performance and reliability of their AI applications.

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Overview

Ragas is an open-source framework designed for evaluating Retrieval Augmented Generation (RAG) systems. It provides metrics to measure aspects such as faithfulness, answer relevance, and context recall within RAG pipelines and other LLM applications. The framework offers fine-grained control over evaluation metrics, requiring technical setup for implementation.

This tool is specialized for RAG-based AI agents, offering domain-specific metrics for programmatic evaluation of LLM outputs. It provides a deep evaluation of LLM outputs, particularly for RAG systems, allowing users to assess the performance and reliability of their AI applications.

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