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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. A copilot must answer multi-part questions that depend on earlier turns in the conversation. You want the system to break each complex question into focused subqueries, run them in parallel, and semantically rerank the results before composing an answer. Which Azure AI Search capability provides this?

A) Increasing the top-k value on a single keyword query
B) Agentic retrieval
C) Classic keyword search with a scoring profile
D) A single vector query with a high similarity threshold

2. You are building a chatbot.
You need to ensure that the chatbot can classify user input into separate categories. The categories must be dynamic and defined at the time of inference.
Which service should you use to classify the input?

A) Azure OpenAI text summarization
B) Azure AI Language custom named entity recognition (NER)
C) Azure AI Language custom text classification
D) Azure OpenAI text classification

3. You have an Azure subscription that contains an Azure OpenAI resource.
You deploy the GPT-4 model to the resource.
You need to ensure that you can upload files that will be used as grounding data for the model.
Which two types of resources should you create? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Azure Blob Storage
B) Azure SQL
C) Azure AI Document Intelligence
D) Azure AI Bot Service
E) Azure AI Search

4. You have a customer support agent built by using the Microsoft Foundry Agent Service. The agent calls an Azure OpenAI model deployment.
During load testing, calls intermittently fail and return an HTTP 429 rate limit exceeded error.
You need to handle throttling to reduce call failures and improve reliability under load. The solution must remain within the service and model limits.
What should you do?

A) Reduce the number of registered tools.
B) Implement a retry policy that uses exponential backoff and jitter.
C) Create a new thread and retry the calls immediately.
D) Spit uploaded content into smaller files.

5. You have a Microsoft Foundry project that contains an agent.
You need to process mixed-format documents that contain scanned text, tables, and multicolumn layouts. The extracted content must preserve the document structure and be converted into the Markdown format for downstream reasoning.
What should you configure first?

A) an Azure OpenAI Responses API call that uses a multimodal model
B) an Azure Content Understanding in Foundry Tools analyzer
C) an Azure Language in Foundry Tools text analysis model deployment
D) a generative chat completion request

Solutions: