yu-ai-agent

# AI Superintelligent Agent Project > Author: [Programmer Yupi](https://yuyuanweb.feishu.cn/wiki/Abldw5WkjidySxkKxU2cQdAtnah) > > This project is an educational initiative that provides complete video tutorials + written tutorials + resume writing guidance + interview question solutions + Q&A services, helping you enhance your project skills and add highlights to your resume! > > ⭐️ Join the project series learning: [Join Programming Navigation](https://www.codefather.cn/vip) ## Project Introduction > Video Introduction: https://www.bilibili.com/video/BV1UoLezKEbm This is a project tutorial centered around **AI Development Practice**, which will guide you through the development of the **AI Love Master Application + Super Intelligent Agent with Autonomous Planning Capability**. You will master essential AI core concepts, practical AI tools, AI programming techniques, AI framework principles, and AI tuning skills that every programmer in the new era must know, significantly increasing your competitiveness in the job market!  The `AI Love Master Application` can rely on AI large models to solve users' emotional problems, supporting multi-turn conversations, Q&A based on a custom knowledge base, and autonomously calling tools and MCP services to complete tasks, such as calling map services to obtain nearby locations and formulate dating plans.  In addition, we will guide you step-by-step to complete the `Autonomous Planning Intelligent Agent YuManus` based on the ReAct model, which can utilize web searches, resource downloads, and PDF generation tools to help users create complete dating plans and generate documents:  Of course, after learning this project, you will not only be able to develop the AI Love Master but also flexibly develop various complex AI applications, so let your imagination run wild! ## Why Should You Undertake This Project? This project features a novel topic and real business applications, distinguishing itself from the "overly common" CRUD projects. Yupi will guide you through practical applications of numerous new technologies and enterprise scenarios, providing a comprehensive tutorial that covers essential **AI technologies** that every programmer should know, helping you become a sought-after talent in the AI era and significantly enhancing your resume and job competitiveness. Yupi will teach you **universal project development methods and architectural design patterns**. From this project, you will learn: - Usage of mainstream AI application platforms - Four integration methods for AI large models - AI development frameworks (Spring AI + LangChain4j) - Local deployment of AI large models - Prompt engineering and optimization techniques - Core features of Spring AI: such as custom Advisors, conversation memory, structured output - Practical experience with RAG (Retrieval-Augmented Generation) knowledge bases, principles, and tuning techniques - PgVector vector database + cloud database services - Practical experience and principles of Tool Calling - MCP (Model Context Protocol) model context protocol and service development - Principles and independent development of AI intelligent agents like Manus - AI service-oriented architecture and Serverless deployment - Various new concepts: such as multimodal, agent workflows, A2A (Agent-to-Agent) protocols, large model evaluation, etc. For example, practical experience with the core features of RAG and end-to-end tuning:  The project also has other advantages: - Practical experience on both AI cloud platforms and programming; not only will you use AI services, but you will also write your own! - Detailed explanations of the latest AI technologies based on official documentation, with in-depth analysis of documents and source code! - Sharing a wealth of AI extension knowledge and programming skills, mastering best practices! Yupi will guide you through the source code of the open-source framework OpenManus:  Additionally, you will learn various methods for diagramming, problem-solving, and comparing solutions, enhancing your ability to troubleshoot issues and independently resolve bugs. ### Advantages of the Fish Skin Series Projects The original projects of Fish Skin focus on **practical experience**, using **live streaming** to guide you **from 0 to 1**. From requirement analysis, technology selection, project design, project initialization, Demo writing, front-end and back-end development implementation, project optimization, to deployment and launch, I explain everything clearly **from theory to practice**, leaving no detail overlooked! Compared to learning from online tutorials, the advantages of the Fish Skin project series include a comprehensive service: from acquiring knowledge => practical projects => review notes => project Q&A => resume writing => interview question solutions:  The programming navigation already has **over 10 project tutorials!** Each project's learning focus is different, and almost all are **full-stack projects** combining front-end and back-end. You can check out the real feedback from everyone; many participants have improved their skills and received job offers by working on projects with me!  Previous project introduction videos: [https://bilibili.com/video/BV1YvmbYbEgS](https://www.bilibili.com/video/BV1YvmbYbEgS/) ## Project Functionality Overview In this project, we will develop an AI Love Master application, a super intelligent agent with autonomous planning capabilities, and a series of tools and MCP services. The specific requirements are as follows: - AI Love Master Application: Users inevitably encounter various challenges during their romantic relationships, and the AI will provide thoughtful emotional guidance. It supports multi-turn conversations, persistent conversation memory, RAG (Retrieval-Augmented Generation) knowledge base retrieval, tool invocation, and MCP service calls. - AI Super Intelligent Agent: It can autonomously reason and act based on user needs until the goal is achieved. - Tools provided to the AI: These include online search, file operations, web scraping, resource downloading, terminal operations, and PDF generation. - AI MCP Service: It can search for images from specific websites.  ## What Technologies Are Used? The project is centered around the practical application of the Spring AI development framework, involving various mainstream AI clients and tool libraries. - Java 21 + Spring Boot 3 framework - ⭐️ Spring AI + LangChain4j - ⭐️ RAG (Retrieval-Augmented Generation) knowledge base - ⭐️ PGvector vector database - ⭐ Tool Calling - ⭐️ MCP (Model Context Protocol) - ⭐️ ReAct Agent construction - ⭐️ Serverless computing services - ⭐️ AI large model development platform BaiLian - ⭐️ Cursor AI code generation - ⭐️ SSE (Server-Sent Events) asynchronous push - Third-party APIs: such as SearchAPI / Pexels API - Ollama large model deployment - Tool libraries such as: Kryo high-performance serialization + Jsoup web scraping + iText PDF generation + Knife4j API documentation Core Features of RAG in Practice:  Project Architecture Design Diagram:  ## Phase One Free Viewing The first phase is a public explanation, introducing the project background, project features, technology selection, architectural design, tutorial plan, and more. Video link: https://www.bilibili.com/video/BV1Eq5DzcE9o ## Join Project Learning Programming Navigation already has **more than 10 project tutorials!** Each project's learning focus is different, and almost all are **full-stack** projects combining both front-end and back-end.  Welcome to join [Programming Navigation](https://mp.weixin.qq.com/s/I1oD6pAaWBvGLyFDT9AgvA?token=1925632390&lang=zh_CN). After joining, you can not only follow this project throughout the learning process, but also have unlimited access to past [10+ original project tutorials](https://mp.weixin.qq.com/s/omIazLMQlTo9M3jFFH7NzQ?token=70787607&lang=zh_CN). You will also enjoy more original technical materials, learning and job-seeking guidance, and hundreds of interview replay videos to kickstart your programming journey~ 🧧 To support new project learning, we are distributing **limited-time Programming Navigation coupons**. Scan the code to receive your coupon and join. If you are not satisfied within three days of joining, you can get a full refund. We welcome you to join and experience it; spots are limited, so hurry to learn! <img width="404" alt="image" src="https://github.com/user-attachments/assets/56411098-b60e-4267-8ba2-4ebc5d416afc" /> Less than 1 dollar a day, it is definitely the best investment in yourself! After becoming a member of Programming Navigation, you can unlock tutorials and materials for more than 10 projects, available for learning on both PC websites and apps, as shown:  ## Preparation Work ### AI Basics Please watch the "Programmer Yupi AI Guide" first to understand the basics of AI and the learning path. This will provide a general impression when you practice in the project later, making it easier to learn and understand. ⭐️ Recommended video version: [https://www.bilibili.com/video/BV1i9Z8YhEja](https://www.bilibili.com/video/BV1i9Z8YhEja/) Text version: https://www.codefather.cn/course/1907378983347892226 ### Create a New Code Repository Use GitHub to set up an open-source code repository, and those who star it are spiritual shareholders. Code Repository: https://github.com/liyupi/yu-ai-agent ### AI Learning Resources It is recommended that everyone continuously read interview questions related to AI large models while learning about AI projects to reinforce their knowledge. This area has been well covered for you; our programmer interview preparation tool, 面试鸭 (Mianshiya), has created an [AI Large Model Interview Question Bank](https://www.mianshiya.com/bank/1906189461556076546). It is advisable to read some questions from time to time for learning purposes.  Moreover, due to the rapid advancements in AI technology, it is suggested that everyone pay more attention to AI-related news and updates. For example, the [鱼皮开源的 AI 知识库 (Yupi Open Source AI Knowledge Base)](https://github.com/liyupi/ai-guide) aggregates popular AI large models and tools, such as Deepseek usage guides, prompt engineering tips, knowledge resources, application scenarios, AI monetization, industry news, tutorial resources, and more, helping you quickly master AI technology and stay at the forefront of the times.  ## Learning Outline ### Phase 1: Project Overview - Project Introduction - Project Advantages - Project Functionality Overview - Technology Selection - Architecture Design - AI Learning Path - - Usage of AI Application Platform (Dify) - Common AI Tools - AI Programming Skills - AI Programming Techniques - Learning Outline ### Phase 2: Accessing AI Large Models - Concept of AI Large Models - Accessing AI Large Models (3 Methods) - Backend Project Initialization - Program Calling AI Large Models (4 Methods) - Local Deployment of AI Large Models - Spring AI Calling Local Large Models ### Phase 3: AI Application Development - Concept of Prompt Engineering - Prompt Optimization Techniques - AI Love Master Application Requirement Analysis - AI Love Master Application Solution Design - Features of Spring AI ChatClient / Advisor / ChatMemory - Multi-turn Dialogue AI Application Development - Spring AI Custom Advisor - Spring AI Structured Output - Love Report Function - Spring AI Dialogue Memory Persistence - Spring AI Prompt Template Features - Concept and Development of Multimodal ### Phase 4: RAG Knowledge Base Basics - AI Love Knowledge Q&A Requirement Analysis - Concept of RAG (Focus on Understanding Core Steps) - RAG Practical: Spring AI + Local Knowledge Base - RAG Practical: Spring AI + Cloud Knowledge Base Service ### Phase 5: RAG Knowledge Base Advanced - Core Features of RAG - - Document Collection and Segmentation (ETL) - Vector Transformation and Storage (Vector Database) - Document Filtering and Retrieval (Document Retriever) - Query Enhancement and Association (Context Query Enhancer) - RAG Best Practices and Tuning - Retrieval Strategies - Large Model Hallucinations ### Phase 6: Tool Invocation - Concept of Tools - Spring AI Tool Development - Mainstream Tool Development - - File Operations - Online Search - Web Scraping - Terminal Operations - Resource Download - PDF Generation - Advanced Knowledge of Tools (Principles and Advanced Features) ### Phase 7: MCP - Concept of MCP - Using MCP (3 Methods) - Spring AI MCP Development Model - Spring AI MCP Development Practice - Image Search MCP - MCP Development Best Practices - Deploying MCP - MCP Security Issues ### Phase 8: AI Agent Construction - Concept of AI Agents - Key to Implementing Agents - Using AI Agents (2 Methods) - Introduction to Autonomous Planning Agents - Implementation Principles of OpenManus - Autonomous Implementation of Manus Agents - Agent Workflow ### Phase 9: AI Serviceization - AI Application Interface Development (SSE) - AI Agent Interface Development - AI Generated Frontend Code - AI Service Serverless Deployment