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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You need to configure an indexing pipeline for Agent1 to retrieve the relevant product information in storage1. The solution must meet the technical requirement.
Which two built-in skills should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Merge
B) key phrase extraction
C) Language Detection
D) Entity Recognition
E) Azure OpenAl Embedding
F) Text Split

2. You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
You need to improve response completeness. The solution must be implemented in the logic of the application code before responses are returned.
What should you do?

A) Enable response streaming.
B) Switch to Retrieval Augmented Generation (RAG).
C) Decrease the value of the temperature parameter.
D) Add a reflection pass before the responses are returned.

3. You have a customer support agent that uses the Microsoft Foundry Agent Service.
Sometimes, customers return to a session days later to continue the same support case, and the agent must resume with the full historical context. The agent must provide the following:
* Multi-turn continuity within the session
* Cross-session continuity for the same case
* Access to the full interaction history, including user messages, agent messages, tool calls, and tool outputs You need to ensure that the agent automatically reloads the complete history on each new turn.
What should you do?

A) Persist only the final model response stored in the client application and prepend the response to future prompts.
B) Enable memory summarization on the agent definition to persist the context automatically.
C) Create and reuse a conversation by storing the conversation's ID and supplying the ID on subsequent requests.

4. You have a Microsoft Foundry project that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAl v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?

A) Cognitive Services Data Reader
B) Cognitive Services User
C) Cognitive Services OpenAl User
D) Contributor

5. You have a Python application named App1 that integrates with a Microsoft Foundry project named Project1.
You need to ensure that App1 meets the following requirements:
* Authenticates by using a Microsoft Entra managed identity
* Sends prompts to a deployed model by using the Azure OpenAI Responses API How should you complete the Python code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solutions: