Microsoft.SemanticKernel.Core
1.0.0-beta6
Prefix Reserved
This is a prerelease version of Microsoft.SemanticKernel.Core.
There is a newer version of this package available.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 1.0.0-beta6
NuGet\Install-Package Microsoft.SemanticKernel.Core -Version 1.0.0-beta6
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="1.0.0-beta6" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.SemanticKernel.Core" Version="1.0.0-beta6" />
<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 1.0.0-beta6
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.SemanticKernel.Core, 1.0.0-beta6"
#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.
#:package Microsoft.SemanticKernel.Core@1.0.0-beta6
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package.
#addin nuget:?package=Microsoft.SemanticKernel.Core&version=1.0.0-beta6&prerelease
#tool nuget:?package=Microsoft.SemanticKernel.Core&version=1.0.0-beta6&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.
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. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-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.SemanticKernel.Abstractions (>= 1.0.0-beta6)
- System.Diagnostics.DiagnosticSource (>= 6.0.1)
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.Agents.Core
Defines core set of concrete Agent and AgentChat classes, based on the Agent Abstractions. |
GitHub repositories (11)
Showing the top 11 popular GitHub repositories that depend on Microsoft.SemanticKernel.Core:
| Repository | Stars |
|---|---|
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dotnet/extensions
This repository contains a suite of libraries that provide facilities commonly needed when creating production-ready applications.
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abpframework/abp-samples
Sample solutions built with the ABP Framework
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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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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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dotnet/ai-samples
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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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AIDotNet/Text2Sql.Net
Text2Sql.Net 是一个使用DotNet和Semantic Kernel开发的Text2Sql工具
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Azure/azure-sdk-tools
Tools repository leveraged by the Azure SDK team.
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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 |
|---|---|---|
| 1.67.1 | 0 | 11/7/2025 |
| 1.67.0 | 10,829 | 11/3/2025 |
| 1.66.0 | 142,477 | 10/8/2025 |
| 1.65.0 | 300,020 | 9/10/2025 |
| 1.64.0 | 207,565 | 8/27/2025 |
| 1.63.0 | 94,201 | 8/20/2025 |
| 1.62.0 | 98,215 | 8/12/2025 |
| 1.61.0 | 197,605 | 7/24/2025 |
| 1.60.0 | 188,966 | 7/8/2025 |
| 1.59.0 | 98,566 | 7/1/2025 |
| 1.58.0 | 77,359 | 6/25/2025 |
| 1.57.0 | 178,394 | 6/16/2025 |
| 1.56.0 | 69,786 | 6/10/2025 |
| 1.55.0 | 219,318 | 6/3/2025 |
| 1.54.0 | 169,207 | 5/22/2025 |
| 1.53.1 | 25,127 | 5/21/2025 |
| 1.52.0 | 16,613 | 5/19/2025 |
| 1.51.0 | 85,763 | 5/16/2025 |
| 1.50.0 | 26,978 | 5/14/2025 |
| 1.49.0 | 113,580 | 5/8/2025 |
| 1.48.0 | 107,004 | 4/29/2025 |
| 1.47.0 | 180,112 | 4/17/2025 |
| 1.46.0 | 119,220 | 4/11/2025 |
| 1.45.0 | 266,184 | 4/3/2025 |
| 1.44.0 | 109,711 | 3/26/2025 |
| 1.43.0 | 28,999 | 3/25/2025 |
| 1.42.0 | 117,884 | 3/18/2025 |
| 1.41.0 | 69,173 | 3/11/2025 |
| 1.40.1 | 82,771 | 3/3/2025 |
| 1.40.0 | 60,059 | 2/28/2025 |
| 1.39.0 | 48,184 | 2/25/2025 |
| 1.38.0 | 81,786 | 2/20/2025 |
| 1.37.0 | 104,377 | 2/12/2025 |
| 1.36.1 | 83,383 | 2/7/2025 |
| 1.36.0 | 53,228 | 2/4/2025 |
| 1.35.0 | 119,405 | 1/28/2025 |
| 1.34.0 | 88,858 | 1/22/2025 |
| 1.33.0 | 232,403 | 1/7/2025 |
| 1.32.0 | 205,993 | 12/9/2024 |
| 1.31.0 | 108,350 | 11/27/2024 |
| 1.30.0 | 99,642 | 11/19/2024 |
| 1.29.0 | 136,208 | 11/13/2024 |
| 1.28.0 | 52,311 | 11/7/2024 |
| 1.27.0 | 21,725 | 11/5/2024 |
| 1.26.0 | 121,318 | 10/31/2024 |
| 1.25.0 | 134,600 | 10/23/2024 |
| 1.24.1 | 92,131 | 10/18/2024 |
| 1.23.0 | 10,106 | 10/17/2024 |
| 1.22.0 | 100,315 | 10/8/2024 |
| 1.21.1 | 127,714 | 9/25/2024 |
| 1.21.0 | 3,957 | 9/25/2024 |
| 1.20.0 | 137,480 | 9/17/2024 |
| 1.19.0 | 33,141 | 9/10/2024 |
| 1.18.2 | 113,180 | 9/4/2024 |
| 1.18.1-rc | 45,640 | 8/27/2024 |
| 1.18.0-rc | 31,924 | 8/12/2024 |
| 1.17.2 | 197,115 | 8/21/2024 |
| 1.17.1 | 125,663 | 8/7/2024 |
| 1.17.0 | 14,759 | 8/7/2024 |
| 1.16.2 | 61,974 | 7/30/2024 |
| 1.16.1 | 47,596 | 7/23/2024 |
| 1.16.0 | 63,176 | 7/16/2024 |
| 1.15.1 | 160,835 | 7/3/2024 |
| 1.15.0 | 109,495 | 6/19/2024 |
| 1.14.1 | 127,729 | 6/5/2024 |
| 1.14.0 | 39,085 | 6/4/2024 |
| 1.13.0 | 117,180 | 5/20/2024 |
| 1.12.0 | 23,393 | 5/16/2024 |
| 1.11.1 | 112,550 | 5/10/2024 |
| 1.11.0 | 7,008 | 5/8/2024 |
| 1.10.0 | 122,760 | 4/29/2024 |
| 1.9.0 | 83,563 | 4/24/2024 |
| 1.8.0 | 29,425 | 4/22/2024 |
| 1.7.1 | 88,238 | 4/5/2024 |
| 1.7.0 | 50,895 | 4/3/2024 |
| 1.6.3 | 173,942 | 3/19/2024 |
| 1.6.2 | 117,400 | 3/14/2024 |
| 1.6.1 | 19,936 | 3/12/2024 |
| 1.5.0 | 100,853 | 2/27/2024 |
| 1.4.0 | 147,856 | 2/14/2024 |
| 1.3.1 | 33,160 | 2/12/2024 |
| 1.3.0 | 114,842 | 1/31/2024 |
| 1.2.0 | 37,847 | 1/24/2024 |
| 1.1.0 | 111,265 | 1/16/2024 |
| 1.0.1 | 157,299 | 12/18/2023 |
| 1.0.0-rc4 | 11,424 | 12/13/2023 |
| 1.0.0-rc3 | 27,616 | 12/6/2023 |
| 1.0.0-rc2 | 5,406 | 12/5/2023 |
| 1.0.0-rc1 | 5,586 | 12/5/2023 |
| 1.0.0-beta8 | 143,946 | 11/16/2023 |
| 1.0.0-beta7 | 31,255 | 11/16/2023 |
| 1.0.0-beta6 | 23,542 | 11/9/2023 |
| 1.0.0-beta5 | 16,596 | 11/6/2023 |
| 1.0.0-beta4 | 23,000 | 10/30/2023 |
| 1.0.0-beta3 | 21,574 | 10/23/2023 |
| 1.0.0-beta2 | 18,334 | 10/16/2023 |
| 1.0.0-beta1 | 19,749 | 10/9/2023 |
| 0.24.230918.1-preview | 149,390 | 9/18/2023 |
| 0.24.230912.2-preview | 13,275 | 9/12/2023 |
| 0.24.230911.2-preview | 1,532 | 9/11/2023 |
| 0.23.230906.2-preview | 10,326 | 9/7/2023 |
| 0.22.230905.3-preview | 6,101 | 9/5/2023 |
| 0.21.230828.2-preview | 28,447 | 8/28/2023 |
| 0.20.230821.4-preview | 14,602 | 8/21/2023 |
| 0.19.230804.2-preview | 111,670 | 8/5/2023 |
| 0.18.230725.3-preview | 63,453 | 7/25/2023 |
| 0.17.230718.1-preview | 99,777 | 7/18/2023 |
| 0.17.230711.7-preview | 85,730 | 7/11/2023 |
| 0.17.230704.3-preview | 43,838 | 7/4/2023 |
| 0.17.230629.1-preview | 8,847 | 6/29/2023 |
| 0.17.230626.1-preview | 5,339 | 6/26/2023 |
| 0.16.230615.1-preview | 27,016 | 6/16/2023 |
| 0.15.231219.1-preview | 7,186 | 12/19/2023 |
| 0.15.230609.2-preview | 8,322 | 6/9/2023 |
| 0.15.230531.5-preview | 25,693 | 6/1/2023 |
| 0.14.547.1-preview | 25,494 | 5/16/2023 |
| 0.13.442.1-preview | 43,832 | 5/9/2023 |
| 0.13.277.1-preview | 19,358 | 4/25/2023 |
| 0.12.207.1-preview | 3,646 | 4/19/2023 |