AI-103 Practice Questions — Page 4

You are building a web app named App1 that generates responses by using a model deployed to a Microsoft Foundry project named Project1.

Before sending the prompts to the model, App1 must retrieve documents by using Azure AI Search.

You need to integrate Project1 and App1. The solution must meet the following requirements:

Multiple client applications must use the same search configuration.

A security policy must prevent key-based authentication.

Administrative effort must be minimized.

What should you do?

You have a Microsoft Foundry project that contains an agent used by the financial analysts at your company.

You need to optimize the agent workflow by providing additional data access and processing capabilities. The solution must meet the following requirements:

Ensure that the agent can perform calculations during conversations.

Ensure that the agent can access up-to-date information from public websites.

Ensure that the agent can retrieve information from documents uploaded directly to the agent.

What should you use for each requirement? To answer, drag the appropriate tools to the correct requirements. Each tool may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

You have a Microsoft Foundry project that contains a prompt agent used by a customer support web app.

The agent is invoked from a Python service that does NOT run in the Foundry portal.

You need to implement end-to-end tracing to capture latency breakdowns and exceptions across agent runs.

Which two components can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

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?

You have a Microsoft Foundry project that contains a deployed chat model.

You have a Python service that sends API requests to the model. The service is integrated with an automated validation system that compares generated outputs against approved response patterns.

Stakeholders report that small wording differences are causing validation mismatches.

You need to update the request parameters to improve output stability. The solution must maximize reasoning quality.

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.

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?

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.

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?

You have a Microsoft Foundry project that contains an agent.

You use a GitHub Actions workflow for CI/CD.

You need to configure the workflow to automatically evaluate the agent when a pull request (PR) is created and prevent branches from merging if the evaluation results do NOT meet the defined thresholds.

How should you configure the workflow? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.