#Spring AI Alibaba Graph
37 related articles
·6 min
Java Developer's Guide to AI Application Development: Building an Airline Intelligent Customer Service System
A practical guide for Java developers to build AI apps without switching to Python. Learn LangChain4j, RAG, Function Calling, and MCP through an airline customer service project.
Read more →
·4 min
Spring AI Alibaba Agent in Practice: Building Enterprise-Grade AI Agents Natively in Java
Deep dive into Spring AI Alibaba Agent framework covering core architecture, tool calling, RAG integration, multi-agent collaboration, and production deployment for Java developers.
Read more →
·2 min
ROS2 Beginner's Guide: Version Selection, Environment Setup & Career Prospects
Complete ROS2 beginner's guide covering core concepts, version selection, Ubuntu VM environment setup, and robotics developer career prospects and salaries.
Read more →
·3 min
Java Developer's Guide to AI Application Development: From Spring AI to Intelligent Customer Service
A comprehensive guide for Java developers transitioning to AI application development, covering Spring AI, RAG, Function Calling, and a hands-on airline intelligent customer service project.
Read more →
·3 min
Getting Started with AI Agents: A Complete Learning Path from Zero to Production
A comprehensive guide to AI Agent architecture covering ReAct paradigm, multi-agent collaboration, RAG integration, and the planning-memory-tools framework, with a complete learning path from concepts to production deployment.
Read more →
·4 min
LangChain4j in Practice: A Complete Tutorial for Building a RAG Medical Q&A System
A complete tutorial on building a RAG medical Q&A system with LangChain4j, covering Ollama local deployment, Redis vector DB, document vectorization, and Cursor AI-assisted development.
Read more →
Tutorials·1 min
Spring AI Alibaba Agent Framework: Three-Layer Architecture and Learning Path
Deep dive into Spring AI Alibaba Agent Framework's three-layer architecture: Spring AI foundation, Graph framework, and Agent Framework, with a recommended learning path for Java developers.
Read more →
Tutorials·3 min
Complete Learning Roadmap for Java Developers Transitioning to AI Engineering
A detailed five-phase learning roadmap for Java developers transitioning to AI engineering, covering Spring AI, LangChain4j, RAG core technology, and Agent development.
Read more →
Tutorials·3 min
Getting Started with Spring AI Alibaba: The Go-To Framework for Java Developers Integrating LLMs
A deep dive into Spring AI Alibaba's core positioning and advantages, helping Java developers quickly understand how to integrate LLMs through this framework.
Read more →
Tutorials·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
Read more →
Tutorials·3 min
LangGraph Multi-Agent Architecture: Core Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph multi-agent architecture covering Graph structure principles, MCP service integration, Time Travel debugging, and supervised multi-agent enterprise implementation patterns.
Read more →
Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
Read more →
Tutorials·2 min
Frontend to AI Full-Stack: Complete Skill Tree & Learning Roadmap
A complete skill tree for frontend developers transitioning to AI full-stack engineers, covering TypeScript, NestJS, LangChain JS, RAG, vector databases, and Tauri 2 with a clear learning roadmap.
Read more →
Tutorials·4 min
Building a Generative Recommendation System with Go and AI Agents: Architecture Design and Practical Analysis
Deep dive into a Go-based generative recommendation system powered by LLMs, covering three-level semantic understanding, three-layer user memory, and five-dimensional feedback design.
Read more →
Deep Dives·4 min
The Four Stages of AI Agent Evolution: A Complete Guide from Copilot to Multi-Agent Collaboration
Deep dive into the four stages of AI Agent evolution: Chat, Copilot, Agent, and Agentic AI. Covers ReAct framework, Spring AI stack, and multi-Agent architecture design for 2025.
Read more →
Deep Dives·4 min
From Copilot to Agentic AI: A Complete Guide to Multi-Agent Collaboration Architectures
Deep dive into AI's four-stage evolution from Chat to Agentic AI, covering multi-Agent architectures, ReAct framework, and MCP protocol for developers.
Read more →
Product Reviews·4 min
RuoYi-AI Open Source Framework: A One-Stop Solution for Java Enterprise AI Application Development
A deep dive into RuoYi-AI, a Java-based enterprise AI development platform supporting multi-vendor LLM integration, RAG knowledge bases, and agent orchestration. 5,200+ Stars on GitHub.
Read more →