open-rag-eval and RAG-Evaluator

open-rag-eval
53
Established
RAG-Evaluator
33
Emerging
Maintenance 6/25
Adoption 10/25
Maturity 25/25
Community 12/25
Maintenance 0/25
Adoption 3/25
Maturity 16/25
Community 14/25
Stars: 347
Forks: 21
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 4
Forks: 3
Downloads:
Commits (30d): 0
Language: Python
License: MIT
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Stale 6m No Package No Dependents

About open-rag-eval

vectara/open-rag-eval

RAG evaluation without the need for "golden answers"

This tool helps RAG (Retrieval Augmented Generation) system builders and integrators assess and improve the quality of their AI-powered question-answering systems. You provide a set of questions (queries) and receive detailed performance scores and diagnostic reports, identifying how well your RAG system retrieves relevant information and generates accurate answers. This is for anyone building or maintaining a RAG system, such as AI product managers, machine learning engineers, or solution architects.

AI-powered search Generative AI evaluation RAG system optimization Customer support automation Knowledge base accuracy

About RAG-Evaluator

GURPREETKAURJETHRA/RAG-Evaluator

A library for evaluating Retrieval-Augmented Generation (RAG) systems

Scores updated daily from GitHub, PyPI, and npm data. How scores work