#LangGraph Java
116 related articles
Tutorials·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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Product Reviews·3 min
Warp 2.0 Deep Dive: An AI Development Environment with Multi-Agent Parallelism
Deep dive into Warp 2.0's Agent Development Environment (ADE): multi-agent parallel orchestration, terminal editor, AI coding platform, hands-on SaaS app building, and comparison with Cursor and Claude Code.
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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.
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Tutorials·3 min
Frontend Engineers Leveling Up to AI Agents: LangGraph.js Architecture Design & Practical Guide
How can frontend engineers advance into AI Agent development? This guide covers LangGraph.js core architecture (state, nodes, edges), LangChain comparison, and workflow agent design with practical examples.
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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.
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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.
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Tutorials·2 min
Career Prospects for LLM Development Engineers: Job Categories, Education Requirements, and Learning Paths
In-depth analysis of three LLM engineer career paths (Application, R&D, Algorithm), bachelor's degree entry, core algorithms, salary benchmarks, and a three-tier learning roadmap.
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Tutorials·1 min
Claude Code Workflow Practical Guide: Multi-Agent Workflow Orchestration Driven by JS Scripts
A detailed guide to Claude Code's new Workflow feature: use JavaScript scripts for precise multi-Agent orchestration. Covers setup, workflow patterns, SubAgents comparison, and reusable scripts.
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Tutorials·2 min
LangChain Unified Interface in Practice: Complete Guide from Model Invocation to Agent Development
A detailed guide to LangChain's unified interface, comparing model invocation methods, explaining LLM vs Agent differences, with complete Python walkthrough from setup to agent development.
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Tutorials·2 min
LangChain Multi-Agent in Practice: End-to-End Automated Generation of API & UI Test Cases
Build a multi-agent testing system with LangChain and LangGraph for automated test case generation, intelligent review, and Playwright execution across 10 progressive projects.
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Tutorials·2 min
NestJS + LangChain + Tauri 2: A Practical AI Full-Stack Development Solution
An enterprise AI full-stack solution using NestJS, LangChain, LangGraph, and Tauri 2, covering AI service platforms, multi-agent orchestration, RAG, and cross-platform delivery for frontend developers.
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Tutorials·2 min
LangChain Unified Interface in Practice: init_chat_model Usage & DeepSeek Troubleshooting Guide
Guide to LangChain's init_chat_model unified interface vs model classes, with DeepSeek V4 Pro thinking mode fix, multi-provider switching tips, and AI Agent integration practices.
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Tutorials·2 min
LangChain Beginner's Guide: A Complete Guide to LLM and Agent Development
A deep dive into LangChain framework essentials, clarifying the key differences between LLMs and Agents, covering Agent development, DeepAgent advanced topics, and learning paths.
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Tutorials·2 min
LangGraph Multi-Agent Architecture in Practice: A Complete Guide from Single Agent to Enterprise-Level Applications
In-depth guide to LangGraph multi-agent architecture: covering Graph structures, MCP protocol integration, single Agent building to enterprise-level multi-agent collaboration for AI developers.
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Tutorials·3 min
LangGraph Multi-Agent in Practice: Building a Medical Agent System from Scratch
A deep dive into LangGraph multi-agent architecture for healthcare, covering LangChain, RAG, and MCP integration, from requirements analysis to Agent orchestration.
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Deep Dives·3 min
ReAct Pattern and Transformer Architecture Explained: High-Frequency AI Interview Topics for Frontend Developers
Deep dive into Agent core logic ReAct (Reasoning + Acting) execution flow, Transformer self-attention mechanism, and essential AI skills for frontend developers including prompt engineering, RAG, and Agent development.
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Deep Dives·4 min
AI Code Review from 30 to 80 Points: A Complete Guide to AST + RAG Architecture Challenges
Deep dive into AI code review system architecture with AST parsing, RAG retrieval, and vector databases. Learn how to boost review effectiveness from 30% to 80%.
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Tutorials·3 min
Implementing LangGraph in TypeScript: Deconstructing the Core Principles of AI Agent Frameworks from Scratch
Learn how to implement LangGraph's core design from scratch in TypeScript, covering state-graph-driven architecture, node-based orchestration, and the ReAct pattern for AI Agent development.
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Product Reviews·3 min
PaiAgent: A Lightweight AI Workflow Orchestration System Built with Vibe Coding
Deep dive into PaiAgent, a lightweight AI workflow orchestration system built with Spring AI and LangGraph4J. Explore its DAG engine design, differentiation from Dify/n8n, and Vibe Coding development insights.
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Product Reviews·2 min
Claude Haiku 4.5 In-Depth Review: One-Third the Cost, Coding Performance Rivaling Sonnet 4
Anthropic releases Claude Haiku 4.5: coding rivaling Sonnet 4 at 1/3 the cost and 2x speed. A dev built browser-based macOS for just 28 cents, redefining small AI model capabilities.
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