Microsoft.SemanticKernel 0.13.277.1-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There is a newer version of this package available.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.
dotnet add package Microsoft.SemanticKernel --version 0.13.277.1-preview                
NuGet\Install-Package Microsoft.SemanticKernel -Version 0.13.277.1-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="0.13.277.1-preview" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Microsoft.SemanticKernel --version 0.13.277.1-preview                
#r "nuget: Microsoft.SemanticKernel, 0.13.277.1-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.
// Install Microsoft.SemanticKernel as a Cake Addin
#addin nuget:?package=Microsoft.SemanticKernel&version=0.13.277.1-preview&prerelease

// Install Microsoft.SemanticKernel as a Cake Tool
#tool nuget:?package=Microsoft.SemanticKernel&version=0.13.277.1-preview&prerelease                

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 ⚡

Product 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. 
.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.

NuGet packages (65)

Showing the top 5 NuGet packages that depend on Microsoft.SemanticKernel:

Package Downloads
FonsecaFramework.Ai

Package Description

Hexalith.Infrastructure.AzureDevOps

Hexalith is a set of libraries to build a micro-service architecture.

Senparc.AI.Kernel

Senparc.AI 核心模块,支持 Semantic Kernel,提供一系列 Senparc.AI 产品基础接口实现

AutoGen.SemanticKernel

This package contains the semantic kernel integration for AutoGen

HexaEightGPTMiddleware

Control An AI Assistant like CHATGPT using this Library. Integrate This Library With HexaEight Middleware to create API that produce controlled AI responses

GitHub repositories (30)

Showing the top 5 popular GitHub repositories that depend on Microsoft.SemanticKernel:

Repository Stars
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
elsa-workflows/elsa-core
A .NET workflows library
ServiceStack/ServiceStack
Thoughtfully architected, obscenely fast, thoroughly enjoyable web services for all
SciSharp/LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
SciSharp/BotSharp
AI Multi-Agent Framework in .NET
Version Downloads Last updated
1.31.0 1,476 11/27/2024
1.30.0 8,391 11/19/2024
1.29.0 15,008 11/13/2024
1.28.0 10,859 11/7/2024
1.27.0 6,458 11/5/2024
1.26.0 11,101 10/31/2024
1.25.0 29,421 10/23/2024
1.24.1 9,283 10/18/2024
1.23.0 2,736 10/17/2024
1.22.0 24,947 10/8/2024
1.21.1 35,576 9/25/2024
1.21.0 924 9/25/2024
1.20.0 19,595 9/17/2024
1.19.0 14,557 9/10/2024
1.18.2 29,274 9/4/2024
1.18.1-rc 8,489 8/27/2024
1.18.0-rc 4,234 8/12/2024
1.17.2 75,477 8/21/2024
1.17.1 67,114 8/7/2024
1.17.0 5,206 8/7/2024
1.16.2 24,571 7/30/2024
1.16.1 27,662 7/23/2024
1.16.0 24,498 7/16/2024
1.15.1 62,874 7/3/2024
1.15.0 67,199 6/19/2024
1.14.1 59,327 6/5/2024
1.14.0 5,169 6/4/2024
1.13.0 72,185 5/20/2024
1.12.0 13,835 5/16/2024
1.11.1 19,822 5/10/2024
1.11.0 3,987 5/8/2024
1.10.0 41,610 4/29/2024
1.9.0 28,156 4/24/2024
1.8.0 9,999 4/22/2024
1.7.1 49,440 4/5/2024
1.7.0 11,651 4/3/2024
1.6.3 49,135 3/19/2024
1.6.2 19,461 3/14/2024
1.6.1 5,897 3/12/2024
1.5.0 41,444 2/27/2024
1.4.0 69,716 2/14/2024
1.3.1 12,540 2/12/2024
1.3.0 57,954 1/31/2024
1.2.0 23,376 1/24/2024
1.1.0 65,590 1/16/2024
1.0.1 71,370 12/18/2023
1.0.0-rc4 4,731 12/13/2023
1.0.0-rc3 10,736 12/6/2023
1.0.0-rc2 1,091 12/5/2023
1.0.0-rc1 2,952 12/5/2023
1.0.0-beta8 100,196 11/16/2023
1.0.0-beta7 7,187 11/16/2023
1.0.0-beta6 15,682 11/9/2023
1.0.0-beta5 9,076 11/6/2023
1.0.0-beta4 12,409 10/30/2023
1.0.0-beta3 15,221 10/23/2023
1.0.0-beta2 13,445 10/16/2023
1.0.0-beta1 17,453 10/9/2023
0.24.230918.1-preview 116,159 9/18/2023
0.24.230912.2-preview 10,874 9/12/2023
0.24.230911.2-preview 1,171 9/11/2023
0.23.230906.2-preview 52,120 9/7/2023
0.22.230905.3-preview 4,828 9/5/2023
0.21.230828.2-preview 20,745 8/28/2023
0.20.230821.4-preview 11,459 8/21/2023
0.19.230804.2-preview 104,964 8/5/2023
0.18.230725.3-preview 54,760 7/25/2023
0.17.230718.1-preview 37,148 7/18/2023
0.17.230711.7-preview 79,640 7/11/2023
0.17.230704.3-preview 41,872 7/4/2023
0.17.230629.1-preview 8,416 6/29/2023
0.17.230626.1-preview 3,083 6/26/2023
0.16.230615.1-preview 23,443 6/16/2023
0.15.231219.1-preview 469 12/19/2023
0.15.230609.2-preview 6,859 6/9/2023
0.15.230531.5-preview 21,721 6/1/2023
0.14.547.1-preview 20,490 5/16/2023
0.13.442.1-preview 19,722 5/9/2023
0.13.277.1-preview 14,746 4/25/2023
0.12.207.1-preview 3,035 4/19/2023
0.11.146.1-preview 3,651 4/12/2023
0.10.72.1-preview 3,629 4/4/2023
0.9.61.1-preview 2,682 3/28/2023
0.8.56.1-preview 1,246 3/27/2023
0.8.48.1-preview 14,063 3/18/2023
0.8.40.1-preview 670 3/14/2023
0.8.11.1-preview 812 3/1/2023