#LangGraph multi-agent
427 related articles
Product Reviews·3 min
Aix-DB Open-Source Framework: A Multi-Agent Approach to Natural Language Database Querying
Deep dive into Aix-DB: an open-source multi-agent framework using LangChain/LangGraph and MCP protocol for natural language to SQL, data analysis, and visualization.
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Tech Frontiers·3 min
Inside the SJSU Hackathon Winning Projects: A Practical Guide to Building High-Impact AI Agents
Deep analysis of SJSU hackathon-winning AI Agent projects covering architecture design, core elements, and UX optimization—a practical guide from prototype to product.
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Tutorials·3 min
Commercial AI Agent Development Guide: 7 Key Steps to Build from Scratch
A complete guide to building commercial AI Agents in 7 steps: requirements analysis, model selection, prompt engineering, Dify/Coze platform comparison, data storage, testing, and deployment.
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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.
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Deep Dives·3 min
Hermes Agent Deep Dive: Five-Layer Memory Architecture and Self-Evolution Mechanism Fully Explained
A deep dive into Huawei's open-source Hermes Agent framework: five-layer memory architecture, self-evolution loop, multi-agent collaboration, and comparison with Open Manus.
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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.
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Tutorials·4 min
A Practical Guide for Java Developers Transitioning to AI Agent Development: Technology Selection, Architecture Design & Resume Positioning
A systematic guide for Java developers entering AI Agent development, covering core concepts, Workflow vs. Agent architecture comparison, Spring AI Alibaba selection, and resume positioning strategies.
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Product Reviews·3 min
How to Choose an AI Agent Framework in 2026? Pros and Cons of Four Leading Solutions
Compare four leading AI Agent frameworks in 2026: Coze, AutoGen, CrewAI, LangChain, and AutoGen Studio — covering coding requirements, private deployment, and commercialization.
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Product Reviews·3 min
Multi-Agent Orchestration Framework: A Super AI Development Team of 98 Expert Agents
Deep dive into a trending GitHub multi-agent framework with 98 expert agents, swarm collaboration, HNSW vector memory, autonomous learning, and Claude Code plugin support for full-lifecycle development.
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Deep Dives·4 min
The Complete Guide to Agentic RAG: Principles and Code Implementation
Deep dive into Agentic RAG vs traditional RAG, covering tool calling, multi-step iteration, query rewriting, with LangChain and LangGraph code examples for building intelligent retrieval systems.
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Tutorials·4 min
LangChain Deep Agents in Practice: Ten Agent Development Pain Points and Their Solutions
Deep dive into LangChain Deep Agents paradigm, analyzing ten Agent development pain points including tool sprawl and context pollution, with practical enterprise solutions using Deep Research.
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Tutorials·4 min
Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation Guide
Compare traditional RAG vs Agentic RAG architectures, explore planning, tool use, and multi-step iteration capabilities, with full LangChain/LangGraph ReAct Agent code and ChatBoss project examples.
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Product Reviews·3 min
awesome-LLM-resources: A Comprehensive Analysis of the 8,200-Star LLM Learning Resource Repository on GitHub
In-depth analysis of the 8,200-star GitHub project awesome-LLM-resources, covering multimodal generation, Agents, model training, MCP protocol, and more — a one-stop LLM learning guide.
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Tutorials·3 min
Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation
Deep dive into Agentic RAG vs traditional RAG, covering planning, tool calling, and multi-step iteration capabilities with complete LangChain and LangGraph code implementation.
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Research·3 min
Multi-Agent AI Detects Zero-Day CVE Exploitation: Technical Deep Dive Behind 85% Accuracy
Deep dive into the multi-agent architecture of ai-detects-if-cve-was-zero-day: how GPT-4o, DeepSeek v3, and Llama 3.3 collaborate to detect zero-day CVE exploitation with 85%+ accuracy on 50 validated samples.
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Deep Dives·3 min
Claude's Advisor Strategy: Small Models Execute, Large Models Supervise — A New Cost-Saving Paradigm for AI Agents
Anthropic's Advisor Strategy lets Sonnet execute tasks while Opus serves as advisor, cutting costs 12% while boosting SWE-Bench by 2.7 points. A new multi-model AI Agent paradigm explained.
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Product Reviews·2 min
Perfect-Web-Clone: A Deep Dive into the Pixel-Perfect Web Cloning Tool Built on Multi-Agent Architecture
Deep dive into the Perfect-Web-Clone open-source project: how its Claude Agent SDK multi-agent architecture and 40+ specialized tools achieve pixel-perfect web cloning beyond Cursor and single-model tools.
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Tech Frontiers·3 min
Simulation Reshaping AI Testing: A New Paradigm for Systematically Validating AI Application Reliability
Explore how simulation solves AI testing challenges, covering scenario simulation, large-scale regression testing, and multi-agent verification to build reliable AI systems.
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Tech Frontiers·2 min
DeepAgents: LangChain's Deep Agent Development Framework Built on LangGraph
DeepAgents is LangChain's open-source Agent framework built on LangGraph, supporting multi-step reasoning, state management, and multi-Agent collaboration for production-grade AI development.
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Deep Dives·3 min
LangGraph Deep Dive: An Open-Source Framework for Building Resilient AI Agents
Deep dive into LangGraph's core architecture, StateGraph design, multi-Agent collaboration, and deployment. Learn how this 31K+ Star project helps build reliable AI Agents.
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