Microsoft Agent Framework

For models that don't support underlying in-service memory capabilities, the Microsoft Agent Framework allows you to use third party solutions to store agent chat history.

How to Store Chat History Using External Storage in Microsoft Agent Framework

Chat history and memory allow agents to maintain context across conversations and remember user preferences, which enables agents to provide personalized experiences. Using the Microsoft Agent Framework, we can use in-memory chat message stores, persistent databases, and specialized memory services to cater to a variety of different use cases. In this article, I’ll show you a simple example of how we can use an Azure Cosmos DB Vector store to store conversations we have with an agent, and how we can retrieve conversations so that our agents can maintain context. ...

January 12, 2026 · 14 min · Will Velida
With GitHub Models, we can test LLMs in Agents for free, rather than paying for Azure Foundry

Using GitHub Models with the Microsoft Agent Framework

Almost a year ago, I wrote a blog post on how you could use GitHub Models with Semantic Kernel applications for dev and test purposes. Now that the Microsoft Agent Framework is available, I thought I’d create an updated article on how you can use GitHub Models with the new framework, so that you don’t have to provision Azure Foundry and pay for using LLM usage to build agents. What is the Microsoft Agent Framework? It’s an open-source kit for building AI Agents and agentic workflows in Python and C#. The Agent Framework is an extension of both Semantic Kernel and AutoGen projects, and it provides a unified approach for building agents. Both the Semantic Kernel and AutoGen teams are working together to build the Microsoft Agent Framework. ...

January 9, 2026 · 8 min · Will Velida