Microsoft.SemanticKernel.Plugins.Memory 1.11.0-alpha

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.Plugins.Memory.
There is a newer prerelease version of this package available.
See the version list below for details. 
dotnet add package Microsoft.SemanticKernel.Plugins.Memory --version 1.11.0-alpha                

                    
                

            
NuGet\Install-Package Microsoft.SemanticKernel.Plugins.Memory -Version 1.11.0-alpha
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.Plugins.Memory" Version="1.11.0-alpha" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add Microsoft.SemanticKernel.Plugins.Memory --version 1.11.0-alpha                

                    
                

            
#r "nuget: Microsoft.SemanticKernel.Plugins.Memory, 1.11.0-alpha"
#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.Plugins.Memory as a Cake Addin
#addin nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.11.0-alpha&prerelease

// Install Microsoft.SemanticKernel.Plugins.Memory as a Cake Tool
#tool nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.11.0-alpha&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.

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 ⚡

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 (7)

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

Package Downloads
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
ERNIE-Bot.SemanticKernel

ERNIE-Bot(文心千帆) 集成 Semantic Kernel
GraphRag.Net

GraphRag for .NET –这是一个参考GraphRag的DotNet简易实现。 基于微软在论文中提到的实现思路，执行过程GraphRAG主要实现了如下功能： Source Documents → Text Chunks：将源文档分割成文本块。 Text Chunks → Element Instances：从每个文本块中提取图节点和边的实例。 Element Instances → Element Summaries：为每个图元素生成摘要。 Element Summaries → Graph Communities：使用社区检测算法将图划分为社区。 Graph Communities → Community Summaries：为每个社区生成摘要。 Community Summaries → Community Answers → Global Answer：使用社区摘要生成局部答案，然后汇总这些局部答案以生成全局答案。 商务需求联系微信xuzeyu91
BotSharp.Plugin.SemanticKernel

Package Description
HillPhelmuth.SemanticKernel.LlmAsJudgeEvals

Enable seamless execution of LLM (Large Language Model) evaluations using Semantic Kernel. This library provides tools and abstractions for running automated assessments where LLMs serve as judges, offering structured, consistent, and scalable evaluation methods. Ideal for AI-driven projects that require evaluative feedback, scoring, or comparative analysis across various use cases. Easily integrates with Semantic Kernel for smooth, flexible LLM operations in .NET environments.

GitHub repositories (7)

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

Repository Stars
SciSharp/LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
SciSharp/BotSharp
AI Multi-Agent Framework in .NET
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！
dotnet/smartcomponents
Sample intelligent app features provided as reusable .NET components
microsoft/project-oagents
Experimental AI Agents Framework
Version Downloads Last updated
1.30.0-alpha 263 11/19/2024
1.29.0-alpha 594 11/13/2024
1.28.0-alpha 593 11/7/2024
1.27.0-alpha 335 11/5/2024
1.26.0-alpha 1,972 10/31/2024
1.25.0-alpha 818 10/23/2024
1.24.1-alpha 1,488 10/18/2024
1.23.0-alpha 123 10/17/2024
1.22.0-alpha 5,589 10/8/2024
1.21.1-alpha 2,431 9/25/2024
1.21.0-alpha 89 9/25/2024
1.20.0-alpha 4,483 9/17/2024
1.19.0-alpha 1,625 9/10/2024
1.18.2-alpha 3,599 9/4/2024
1.18.1-alpha 1,925 8/27/2024
1.18.0-alpha 4,373 8/12/2024
1.17.2-alpha 1,221 8/21/2024
1.17.1-alpha 2,118 8/7/2024
1.17.0-alpha 129 8/7/2024
1.16.2-alpha 2,935 7/30/2024
1.16.1-alpha 1,471 7/23/2024
1.16.0-alpha 4,969 7/16/2024
1.15.1-alpha 6,787 7/3/2024
1.15.0-alpha 3,042 6/19/2024
1.14.1-alpha 16,309 6/5/2024
1.14.0-alpha 240 6/4/2024
1.13.0-alpha 18,291 5/20/2024
1.12.0-alpha 819 5/16/2024
1.11.1-alpha 3,824 5/10/2024
1.11.0-alpha 686 5/8/2024
1.10.0-alpha 5,700 4/29/2024
1.9.0-alpha 3,247 4/24/2024
1.8.0-alpha 1,412 4/22/2024
1.7.1-alpha 3,413 4/5/2024
1.7.0-alpha 2,725 4/3/2024
1.6.3-alpha 4,498 3/19/2024
1.6.2-alpha 11,236 3/14/2024
1.6.1-alpha 768 3/12/2024
1.5.0-alpha 26,585 2/27/2024
1.4.0-alpha 7,525 2/14/2024
1.3.1-alpha 1,201 2/12/2024
1.3.0-alpha 5,418 1/31/2024
1.2.0-alpha 4,264 1/24/2024
1.1.0-alpha 8,740 1/16/2024
1.0.1-alpha 18,124 12/18/2023
1.0.0-rc4 6,776 12/13/2023
1.0.0-rc3 14,814 12/6/2023
1.0.0-rc2 2,640 12/5/2023
1.0.0-rc1 3,484 12/5/2023
1.0.0-beta8 110,850 11/16/2023
1.0.0-beta7 17,199 11/16/2023
1.0.0-beta6 17,003 11/9/2023
1.0.0-beta5 9,204 11/6/2023
1.0.0-beta4 12,735 10/30/2023
1.0.0-beta3 16,147 10/23/2023
1.0.0-beta2 14,046 10/16/2023
1.0.0-beta1 18,279 10/9/2023