AI-103: Developing AI Apps and Agents on Azure

AI-103: Developing AI Apps and Agents on Azure practice questions, page 8 of 8, with answer review and explanations.

Question 36

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?

  1. iterative retrieval
  2. agentic Retrieval Augmented Generation (RAG)
  3. chain of thought
  4. classic Retrieval Augmented Generation (RAG)

Question 37

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.