Showing results for Tag: python from Semantic Kernel

As we continue to empower developers in embedding AI into their workflows, we are thrilled to announce significant updates to the Microsoft Semantic Kernel's Process Framework. Building on our introductory blog, we’ve made enhancements that further streamline business process automation and AI integration and help you to be successful with the Sema...

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...

We are thrilled to announce that Microsoft Semantic Kernel Python Kernel has reached an incredible milestone of 1,000,000 downloads! This achievement would not have been possible without the unwavering support and enthusiasm of our community. We want to extend our heartfelt thanks to every developer, contributor, and user who has embraced the Pytho...

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...