We are thrilled to announce the General Availability (GA) release of the OpenAPI package for Semantic Kernel, available for both .NET and Python! With this significant milestone, developers can easily integrate existing APIs as plugins, enhancing the capabilities of their AI agents while making them more versatile in real-world applications. Why O...

The Semantic Kernel Agent Framework revolutionizes how developers can interact with Large Language Models (LLMs) by embedding dynamic, multi-step agents into their applications. By combining the power of LLMs with structured programming, the framework allows developers to build intelligent systems that can autonomously carry out tasks, reason based...

In working with AI applications, ensuring that the output generated by a language model is structured and follows a consistent format is critical—especially when handling complex tasks like solving math problems. A powerful way to achieve this is through the use of JSON Schema, which allows the AI model to produce outputs that align with a predefin...

One of the most exciting features available in certain Large Language Models (LLMs) is function-calling. In Semantic Kernel, we handle the heavy lifting so that you can bring your own code or utilize built-in plugins that cater to your use case. Our goal is to make it easy for you to incorporate function calling into your application. Today, we'll ...

The term "agent" has become a popular term within the industry. There have many different definitions, but at their core, they consist of a system prompt (i.e., a persona), plugins, and an ability to automatically reason and create plans to address user goals. Up until today, we've demonstrated how you could use components of Semantic Kernel to ...

  Introducing Function Choice Behavior Today, we're excited to introduce the Function Choice Behavior, an enhancement over the existing Function Call Behavior. This new feature streamlines configuration and supports specifying multiple required functions, simplifying code and enhancing functionality. One significant advantage of Function ...

We are thrilled to announce the release of the long-awaited Semantic Kernel Python SDK 1.0.0! This milestone version brings a plethora of enhancements and new features designed to empower AI and app developers with more robust and versatile tools. Exciting New Feature: Shared Prompts Across Languages One of the groundbreaking features of this rel...

We are excited to showcase a Semantic Kernel sample across all 3 languages: .NET, Python and Java! Today we’re going to dive into the Python version of the TimePlugin sample which is featured here. Prerequisites for the Azure OpenAI key or OpenAI key: As covered in our Python README.md or DEV_SETUP.md, Python leverages Pydantic settings. This...

Hi all, We’re looking forward to highlight a Python sample today focused on a Restaurant Bookings sample here. Booking Restaurant - Demo Application This sample provides a practical demonstration of how to leverage features from the Semantic Kernel to build a console application. Specifically, the application utilizes the Business Schedule...

As we approach a stable v1.0 version of the Python Semantic Kernel SDK, we analysed the methods used to add plugins and functions to the kernel. We realised that the variety of available methods might confuse developers. For instance, when should one use versus ? Or versus ? Our goal has always been to keep the SDK as Pythonic and simple as possi...