Showing results for Category: Announcement from Semantic Kernel

Introducing new Ollama Connector for Local Models  As a long-awaited feature we are happy to bring a dedicated Ollama Connector. In the core implementation of this connector, we are also using the Ollama Sharp library which allows you to manipulate some native Ollama APIs as well as using it with our connector for breaking glass scenarios (...

Update: We have released a new NuGet Gallery | Microsoft.SemanticKernel 1.18.1-rc release candidate which has been updated to depend on NuGet Gallery | OpenAI 2.0.0-beta.10 and NuGet Gallery | Azure.AI.OpenAI 2.0.0-beta.3. Today we are announcing that support for Azure.AI.OpenAI and OpenAI v2 .NET SDK is available in the Semantic Kernel v1.18.0-...

Hello Java AI developers! We are announcing the release of Semantic Kernel for Java v1.2.0! Since our release of v1.0 this past May, we have been working to improve and expand the capabilities we provide. Today, we are thrilled to share the latest updates, new features, and experimental features with you. What’s New in Semantic Kernel for ...

Hello, everyone! AI planning is a powerful tool that allows to generate and execute complex workflows in applications based on specified goal. In Semantic Kernel, it's possible to implement planning logic using FunctionCallingStepwisePlanner class. Today we want to introduce a new way how to achieve the same results by using Automatic Function ...

Since the very earlier days of Semantic Kernel, we have shipped experimental “planners” that use prompts to generate multi-step plans. This was extremely powerful because it allowed developers to use LLMs (which were created to merely generate text) to begin automating business processes. Since then, the Semantic Kernel team has evolved its ...

Hello! We are delighted to make an announcement regarding the availability of Azure AI Inference within Semantic Kernel (Python). This latest AI connector empowers you to experiment with a broader range of models hosted on Azure within your applications.   The Sample Application: Evaluating LLMs Here is the location of the full sample...

  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 ...

Today we're excited to announce the updated documentation on the Semantic Kernel learn site here: Introduction to Semantic Kernel | Microsoft Learn. We've updated the docs to include in depth samples, updated pages focused on concepts and much more for your learning! Key Enhancements: We've updated the table of contents and layout of the ...

Last year we published the initial release of Semantic Kernel for Java. It has been nearly a year of work building and shaping this SDK to help developers quickly and idiomatically build intelligent Java apps with OpenAI. Throughout this time, all teams behind Semantic Kernel SDKs (for Python, Java, and .NET) have done significant research in terms...

At the heart of every company are custom APIs that are built to solve specific business problems. These APIs often use Logic Apps, which is a powerful way to build APIs without writing code. With Logic Apps' over 1,400 enterprise connectors, you can connect to your enterprise systems, transform data, and automate processes to solve your business ...