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Microsoft Agent Framework Examples for AI Agents Beginners

This section provides comprehensive Microsoft Agent Framework examples that extend and complement the content from Microsoft's AI Agents for Beginners curriculum. These practical code samples demonstrate how to build intelligent agents using both Python and .NET implementations of the Microsoft Agent Framework.

🎯 Overview

The examples in this directory are designed to provide hands-on experience with Microsoft Agent Framework, covering fundamental concepts through advanced multi-agent systems. Each lesson includes both Python and .NET code samples to accommodate different development preferences and environments.

📚 Learning Path

01. Introduction to AI Agents

Learn the foundational concepts of AI agents and get started with your first Microsoft Agent Framework implementation.

Code Samples:

02. Explore Agentic Frameworks

Dive deeper into the Microsoft Agent Framework architecture and understand different implementation patterns.

Code Samples:

03. Agentic Design Patterns

Explore common design patterns and best practices for building robust AI agents with GitHub Models integration.

Code Samples:

04. Tool Use and Integration

Learn how to enhance your agents with external tools and capabilities using GitHub Models.

Code Samples:

05. Agentic RAG (Retrieval-Augmented Generation)

Implement knowledge-enhanced agents using Azure AI Foundry's file search capabilities.

Code Samples:

Supporting Files:

07. Planning and Design

Explore advanced planning capabilities and design patterns with GitHub Models integration.

Code Samples:

08. Multi-Agent Systems

Build collaborative multi-agent workflows using GitHub Models for complex problem-solving scenarios.

Code Samples:

09. Metacognition

Coming Soon - Advanced metacognitive capabilities for self-aware agents.

10. AI Agents in Production

Coming Soon - Best practices for deploying and managing agents in production environments.

11. Agentic Protocols

Coming Soon - Advanced communication protocols and standards for agent interactions.

12. Context Engineering

Coming Soon - Advanced techniques for context management and optimization.

🛠 Prerequisites

Development Environment

  • Python: Python 3.10 or higher
  • .NET: .NET 9.0 or higher
  • Visual Studio Code with appropriate extensions

Required Services

  • Azure AI Foundry: For RAG examples and advanced capabilities
  • GitHub Models: For GitHub-integrated examples
  • Azure OpenAI Service: For certain provider examples

Environment Configuration

Create a .env file or set environment variables for the examples:

# GitHub Models Configuration
GITHUB_TOKEN=your_github_token
GITHUB_ENDPOINT=https://models.inference.ai.azure.com
GITHUB_MODEL_ID=gpt-4o-mini

# Azure AI Foundry Configuration
FOUNDRY_PROJECT_ENDPOINT=your_foundry_endpoint
FOUNDRY_MODEL_DEPLOYMENT_NAME=your_model_name

# Azure OpenAI Configuration (if needed)
AZURE_OPENAI_ENDPOINT=your_aoai_endpoint
AZURE_OPENAI_API_KEY=your_aoai_key
AZURE_OPENAI_DEPLOYMENT_NAME=your_deployment_name

🚀 Getting Started

  1. Choose your preferred language: Python or .NET
  2. Start with lesson 01: Introduction to AI Agents
  3. Follow the sequential path: Each lesson builds upon previous concepts
  4. Experiment with the code: Modify examples to understand the framework better
  5. Apply learnings: Use the patterns in your own agent projects

📝 Code Sample Structure

Each code sample is provided as a Jupyter notebook (.ipynb) containing:

  • Detailed explanations of concepts and implementation
  • Step-by-step code with comments and documentation
  • Practical examples you can run and modify
  • Best practices for Microsoft Agent Framework usage

🔗 Related Resources

🤝 Contributing

We welcome contributions to improve these examples:

  • Report issues or bugs
  • Suggest new examples or improvements
  • Submit pull requests with enhancements
  • Share your own agent implementations

Ready to build intelligent agents? Start with lesson 01 and begin your Microsoft Agent Framework journey! 🚀