Comprehensive-RAG-Evaluation-Metrics
This library provides a comprehensive suite of metrics to evaluate the performance of Retrieval-Augmented Generation (RAG) systems. RAG systems, which combine information retrieval with text generation, present unique evaluation challenges beyond those found in standard language generation tasks
Details
- Author
- Beekash Mohanty
- GitHub profile
- @beekash222
- Category
- AI Infrastructure
- Platform
- PyPI
- GitHub
- https://github.com/beekash222/RAG_EVAL
- Framework
- unknown
- Language
- python
- Stars
- 0
- First indexed
- 2026-05-15
- Last active
- —
- Directory sync
- 2026-05-15
Overview
This library provides a comprehensive suite of metrics to evaluate the performance of Retrieval-Augmented Generation (RAG) systems. RAG systems, which combine information retrieval with text generation, present unique evaluation challenges beyond those found in standard language generation tasks
Quick start
pip
pip install Comprehensive-RAG-Evaluation-MetricsSnippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.
What Comprehensive-RAG-Evaluation-Metrics can do
Frequently asked questions
What is Comprehensive-RAG-Evaluation-Metrics?
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