yu-ai-agent

liyupi
562
# Programming Navigation 2025 AI Development Practical New Project This project is based on Spring Boot 3 + Java 21 + Spring AI to build the AI Love Master application and the ReAct mode autonomous planning intelligent agent YuManus. It covers core knowledge such as AI large model integration, Spring AI core features, Prompt engineering and optimization, RAG (Retrieval-Augmented Generation), vector databases, Tool Calling, MCP (Model Context Protocol), AI Agent development (Manas Java implementation), Cursor AI tools, and more. With a comprehensive set of tutorials, this project aims to equip programmers with essential AI technologies, helping you become a sought-after talent in the AI era and significantly enhancing your resume and job competitiveness.
#ai #ai-model #backend #frontend #java #langchain4j #mcp #rag #spring-ai #springboot #springmvc #vector-database

Overview

yu-ai-agent Introduction

yu-ai-agent is an AI development project focused on practical applications, built using Spring Boot 3, Java 21, and Spring AI. It aims to create an AI relationship assistant application and a self-planning intelligent agent, YuManus, covering essential AI technologies and concepts.

How to Use

To use yu-ai-agent, participants can follow a comprehensive tutorial that includes video and text instructions, resume writing tips, interview question explanations, and Q&A services to enhance their project capabilities and improve their resumes.

Key Features

Key features include AI model integration, core functionalities of Spring AI, prompt engineering and optimization, RAG retrieval enhancement, vector databases, tool calling, MCP model context protocol, and the development of AI agents using Java.

Where to Use

yu-ai-agent can be applied in various fields such as AI application development, emotional support systems, intelligent agents, and any domain requiring advanced AI functionalities and tools.

Use Cases

Use cases for yu-ai-agent include developing an AI relationship assistant that can handle multi-turn dialogues, answer questions based on custom knowledge bases, and autonomously call tools and MCP services to complete tasks like planning dates.

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