Welcome back to the Microsoft Agent Framework Series!
In this episode, we’ll take your AI development to the next level by integrating GitHub Models with Microsoft Agent Framework to build a fully functional Financial Adviser AI Agent in C#.
This tutorial will show you how to connect to GitHub’s new AI models, configure your credentials, and build a C# console app that can give realistic, intelligent financial insights — powered by the Microsoft Agent Framework.
What You’ll Learn:
✅ How to use GitHub Models inside Microsoft Agent Framework
✅ How to connect your GitHub API key securely in C#
✅ How to create a Financial Adviser AI Agent step-by-step
✅ How to send and receive dynamic AI responses using .NET
✅ How to extend Agent Framework to work beyond Azure OpenAI
By the end of this video, you’ll understand how to build an AI agent powered by GitHub Models that can analyze user queries and provide financial guidance — right from your console app.
- Microsoft Agent Framework (Preview)
- GitHub Models (gpt-4o-mini)
- .NET 9 / C#
- Visual Studio 2022
- GitHub API Key / Credentials
Why You Should Watch:
The Microsoft Agent Framework isn’t limited to Azure OpenAI — it’s built to be model-agnostic.
This tutorial demonstrates how to use GitHub’s open LLM endpoints to create a custom agent — showing the flexibility and power of the framework.
If you’re building AI-driven business apps, this is the perfect starting point for creating domain-specific agents, like financial, legal, or customer-support assistants.
Resources & Links:
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Visit our Website: https://thecodestreet.dev
Microsoft Agent Framework Docs: https://learn.microsoft.com/agent-framework
Who This Video Is For:
- Developers exploring AI integration with GitHub Models
- .NET developers experimenting with Microsoft Agent Framework
- Engineers building AI assistants and advisory bots
- Anyone curious about mixing LLMs and .NET applications
Next in This Series
➡ How to Use Tools and Plugins in Microsoft Agent Framework
➡ Building Multi-Agent Collaboration in C#
➡ Adding Memory and Context to Your AI Agent
➡ Deploying Agent Framework Projects to Azure
