Tutorials Microsoft Agent Framework with Ollama Tutorial

Semantic Kernel Basics

Semantic Kernel Basics: free step-by-step lesson with examples, common mistakes, and interview tips — part of Microsoft Agent Framework with Ollama Tutorial on Toolliyo Academy.

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Microsoft Agent Framework with Ollama Tutorial · Lesson 31 of 100

Semantic Kernel Basics

Foundations & Ollama ✓.NET & AgentsRAG & OpsProjects

.NET & Agents · 2 — Kernel · ~6 min · Semantic Kernel & Agents

What is this?

Semantic Kernel (SK) is a .NET SDK that connects LLMs, prompts, and tools (plugins). You build a Kernel, add a chat service, then invoke prompts or agents.

Why should you care?

Microsoft’s agent-style apps in .NET commonly use SK to keep tool calling and prompts organized.

See it live — copy this example

Run CLI steps in a terminal. Run C# samples in a .NET 8 console or Web API project with Ollama running on localhost:11434.

// dotnet add package Microsoft.SemanticKernel
using Microsoft.SemanticKernel;

var builder = Kernel.CreateBuilder();
// Next lesson: add Ollama chat completion
var kernel = builder.Build();
Console.WriteLine("Kernel ready");

What happened?

  • CreateBuilder starts configuration.
  • Build() creates the Kernel object your plugins and chat services hang off.

Practice next

  1. Create a Web/console app.
  2. Add the SemanticKernel package.
  3. Build an empty kernel.
  4. Print kernel.Plugins.Count.
  5. Add logging to the builder.

Remember

SK organizes LLM + tools in .NET. Kernel is the hub object. Plugins expose tools to the model.

SK as the agent spine

LocalAIDesk uses one Kernel per request scope.

Outcome: Clear place to register tools.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain Concepts in the context of Microsoft Agent Framework with Ollama.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Concepts in plain language f…
Mid Detailed
What are common mistakes teams make with LLMs when using Microsoft Agent Framework with Ollama?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define LLMs in plain language for M…
Senior Detailed
How would you debug a production issue related to RAG in a Microsoft Agent Framework with Ollama application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define RAG in plain language for Mi…
Mid Detailed
Compare two approaches to Ethics—when would you choose each?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Ethics in plain language for…
Junior Detailed
Describe a real-world scenario where Production mattered in a Microsoft Agent Framework with Ollama project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Production in plain language…
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Microsoft Agent Framework with Ollama Tutorial
Course syllabus

Microsoft Agent Framework with Ollama Tutorial

Foundations — AI & Agents
Ollama — Local Models
ASP.NET Core + Ollama
Semantic Kernel & Agents
RAG & Vector Search
Security & Observability
DevOps & Infrastructure
Product Use Cases
System Design
Capstone Projects
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