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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have a multimodal Al generative model that accepts image uploads and uses extracted image text to generate responses.
You discover that users can upload unsafe images and embed hidden instructions into images to manipulate the model.
You need to implement controls to mitigate the risk.
Solution: You configure a prompt shield for documents.
Does this meet the goal?

A) No
B) Yes

2. You have a Python application named App1 that integrates with a Microsoft Foundry project named Project1.
You need to ensure that App1 meets the following requirements:
* Authenticates by using a Microsoft Entra managed identity
* Sends prompts to a deployed model by using the Azure OpenAI Responses API How should you complete the Python code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

3. You have a Microsoft Foundry project.
You plan to build a customer support solution that contains an agent. The solution must meet the following requirements:
* Provide accurate, context-aware responses grounded in internal product documentation stored in Azure AI Search.
* Require deep, multi-step reasoning across long contexts.
* Generate detailed natural language responses.
Which type of model should you use to power the agent?

A) a small language model (SLM)
B) a large language model (LLM)
C) a multimodal model
D) a key phrase extraction model

4. You are creating an image-editing workflow in a Microsoft Foundry project.
The workflow must meet the following requirements:
* Ensure that background objects can be removed by applying a mask-based inpainting edit.
* Preserve the original lighting and style of the edited images.
* Use the built-in image editing controls, NOT a custom model.
You need to ensure that image edits apply exclusively inside the masked area.
How should you configure the workflow?

A) Set generation mode to image_variation and provide the original image as a reference.
B) Enable image_to_image mode and a high-strength value to regenerate the full image based on the prompt.
C) Enable mask_inpainting and supply both the input image and a mask indicating which part of the image to modify.
D) Enable text_to_image mode and a prompt describing the desired background removal.

5. You have an Azure Speech in Foundry Tools resource that hosts a custom speech to text model deployed to a custom endpoint. An agent uses the endpoint to perform real-time speech recognition.
You are approaching the expiration date of the custom speech to text model.
What is the expected behavior when the model expires?

A) The custom model will be deleted automatically when the model expires.
B) Speech recognition requests will continue to use the expired custom model until the model is removed manually.
C) Speech recognition requests will return a 4xx error until a new custom model is deployed.
D) Speech recognition requests will fall back to the most recent base model for the same locale.

Solutions: