Showing results for Category: Samples from Semantic Kernel

This is Part 2 of our series on integrating Microsoft.Extensions.AI with Semantic Kernel. In Part 1, we explored the relationship between these technologies and how they complement each other. Now, let's dive into practical examples showing how to use Microsoft.Extensions.AI abstractions with Semantic Kernel in non-agent scenarios. Getting Start...

This is the start of a series highlighting the integration between Microsoft Semantic Kernel and Microsoft.Extensions.AI. Future parts will provide detailed examples of using Semantic Kernel with Microsoft.Extensions.AI abstractions.  The most common questions are:  This blog post will address these questions and offer guidance ...

As Semantic Kernel shifts its foundational abstractions to Microsoft.Extensions.AI, we are obsoleting and moving away from our experimental embeddings interfaces to the new standardized abstractions that provide a more consistent and powerful way to work with AI services across the .NET ecosystem. The Evolution of Embedding Generation in Seman...

Google's Agent-to-Agent (A2A) protocol is designed to enable seamless interoperability among diverse AI agents. Microsoft’s Semantic Kernel (SK), an open-source platform for orchestrating intelligent agent interactions, is now being integrated into the A2A ecosystem. In this blog, we demonstrate how Semantic Kernel agents can easily function as an ...

We are excited to announce that Semantic Kernel (SK) now has first-class support for the Model Context Protocol (MCP) — a standard created by Anthropic to enable models, tools, and agents to share context and capabilities seamlessly. With this release, SK can act as both an MCP host (client) and an MCP server, and you can leverage these capabili...

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...

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...

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...

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...