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Agents with Semantic Kernel Labs

This repository contains hands-on labs demonstrating the integration of Azure AI Agents Service with Semantic Kernel. The labs are designed to help developers understand and implement AI-powered solutions using Microsoft's latest AI technologies.

Overview

This project was created during a hackathon to showcase practical applications of Azure AI Agents and Semantic Kernel working together. Through a series of Jupyter notebooks and sample applications, you'll learn how to work with both single agents and multi-agent systems.

The repository includes:

  • Interactive Jupyter notebooks that teach the fundamentals of Azure AI Agents and Semantic Kernel
  • Step-by-step tutorials progressing from basic single-agent scenarios to complex multi-agent interactions
  • Sample applications demonstrating practical implementations of concepts covered in the notebooks
  • Complete example scenarios showing real-world applications of AI agents

Prerequisites

  • Azure subscription
  • Azure AI Services account
  • Python 11.0.0 or later
  • Visual Studio Code or Visual Studio 2022
  • Basic knowledge of Python and async programming
  • Azure CLI installed

Repository Structure

  • labs/: Contains hands-on Jupyter notebooks with interactive tutorials

    • lab_1.ipynb: Introduction to Semantic Kernel Agents
      • Basic agent creation and configuration
      • Chat history and agent interactions
      • Function calling and plugins integration
      • Practical exercises with single agents
    • lab_2.ipynb: Multi-Agent Systems with Semantic Kernel
      • Transitioning from single to multi-agent systems
      • Agent collaboration using AgentGroupChat
      • Specialized agent roles and team design
      • Agent selection and termination strategies
  • solutions/: Practical implementations showcasing concepts from the labs

    • rws-app/: Complete multi-agent application for infrastructure management
      • setup/: Infrastructure deployment with Azure Bicep templates and configuration files
        • Infrastructure as Code (IaC) using Bicep for Azure resources
        • Azure Functions for backend services (SQL, Weather)
        • Configuration for Azure API Management and Azure Cognitive Search
      • src/: Source code for the multi-agent system
        • Specialized agents for infrastructure analysis, water management, and business advising
        • RAG plugin for knowledge retrieval from documents
        • API plugin for connecting to backend services
        • Agent collaboration frameworks for sequential and custom workflows

Getting Started

  1. Clone this repository
  2. Configure your Azure credentials
  3. Follow the lab instructions in each directory

Resources and References

Azure AI Agents

Semantic Kernel

Additional Resources

License

This project is licensed under the MIT License - see the LICENSE file for details.

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