GitHub - arthur-ai/bench: A tool for evaluating LLMs

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Large variety of ready-to-use LLM evaluation metrics (all with explanations) powered by

ANY

LLM of your choice, statistical methods, or NLP models that runs

locally on your machine

:

G-Eval

Summarization

Answer Relevancy

Faithfulness

Contextual Recall

Contextual Precision

RAGAS

Hallucination

Toxicity

Bias

etc.

GitHub - confident-ai/deepeval: The LLM Evaluation Framework

DeepEval — It’s a tool for easy and efficient LLM testing. Deepeval aims to make writing tests for LLM applications (such as RAG) as easy as writing Python unit tests.

Testing framework for LLM Part

Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.

In just a few lines of codes, you can