.NET AI Agent Tutorial with Semantic Kernel

This repository contains a comprehensive tutorial for building AI-powered agents using .NET and the Microsoft Semantic Kernel. The tutorial is divided into three parts, each building upon the previous one, to provide a step-by-step guide from a simple agent to a more complex multi-client setup.

Tutorial Structure

Part 1: Build a Restaurant Menu Agent

This part covers the fundamentals of the Semantic Kernel. You will build a simple "Restaurant Menu Agent" that can answer questions about a restaurant's menu.

Key concepts covered:

• Setting up Semantic Kernel with OpenAI
• Creating and using plugins
• Interacting with the agent from a console application

Part 2: Run LLM Locally

In the second part, you will learn how to switch from a cloud-based LLM service like OpenAI to a locally running model using Ollama. This is useful for offline development, cost savings, and data privacy.

Key concepts covered:

• Integrating Semantic Kernel with Ollama
• Running local LLMs like Llama 3
• Modifying the agent to use a local model

Part 3: Multi-Client/Server Agent using Model Context Protocol

The final part demonstrates a more advanced architecture where a central agent server manages the core logic and multiple clients can connect to it.

Key concepts covered:

• Building a server for the Semantic Kernel agent
• Creating a client application to interact with the agent server
• Real-world application architecture for AI agents

Prerequisites

Before you begin, ensure you have the following installed:

• .NET 9 SDK
• Visual Studio Code or Visual Studio
• An OpenAI API key (for Part 1)
• Ollama (for Part 2)

How to Use This Tutorial

1. Start with Part 1: It is highly recommended to follow the tutorial in order.
2. Navigate to each part's directory: Each part is a self-contained .NET project.
3. Follow the instructions: Each part has its own README.md file with detailed instructions on how to run the project.

Happy coding!