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NEW QUESTION # 24
You plan to deploy a generative AI model to a Microsoft Foundry project in the East US Azure region. What should you check first?
Answer: A
Explanation:
Model availability should be checked first. You must confirm that the specific generative AI model is supported and offered in the East US region before checking your token rate limits or allocation quota, as a model cannot be deployed in a region where it does not exist.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/quotas-limits
NEW QUESTION # 25
You have a Microsoft Foundry project that contains a model deployment.
You are developing an application that sends an image and a user question to the model.
You need to send both text and image content in the same request so the model can return an answer.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets.
Each value 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.
Answer:
Explanation:
Explanation:
input=[
{
" role " : " user " ,
" content " : [
{ " type " : " input_text " , " text " : " What is in this image? Provide 3 bullet points. " },
{ " type " : " input_image " , " image_url " : image_url},
],
}
]
print(response.output_text)
For a multimodal request that sends both text and an image to an Azure OpenAI model, the input content array uses separate content item types. Text content is sent with type: " input_text " , and image content is sent with type: " input_image " . Microsoft's Azure OpenAI Responses API documentation shows the Responses API supports multimodal inputs and uses structured input content items in the request.
The options output_text and output_image are not used inside the user input content array. In the shown code, response.output_text is used after the response is returned to print the model's text answer.
NEW QUESTION # 26
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:
Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services. = No Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.
NEW QUESTION # 27
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:
Statement 1: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze different content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format.
= Yes
Azure Content Understanding returns structured analysis output in JSON format.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can extract structured fields from documents and forms by using analyzers and schemas.
NEW QUESTION # 28
You have 100 instructional videos that do NOT contain any audio. Each instructional video has a script.
You need to generate a narration audio file for each video based on the script.
Which type of workload should you use?
Answer: D
NEW QUESTION # 29
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