Introducing the MLX Integration Library for Agent Framework

Thu, 11 Dec 2025 08:00:00 +0000

I’ve recently been working on setting up a bunch of Agent Framework samples, which would showcase the cooperation between cloud agents (backed by LLMs in the cloud) and local agents (running on your own machine). Since I primarily work on a Mac, the natural choice for me was to use MLX as the local model runner, which required a bit of bootstrapping - and felt quite tedious. So, the natural next step was to create a library that would make it easy to integrate MLX models into Agent Framework applications, since there wasn’t one available yet.

Today, I’m excited to announce the release of the MLX Integration Library for Agent Framework! This library simplifies the process of integrating MLX models into your Agent Framework applications, allowing you to leverage local Mac AI capabilities seamlessly alongside cloud-based agents.

Simplifying the AI workflow: Access different types of model deployments with Azure AI Inference

Fri, 22 Nov 2024 07:06:14 +0000

In this post, we will explore the flexibility behind Azure AI Inference, a new library from Azure, which allows us to run inference against a wide range of AI model deployments - both in Azure and, as we will see in this notebook, in other places as well.

It is available for Python and for .NET - in this post, we will focus on the Python version.

Python on Strathweb. A free flowing tech monologue.

Introducing the MLX Integration Library for Agent Framework

Simplifying the AI workflow: Access different types of model deployments with Azure AI Inference