Microsoft.SemanticKernel.Abstractions 0.12.207.1-preview

Prefix Reserved
.NET Standard 2.0 This package targets .NET Standard 2.0. The package is compatible with this framework or higher.
This is a prerelease version of Microsoft.SemanticKernel.Abstractions.
There is a newer version of this package available.
See the version list below for details. 
dotnet add package Microsoft.SemanticKernel.Abstractions --version 0.12.207.1-preview                

                    
                

            
NuGet\Install-Package Microsoft.SemanticKernel.Abstractions -Version 0.12.207.1-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.Abstractions" Version="0.12.207.1-preview" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.SemanticKernel.Abstractions --version 0.12.207.1-preview                

                    
                

            
#r "nuget: Microsoft.SemanticKernel.Abstractions, 0.12.207.1-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.Abstractions as a Cake Addin
#addin nuget:?package=Microsoft.SemanticKernel.Abstractions&version=0.12.207.1-preview&prerelease

// Install Microsoft.SemanticKernel.Abstractions as a Cake Tool
#tool nuget:?package=Microsoft.SemanticKernel.Abstractions&version=0.12.207.1-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 (37)

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

Package Downloads
Microsoft.SemanticKernel.Core

Semantic Kernel core orchestration, runtime and functions. This package is automatically installed by 'Microsoft.SemanticKernel' package with other useful packages. Install this package manually only if you are selecting individual Semantic Kernel components.
Microsoft.KernelMemory.Abstractions

Kernel Memory is a Copilot/Semantic Kernel Plugin and Memory Web Service to index and query any data and documents, using LLM and natural language, tracking sources and showing citations. The package contains the interfaces and models shared by all Kernel Memory packages.
Microsoft.SemanticKernel.Plugins.Web

Semantic Kernel web plugins: search the web, download files, etc.
Microsoft.KernelMemory.SemanticKernelPlugin

Kernel Memory Plugin allows to use Kernel Memory Service as a Semantic Kernel plugin, to index and query any data and documents, using LLM and natural language, tracking sources and showing citations.
Microsoft.SemanticKernel.Plugins.MsGraph

Semantic Kernel Microsoft Graph Plugins: access your tenant data, schedule meetings, send emails, etc.

GitHub repositories (7)

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

Repository Stars
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
SciSharp/LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
SciSharp/BotSharp
AI Multi-Agent Framework in .NET
microsoft/kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
Richasy/FantasyCopilot
A new-age AI desktop tool
Version Downloads Last updated
1.31.0 25 11/27/2024
1.30.0 7,746 11/19/2024
1.29.0 20,833 11/13/2024
1.28.0 12,491 11/7/2024
1.27.0 7,521 11/5/2024
1.26.0 19,851 10/31/2024
1.25.0 31,132 10/23/2024
1.24.1 36,204 10/18/2024
1.23.0 4,439 10/17/2024
1.22.0 30,204 10/8/2024
1.21.1 69,572 9/25/2024
1.21.0 1,333 9/25/2024
1.20.0 38,411 9/17/2024
1.19.0 17,258 9/10/2024
1.18.2 54,216 9/4/2024
1.18.1-rc 15,297 8/27/2024
1.18.0-rc 18,796 8/12/2024
1.17.2 88,352 8/21/2024
1.17.1 96,355 8/7/2024
1.17.0 11,466 8/7/2024
1.16.2 42,373 7/30/2024
1.16.1 34,003 7/23/2024
1.16.0 32,598 7/16/2024
1.15.1 97,546 7/3/2024
1.15.0 75,701 6/19/2024
1.14.1 101,530 6/5/2024
1.14.0 30,082 6/4/2024
1.13.0 91,921 5/20/2024
1.12.0 16,195 5/16/2024
1.11.1 91,692 5/10/2024
1.11.0 5,037 5/8/2024
1.10.0 87,719 4/29/2024
1.9.0 43,220 4/24/2024
1.8.0 14,432 4/22/2024
1.7.1 71,532 4/5/2024
1.7.0 35,603 4/3/2024
1.6.3 75,066 3/19/2024
1.6.2 97,517 3/14/2024
1.6.1 76,280 3/12/2024
1.5.0 69,203 2/27/2024
1.4.0 111,125 2/14/2024
1.3.1 19,331 2/12/2024
1.3.0 87,599 1/31/2024
1.2.0 33,187 1/24/2024
1.1.0 108,165 1/16/2024
1.0.1 106,618 12/18/2023
1.0.0-rc4 8,844 12/13/2023
1.0.0-rc3 17,488 12/6/2023
1.0.0-rc2 3,700 12/5/2023
1.0.0-rc1 4,114 12/5/2023
1.0.0-beta8 121,770 11/16/2023
1.0.0-beta7 19,488 11/16/2023
1.0.0-beta6 19,215 11/9/2023
1.0.0-beta5 10,219 11/6/2023
1.0.0-beta4 19,044 10/30/2023
1.0.0-beta3 17,747 10/23/2023
1.0.0-beta2 15,240 10/16/2023
1.0.0-beta1 20,194 10/9/2023
0.24.230918.1-preview 94,845 9/18/2023
0.24.230912.2-preview 11,487 9/12/2023
0.24.230911.2-preview 2,112 9/11/2023
0.23.230906.2-preview 11,235 9/7/2023
0.22.230905.3-preview 5,237 9/5/2023
0.21.230828.2-preview 21,653 8/28/2023
0.20.230821.4-preview 12,910 8/21/2023
0.19.230804.2-preview 105,660 8/5/2023
0.18.230725.3-preview 57,947 7/25/2023
0.17.230718.1-preview 66,965 7/18/2023
0.17.230711.7-preview 84,666 7/11/2023
0.17.230704.3-preview 43,037 7/4/2023
0.17.230629.1-preview 8,404 6/29/2023
0.17.230626.1-preview 3,684 6/26/2023
0.16.230615.1-preview 24,347 6/16/2023
0.15.231219.1-preview 4,589 12/19/2023
0.15.230609.2-preview 7,716 6/9/2023
0.15.230531.5-preview 23,451 6/1/2023
0.14.547.1-preview 23,470 5/16/2023
0.13.442.1-preview 20,105 5/9/2023
0.13.277.1-preview 15,368 4/25/2023
0.12.207.1-preview 3,497 4/19/2023