#LangChain4j tutorial
224 related articles
Deep Dives·3 min
MCP (Model Context Protocol): Solving the Three Core Pain Points of AI Tool Calling
Deep dive into how MCP (Model Context Protocol) solves three core pain points of Tool Calling: verbose descriptions, unstable invocations, and lack of unified standards.
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Tutorials·3 min
Ollama + Gemma 4 Local Codex Setup: Complete Guide to Zero-Cost AI Programming
Learn how to run Codex locally with Ollama and Gemma 4 for zero-cost AI programming. Covers installation, model selection, and real demos as an alternative to $20-200/month paid plans.
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Tutorials·3 min
In-Depth Review of a 628-Episode Python Full-Stack Tutorial: Can a Free Course Launch Your Career?
In-depth review of a 628-episode free Python full-stack tutorial on Bilibili, analyzing its strengths, limitations, and providing learning strategy advice for Python beginners.
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Tutorials·3 min
In-Depth Review of a 628-Episode Python Full-Stack Tutorial: Can a Free Course Launch Your Career?
In-depth review of a 628-episode free Python full-stack tutorial on Bilibili, analyzing its strengths, limitations, and providing learning strategy advice for Python beginners.
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Tutorials·3 min
Dify Local Deployment Tutorial: Setting Up an AI Development Platform from Scratch with BT Panel + Docker
Step-by-step tutorial on deploying Dify locally using VMware, Ubuntu, BT Panel, and Docker. Covers environment setup, common error fixes, and next steps for building AI apps.
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Tutorials·2 min
LangChain 1.0 Complete Guide: Architecture, Core Modules, and Learning Path
Deep dive into LangChain 1.0's three-layer architecture (LangChain, LangGraph, Deep Agents), core components like Models, Tools, and Memory, plus a complete learning path from semantic search to multi-agent collaboration.
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Tutorials·3 min
LangGraph + MCP in Practice: A Deep Dive into Agent Architecture and the MCP Protocol
Deep dive into the MCP protocol's core principles and practical applications, covering agent capabilities, MCP architecture, ERP integration, and building agents with LangGraph.
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Tutorials·3 min
LangGraph + MCP in Practice: A Deep Dive into Agent Architecture and the MCP Protocol
Deep dive into MCP (Model Context Protocol) core principles and practical applications, covering agent capabilities, MCP architecture, ERP integration, and building agents with LangGraph.
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Tutorials·3 min
Zero2Agent: An Open-Source Job Interview Prep Tutorial for Agent Engineer Positions at Top Tech Companies
Zero2Agent is an open-source interview prep tutorial covering Agent fundamentals, LangGraph/Claude Code analysis, interview question banks, and coding practice tools for landing Agent engineer roles at top tech companies.
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Tutorials·3 min
OpenCode Getting Started Guide: Choosing Your Installation Method & Core Features Explained
A detailed guide to OpenCode's three installation methods (Desktop, CMD, WSL) and core features including Agent architecture, custom commands, MCP integration, and Agent Skills.
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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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Tutorials·3 min
Learn AI Agents in 30 Days: A Four-Stage Learning Roadmap from Zero to Production
A systematic breakdown of the AI Agent learning roadmap covering core architecture, ReAct/CoT paradigms, multi-agent collaboration, and Prompt optimization across four stages with quality resource recommendations.
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Tutorials·1 min
AI Agent Learning Roadmap: A Complete Guide from LLM Fundamentals to Enterprise-Level Project Implementation
A systematic AI Agent learning roadmap covering Python setup, Prompt Engineering, RAG, LangChain, multi-Agent collaboration, with enterprise medical consultation system case study and phased learning plan.
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Tutorials·1 min
AI Large Language Model Learning Roadmap: Six Stages from Zero to Engineer
A systematic LLM engineer learning roadmap covering Transformer basics, prompt engineering, RAG, Agent development, API integration, fine-tuning, deployment, and project practice across six stages.
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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.
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Tutorials·3 min
Andrew Ng's Agent AI Course Fully Explained: Why It's Taking the Tech World by Storm
Deep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Deep Dives·4 min
AI Agents 101: Core Concepts, Technical Architecture, and How They Work
A beginner's guide to AI Agents: understand core concepts, the perception-decision-action loop, LLM, tool calling, memory systems, and RAG architecture explained from scratch.
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Tutorials·4 min
New API in Practice: Complete Tutorial for Building Your Own AI API Relay Station
Complete tutorial on building an AI API relay station using the New API open-source project, covering Docker deployment, server configuration, channel management, token distribution, and client verification.
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Tutorials·3 min
Andrew Ng's New Course: A Complete Guide to Building Database Agents
Deep dive into Andrew Ng's Building Your Own Database Agent course with Microsoft, covering LLM-SQL interaction, LangChain Agents, Function Calling, and RAG for tabular data.
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