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Microsoft Developing AI Apps and Agents on Azure Sample Questions:
1. You have a Microsoft Foundry project that contains an agent.
You need to process mixed-format documents that contain scanned text, tables, and multicolumn layouts. The extracted content must preserve the document structure and be converted into the Markdown format for downstream reasoning.
What should you configure first?
A) a generative chat completion request
B) an Azure OpenAl Responses API call that uses a multimodal model
C) an Azure Language in Foundry Tools text analysis model deployment
D) an Azure Content Understanding in Foundry Tools analyzer
2. 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 endpoint URL
B) the project URL
C) the project ID
D) the custom speech project ID
3. You are building a web app named App1 that generates responses by using a model deployed to a Microsoft Foundry project named Project1.
Before sending the prompts to the model, App1 must retrieve documents by using Azure AI Search.
You need to integrate Project1 and App1. The solution must meet the following requirements:
* Multiple client applications must use the same search configuration.
* A security policy must prevent key-based authentication.
* Administrative effort must be minimized.
What should you do?
A) Create a custom HTTP connection in Foundry and manually configure Azure AI Search endpoints per application.
B) Configure an Azure AI Search connection in Project1 and reference the connection in each application.
C) Call Azure AI Search directly from each application by using Microsoft Entra authentication.
D) Enable a managed identity for each application and call Azure AI Search directly.
4. You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools. The solution must meet the following requirements:
* Include a pipeline named Pipeline1 that supports cost-effective, high-volume processing of standalone PDF invoices.
* Include a pipeline named Pipeline2 that supports cross-document validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
5. You have a Microsoft Foundry project that generates product marketing images from text prompts.
After publishing several images, the legal team at your company identifies a competitor ' s logo on a sign in the background of an image.
You need to remove only the logo, while preserving the rest of the image.
What should you do?
A) Rerun the prompt by using a different random seed.
B) Modify the original prompt to exclude brand names.
C) Increase the prompt guidance strength.
D) Apply a mask-based inpainting edit to the part of the image that contains the logo.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: Only visible for members | Question # 5 Answer: D |




