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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have an application that processes scanned PDF invoices. The invoices have varied layouts and include multipage tables.
You have a pipeline that uses optical character recognition (OCR) and extracts totals and invoice numbers.
The results are often
incorrect because the document structure is ignored.
You need to implement a solution that provides OCR, layout analysis, and template-generalizing field extraction. The solution must NOT require training a custom model. The solution must minimize administrative effort.
What should you include in the solution?

A) Azure Content Understanding in Foundry Tools
B) an Azure Machine Learning model
C) Azure Language in Foundry Tools

2. You have a Microsoft Foundry project that ingests scanned PDF invoices stored in Azure Blob Storage. Each invoice contains printed line items and has a table-based layout.
Extracted results are stored as structured JSON and used as grounding data for an agent in a Retrieval Augmented Generation (RAG) solution.
You need to create a single analyzer that meets the following requirements:
* Extracts the invoice number, invoice date, vendor name, and total amount across varying templates
* Returns confidence scores so that results with confidence below 0.80 can be routed for supervisor review What should you use?

A) the Azure Content Understanding in Foundry Tools prebuilt-documentSearch analyzer and search.score from the Azure AI Search results for routing
B) a Foundry agent that has groundedness guardrails enabled to extract invoice fields and confidence scores
C) a custom Azure Content Understanding in Foundry Tools analyzer that defines the required fields as the extracted fields and the returned confidence scores for routing
D) the Azure Content Understanding in Foundry Tools prebuilt-layout analyzer

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) Configure an Azure AI Search connection in Project1 and reference the connection in each application.
B) Enable a managed identity for each application and call Azure AI Search directly.
C) Create a custom HTTP connection in Foundry and manually configure Azure AI Search endpoints per application.
D) Call Azure AI Search directly from each application by using Microsoft Entra authentication.

4. 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) Yes
B) No

5. You have a customer support agent built by using the Microsoft Foundry Agent Service. The agent calls an Azure OpenAl model deployment.
During load testing, calls intermittently fail and return an HTTP 429 rate limit exceeded error.
You need to handle throttling to reduce call failures and improve reliability under load. The solution must remain within the service and model limits.
What should you do?

A) Split uploaded content into smaller files.
B) Implement a retry policy that uses exponential backoff and jitter.
C) Reduce the number of registered tools.
D) Create a new thread and retry the calls immediately.

Solutions: