Microsoft.SemanticKernel
0.8.40.1-preview
Prefix Reserved
This is a prerelease version of Microsoft.SemanticKernel.
There is a newer version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package Microsoft.SemanticKernel --version 0.8.40.1-preview
NuGet\Install-Package Microsoft.SemanticKernel -Version 0.8.40.1-preview
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Microsoft.SemanticKernel" Version="0.8.40.1-preview" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.SemanticKernel" Version="0.8.40.1-preview" />
<PackageReference Include="Microsoft.SemanticKernel" />
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add Microsoft.SemanticKernel --version 0.8.40.1-preview
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.SemanticKernel, 0.8.40.1-preview"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
#addin nuget:?package=Microsoft.SemanticKernel&version=0.8.40.1-preview&prerelease
#tool nuget:?package=Microsoft.SemanticKernel&version=0.8.40.1-preview&prerelease
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
About Semantic Kernel
Semantic Kernel (SK) is a lightweight SDK enabling integration of AI Large Language Models (LLMs) with conventional programming languages. The SK extensible programming model combines natural language semantic functions, traditional code native functions, and embeddings-based memory unlocking new potential and adding value to applications with AI.
SK supports prompt templating, function chaining, vectorized memory, and intelligent planning capabilities out of the box.
Semantic Kernel is designed to support and encapsulate several design patterns from the latest in AI research, such that developers can infuse their applications with complex skills like prompt chaining, recursive reasoning, summarization, zero/few-shot learning, contextual memory, long-term memory, embeddings, semantic indexing, planning, and accessing external knowledge stores as well as your own data.
A skill refers to a domain of expertise made available to the kernel as a single function, or as a group of functions related to the skill. The design of SK skills has prioritized maximum flexibility for the developer to be both lightweight and extensible.
Getting Started ⚡
- Check out the GitHub repository for the latest updates
- Learn more at the documentation site
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. |
| .NET Core | netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.1 is compatible. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
.NETStandard 2.1
- Microsoft.Extensions.Logging (>= 7.0.0)
- System.Linq.Async (>= 6.0.1)
- System.Text.Json (>= 7.0.2)
NuGet packages (86)
Showing the top 5 NuGet packages that depend on Microsoft.SemanticKernel:
| Package | Downloads |
|---|---|
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FonsecaFramework.Ai
Package Description |
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Soenneker.SemanticKernel.Cache
Providing async thread-safe singleton Semantic Kernel instances |
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AutoGen.SemanticKernel
This package contains the semantic kernel integration for AutoGen |
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Hexalith.Infrastructure.AzureDevOps
Hexalith is a set of libraries to build a micro-service architecture. |
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SemanticKernelPooling
SemanticKernelPooling is a .NET library designed to facilitate seamless integration with multiple AI Semantic Kernel service providers, such as OpenAI, Azure OpenAI, HuggingFace, Google, Mistral AI, and others. It utilizes a kernel pooling approach to manage resources efficiently and provide robust AI capabilities in your .NET applications. |
GitHub repositories (33)
Showing the top 20 popular GitHub repositories that depend on Microsoft.SemanticKernel:
| Repository | Stars |
|---|---|
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microsoft/PowerToys
Windows system utilities to maximize productivity
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dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
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ServiceStack/ServiceStack
Thoughtfully architected, obscenely fast, thoroughly enjoyable web services for all
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SciSharp/LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
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SciSharp/BotSharp
AI Multi-Agent Framework in .NET
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microsoft/kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
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microsoft/WhatTheHack
A collection of challenge based hack-a-thons including student guide, coach guide, lecture presentations, sample/instructional code and templates. Please visit the What The Hack website at: https://aka.ms/wth
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microsoft/Generative-AI-for-beginners-dotnet
Five lessons, learn how to really apply AI to your .NET Applications
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Azure-Samples/azure-search-openai-demo-csharp
A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
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dotnet/ai-samples
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microsoft/node-api-dotnet
Advanced interoperability between .NET and JavaScript in the same process.
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Richasy/FantasyCopilot
A new-age AI desktop tool
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microsoft/semantic-kernel-starters
Starter Projects for Semantic Kernel
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axzxs2001/Asp.NetCoreExperiment
原来所有项目都移动到**OleVersion**目录下进行保留。新的案例装以.net 5.0为主，一部分对以前案例进行升级，一部分将以前的工作经验总结出来，以供大家参考！
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CervantesSec/cervantes
Cervantes is an open-source, collaborative platform designed specifically for pentesters and red teams. It serves as a comprehensive management tool, streamlining the organization of projects, clients, vulnerabilities, and reports in a single, centralized location.
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syncfusion/wpf-demos
This repository contains the samples for Syncfusion WPF UI Controls and File Format libraries and the guide to use them.
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239573049/ChatGpt.Desktop
ChatGpt Dekstop support Android，IOS，Mac，Linux，Win，Web
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microsoft/project-oagents
Experimental AI Agents Framework
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Azure-Samples/cosmosdb-chatgpt
Sample application that combines Azure Cosmos DB with Azure OpenAI ChatGPT service
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AIDotNet/GraphRag.Net
参考GraphRag使用 Semantic Kernel 来实现的dotnet版本，可以使用NuGet开箱即用集成到项目中
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| Version | Downloads | Last updated |
|---|---|---|
| 1.45.0 | 6,671 | 4/3/2025 |
| 1.44.0 | 12,774 | 3/26/2025 |
| 1.43.0 | 4,882 | 3/25/2025 |
| 1.42.0 | 12,783 | 3/18/2025 |
| 1.41.0 | 15,153 | 3/11/2025 |
| 1.40.1 | 27,335 | 3/3/2025 |
| 1.40.0 | 9,668 | 2/28/2025 |
| 1.39.0 | 14,728 | 2/25/2025 |
| 1.38.0 | 23,514 | 2/20/2025 |
| 1.37.0 | 26,899 | 2/12/2025 |
| 1.36.1 | 13,794 | 2/7/2025 |
| 1.36.0 | 12,834 | 2/4/2025 |
| 1.35.0 | 41,685 | 1/28/2025 |
| 1.34.0 | 30,120 | 1/22/2025 |
| 1.33.0 | 83,436 | 1/7/2025 |
| 1.32.0 | 88,413 | 12/9/2024 |
| 1.31.0 | 45,860 | 11/27/2024 |
| 1.30.0 | 50,520 | 11/19/2024 |
| 1.29.0 | 76,984 | 11/13/2024 |
| 1.28.0 | 26,645 | 11/7/2024 |
| 1.27.0 | 12,656 | 11/5/2024 |
| 1.26.0 | 26,845 | 10/31/2024 |
| 1.25.0 | 79,352 | 10/23/2024 |
| 1.24.1 | 17,342 | 10/18/2024 |
| 1.23.0 | 4,725 | 10/17/2024 |
| 1.22.0 | 54,860 | 10/8/2024 |
| 1.21.1 | 68,887 | 9/25/2024 |
| 1.21.0 | 1,758 | 9/25/2024 |
| 1.20.0 | 40,768 | 9/17/2024 |
| 1.19.0 | 20,884 | 9/10/2024 |
| 1.18.2 | 34,033 | 9/4/2024 |
| 1.18.1-rc | 19,183 | 8/27/2024 |
| 1.18.0-rc | 5,374 | 8/12/2024 |
| 1.17.2 | 125,777 | 8/21/2024 |
| 1.17.1 | 87,433 | 8/7/2024 |
| 1.17.0 | 6,657 | 8/7/2024 |
| 1.16.2 | 33,943 | 7/30/2024 |
| 1.16.1 | 33,147 | 7/23/2024 |
| 1.16.0 | 32,938 | 7/16/2024 |
| 1.15.1 | 80,236 | 7/3/2024 |
| 1.15.0 | 80,506 | 6/19/2024 |
| 1.14.1 | 68,737 | 6/5/2024 |
| 1.14.0 | 6,121 | 6/4/2024 |
| 1.13.0 | 84,353 | 5/20/2024 |
| 1.12.0 | 14,989 | 5/16/2024 |
| 1.11.1 | 25,921 | 5/10/2024 |
| 1.11.0 | 4,551 | 5/8/2024 |
| 1.10.0 | 51,701 | 4/29/2024 |
| 1.9.0 | 40,417 | 4/24/2024 |
| 1.8.0 | 12,168 | 4/22/2024 |
| 1.7.1 | 55,173 | 4/5/2024 |
| 1.7.0 | 16,018 | 4/3/2024 |
| 1.6.3 | 64,422 | 3/19/2024 |
| 1.6.2 | 24,683 | 3/14/2024 |
| 1.6.1 | 6,191 | 3/12/2024 |
| 1.5.0 | 46,978 | 2/27/2024 |
| 1.4.0 | 81,645 | 2/14/2024 |
| 1.3.1 | 16,084 | 2/12/2024 |
| 1.3.0 | 68,744 | 1/31/2024 |
| 1.2.0 | 27,191 | 1/24/2024 |
| 1.1.0 | 66,486 | 1/16/2024 |
| 1.0.1 | 85,676 | 12/18/2023 |
| 1.0.0-rc4 | 4,840 | 12/13/2023 |
| 1.0.0-rc3 | 11,053 | 12/6/2023 |
| 1.0.0-rc2 | 1,111 | 12/5/2023 |
| 1.0.0-rc1 | 3,010 | 12/5/2023 |
| 1.0.0-beta8 | 108,109 | 11/16/2023 |
| 1.0.0-beta7 | 10,356 | 11/16/2023 |
| 1.0.0-beta6 | 16,281 | 11/9/2023 |
| 1.0.0-beta5 | 10,325 | 11/6/2023 |
| 1.0.0-beta4 | 13,063 | 10/30/2023 |
| 1.0.0-beta3 | 15,974 | 10/23/2023 |
| 1.0.0-beta2 | 15,614 | 10/16/2023 |
| 1.0.0-beta1 | 17,680 | 10/9/2023 |
| 0.24.230918.1-preview | 141,734 | 9/18/2023 |
| 0.24.230912.2-preview | 11,359 | 9/12/2023 |
| 0.24.230911.2-preview | 1,284 | 9/11/2023 |
| 0.23.230906.2-preview | 52,390 | 9/7/2023 |
| 0.22.230905.3-preview | 4,944 | 9/5/2023 |
| 0.21.230828.2-preview | 23,345 | 8/28/2023 |
| 0.20.230821.4-preview | 11,524 | 8/21/2023 |
| 0.19.230804.2-preview | 106,503 | 8/5/2023 |
| 0.18.230725.3-preview | 57,420 | 7/25/2023 |
| 0.17.230718.1-preview | 43,793 | 7/18/2023 |
| 0.17.230711.7-preview | 79,831 | 7/11/2023 |
| 0.17.230704.3-preview | 42,106 | 7/4/2023 |
| 0.17.230629.1-preview | 8,629 | 6/29/2023 |
| 0.17.230626.1-preview | 3,163 | 6/26/2023 |
| 0.16.230615.1-preview | 24,144 | 6/16/2023 |
| 0.15.231219.1-preview | 490 | 12/19/2023 |
| 0.15.230609.2-preview | 7,025 | 6/9/2023 |
| 0.15.230531.5-preview | 22,573 | 6/1/2023 |
| 0.14.547.1-preview | 20,929 | 5/16/2023 |
| 0.13.442.1-preview | 19,877 | 5/9/2023 |
| 0.13.277.1-preview | 15,981 | 4/25/2023 |
| 0.12.207.1-preview | 3,059 | 4/19/2023 |
| 0.11.146.1-preview | 3,780 | 4/12/2023 |
| 0.10.72.1-preview | 3,996 | 4/4/2023 |
| 0.9.61.1-preview | 2,721 | 3/28/2023 |
| 0.8.56.1-preview | 1,263 | 3/27/2023 |
| 0.8.48.1-preview | 14,108 | 3/18/2023 |
| 0.8.40.1-preview | 690 | 3/14/2023 |
| 0.8.11.1-preview | 830 | 3/1/2023 |