rag-evaluator and nuclia-eval

rag-evaluator
52
Established
nuclia-eval
43
Emerging
Maintenance 0/25
Adoption 8/25
Maturity 25/25
Community 19/25
Maintenance 0/25
Adoption 6/25
Maturity 25/25
Community 12/25
Stars: 42
Forks: 18
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 18
Forks: 3
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m
Stale 6m

About rag-evaluator

AIAnytime/rag-evaluator

A library for evaluating Retrieval-Augmented Generation (RAG) systems (The traditional ways).

This tool helps you check the quality of answers generated by AI systems, especially those that combine information retrieval with text generation (RAG systems). You provide an AI's answer, the original question, and a perfect reference answer, and it tells you how good the AI's answer is. This is ideal for AI developers, researchers, and anyone building or testing conversational AI applications.

AI-development NLP-evaluation conversational-AI-testing content-generation-quality

About nuclia-eval

nuclia/nuclia-eval

Library for evaluating RAG using Nuclia's models

This tool helps evaluate the performance of your RAG (Retrieval Augmented Generation) applications. You provide a question, the answer generated by your RAG system, and the source documents (context) it used. The tool then assesses how relevant the answer is to the question, how relevant each source document is to the question, and whether the answer is truly supported by the source documents. This is for developers and AI engineers building and refining RAG systems.

RAG evaluation LLM development AI quality assurance natural language processing information retrieval

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