Microsoft.SemanticKernel.Plugins.Memory
1.28.0-alpha
Prefix Reserved
dotnet add package Microsoft.SemanticKernel.Plugins.Memory --version 1.28.0-alpha
NuGet\Install-Package Microsoft.SemanticKernel.Plugins.Memory -Version 1.28.0-alpha
<PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.28.0-alpha" />
paket add Microsoft.SemanticKernel.Plugins.Memory --version 1.28.0-alpha
#r "nuget: Microsoft.SemanticKernel.Plugins.Memory, 1.28.0-alpha"
// Install Microsoft.SemanticKernel.Plugins.Memory as a Cake Addin #addin nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.28.0-alpha&prerelease // Install Microsoft.SemanticKernel.Plugins.Memory as a Cake Tool #tool nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.28.0-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 ⚡
- 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 is compatible. 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. |
-
.NETStandard 2.0
- Microsoft.SemanticKernel.Core (>= 1.28.0)
- System.Numerics.Tensors (>= 8.0.0)
- System.Text.Json (>= 8.0.5)
-
net8.0
- Microsoft.SemanticKernel.Core (>= 1.28.0)
- System.Numerics.Tensors (>= 8.0.0)
- System.Text.Json (>= 8.0.5)
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 |
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ERNIE-Bot.SemanticKernel
ERNIE-Bot(文心千帆) 集成 Semantic Kernel |
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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 |
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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!
|
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dotnet/smartcomponents
Sample intelligent app features provided as reusable .NET components
|
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microsoft/project-oagents
Experimental AI Agents Framework
|
Version | Downloads | Last updated |
---|---|---|
1.28.0-alpha | 127 | 11/7/2024 |
1.27.0-alpha | 179 | 11/5/2024 |
1.26.0-alpha | 1,109 | 10/31/2024 |
1.25.0-alpha | 537 | 10/23/2024 |
1.24.1-alpha | 1,048 | 10/18/2024 |
1.23.0-alpha | 114 | 10/17/2024 |
1.22.0-alpha | 3,503 | 10/8/2024 |
1.21.1-alpha | 2,146 | 9/25/2024 |
1.21.0-alpha | 83 | 9/25/2024 |
1.20.0-alpha | 3,958 | 9/17/2024 |
1.19.0-alpha | 1,503 | 9/10/2024 |
1.18.2-alpha | 2,903 | 9/4/2024 |
1.18.1-alpha | 1,835 | 8/27/2024 |
1.18.0-alpha | 4,246 | 8/12/2024 |
1.17.2-alpha | 1,018 | 8/21/2024 |
1.17.1-alpha | 2,060 | 8/7/2024 |
1.17.0-alpha | 124 | 8/7/2024 |
1.16.2-alpha | 2,553 | 7/30/2024 |
1.16.1-alpha | 1,331 | 7/23/2024 |
1.16.0-alpha | 4,553 | 7/16/2024 |
1.15.1-alpha | 6,481 | 7/3/2024 |
1.15.0-alpha | 2,896 | 6/19/2024 |
1.14.1-alpha | 15,804 | 6/5/2024 |
1.14.0-alpha | 234 | 6/4/2024 |
1.13.0-alpha | 17,766 | 5/20/2024 |
1.12.0-alpha | 810 | 5/16/2024 |
1.11.1-alpha | 2,976 | 5/10/2024 |
1.11.0-alpha | 681 | 5/8/2024 |
1.10.0-alpha | 5,626 | 4/29/2024 |
1.9.0-alpha | 2,863 | 4/24/2024 |
1.8.0-alpha | 875 | 4/22/2024 |
1.7.1-alpha | 3,300 | 4/5/2024 |
1.7.0-alpha | 2,519 | 4/3/2024 |
1.6.3-alpha | 4,299 | 3/19/2024 |
1.6.2-alpha | 10,909 | 3/14/2024 |
1.6.1-alpha | 635 | 3/12/2024 |
1.5.0-alpha | 25,798 | 2/27/2024 |
1.4.0-alpha | 7,372 | 2/14/2024 |
1.3.1-alpha | 1,150 | 2/12/2024 |
1.3.0-alpha | 5,342 | 1/31/2024 |
1.2.0-alpha | 4,228 | 1/24/2024 |
1.1.0-alpha | 8,641 | 1/16/2024 |
1.0.1-alpha | 17,818 | 12/18/2023 |
1.0.0-rc4 | 6,701 | 12/13/2023 |
1.0.0-rc3 | 14,614 | 12/6/2023 |
1.0.0-rc2 | 2,636 | 12/5/2023 |
1.0.0-rc1 | 3,449 | 12/5/2023 |
1.0.0-beta8 | 109,905 | 11/16/2023 |
1.0.0-beta7 | 16,745 | 11/16/2023 |
1.0.0-beta6 | 16,932 | 11/9/2023 |
1.0.0-beta5 | 8,992 | 11/6/2023 |
1.0.0-beta4 | 12,366 | 10/30/2023 |
1.0.0-beta3 | 16,092 | 10/23/2023 |
1.0.0-beta2 | 13,806 | 10/16/2023 |
1.0.0-beta1 | 18,215 | 10/9/2023 |