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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/1-introduction.yml

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description: Learn how to create Microsoft Foundry Agent Service agents with Microsoft Agent Framework.
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/2-understand-semantic-kernel-agents.yml

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description: This unit explains the Microsoft Agent Framework SDK.
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/3-create-azure-ai-agent.yml

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description: Learn how to use the Microsoft Agent Framework to create an Azure AI agent
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/4-add-plugins-to-agent.yml

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description: Learn how to add tools to your Azure AI agent
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/5-exercise.yml

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description: Learn how to build an agent using the Microsoft Agent Framework SDK. This unit provides an exercise to build an agent using the Microsoft Agent Framework SDK.
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/6-knowledge-check.yml

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description: This unit contains a knowledge check, which can help learners reinforce their understanding of the material.
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/7-summary.yml

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description: This unit summarizes the key concepts covered in the module, including key features and how to use Microsoft Foundry Agent Service.
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learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/includes/4-add-plugins-to-agent.md

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When creating custom tools for your Microsoft Foundry Agent, you need to understand several key concepts:
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1. **Use the tool decorator**
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Create a custom function tool by defining a Python function and decorating it with the `@tool` decorator from the Microsoft Agent Framework. This decorator registers your function as a tool that the AI can call. The `@tool` decorator includes parameters for providing a name and description for your tool, as well as the `approval_mode` to specify whether tool calls require approval.
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1. **Function definition and annotations**
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Create your tool by defining a regular Python function with proper type annotations. Use `Annotated` and `Field` from Pydantic to provide detailed descriptions that help the AI understand the function's purpose and how to use its parameters. The more descriptive your annotations, the better the AI can understand when and how to call your function.

learn-pr/wwl-data-ai/develop-ai-agent-with-semantic-kernel/index.yml

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description: Learn how to start building agents with Microsoft Agent Framework
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learn-pr/wwl-data-ai/discover-agents-with-a2a/1-introduction.yml

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title: Introduction
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description: "Learn how to use the A2A (Agent-to-Agent) protocol to discover and connect to remote Azure AI Agents."
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