evaluation-framework

The LLM Evaluation Framework

A framework for few-shot evaluation of language models.

Test your prompts, agents, and RAGs. AI Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Data-Driven Evaluation for LLM-Powered Applications

AgentLab: An open-source framework for developing, testing, and benchmarking web agents on diverse tasks, designed for scalability and reproducibility.

Metrics to evaluate the quality of responses of your Retrieval Augmented Generation (RAG) applications.

Python SDK for running evaluations on LLM generated responses

Moonshot - A simple and modular tool to evaluate and red-team any LLM application.

The official evaluation suite and dynamic data release for MixEval.

A research library for automating experiments on Deep Graph Networks

AI Data Management & Evaluation Platform

DevQualityEval: An evaluation benchmark 📈 and framework to compare and evolve the quality of code generation of LLMs.

PySODEvalToolkit: A Python-based Evaluation Toolbox for Salient Object Detection and Camouflaged Object Detection

Expressive is a cross-platform expression parsing and evaluation framework. The cross-platform nature is achieved through compiling for .NET Standard so it will run on practically any platform.

A framework for standardizing evaluations of large foundation models, beyond single-score reporting and rankings.

Test and evaluate LLMs and model configurations, across all the scenarios that matter for your application

Multilingual Large Language Models Evaluation Benchmark

MedEvalKit: A Unified Medical Evaluation Framework