#LLM integration
15 related articles
Java Developer's Guide to AI Applicati…
·3 min
Java Developer's Guide to AI Application Development: Career Path, Skills, and Hands-On Strategy
A practical guide for Java developers transitioning to AI app development. Includes a 45-day learning plan covering Spring AI, RAG, Agent skills, plus resume and interview strategies.
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LangChain from Beginner to Agent Devel…
·3 min
LangChain from Beginner to Agent Development: A Complete Learning Path for LLM Application Development
A systematic guide to LangChain LLM application development, covering environment setup, core components (RAG, Chain, Memory), and Agent development to help developers master LLM app building.
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·2 min
OpenAI Sites Explained: Codex One-Click Generation of Shareable Interactive Apps
OpenAI launches Sites, letting Codex transform ideas into shareable interactive apps via URL. Analysis of core value, enterprise strategy, and competitive differentiation.
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Tutorials·4 min
AI Agents for Auto-Generating Excel Test Cases: From Setup to Private Deployment — A Complete Guide
Learn how to use AI agents to auto-generate Excel test cases. Covers Coze platform setup, Dify private deployment with DeepSeek + Ollama, workflow design tips, and prompt engineering for testers.
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Product Reviews·2 min
Tencent CodeBuddy IDE Hands-On Review: Full-Stack AI Platform Development Experience
Hands-on review of Tencent's CodeBuddy standalone IDE: building the Xiaohe Architecture AI Platform with Chat/Craft/Plan modes, CloudBase integration, and free Claude 4 and GPT-5 access.
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Tutorials·2 min
Vue3 + Node.js Full-Stack Tutorial: Building an AI Travel Assistant
Learn how to build an AI travel assistant using Vue3, Node.js, and Alibaba's Qwen LLM, covering multi-turn dialogue, function calling, product recommendations, and full deployment.
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Tutorials·2 min
Getting Started with Spring AI Alibaba: Best Practices for Java Developers to Integrate LLMs
Deep dive into Spring AI Alibaba's positioning and value, using a JDBC analogy to help Java developers understand how to integrate LLM capabilities into existing microservices architecture.
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Tutorials·3 min
Java Developers Transitioning to AI Engineers: New Interview Trends and Learning Roadmap
Deep analysis of interview trends for Java developers transitioning to AI engineers, covering LLM integration, RAG, Spring AI framework practice, with a complete learning roadmap.
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Industry Insights
Should Custom Software Teams Go All-In…
·3 min
Should Custom Software Teams Go All-In on LLMs? ChatGPT Itself Gave the Answer
Should custom software teams go all-in on LLMs? Through a deep conversation with ChatGPT, we analyze scenario selection, Token costs, and industry fit to provide a rational decision framework for ToB developers.
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Tutorials
CrewAI Multi-Agent Collaboration in Pr…
·2 min
CrewAI Multi-Agent Collaboration in Practice: Core Concepts, Model Comparison & API Deployment
A deep dive into CrewAI's four core concepts for multi-agent collaboration, with hands-on FastAPI deployment and a comparison of GPT-4o-mini, Qwen MAX, and Llama 3.1.
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Tutorials
Practical Guide to Building Multi-Agen…
·3 min
Practical Guide to Building Multi-Agent Collaborative Applications with CrewAI + FastAPI
Learn how to build a multi-Agent collaborative system with CrewAI and FastAPI. Covers Agent, Task, Crew concepts, GPT/Tongyi Qianwen/Ollama integration, with complete code examples and model comparisons.
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Tutorials
The Complete Guide to Spring AI: A Ful…
·3 min
The Complete Guide to Spring AI: A Full Learning Path for Java Engineers Building AI Applications
A comprehensive guide to Spring AI covering LLM integration, prompt engineering, RAG knowledge bases, and five AI Agent patterns, with three enterprise projects for Java engineers.
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Tutorials
Getting Started with LangChain: Core C…
·3 min
Getting Started with LangChain: Core Concepts and Hands-On Guide for LLM and Agent Development
A systematic guide to LangChain's core features, covering LLM vs. Agent concepts, unified interface design, multi-provider support, environment setup, and hands-on code examples for AI app development.
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Tutorials
Build AI Apps Without Code: A Practica…
·3 min
Build AI Apps Without Code: A Practical Guide to Rapid Development with No-Code Platforms
Learn how to build AI apps with no-code platforms: visual UI building, LLM integration, data management, and payment monetization—no programming required.
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Product Reviews·2 min
LangBot: A Deep Dive into the 16K-Star Multi-Platform AI Bot Development Framework
An in-depth look at LangBot, an open-source production-grade AI bot platform supporting WeChat, DingTalk, Discord & more, with ChatGPT, DeepSeek, Agent, RAG & plugin capabilities.
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