{"repo":"wzdavid/ThinkRAG","free":true,"listed":false,"github":"https://github.com/wzdavid/ThinkRAG","clone":"git clone https://github.com/wzdavid/ThinkRAG.git","description":"A LLM RAG system runs on your laptop. 大模型检索增强生成系统，可以轻松部署在笔记本电脑上，实现本地知识库智能问答。","language":"Python","stars":348,"topics":["baai","deepseek","llamaindex","moonshot","ollama","rag","streamlit","zhipuai","langchain","laptop"],"license":"MIT","category":"ai-agents","readme_excerpt":"English 简体中文 Table of Contents - 🤔 Overview - ✨ Features - 🧸 Model Support - 🛫 Quick Start - 📖 User Guide - 🔬 Architecture - 📜 Roadmap - 📄 License ThinkRAG ThinkRAG is a LLM RAG system that can be easily deployed on a laptop to implement Q&A with local knowledge base. This system is built on LlamaIndex and Streamlit, and has been optimized for Chinese users in various fields such as model selection and text processing. Key Features ThinkRAG is a LLM application developed for professionals, researchers, students, and other knowledge workers, which can be used directly on a laptop with all knowledge and data stored locally on the computer. ThinkRAG has the following features: - Complete application of the LlamaIndex framework - Development mode supports local file storage without the need to install any databases - No GPU support is required to run on a laptop - Supports locally deployed models and offline use Specifically, ThinkRAG has also made a lot of customizations and optimizations for Chinese users: - Uses Spacy text splitter for better handling of Chinese characters - Employs Chinese title enhancement features - Uses Chinese prompt templates for Q&A and refinement processes - Default support for China LLM service provider such as DeepSeek, Moonshot and ZhiPu - Uses bilingual embedding models, such as bge-large-zh-v1.5 from BAAI Model Support ThinkRAG can use all models supported by the LlamaIndex data framework. For model list information, please refer to relevan","default_branch":null,"files":null,"tree":[],"storefront":"/r/wzdavid","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/wzdavid/ThinkRAG/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}