Microsoft.SemanticKernel.Plugins.Memory
1.29.0-alpha
Prefix Reserved
See the version list below for details.
dotnet add package Microsoft.SemanticKernel.Plugins.Memory --version 1.29.0-alpha
NuGet\Install-Package Microsoft.SemanticKernel.Plugins.Memory -Version 1.29.0-alpha
<PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.29.0-alpha" />
paket add Microsoft.SemanticKernel.Plugins.Memory --version 1.29.0-alpha
#r "nuget: Microsoft.SemanticKernel.Plugins.Memory, 1.29.0-alpha"
// Install Microsoft.SemanticKernel.Plugins.Memory as a Cake Addin #addin nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.29.0-alpha&prerelease // Install Microsoft.SemanticKernel.Plugins.Memory as a Cake Tool #tool nuget:?package=Microsoft.SemanticKernel.Plugins.Memory&version=1.29.0-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 (>= 1.29.0)
- System.Numerics.Tensors (>= 8.0.0)
- System.Text.Json (>= 8.0.5)
-
net8.0
- Microsoft.SemanticKernel.Core (>= 1.29.0)
- System.Numerics.Tensors (>= 8.0.0)
- System.Text.Json (>= 8.0.5)
NuGet packages (6)
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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AIToolbox.Abstractions
AI Toolbox interfaces and abstractions. This package is automatically installed by AI Toolbox packages if needed. |
GitHub repositories (8)
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.
|
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SciSharp/BotSharp
AI Multi-Agent Framework in .NET
|
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microsoft/WhatTheHack
A collection of challenge based hack-a-thons including student guide, coach guide, lecture presentations, sample/instructional code and templates. Please visit the What The Hack website at: https://aka.ms/wth
|
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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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dotnet/smartcomponents
Sample intelligent app features provided as reusable .NET components
|
Version | Downloads | Last updated |
---|---|---|
1.32.0-alpha | 1,070 | 12/9/2024 |
1.31.0-alpha | 1,630 | 11/27/2024 |
1.30.0-alpha | 3,823 | 11/19/2024 |
1.29.0-alpha | 1,238 | 11/13/2024 |
1.28.0-alpha | 1,066 | 11/7/2024 |
1.27.0-alpha | 493 | 11/5/2024 |
1.26.0-alpha | 2,221 | 10/31/2024 |
1.25.0-alpha | 1,168 | 10/23/2024 |
1.24.1-alpha | 2,929 | 10/18/2024 |
1.23.0-alpha | 138 | 10/17/2024 |
1.22.0-alpha | 9,283 | 10/8/2024 |
1.21.1-alpha | 2,914 | 9/25/2024 |
1.21.0-alpha | 104 | 9/25/2024 |
1.20.0-alpha | 5,425 | 9/17/2024 |
1.19.0-alpha | 1,850 | 9/10/2024 |
1.18.2-alpha | 4,256 | 9/4/2024 |
1.18.1-alpha | 2,072 | 8/27/2024 |
1.18.0-alpha | 4,617 | 8/12/2024 |
1.17.2-alpha | 1,490 | 8/21/2024 |
1.17.1-alpha | 2,308 | 8/7/2024 |
1.17.0-alpha | 142 | 8/7/2024 |
1.16.2-alpha | 3,361 | 7/30/2024 |
1.16.1-alpha | 1,788 | 7/23/2024 |
1.16.0-alpha | 5,618 | 7/16/2024 |
1.15.1-alpha | 7,355 | 7/3/2024 |
1.15.0-alpha | 3,478 | 6/19/2024 |
1.14.1-alpha | 17,231 | 6/5/2024 |
1.14.0-alpha | 250 | 6/4/2024 |
1.13.0-alpha | 19,456 | 5/20/2024 |
1.12.0-alpha | 873 | 5/16/2024 |
1.11.1-alpha | 5,013 | 5/10/2024 |
1.11.0-alpha | 697 | 5/8/2024 |
1.10.0-alpha | 5,772 | 4/29/2024 |
1.9.0-alpha | 3,747 | 4/24/2024 |
1.8.0-alpha | 1,920 | 4/22/2024 |
1.7.1-alpha | 3,559 | 4/5/2024 |
1.7.0-alpha | 3,088 | 4/3/2024 |
1.6.3-alpha | 4,719 | 3/19/2024 |
1.6.2-alpha | 11,751 | 3/14/2024 |
1.6.1-alpha | 1,035 | 3/12/2024 |
1.5.0-alpha | 27,467 | 2/27/2024 |
1.4.0-alpha | 7,929 | 2/14/2024 |
1.3.1-alpha | 1,255 | 2/12/2024 |
1.3.0-alpha | 5,487 | 1/31/2024 |
1.2.0-alpha | 4,318 | 1/24/2024 |
1.1.0-alpha | 9,091 | 1/16/2024 |
1.0.1-alpha | 18,574 | 12/18/2023 |
1.0.0-rc4 | 6,925 | 12/13/2023 |
1.0.0-rc3 | 15,067 | 12/6/2023 |
1.0.0-rc2 | 2,650 | 12/5/2023 |
1.0.0-rc1 | 3,576 | 12/5/2023 |
1.0.0-beta8 | 113,160 | 11/16/2023 |
1.0.0-beta7 | 18,287 | 11/16/2023 |
1.0.0-beta6 | 17,196 | 11/9/2023 |
1.0.0-beta5 | 9,533 | 11/6/2023 |
1.0.0-beta4 | 13,463 | 10/30/2023 |
1.0.0-beta3 | 16,273 | 10/23/2023 |
1.0.0-beta2 | 14,543 | 10/16/2023 |
1.0.0-beta1 | 18,338 | 10/9/2023 |