🐢 Open-Source Evaluation & Testing for AI & LLM systems

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM Observability all in one place.

Framework for testing vulnerabilities of large language models (LLM).

This project aims to compare different Retrieval-Augmented Generation (RAG) frameworks in terms of speed and performance.

A framework for systematic evaluation of retrieval strategies and prompt engineering in RAG systems, featuring an interactive chat interface for document analysis.

Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python

Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq

Different approaches to evaluate RAG !!!

Proposal for industry RAG evaluation: Generative Universal Evaluation of LLMs and Information retrieval

PandaChat-RAG benchmark for evaluation of RAG systems on a non-synthetic Slovenian test dataset.