Showing category results for .NET

We are thrilled to announce the General Availability (GA) of our Memory packages for .NET, Java, and Python! The Semantic Kernel team and our partners have been working hard to allow you to quickly connect to vector stores and make it easy for you to do embeddings and data retrieval between stores. Transforming Data Management with Vector Stores...

We are excited to announce the General Availability (GA) release of Filters for our .NET and Python Semantic Kernel! This vital enhancement strengthens the control and visibility developers have when running functions, ensuring responsible AI practices are instilled from the ground up. Filters not only improve security but also contribute to buildi...

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...

As the landscape of AI continues to evolve, meeting users where they are is vital. We want to spotlight the newly released Microsoft 365 Agents SDK and its seamless integration with Semantic Kernel. This powerful combination empowers developers to create robust AI agents capable of operating across multiple channels, engaging users wherever they ar...

We are thrilled to announce the launch of Microsoft.Extensions.VectorData for .NET! Our collaboration with the .NET team since the debut of Semantic Kernel has resulted in a powerful new feature that aligns with the best practices of both current and upcoming .NET releases.  This is the second new package as part of this collaboration.  You can lea...

Diving into Function Calling and its JSON Schema in Semantic Kernel .NET Function-calling is one of the most exciting features of certain Large Language Models (LLMs), enabling developers to execute code directly in response to user queries. In Semantic Kernel, we streamline the process by allowing you to use built-in plugins or integrate your own...

Today we're featuring a sample application, called eShop. You can read the entire blog post and steps for running the application here: eShop infused with AI - a comprehensive intelligent app sample - .NET Blog Below, we have a brief summary of eShop and the integration with Semantic Kernel. Introducing eShop “support with AI” edition The AI-e...

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 the launch of Microsoft.Extensions.AI for .NET! Our collaboration with the .NET team since the debut of Semantic Kernel has resulted in a powerful new feature that aligns with the best practices of both current and upcoming .NET releases. With the introduction of Microsoft.Extensions.AI, Independent Software Vendors (...

In one of the previous posts, we demonstrated how to use JSON Schema to get Structured Output with OpenAI and Python version of Semantic Kernel: Using JSON Schema for Structured Output in Python for OpenAI Models. In this post, we will explore how to implement a JSON Schema-based structured output using .NET version of Semantic Kernel. For mo...