使用 Google ADK 构建 AI Agents 的设计模式及代码示例

Building effective AI agents requires understanding and implementing proven design patterns. This blog explores key agentic design patterns and demonstrates their implementation using Google’s Agent Development Kit (ADK), an open-source framework designed to simplify agent development.

What is Google’s Agent Development Kit (ADK)?

什么是 Google 的 Agent Development Kit (ADK)？

Google’s Agent Development Kit (ADK) is a flexible, modular framework for developing and deploying AI agents. While optimized for Gemini and the Google ecosystem, ADK is model-agnostic and deployment-agnostic, designed to make agent development feel more like software development .

Google 的 Agent Development Kit (ADK) 是一个灵活、模块化的框架，用于开发和部署 AI 智能体。虽然针对 Gemini 和 Google 生态系统进行了优化，但 ADK 是模型无关且部署无关的，旨在让智能体开发更像软件开发。

Key features include:

主要特性包括：

Code-first Python development approach
Code-first Python development approach
Rich tool ecosystem
丰富的工具生态系统
Modular multi-agent system capabilities
模块化多智能体系统能力
Flexible deployment options
灵活的部署选项
Built-in testing and evaluation tools
内置测试和评估工具

Let’s dive into the essential agentic design patterns and see how to implement them using ADK.

让我们深入探讨基本的智能体设计模式，并了解如何使用 ADK 实现它们。

1. ReACT (Reasoning and Acting)

1. ReACT（推理与行动）

ReACT is a framework that combines reasoning and acting capabilities within language models. This approach enables AI agents to dynamically alternate between thinking through a problem (reasoning) and taking specific steps to address it (acting) .

ReACT 是一个在语言模型中融合推理与行动能力的框架。该方法使 AI 智能体能够在思考问题（推理）与采取具体步骤解决问题（行动）之间动态切换。

How ReACT Works:

ReACT 的工作原理：

graph TD
    A[User Input] --> B[LLM1-Reasoning]
    B --> C[Tool Calling]
    C --> D[External API/Tool]
    D --> E[Tool Results]
    E --> F[LLM2-Actions]
    F --> G[Agent R...