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NEW QUESTION # 61
You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?
Answer: A
Explanation:
To call a deployed Azure OpenAI model from an application, the app must know the service endpoint and authenticate its request. Microsoft documentation states that Azure OpenAI supports API key authentication or Microsoft Entra ID authentication, and API key authentication requires including the API key in the request. Microsoft quickstart guidance also states that to successfully make a call against Azure OpenAI, you need an endpoint and a key.
The application does not need the model training dataset, the Foundry project display name, or exported playground session history to call the deployed model.
NEW QUESTION # 62
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
No, you do not need to manually construct HTTP requests when using the Microsoft Foundry SDK. The SDK provides high-level client abstractions, such as AIProjectClient, that allow you to interact with your deployed models using standard programming languages and object-oriented paradigms.
Box 2: No
No, you do not need to create a separate web service to interact with a deployed model when using the Microsoft Foundry SDK.
The Microsoft Foundry SDK allows your application to communicate directly with the cloud-hosted model endpoint through built-in project clients.
Box 3: Yes
Yes, the AIProjectClient class in the Microsoft Foundry SDK (part of the Azure AI Projects client library) provides programmatic access to manage and interact with a deployed project and its connected resources.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/endpoints
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
https://learn.microsoft.com/en-us/dotnet/api/overview/azure/ai.projects-readme
NEW QUESTION # 63
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 64
You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments. This is an example of which Microsoft guiding principle for responsible AI?
Answer: C
Explanation:
An AI system designed to empower everyone, including people with hearing, visual, and other impairments, is a direct example of the inclusiveness guiding principle for responsible AI.
Accessibility: It ensures technology adapts to human needs rather than forcing humans to adapt to technology.
Equal Opportunity: It provides users of all abilities with the same access to information, tools, and digital experiences.
Diverse Design: It reflects a development process that intentionally considers and incorporates the needs of historically underserved populations.
Reference:
https://uitop.design/blog/design/inclusive-design/
NEW QUESTION # 65
You are developing an application that extracts fields from PDFs by using Azure Content Understanding in Foundry Tools.
You need to use the Python SDK to submit a PDF for analysis and retrieve the extraction results.
What should you do?
Answer: C
Explanation:
To build an application that extracts fields from PDFs using Azure Content Understanding in Foundry Tools, you need to initialize the client library, use begin_analyze_binary to submit the file stream, and poll the long-running operation for the result.
Detail from implemenation:
Wait for the operation to complete and poll the results
result = poller.result()
Reference:
https://lobehub.com/pt-BR/skills/frank-luongt-faos-skills-marketplace-azure-ai-contentunderstanding-py
NEW QUESTION # 66
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