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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

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

2. You need to recommend a solution to support the planned changes and technical requirements for Agent1 to use the product information stored in storage1.
What should you include in the recommendation?

A) Azure Al Search
B) Grounding with Bing Search
C) Azure Translator in Foundry Tools
D) Azure Document Intelligence in Foundry Tools

3. You have a Microsoft Foundry project that contains an agent named PaymentAgent.
PaymentAgent includes a function tool that issues customer refunds by using an external API.
You are creating a workflow in YAML.
You need to ensure that the workflow pauses for human approval and continues with the refund step only after approval is granted.
How should you complete the workflow definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

4. You have a chat app in a Microsoft Foundry project and an Azure AI Search vectorized index.
You need to connect to the index to meet the following requirements:
* Complex questions must retrieve information from multiple chunks.
* Multi-turn conversations must influence retrieval planning.
* Retrievals must run in parallel to reduce latency.
Which retrieval approach should you use?

A) agentic Retrieval Augmented Generation (RAG)
B) classic Retrieval Augmented Generation (RAG)
C) chain of thought
D) iterative retrieval

5. Your company is piloting a customer support agent in a Microsoft Foundry project name Project1. Project1 is connected to an existing Application Insights resource, and the company ' s support team reviews runs in the Traces tab.
The Foundry Agent Service is configured to perform the following actions:
* Retrieve the Application Insights connection string by calling
project_client.telemetry.get_application_insights_connection_string().
* Call configure_azure_monitor(connection_string=...) to enable telemetry.
A separate LangChain service configured to use OpenTelemetry and has the following configurations:
* Uses AzureAIOpenTelemetryTracer(connection_string=..., enable_content_recording=False)
* Passes the tracer by using config={ " callbacks " :[azure_tracer]}
Company policy has the following requirements:
* Telemetry from LangChain and OpenTelemetry must be distinguishable within the same Application Insights resource.
* Secrets and credentials must NOT be stored in prompts, tool arguments, or span attributes.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Solutions: