Yu AI Agent (YuManus)
✨A tutorial project for an AI Love Master app and ReAct autonomous agent built on Spring Boot 3 and Java 21, featuring Spring AI, RAG, Tool Calling, and MCP practices.
A tutorial project for an AI Love Master app and ReAct autonomous agent built on Spring Boot 3 and Java 21, featuring Spring AI, RAG, Tool Calling, and MCP practices.
An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.
A curated collection of extracted system prompts from popular chatbots like ChatGPT, Claude, and Gemini, helping researchers understand the behavior boundaries of AI models。
A minimal Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes. Build a production-ready Agentic RAG system with LangGraph, conversation memory, and human-in-the-loop query clarification.
AI-Compass is a comprehensive open-source project that provides learning paths and practical guidelines for AI technologies, helping users from beginners to professionals build a complete AI knowledge system from fundamental theory to cutting-edge applications.
A curated collection of autonomous agents (LLM) research papers updated daily, providing the latest AI research findings for researchers and developers。
A comprehensive educational project using SpringAI framework that demonstrates and practices SSE streaming, Agent intelligent systems, knowledge graph RAG, FunctionCall, historical message processing, image generation and understanding, and Embedding technologies.
A symbiotic AI agent that remembers everything, challenges you, and extends your cognition. Not just a chatbot, but an intelligent partner that works alongside you in your system.
Science-Star is an open platform for building, extending, and experimenting with scientific AI agents. It features a ReAct-based engine with integrated planning, action, memory and reflection modules, visualization tools, and a modular architecture for easy customization.
A comprehensive guide for prompt engineering containing papers, guides, lessons, notebooks, and resources on prompt engineering, context engineering, RAG, and AI Agents.
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