Showing category results for .NET

Semantic Kernel: Package Previews, Graduations & Deprecations We are excited to share a summary of recent updates and continuous clean-up efforts across the Semantic Kernel .NET codebase. These changes focus on improving maintainability, aligning with the latest APIs, and ensuring a consistent experience for users. Below you’ll find details on...

Today we’re thrilled to announce support for Hybrid search with Semantic Kernel Vector Stores for .NET. What is Hybrid Search? Hybrid search performs two parallel searches on a vector database.  The union of the results of these two searches are then returned to callers with a combined rank, based on the rankings from each of the constituent sear...

OpenAI's gpt-4o-audio-preview is a powerful multimodal model that enables audio input and output capabilities, allowing developers to create more natural and accessible AI interactions. This model supports both speech-to-text and text-to-speech functionalities in a single API call through the Chat Completions API, making it suitable for building vo...

This is second MCP related blog post that is part of a series of blog posts that will cover how to use Semantic Kernel (SK) with the Model Context Protocol (MCP). This blog post demonstrates how to build an MCP server using MCP C# SDK and SK, expose SK plugins as MCP tools and call the tools from client side via SK. Here are a few reasons wh...

For Semantic Kernel users, integrating xAI's Grok API using the OpenAI connector is a breeze thanks to its compatibility with OpenAI's API format. This tutorial focuses on setting up Grok in your Semantic Kernel projects with minimal fuss, using C# and Python examples. Why Grok? Grok, built by xAI, is a powerful AI model, offers a 128k conte...

Hybrid model orchestration is a powerful technique that AI applications can use to intelligently select and switch between multiple models based on various criteria, all while being transparent to the calling code. This technique not only allows for model selection based on factors such as the prompt's input token size and each model's min/max toke...

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...