Multi-Agent Systems

Key Points of MetaGPT Technology and Open Source Model Practice

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Key Points of MetaGPT Technology and Open Source Model Practice

MetaGPT is named after the “GPT-based Meta-Programming framework”, which means that MetaGPT is a meta-programming framework. It utilizes Standard Operating Procedures (SOP) to enhance the problem-solving capabilities of multi-agent systems based on large language models (LLMs). The framework simulates a virtual software team that includes roles such as product managers, architects, project managers, engineers, and … Read more

MetaGPT: Enhancing Software Engineering Efficiency with SOPs

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MetaGPT: Enhancing Software Engineering Efficiency with SOPs

1 Content Overview Significant progress has been made in automating problem-solving through a group of agents based on large language models (LLMs). Existing LLM-based multi-agent systems can now handle simple conversational tasks. However, solutions for more complex tasks become complicated due to logical inconsistencies, which are caused by the cascading hallucinations that arise from directly … Read more

Understanding AI Agents: Classic Cases and Frameworks

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Understanding AI Agents: Classic Cases and Frameworks

Hello everyone, I am Student Zhang. Continuous learning and continuous output of valuable content, follow me, and let’s learn AI large model technology together! Overview of Articles in the Official Account If you have any questions, feel free to add me on WeChat: jasper_8017. Looking forward to discussing and progressing together with like-minded friends! This … Read more

Differences Between LangChain and LangGraph

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Differences Between LangChain and LangGraph

In the field of large models, LangChain and LangGraph are two frameworks that have attracted considerable attention. Both aim to help developers build applications using large language models (LLMs), but they differ significantly in design philosophy, architecture, functionality, and applicable scenarios. 1. Introduction to LangChain LangChain is a framework for developing applications powered by large … Read more

Comprehensive Guide to Creating Multi-Agent Methods in Langgraph

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Comprehensive Guide to Creating Multi-Agent Methods in Langgraph

There are five ways to create multi-agents in Langgraph: Network: Each agent can communicate with all other agents, and all agents can decide which agent to call next. Supervisor: Each agent can communicate with a supervisor agent, which decides which agent to call next. Supervisor (tool-calling): This is a special case of the supervisor architecture … Read more

Multi-Agent Workflow with LangGraph

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Multi-Agent Workflow with LangGraph

Introduction The emergence of large language models (LLMs) has reshaped how AI systems interact with and interpret the world. Traditionally, single-agent architectures have been used to handle inputs, make decisions, and produce outputs. However, as AI systems scale to manage more complex, multi-step tasks, researchers and developers are increasingly turning to multi-agent systems and advanced … Read more

Mastering LangGraph: Subgraphs

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Mastering LangGraph: Subgraphs

How to Add and Use Subgraphs Subgraphs allow the construction of complex systems with multiple components, each of which is a graph. A common use case for using subgraphs is building multi-agent systems. The main issue when adding subgraphs is how the parent graph and the subgraph communicate, i.e., how they pass state to each … Read more

2025: The Year of AI Agents – Building Multi-Agent Systems with CrewAi and Gemini 1.5

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2025: The Year of AI Agents - Building Multi-Agent Systems with CrewAi and Gemini 1.5

2025: The Year of AI Agents – Building Multi-Agent Systems with CrewAi and Gemini 1.5 As many experts predict, 2025 is gradually becoming the year of agent-based artificial intelligence. This emerging field is poised to redefine the way we interact with technology by introducing highly autonomous systems that can make decisions and execute complex tasks … Read more

Introduction to AI Agents Based on crewAI

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Introduction to AI Agents Based on crewAI

Recently, I shared Dr. Andrew Ng’s series of Prompt courses. If this is your first time watching Dr. Ng’s original videos, you might find them somewhat content-light and a bit dry, and perhaps you would prefer to watch summaries from popular content creators on good Prompt writing techniques. However, that’s not the case; when you … Read more

In-Depth Analysis of Creating Agents with CrewAI

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In-Depth Analysis of Creating Agents with CrewAI

CrewAI Official Website: https://www.crewai.comGithub: https://github.com/joaomdmoura/crewAIChinese Documentation: http://www.aidoczh.com/docs/crewai/ 1. Introduction2. Detailed Explanation of Core Concepts in CrewAI2.1 Agent2.1.1 Definition and Function of Agents2.1.2 Agent Attributes2.1.3 Creating Agents2.2 Tasks2.2.1 Task Definition and Collaboration2.2.2 Task Attributes2.2.3 Creating Tasks2.2.4 Creating Tasks Using Tools2.2.5 Task Dependencies2.2.6 Asynchronous Execution2.2.7 Callback Mechanism2.2.8 Accessing Specific Task Outputs2.2.9 Tool Overriding Mechanism2.2.10 Error Handling and … Read more