Showing results for Category: Semantic Kernel from Semantic Kernel

Azure OpenAI Chat Completion with data source provides powerful capabilities for integrating conversational AI into applications. However, using a data source and function calling in a single request is not supported yet. When both features are enabled, function calling is ignored, and only the data source is used. This presents a challenge when re...

As we move into the first half of 2025, I'm excited to share our ambitious roadmap that we hope will enable you to build even more sophisticated AI applications with Semantic Kernel. Agent Framework 1.0 By the end of Q1 2025, the SK Agent Framework will transition from preview to general availability (GA). This milestone marks a commitmen...

DeepSeek recently awed the AI community by open sourcing two new state-of-the-art models, the DeepSeek-V3 and a reasoning model, the DeepSeek-R1, that not only claim to be op-par with the most capable models from OpenAI but are also extremely cost-effective. We'd like to highlight the recent announcement from the Azure AI Foundry team highlighting ...

AI Connectors in Semantic Kernel are components that facilitate communication between the Kernel's core functionalities and various AI services. They abstract the intricate details of service-specific protocols, allowing developers to seamlessly interact with AI services for tasks like text generation, chat interactions, and more.   ...

Windows PowerToys has always been one of my favorite productivity hacks, and its latest release adds Paste with Advanced AI, which takes it to a new level. This feature, powered by Semantic Kernel, transforms how you work with text, images, and data from your clipboard by applying AI-driven enhancements. What Does It Do? Advanced Paste us...

ONNX GenAI Connector for Python (Experimental)  With the latest update we added support for running models locally with the onnxruntime-genai. The onnxruntime-genai package is powered by the ONNX Runtime in the background, but first let’s clarify what ONNX, ONNX Runtime and ONNX Runtime-GenAI are.  ONNX ONNX is an open-source format for AI model...

How to use Elasticsearch Vector Store Connector for Microsoft Semantic Kernel for AI Agent development Today we're excited to feature the Elastic team to share more about their Semantic Kernel Elasticsearch Vector Store connector for Microsoft Semantic Kernel. Read the entire announcement here. I'll turn it over to Srikanth Manvi and Florian Bernd...

We previously introduced observability within the Semantic Kernel. For further insights, please refer to our previous blog post, and you can also explore our learn site for additional details. To summarize, observability is an essential aspect of your application stack, particularly in today's landscape where AI plays a significant role in numer...

Semantic Kernel (SK) 是由微软开发的一款开源开发工具包，旨在帮助开发者和企业利用最新的人工智能技术构建更智能和复杂的AI驱动解决方案，例如检索增强生成 (RAG) 和智能体 (Agent)。 核心概念 内核（Kernel） 您可以将SK的内核视为一个容器，该容器包含您所需的所有与AI相关的组件，如提示语模板、AI服务和插件。如果将所有的服务和插件提供给内核，则AI会根据需求自动使用它们。SK还提供多项企业级功能，使您可以保证您的AI符合安全要求且在部署后能够持续监控AI的表现。 提示语（Prompt Engineering） 提示语在使用大型语言模型中至关重要。优质的提示语能够显著提升用户体验。SK通过提示语模板（template）的方式来实现自然语言与...

Microsoft Semantic Kernel Office Hours Update Over the upcoming Holidays period there are several office hours sessions that we'll be cancelling. Below is an updated view of our upcoming office hours availability. We will resume with regularly scheduled Office Hours on January 8th for our weekly and monthly sessions. During this time, feel free...