Tutorials ASP.NET Core with Agentic AI Tutorial

Introduction to LLMs — Complete Guide

Introduction to LLMs — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ASP.NET Core with Agentic AI Tutorial on Toolliyo Academy.

8 min read Updated 8/3/2026

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ASP.NET Core with Agentic AI Tutorial · Lesson 3 of 100

LLMs

AI basics → Agents

AI basics · 1 — Setup · ~6 min · Module 1: AI and Agentic AI Foundations

What is this?

Large language models are neural networks trained on vast text to predict the next token. They power chat, tool selection, and summarization in AgentNest. You choose model, temperature, and max tokens per use case — CRM copy differs from clinical summaries.

Why should you care?

ERP and analytics assistants need consistent model settings per tenant so latency, cost, and safety stay predictable at enterprise scale.

See it live — copy this example

Paste into an ASP.NET Core 8+ / AgentNest project, then run with dotnet run (set your API keys in user-secrets).

// AgentNest.Api/Options/LlmOptions.cs
public sealed class LlmOptions
{
    public const string Section = "Llm";
    public string Deployment { get; init; } = "gpt-4o-mini";
    public float Temperature { get; init; } = 0.2f;
    public int MaxTokens { get; init; } = 800;
}

What happened?

LlmOptions binds deployment name and generation limits from configuration.
Hospital flows use lower temperature; creative marketing drafts can read a separate profile.

Practice next

Add LlmOptions class and bind it in Program.cs with builder.Services.Configure(...).
Store deployment names in appsettings per environment.
Inject IOptions into chat services.
Add a second LlmOptions profile named AnalyticsSummary with Temperature 0.
Validate MaxTokens with DataAnnotations and fail fast at startup.

Remember

LLMs are configurable text engines behind AgentNest agents. Bind model settings to IOptions for per-environment control. Match temperature and token limits to the business risk of each feature.