选择合适的多智能体架构

中文摘要

本文探讨了何时需要采用多智能体架构，并介绍了观察到的四种主要模式。多智能体系统在复杂任务中表现出色，能够通过分工协作提高效率。文章详细分析了每种架构的适用场景和优缺点，包括集中式、分散式、混合式和分层式架构。此外，还介绍了LangChain如何赋能开发者高效构建多智能体系统，提供了实用的工具和框架支持。对于需要处理复杂交互和分布式决策的AI应用场景，本文提供了有价值的架构选择指导。

English Summary

Choosing the Right Multi-Agent Architecture

This post examines when multi-agent architectures become necessary and introduces four primary patterns observed in practice. Multi-agent systems excel in complex tasks by enabling division of labor and collaboration. The article provides a detailed analysis of each architecture's applicable scenarios, advantages, and limitations, covering centralized, decentralized, hybrid, and hierarchical models. Furthermore, it explains how LangChain empowers developers to effectively build multi-agent systems by offering practical tools and framework support. For AI applications requiring complex interactions and distributed decision-making, this content offers valuable guidance on architecture selection.