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dotnet add package Microsoft.Extensions.AI.Evaluation.Quality --version 10.7.0
NuGet\Install-Package Microsoft.Extensions.AI.Evaluation.Quality -Version 10.7.0
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.7.0" />
<PackageVersion Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="10.7.0" />Directory.Packages.props
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.Quality" />Project file
paket add Microsoft.Extensions.AI.Evaluation.Quality --version 10.7.0
#r "nuget: Microsoft.Extensions.AI.Evaluation.Quality, 10.7.0"
#:package Microsoft.Extensions.AI.Evaluation.Quality@10.7.0
#addin nuget:?package=Microsoft.Extensions.AI.Evaluation.Quality&version=10.7.0Install as a Cake Addin
#tool nuget:?package=Microsoft.Extensions.AI.Evaluation.Quality&version=10.7.0Install as a Cake Tool
Microsoft.Extensions.AI.Evaluation is a set of .NET libraries defined in the following NuGet packages that have been designed to work together to support building processes for evaluating the quality of AI software.
Microsoft.Extensions.AI.Evaluation - Defines core abstractions and types for supporting evaluation.Microsoft.Extensions.AI.Evaluation.Quality - Contains evaluators that can be used to evaluate the quality of AI responses in your projects including Relevance, Truth, Completeness, Fluency, Coherence, Retrieval, Equivalence and Groundedness.Microsoft.Extensions.AI.Evaluation.Safety - Contains a set of evaluators that are built atop the Azure AI Foundry Evaluation service that can be used to evaluate the content safety of AI responses in your projects including Protected Material, Groundedness Pro, Ungrounded Attributes, Hate and Unfairness, Self Harm, Violence, Sexual, Code Vulnerability and Indirect Attack.Microsoft.Extensions.AI.Evaluation.NLP - Contains a set of evaluators that implement common algorithms for evaluating machine translation and natural
language processing tasks. Evaluators currently include BLEU, GLEU and F1 scores.Microsoft.Extensions.AI.Evaluation.Reporting - Contains support for caching LLM responses, storing the results of evaluations and generating reports from that data.Microsoft.Extensions.AI.Evaluation.Reporting.Azure - Supports the Microsoft.Extensions.AI.Evaluation.Reporting library with an implementation for caching LLM responses and storing the evaluation results in an Azure Storage container.Microsoft.Extensions.AI.Evaluation.Console - A command line dotnet tool for generating reports and managing evaluation data.From the command-line:
dotnet add package Microsoft.Extensions.AI.Evaluation
dotnet add package Microsoft.Extensions.AI.Evaluation.Quality
dotnet add package Microsoft.Extensions.AI.Evaluation.Safety
dotnet add package Microsoft.Extensions.AI.Evaluation.Reporting
dotnet add package Microsoft.Extensions.AI.Evaluation.NLP
Or directly in the C# project file:
<ItemGroup>
<PackageReference Include="Microsoft.Extensions.AI.Evaluation" Version="[CURRENTVERSION]" />
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.Quality" Version="[CURRENTVERSION]" />
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.Safety" Version="[CURRENTVERSION]" />
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.Reporting" Version="[CURRENTVERSION]" />
<PackageReference Include="Microsoft.Extensions.AI.Evaluation.NLP" Version="[CURRENTVERSION]" />
</ItemGroup>
You can optionally add the Microsoft.Extensions.AI.Evaluation.Reporting.Azure package in either of these places if you need Azure Storage support.
dotnet tool install Microsoft.Extensions.AI.Evaluation.Console --create-manifest-if-needed
For a comprehensive tour of all the functionality, concepts and APIs available in the Microsoft.Extensions.AI.Evaluation libraries, check out the API Usage Examples available in the dotnet/ai-samples repo. These examples are structured as a collection of unit tests. Each unit test showcases a specific concept or API, and builds on the concepts and APIs showcased in previous unit tests.
We welcome feedback and contributions in our GitHub repo.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 net5.0 was computed. net5.0-windows net5.0-windows was computed. net6.0 net6.0 was computed. net6.0-android net6.0-android was computed. net6.0-ios net6.0-ios was computed. net6.0-maccatalyst net6.0-maccatalyst was computed. net6.0-macos net6.0-macos was computed. net6.0-tvos net6.0-tvos was computed. net6.0-windows net6.0-windows was computed. net7.0 net7.0 was computed. net7.0-android net7.0-android was computed. net7.0-ios net7.0-ios was computed. net7.0-maccatalyst net7.0-maccatalyst was computed. net7.0-macos net7.0-macos was computed. net7.0-tvos net7.0-tvos was computed. net7.0-windows net7.0-windows was computed. net8.0 net8.0 is compatible. net8.0-android net8.0-android was computed. net8.0-browser net8.0-browser was computed. net8.0-ios net8.0-ios was computed. net8.0-maccatalyst net8.0-maccatalyst was computed. net8.0-macos net8.0-macos was computed. net8.0-tvos net8.0-tvos was computed. net8.0-windows net8.0-windows was computed. net9.0 net9.0 is compatible. net9.0-android net9.0-android was computed. net9.0-browser net9.0-browser was computed. net9.0-ios net9.0-ios was computed. net9.0-maccatalyst net9.0-maccatalyst was computed. net9.0-macos net9.0-macos was computed. net9.0-tvos net9.0-tvos was computed. net9.0-windows net9.0-windows was computed. net10.0 net10.0 is compatible. net10.0-android net10.0-android was computed. net10.0-browser net10.0-browser was computed. net10.0-ios net10.0-ios was computed. net10.0-maccatalyst net10.0-maccatalyst was computed. net10.0-macos net10.0-macos was computed. net10.0-tvos net10.0-tvos was computed. net10.0-windows net10.0-windows was computed. |
| .NET Core | netcoreapp2.0 netcoreapp2.0 was computed. netcoreapp2.1 netcoreapp2.1 was computed. netcoreapp2.2 netcoreapp2.2 was computed. netcoreapp3.0 netcoreapp3.0 was computed. netcoreapp3.1 netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 netstandard2.0 is compatible. netstandard2.1 netstandard2.1 was computed. |
| .NET Framework | net461 net461 was computed. net462 net462 is compatible. net463 net463 was computed. net47 net47 was computed. net471 net471 was computed. net472 net472 was computed. net48 net48 was computed. net481 net481 was computed. |
| MonoAndroid | monoandroid monoandroid was computed. |
| MonoMac | monomac monomac was computed. |
| MonoTouch | monotouch monotouch was computed. |
| Tizen | tizen40 tizen40 was computed. tizen60 tizen60 was computed. |
| Xamarin.iOS | xamarinios xamarinios was computed. |
| Xamarin.Mac | xamarinmac xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos xamarinwatchos was computed. |
Showing the top 5 NuGet packages that depend on Microsoft.Extensions.AI.Evaluation.Quality:
| Package | Downloads |
|---|---|
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Microsoft.Azure.Workflows.WebJobs.Extension
Extensions for running workflows in Azure Functions |
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AgentEval
The comprehensive .NET evaluation toolkit for AI agents—tool usage validation, RAG quality metrics, stochastic evaluation, model comparison, and red team security testing. Built for Microsoft Agent Framework (MAF) with fluent assertion APIs. |
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NexusLabs.Needlr.AgentFramework.Evaluation
Evaluation adapter for NexusLabs.Needlr.AgentFramework. Maps captured agent-run diagnostics to Microsoft.Extensions.AI.Evaluation inputs so MEAI evaluators can score Needlr agent runs without re-invoking the model. |
|
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Fuuga.cpu
Large Language Model (LLM) generator. And Small as well, SML. Give data and generate your model. Fuuga implements a complete language model pipeline: tokenization, data ingestion, model training, fine-tuning, and text generation. Code in .NET (F#). |
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Fuuga
Large Language Model (LLM) generator. And Small as well, SML. Give data and generate your model. Fuuga implements a complete language model pipeline: tokenization, data ingestion, model training, fine-tuning, and text generation. Code in .NET (F#). |
Showing the top 4 popular GitHub repositories that depend on Microsoft.Extensions.AI.Evaluation.Quality:
| Repository | Stars |
|---|---|
| dotnet/ai-samples | |
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foxminchan/BookWorm
The practical implementation of Aspire using Microservices, AI-Agents
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Azure/azure-sdk-tools
Tools repository leveraged by the Azure SDK team.
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AgentEvalHQ/AgentEval
AgentEval is the comprehensive .NET toolkit for AI agent evaluation—tool usage validation, RAG quality metrics, stochastic evaluation, and model comparison—built first for Microsoft Agent Framework (MAF) and Microsoft.Extensions.AI. What RAGAS, PromptFoo and DeepEval do for Python, AgentEval does for .NET
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| Version | Downloads | Last Updated |
|---|---|---|
| 10.7.0 | 4,290 | 6/9/2026 |
| 10.6.0 | 28,517 | 5/12/2026 |
| 10.5.0 | 30,488 | 4/15/2026 |
| 10.4.0 | 81,938 | 3/10/2026 |
| 10.3.0 | 50,035 | 2/10/2026 |
| 10.2.0 | 53,925 | 1/13/2026 |
| 10.1.0 | 44,200 | 12/9/2025 |
| 10.0.0 | 45,265 | 11/11/2025 |
| 9.10.0 | 164,816 | 10/14/2025 |
| 9.9.0 | 110,465 | 9/9/2025 |
| 9.8.0 | 36,697 | 8/12/2025 |
| 9.7.0 | 26,697 | 7/8/2025 |
| 9.6.0 | 15,079 | 6/10/2025 |
| 9.5.0 | 60,661 | 5/16/2025 |
| 9.5.0-preview.1.25262.9 | 468 | 5/13/2025 |
| 9.4.4-preview.1.25259.16 | 604 | 5/10/2025 |
| 9.4.3-preview.1.25230.7 | 451 | 5/1/2025 |
| 9.4.0-preview.1.25207.5 | 7,898 | 4/8/2025 |
| 9.3.0-preview.1.25164.6 | 3,770 | 3/14/2025 |
| 9.3.0-preview.1.25126.9 | 1,483 | 2/27/2025 |