Cao Ai Agent
What is Cao Ai Agent
Cao-ai-agent is an AI super-intelligent agent built on Spring Boot 3 and Java 21, designed to create AI applications such as a love master and a ReAct mode autonomous planning agent called YuManus. It encompasses core knowledge in AI large model integration, Spring AI features, prompt engineering, RAG retrieval enhancement, vector databases, tool calling, MCP model context protocols, AI agent development, and Cursor AI tools.
Use cases
Use cases for cao-ai-agent include developing personalized AI assistants, creating intelligent customer service bots, implementing AI-driven recommendation systems, and building autonomous agents for task planning and execution.
How to use
To use cao-ai-agent, developers can follow a comprehensive tutorial that covers essential AI technologies, including the use of AI application platforms, integration of large AI models, local deployment of AI models, prompt engineering techniques, and the development of AI services using Spring AI and LangChain4j.
Key features
Key features of cao-ai-agent include: integration with AI large models, Spring AI core features like custom interceptors and context persistence, RAG knowledge bases, vector databases, tool calling capabilities, MCP model context protocols, and the ability to develop autonomous AI agents.
Where to use
Cao-ai-agent can be utilized in various fields such as software development, AI application development, educational platforms for learning AI technologies, and any domain requiring intelligent automation and AI-driven solutions.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Cao Ai Agent
Cao-ai-agent is an AI super-intelligent agent built on Spring Boot 3 and Java 21, designed to create AI applications such as a love master and a ReAct mode autonomous planning agent called YuManus. It encompasses core knowledge in AI large model integration, Spring AI features, prompt engineering, RAG retrieval enhancement, vector databases, tool calling, MCP model context protocols, AI agent development, and Cursor AI tools.
Use cases
Use cases for cao-ai-agent include developing personalized AI assistants, creating intelligent customer service bots, implementing AI-driven recommendation systems, and building autonomous agents for task planning and execution.
How to use
To use cao-ai-agent, developers can follow a comprehensive tutorial that covers essential AI technologies, including the use of AI application platforms, integration of large AI models, local deployment of AI models, prompt engineering techniques, and the development of AI services using Spring AI and LangChain4j.
Key features
Key features of cao-ai-agent include: integration with AI large models, Spring AI core features like custom interceptors and context persistence, RAG knowledge bases, vector databases, tool calling capabilities, MCP model context protocols, and the ability to develop autonomous AI agents.
Where to use
Cao-ai-agent can be utilized in various fields such as software development, AI application development, educational platforms for learning AI technologies, and any domain requiring intelligent automation and AI-driven solutions.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
项目介绍
本项目选题新颖、业务真实，用一套实战教程将程序员必知必会的 AI 技术一网打尽。
你将掌握下面的知识：
- AI 应用平台的使用
- 接入 AI 大模型
- AI 开发框架（Spring AI + LangChain4j）
- AI 大模型本地部署
- Prompt 工程和优化技巧
- 多模态特性
- Spring AI 核心特性：如自定义拦截器、上下文持久化、结构化输出
- RAG 知识库和向量数据库
- Tool Calling 工具调用
- MCP 模型上下文协议和服务开发
- AI 智能体 Manus 原理和自主开发
- AI 服务化和 Serverless 部署
技术栈
- Java 21 + Spring Boot 3 框架
- ⭐️ Spring AI + LangChain4j
- ⭐️ RAG 知识库
- ⭐️ PGvector 向量数据库
- ⭐ Tool Calling ️工具调用
- ⭐️ MCP 模型上下文协议
- ⭐️ ReAct Agent 智能体构建
- ⭐️ Serverless 计算服务
- ⭐️ AI 大模型开发平台百炼
- ⭐️ Cursor AI 代码生成 + MCP
- 第三方接口：如 SearchAPI / Pexels API
- Ollama 大模型部署
- Kryo 高性能序列化
- Jsoup 网页抓取
- iText PDF 生成
- Knife4j 接口文档
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
