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| Section | Objectives |
|---|---|
| Implement Computer Vision Solutions | - OCR and document intelligence - Image classification and object detection |
| Develop Generative AI Applications and Agents | - Azure OpenAI Service integration
|
| Implement Natural Language Processing Solutions | - Language understanding and intent recognition - Translation and multilingual support - Text analytics and summarization |
| Knowledge Mining and Information Retrieval | - Indexing and semantic search - Azure AI Search configuration - RAG (Retrieval Augmented Generation) patterns |
| Plan and Manage Azure AI Solutions | - Model selection and lifecycle management - Azure AI resource provisioning and configuration - Responsible AI principles and governance |
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NEW QUESTION # 150
You have an Azure subscription that contains an Azure Language in Foundry Tools service resource. You need to identify the URL of the REST interface for the Language service. Which blade should you use in the Azure portal?
Answer: B
Explanation:
The Keys and Endpoint blade displays the resource-specific endpoint URL used to construct REST API requests to Azure Language in Foundry Tools. It also provides the resource access keys when local key-based authentication is enabled. Microsoft's Azure Language documentation directs administrators to open the resource in the Azure portal and select Keys and Endpoint from the left menu to obtain the endpoint and credentials required for API calls.
The endpoint normally forms the base URI for the service. The application appends the operation-specific route and API version required by features such as sentiment analysis, named entity recognition, entity linking, or conversational language understanding. The key may then be supplied in the request's authentication header, although Microsoft Entra ID and managed identities are recommended for supported production workloads because they avoid embedding secrets in application code.
The Networking blade controls public access, firewalls, virtual networks, and private endpoints. Identity manages the resource's managed identity. Properties presents general resource metadata but is not the designated location for retrieving the REST API endpoint and access keys.
Study Guide alignment: plan and manage Azure AI resources, configure service access, and integrate Foundry Tools through their APIs and authentication mechanisms .
NEW QUESTION # 151
In mid-2026 you are starting a brand-new agentic application on Azure and want to build on the generally available, supported entry point for Foundry agents. Which API should you target?
Answer: D
Explanation:
The Responses API is the generally available single entry point for Foundry Agent Service and supports both prompt agents and hosted agents. It is the API Microsoft directs new agentic development towards.
NEW QUESTION # 152
You need to configure Agent1 to meet the security and compliance requirements.
What should you use?
Answer: A
Explanation:
The correct answer is B. Personally Identifiable Information (PII) Detection . The case study states that Agent1 must never reveal customer information , even if a document containing customer data is added accidentally to the product sheet repository in storage1. This is a privacy and compliance control requirement, so the appropriate capability is PII Detection.
Azure Language PII Detection is a Foundry Tools capability that identifies, classifies, and redacts sensitive information across text, conversations, and native documents. Microsoft states that PII Detection can be used to implement privacy controls, reduce sensitive data exposure, and support compliance requirements. In this scenario, PII Detection should be applied to retrieved product-sheet content and generated responses so customer names, contact details, identifiers, and other sensitive values are not exposed to users.
Prompt Shields are important for a separate requirement: protecting Agent1 from malicious instructions hidden in documents or embedded text. Microsoft describes Prompt Shields for documents as protection against hidden instructions embedded in external content. However, the option that directly satisfies the requirement to prevent disclosure of customer information is PII Detection. Self-harm and violence filters address harmful-content categories, not privacy leakage.
NEW QUESTION # 153
You have a Microsoft Foundry project that contains a workflow for a customer support triage process.
You have an Ask a question node that stores user responses in a local variable named Var01.
You need to create the following Power Fx expressions:
* An if/else condition expression that ensures that Var01 contains a value
* A Send message expression that returns the stored user response in uppercase How should you configure the expressions? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
If/else condition expression: Not(IsBlank(Local.Var01))
Send message expression: {Upper(Local.Var01)}
The correct if/else condition is Not(IsBlank(Local.Var01)) because the workflow must continue only when the Ask a question node has captured a nonblank value. In Power Fx, IsBlank checks whether a value is blank, while Not reverses that Boolean result; therefore, Not(IsBlank(Local.Var01)) evaluates to true only when Var01 contains user input. IsEmpty(Local.Var01) is not the correct choice because IsEmpty checks whether a table contains records, not whether a text variable has a value. The Power Fx formula reference distinguishes these functions by defining IsBlank for blank values and IsEmpty for empty tables.
The Send message expression must be {Upper(Local.Var01)}. Microsoft Foundry workflow guidance uses the same pattern for an Ask a question node saved as Var01, followed by a Send message action that outputs
{Upper(Local.Var01)}. The Local. prefix is required because the response is stored in a local workflow variable, and Upper() converts the stored text response to uppercase. Reference topics: Microsoft Foundry workflows, Power Fx expressions, local variables, if/else branching, and Send message actions.
NEW QUESTION # 154
You have an agent named Agent1 that uses Model Context Protocol (MCP) calls to retrieve external data.
You need to implement guardrails to ensure that Agent1 cannot send any content tagged as Violence to the MCP server. Which intervention point should you use?
Answer: B
Explanation:
The correct intervention point is tool call because the prohibited content must be inspected before Agent1 transmits the MCP request to the external server. Microsoft Foundry defines a tool call as "the action and data the agent proposes to send to a tool." This includes the selected MCP operation and its arguments or payload.
A guardrail configured at this stage evaluates the outbound content immediately before execution. When the Violence risk is detected and the response action is configured as Annotate and block , the tool invocation is not executed, preventing the restricted data from leaving the agent boundary.
The other intervention points operate at different stages. User input scans the original user prompt, but harmful content could subsequently be generated within the tool arguments. Tool response scans information returned by the MCP server, which occurs after the outbound content has already been transmitted. Output scans the final answer delivered to the user and therefore does not control agent-to-tool communication.
This aligns with the AI-103 Study Guide topics Configure safety filters, guardrails, risk detection, and content moderation and Govern agent behavior with oversight modes, constraints, and tool-access controls under responsible AI and agentic systems.
NEW QUESTION # 155
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