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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 enable long-term memory to ensure that the agent can recall user preferences across separate conversations. Stored memories must be isolated per authenticated user without the client application manually generating user IDs.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets.
Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

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

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

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 protected material detection.
Does this meet the goal?

A) Yes
B) No

5. You have an application named App1 that uses Azure Speech in Foundry Tools to transcribe live calls.
Transcript segments often contain both English and Spanish. App1 sends each segment to Azure Translator in Foundry Tools to translate to another language.
Sometimes, mixed-language segments result in incomplete or incorrect translations.
You need to reduce translation errors. The solution must ensure that the entire transcript is translated successfully.
What should you do before sending the segments to Translator?

A) Split the mixed-language segments into single-language segments and translate each segment separately.
B) Enable automatic language detection for the translation request.
C) Specify English as the source language in the translation request for all the segments.
D) Use document translation to translate the entire transcript as a single document.

Solutions: