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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You need to recommend a plan to create a customer support agent by using the Microsoft Foundry Agent Service. The agent must meet the following requirements:
* Retain user preferences across multiple conversations.
* Enable users to provide contextual grounding by directly uploading documents during a chat.
Which Foundry capability should you recommend for each requirement? 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 speech translation to generate the transcripts into multiple languages.
B) Run a batch transcription job on recorded audio files.
C) Use text to speech by using a custom neural voice.
D) Use real-time speech to text to process streaming audio input.

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

4. You have a Microsoft Foundry project that contains an agent. The agent uses Azure Al Search as the retriever.
You plan to ingest PDFs into an Azure Al Search index to ensure that the agent can ground responses in texts in both documents and embedded images.
Users require citations that link to the source files.
You need to ensure that during indexing, the images are extracted into a structure that can be used as input for the built-in optical character recognition (OCR) skill.
Which indexing approach should you use?

A) a skillset to run the OCR skill directly against the content field of the index
B) an indexer to extract image data into a normalized_images collection
C) the outputFieldMappings parameter to write image data to a searchable field
D) a Shaper skill to restructure the OCR input

5. 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 Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You increase the value of the max_tokens parameter.
Does this meet the goal?

A) No
B) Yes

Solutions: