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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You have a Microsoft Foundry project that contains an internal Q & A agent.
Users report the following issues when they ask the agent questions:
* An increase in the following response: "No relevant information found"
* Periodic HTTP 429 rate limit exceeded errors during peak hours
You need to identify whether each issue is caused by model unavailability, resource limits, or inference failures.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

2. You are building a speech processing solution in Microsoft Foundry for a customer support platform.
The platform will transcribe live phone calls, so that supervisors at your company can view call transcripts and detect issues while the calls are in progress. The call audio will arrive as a continuous stream from the telephony system.
You need to ensure that the call transcripts appear within only a few seconds of the audio stream.
What should you do?

A) Use text to speech by using a custom neural voice.
B) Use real-time speech to text to process streaming audio input.
C) Use speech translation to generate the transcripts into multiple languages.
D) Run a batch transcription job on recorded audio files.

3. You are deploying a support agent that enables users to upload photos.
You need to automatically classify uploaded images for harmful content. The solution must block content based on severity levels.
What should you do?

A) Enable prompt shields.
B) Apply keyword scanning to optical character recognition (OCR) output by using Azure Vision in Foundry Tools.
C) Implement image moderation.
D) Use blocklists.

4. 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) Enable a managed identity for each application and call Azure AI Search directly.
B) Configure an Azure AI Search connection in Project1 and reference the connection in each application.
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.

5. You have a Microsoft Foundry project that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAl v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?

A) Cognitive Services User
B) Cognitive Services OpenAl User
C) Cognitive Services Data Reader
D) Contributor

Solutions: