You have a Microsoft Foundry project that generates short promotional product videos.After several clips are approved, reviewers notice a small watermark in the top-right corner of some videos.You need to remove the watermark without regenerating the videos.What should you do?
Answer(s): D
The correct action to take is to apply a mask-based inpainting edit to the affected part of the video.This is the only option that directly modifies the existing, approved video files. Inpainting allows you to isolate the specific top-right corner using a mask and seamlessly blend it with the surrounding pixels to erase the watermark without altering or regenerating the rest of the video footage.
https://openart.ai/features/ai-video-inpainting/
You have a web app named App1 that sends requests to a multimodal chat model deployment in a MicrosoftFoundry project.User messages can contain both text and images.Currently, App1 includes image URLs as plain text inside the message content, so the model cannot recognize them as images.Traces show that the requests contain a single text message instead of a multimodal content array.You need to send the message as a structured array that includes both the text portion and the image reference to ensure that the model can process the image correctly.What should you do?
Answer(s): A
To fix this, you must change your request payload structure from a single string to a structured content array.Multimodal models in Azure AI Foundry expect an array of distinct objects for text and images.
https://towardsdatascience.com/multimodal-ai-search-for-business-applications-65356d011009/
You are building a customer support web app named App1 in Microsoft Foundry that uses a GPT realtime model.App1 must support:▪ Live, low-latency voice conversations that use Azure OpenAI▪ Streaming audio input from users and playback audio responsesYou need to configure a connection method that supports real-time audio streaming in client application and targets approximately 100 ms latency.Which connection method should you use?
Answer(s): B
You have a Microsoft Foundry project that contains an agent and uses a GitHub repository. The repository contains a YAML file named File1 that defines the evaluation settings of the agent.You need to create a GitHub Actions workflow that runs the evaluation defined in File1 when a pull request(PR) is opened. How should you configure the workflow?
The correct configuration choice is to set project-endpoint to the endpoint of the project.azure-ai-project-endpoint: This parameter is required and must be set to the URL endpoint of your MicrosoftFoundry project. This aligns with setting project-endpoint.
https://learn.microsoft.com/en-us/azure/foundry/how-to/evaluation-github-action
HOTSPOT (Drag and Drop is not supported)You have a Microsoft Foundry project that contains an agent.The agent uses a stored access key to retrieve secrets from an Azure key vault, which violates a keyless-credentials requirement.You need to ensure that the agent can retrieve the secrets. The solution must follow the principle of least privilege.What should you configure? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Box 1: Enable a system-assigned managed identity at the project levelThe correct configuration is to enable a system-assigned managed identity at the project level.This is the correct approach. Azure AI Foundry (formerly Azure Machine Learning) allows you to enable a system-assigned managed identity directly at the project level. This identity acts as a keyless credential native to Azure. To follow the principle of least privilege, you then assign this project-level identity a specific role (such as Key Vault Secrets User) restricted only to the required Azure Key Vault. This ensures that the agent can retrieve secrets securely without exposing credentials to other projects or resourcesBox 2: Assign the Key Vault Secrets User role to the managed identityTo comply with the keyless-credentials requirement and follow the principle of least privilege, you should configure the Key Vault authorization method to assign the Key Vault Secrets User role to the managed identity using Azure Role-Based Access Control (Azure RBAC).
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/ai-gateway https://learn.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
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