pchunduri6/rag-demystified
An LLM-powered advanced RAG pipeline built from scratch
KoalaQA 是一款 AI 大模型驱动的开源售后服务社区,提供 AI 回答、AI 搜索、AI 运营等能力,帮助你快速落地售后客服、社区问答、自助服务等场景,帮助团队显著降低人工运营成本、提升客户满意度与响应效率,助力实现 ZCR(Zero Contact Resolution)目标。
$ git clone https://github.com/chaitin/KoalaQA.gitAn LLM-powered advanced RAG pipeline built from scratch
🔥 Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation 🔥. Our toolkit integrates 40 pre-retrieved benchmark datasets and supports 7+ retrieval techniques, 24+ state-of-the-art Reranking models, and multiple RAG methods.
Use ArXiv ChatGuru to talk to research papers. This app uses LangChain, OpenAI, Streamlit, and Redis as a vector database/semantic cache.
A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
Data from GitHub · snapshot Sep 24, 2026