🐢 Open-Source Evaluation & Testing library for LLM Agents
-
Updated
Nov 18, 2025 - Python
🐢 Open-Source Evaluation & Testing library for LLM Agents
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.
RAG evaluation without the need for "golden answers"
Framework for testing vulnerabilities of large language models (LLM).
RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).
Open source framework for evaluating AI Agents
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
RAG Chatbot for Financial Analysis
EvalWise is a developer-friendly platform for LLM evaluation and red teaming that helps test AI models for safety, compliance, and performance issues
A modular, multi-model AI assistant UI built on .NET 9, featuring RAG, extensible tools, and deep code + database knowledge through semantic search.
A comprehensive evaluation toolkit for assessing Retrieval-Augmented Generation (RAG) outputs using linguistic, semantic, and fairness metrics
EntRAG - Enterprise RAG Benchmark
AIE7: Certification Challenge
Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq
Python SDK
Add a description, image, and links to the rag-evaluation topic page so that developers can more easily learn about it.
To associate your repository with the rag-evaluation topic, visit your repo's landing page and select "manage topics."