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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

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

2. You have a Microsoft Foundry project that contains a prompt agent used by a customer support web app.
The agent is invoked from a Python service that does NOT run in the Foundry portal.
You need to implement end-to-end tracing to capture latency breakdowns and exceptions across agent runs.
Which two components can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A) a Log Analytics workspace
B) OpenTelemetry
C) Application Insights
D) Microsoft Sentinel
E) the Azure Monitor Agent

3. You have a Microsoft Foundry project named Project1.
Project1 contains an application that processes PDF vendor invoices.
You need to configure Azure Document Intelligence in Foundry Tools to generate a Markdown output that preserves the sections and table structure of the PDFs. The solution must minimize development effort.
What should you do?

A) Configure content=markdown when you analyze the document.
B) Set the output_content_format=ContentFormat. MARKDOWN value.
C) Increase the confidence threshold.
D) Configure output=figures when you analyze the PDF.

4. You have a Microsoft Foundry project that contains an agent. The agent uses Azure Speech in Foundry Tools.
You fine-tune a baseline speech to text model for the en-us locale and publish the model.
The agent calls the Speech to text REST API and returns an error message indicating that the project ID is invalid.
You need to set the project property to the correct ID.
To what should you set the project property?

A) the custom speech project ID
B) the project ID
C) the custom speech endpoint URL
D) the project URL

5. You have a Microsoft Foundry project that contains three agents as shown in the following table.
Name
Description
TriageAgent
Classifies incoming customer requests
PolicyAgent
Answers policy questions by searching internal content
ActionAgent
Creates or updates tickets by calling an HTTP API
You need to orchestrate the agents to ensure that the customer requests meet the following requirements:
* Support a deterministic, step-based process that uses conditional branching and shared state across the agents.
* Optionally trigger a ticket action based on the triage result.
The solution must minimize development effort.
What should you include in the solution?

A) a multi-agent group chat session
B) a workflow
C) threads and runs without a workflow
D) separate agent runs coordinated in the application code

Solutions: