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Chinese Edition of Anthropic’s “Building Effective Agents”

AI summary

A Chinese translation and illustrated edition of Anthropic’s “Building Effective Agents,” credited to original authors Erik Schluntz and Barry Zhang and dated December 19, 2024. The report describes it as a complete translation with seven redrawn architecture diagrams. It distinguishes workflows, which follow predefined code paths, from agents, which dynamically direct their own processes and tool use. The guide covers prompt chaining, routing, parallelization, orchestrator-workers, and evaluator-optimizer patterns, and recommends starting with direct LLM API calls, keeping designs simple and transparent, and carefully designing tool interfaces. The supplied report does not independently verify the translation’s completeness or editorial fidelity.

In-depth insight

The guide provides developers with practical advice on choosing predefined workflows or autonomous agents while weighing latency, cost, reliability, and maintainability.

原文地址:www.anthropic.com/research/bu… 原作者:Erik Schluntz & Barry Zhang (Anthropic) 发布日期:2024 年 12 月 19 日 译注:本文完整还原了 Anthropic 原文的所有章节、案例以及 7 张核心架构图(使用 Mermaid 重新绘制),并保留了关键英文术语对照。


导言

在过去的一年里,我们与各行各业的数十个团队合作,共同构建大语言模型(LLM)智能体(Agents)。我们一致发现:最成功的落地实现并没有使用复杂的框架或专门的库,而是采用简单、可组合的设计模式(simple, composable patterns)构建的。

在本文中,我们将分享从客户合作以及自身构建智能体过程中沉淀下来的经验,并为开发者提供构建高效智能体的实用建议。


什么是智能体(What are agents?)

“智能体(Agent)”可以有多种定义。一些客户将其定义为能够长时间独立运行、使用各种工具完成复杂任务的完全自主系统;另一些人则用这个词来描述遵循预定义工作流、更具规范性的实现。在 Anthropic,我们将所有这些变体统称为智能体系统(Agentic systems),但在架构上对 工作流(Workflows) 和 智能体(Agents) 做了关键区分:

#Anthropic#LangGraph#Amazon Bedrock#Rivet#Vellum#Model Context Protocol#Claude 3.5 Haiku#Claude 3.5 Sonnet#SWE-bench Verified

Original · 16 min readRead the original
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