🐢 Open-Source Evaluation & Testing library for LLM Agents
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Updated
Mar 19, 2026 - 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"
Red Teaming python-framework for testing chatbots and GenAI systems.
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).
⚡️ The "1-Minute RAG Audit" — Generate QA datasets & evaluate RAG systems in Colab, Jupyter, or CLI. Privacy-first, async, visual reports.
Open source framework for evaluating AI Agents
A visual tool to convert PDFs to Markdown and create, inspect, and refine document chunks for RAG pipelines.
smallevals — CPU-fast, GPU-blazing fast offline retrieval evaluation for RAG systems with tiny QA models.
Evaluation Framework for LLM applications in Java and Kotlin
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
EntRAG - Enterprise RAG Benchmark
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
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