Microsoft.SemanticKernel.Core
1.11.1
Prefix Reserved
There is a newer version of this package available.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.Core --version 1.11.1
NuGet\Install-Package Microsoft.SemanticKernel.Core -Version 1.11.1
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.Core" Version="1.11.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.SemanticKernel.Core" Version="1.11.1" />
<PackageReference Include="Microsoft.SemanticKernel.Core" />
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.Core --version 1.11.1
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.SemanticKernel.Core, 1.11.1"
#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.Core&version=1.11.1
#tool nuget:?package=Microsoft.SemanticKernel.Core&version=1.11.1
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.
Semantic Kernel incorporates cutting-edge design patterns from the latest in AI research. This enables developers to augment their applications with advanced capabilities, such as prompt engineering, prompt chaining, retrieval-augmented generation, contextual and long-term vectorized memory, embeddings, summarization, zero or few-shot learning, semantic indexing, recursive reasoning, intelligent planning, and access to external knowledge stores and proprietary data.
Getting Started ⚡
- Learn more at the documentation site.
- Join the Discord community.
- Follow the team on Semantic Kernel blog.
- Check out the GitHub repository for the latest updates.
| 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 | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
| .NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | tizen40 was computed. 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 2.0
- Microsoft.Extensions.DependencyInjection (>= 8.0.0)
- Microsoft.SemanticKernel.Abstractions (>= 1.11.1)
NuGet packages (95)
Showing the top 5 NuGet packages that depend on Microsoft.SemanticKernel.Core:
| Package | Downloads |
|---|---|
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Microsoft.SemanticKernel.Connectors.OpenAI
Semantic Kernel connectors for OpenAI. Contains clients for chat completion, embedding and DALL-E text to image. |
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Microsoft.SemanticKernel
Semantic Kernel common package collection, including SK Core, OpenAI, Azure OpenAI, DALL-E 2. Empowers app owners to integrate cutting-edge LLM technology quickly and easily into their apps. |
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Microsoft.SemanticKernel.Connectors.AzureOpenAI
Semantic Kernel connectors for Azure OpenAI. Contains clients for chat completion, embedding and DALL-E text to image. |
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Microsoft.SemanticKernel.PromptTemplates.Handlebars
Semantic Kernel Handlebars Prompt Template Engine |
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Microsoft.SemanticKernel.Plugins.Core
Semantic Kernel core plugins. |
GitHub repositories (7)
Showing the top 7 popular GitHub repositories that depend on Microsoft.SemanticKernel.Core:
| Repository | Stars |
|---|---|
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microsoft/ai-dev-gallery
An open-source project for Windows developers to learn how to add AI with local models and APIs to Windows apps.
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dotnet/ai-samples
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fagenorn/handcrafted-persona-engine
An AI-powered interactive avatar engine using Live2D, LLM, ASR, TTS, and RVC. Ideal for VTubing, streaming, and virtual assistant applications.
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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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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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SteveSandersonMS/dotnet-ai-workshop
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kbeaugrand/SemanticKernel.Assistants
Microsoft Semantic Kernel Assistants This enables the usage of assistants for the Semantic Kernel. It provides different scenarios for the usage of assistants such as: Assistant with Semantic Kernel plugins Multi-Assistant conversation
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| Version | Downloads | Last updated |
|---|---|---|
| 1.47.0 | 13,797 | 4/17/2025 |
| 1.46.0 | 22,613 | 4/11/2025 |
| 1.45.0 | 39,207 | 4/3/2025 |
| 1.44.0 | 36,006 | 3/26/2025 |
| 1.43.0 | 16,517 | 3/25/2025 |
| 1.42.0 | 29,011 | 3/18/2025 |
| 1.41.0 | 32,784 | 3/11/2025 |
| 1.40.1 | 47,483 | 3/3/2025 |
| 1.40.0 | 24,147 | 2/28/2025 |
| 1.39.0 | 22,984 | 2/25/2025 |
| 1.38.0 | 33,114 | 2/20/2025 |
| 1.37.0 | 56,808 | 2/12/2025 |
| 1.36.1 | 40,952 | 2/7/2025 |
| 1.36.0 | 24,021 | 2/4/2025 |
| 1.35.0 | 54,740 | 1/28/2025 |
| 1.34.0 | 43,517 | 1/22/2025 |
| 1.33.0 | 135,509 | 1/7/2025 |
| 1.32.0 | 140,110 | 12/9/2024 |
| 1.31.0 | 60,097 | 11/27/2024 |
| 1.30.0 | 73,122 | 11/19/2024 |
| 1.29.0 | 123,789 | 11/13/2024 |
| 1.28.0 | 36,506 | 11/7/2024 |
| 1.27.0 | 16,132 | 11/5/2024 |
| 1.26.0 | 86,956 | 10/31/2024 |
| 1.25.0 | 96,600 | 10/23/2024 |
| 1.24.1 | 63,684 | 10/18/2024 |
| 1.23.0 | 6,973 | 10/17/2024 |
| 1.22.0 | 81,191 | 10/8/2024 |
| 1.21.1 | 111,289 | 9/25/2024 |
| 1.21.0 | 2,241 | 9/25/2024 |
| 1.20.0 | 74,794 | 9/17/2024 |
| 1.19.0 | 26,976 | 9/10/2024 |
| 1.18.2 | 78,531 | 9/4/2024 |
| 1.18.1-rc | 30,394 | 8/27/2024 |
| 1.18.0-rc | 24,361 | 8/12/2024 |
| 1.17.2 | 160,760 | 8/21/2024 |
| 1.17.1 | 111,443 | 8/7/2024 |
| 1.17.0 | 13,901 | 8/7/2024 |
| 1.16.2 | 48,637 | 7/30/2024 |
| 1.16.1 | 42,161 | 7/23/2024 |
| 1.16.0 | 45,802 | 7/16/2024 |
| 1.15.1 | 128,283 | 7/3/2024 |
| 1.15.0 | 94,250 | 6/19/2024 |
| 1.14.1 | 118,130 | 6/5/2024 |
| 1.14.0 | 35,761 | 6/4/2024 |
| 1.13.0 | 104,798 | 5/20/2024 |
| 1.12.0 | 18,815 | 5/16/2024 |
| 1.11.1 | 102,542 | 5/10/2024 |
| 1.11.0 | 5,940 | 5/8/2024 |
| 1.10.0 | 104,715 | 4/29/2024 |
| 1.9.0 | 60,883 | 4/24/2024 |
| 1.8.0 | 22,044 | 4/22/2024 |
| 1.7.1 | 79,392 | 4/5/2024 |
| 1.7.0 | 45,759 | 4/3/2024 |
| 1.6.3 | 109,395 | 3/19/2024 |
| 1.6.2 | 101,516 | 3/14/2024 |
| 1.6.1 | 16,754 | 3/12/2024 |
| 1.5.0 | 89,353 | 2/27/2024 |
| 1.4.0 | 130,567 | 2/14/2024 |
| 1.3.1 | 25,347 | 2/12/2024 |
| 1.3.0 | 97,893 | 1/31/2024 |
| 1.2.0 | 35,128 | 1/24/2024 |
| 1.1.0 | 105,780 | 1/16/2024 |
| 1.0.1 | 115,690 | 12/18/2023 |
| 1.0.0-rc4 | 9,898 | 12/13/2023 |
| 1.0.0-rc3 | 22,720 | 12/6/2023 |
| 1.0.0-rc2 | 4,425 | 12/5/2023 |
| 1.0.0-rc1 | 4,688 | 12/5/2023 |
| 1.0.0-beta8 | 133,818 | 11/16/2023 |
| 1.0.0-beta7 | 24,886 | 11/16/2023 |
| 1.0.0-beta6 | 20,717 | 11/9/2023 |
| 1.0.0-beta5 | 11,910 | 11/6/2023 |
| 1.0.0-beta4 | 22,361 | 10/30/2023 |
| 1.0.0-beta3 | 18,876 | 10/23/2023 |
| 1.0.0-beta2 | 17,750 | 10/16/2023 |
| 1.0.0-beta1 | 19,223 | 10/9/2023 |
| 0.24.230918.1-preview | 115,593 | 9/18/2023 |
| 0.24.230912.2-preview | 12,454 | 9/12/2023 |
| 0.24.230911.2-preview | 1,443 | 9/11/2023 |
| 0.23.230906.2-preview | 10,113 | 9/7/2023 |
| 0.22.230905.3-preview | 5,403 | 9/5/2023 |
| 0.21.230828.2-preview | 24,484 | 8/28/2023 |
| 0.20.230821.4-preview | 13,042 | 8/21/2023 |
| 0.19.230804.2-preview | 108,008 | 8/5/2023 |
| 0.18.230725.3-preview | 61,155 | 7/25/2023 |
| 0.17.230718.1-preview | 78,982 | 7/18/2023 |
| 0.17.230711.7-preview | 84,842 | 7/11/2023 |
| 0.17.230704.3-preview | 43,200 | 7/4/2023 |
| 0.17.230629.1-preview | 8,673 | 6/29/2023 |
| 0.17.230626.1-preview | 3,753 | 6/26/2023 |
| 0.16.230615.1-preview | 24,768 | 6/16/2023 |
| 0.15.231219.1-preview | 5,986 | 12/19/2023 |
| 0.15.230609.2-preview | 7,530 | 6/9/2023 |
| 0.15.230531.5-preview | 24,458 | 6/1/2023 |
| 0.14.547.1-preview | 24,169 | 5/16/2023 |
| 0.13.442.1-preview | 40,550 | 5/9/2023 |
| 0.13.277.1-preview | 16,449 | 4/25/2023 |
| 0.12.207.1-preview | 3,474 | 4/19/2023 |