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Image Credit: Microsoft

Evaluating content safety in your .NET AI applications

  • The Microsoft.Extensions.AI.Evaluation.Safety package has been added to the Microsoft.Extensions.AI.Evaluation libraries for detecting harmful content in AI-generated applications.
  • The safety evaluators, powered by Azure AI Foundry Evaluation service, can be seamlessly integrated into existing workflows.
  • Steps to set up Azure AI Foundry for safety evaluations include creating an Azure subscription, resource group, AI hub, and project.
  • A C# example shows how to configure and run safety evaluators to check AI responses for various criteria.
  • Running unit tests and generating reports can be done using Visual Studio, Visual Studio Code, or the .NET CLI.
  • The API usage samples cover scenarios like evaluating content safety of AI responses with images and running safety and quality evaluators together.
  • Updates to Microsoft.Extensions.AI.Evaluation libraries include enhanced quality evaluators and improved reporting functionality.
  • New reporting features allow searching and filtering scenarios using tags, viewing rich metadata for metrics, and tracking historical trends.
  • Developers are encouraged to explore the content safety evaluators and provide feedback for further enhancements.
  • The aim is to elevate the quality and safety of AI applications using these tools.
  • The post emphasizes continuous improvement and invites engagement for better utilization of the libraries.

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