rag-evaluation

🐢 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.

Open source RAG evaluation package

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.

RAG Chatbot for Financial Analysis

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

BetterRAG: Powerful RAG evaluation toolkit for LLMs. Measure, analyze, and optimize how your AI processes text chunks with precision metrics. Perfect for RAG systems, document processing, and embedding quality assessment.

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

A web sandbox for hands-on learning of LLM and RAG Evaluation

RAG Chatbot over pre-defined set of articles about LangChain

Home assignment featuring two AI projects: a Medical Q&A Bot for Israeli HMOs and a National Insurance Form Extractor. Built with Azure OpenAI to demonstrate practical GenAI implementation skills.

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.