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| Section | Weight | Objectives |
|---|---|---|
| Implement information extraction and knowledge mining | 10–15% | - Extract structured data from documents
|
| Implement generative AI and agentic solutions | 30–35% | - Build generative AI applications
|
| Plan and manage Azure AI solutions | 25–30% | - Design Azure AI infrastructure
|
| Implement text and speech analysis solutions | 10–15% | - Implement speech capabilities
|
| Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
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NEW QUESTION # 91
You have a Microsoft Foundry project that contains an agent. The agent uses Azure Speech in Foundry Tools.
You fine-tune a baseline speech to text model for the en-us locale and publish the model.
The agent calls the Speech to text REST API and returns an error message indicating that the project ID is invalid.
You need to set the project property to the correct ID.
To what should you set the project property?
Answer: D
Explanation:
To remedy the "invalid project ID" error when calling the Azure Speech to Text REST API within your Microsoft AI Foundry project, you must update the project property in your API request body from a plain string name/ID to the fully qualified Azure Resource URI of the project.
The Speech to Text REST API (v3.0 and later) strictly expects resource links formatted as URIs rather than individual ID strings.
*-> Step 1: Construct the Correct Project URI
You need to pass the project as an absolute object reference. Construct your project property value using the following format:text
https://<your-region>://<your-project-guid>
Use code with caution.Replace <your-region> with your actual Azure Speech resource region (e.g., eastus, westeurope).Replace <your-project-guid> with the actual system-generated Unique Identifier of your project.
Step 2: Retrieve your Project GUID
Step 3: Update your Agent / REST API Request Body
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/azure-ai-speech
NEW QUESTION # 92
Drag and Drop Question
You have a Microsoft Foundry project that contains a deployed ticket-triage agent.
You discover that sometimes the agent responds without calling any tools, even when a tool is required.
You need to ensure that the agent calls a tool during execution.
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:
NEW QUESTION # 93
You are building a customer support web app named App1 in Microsoft Foundry that uses a GPT realtime model.
App1 must support:
- Live, low-latency voice conversations that use Azure OpenAI
- Streaming audio input from users and playback audio responses
You need to configure a connection method that supports real-time audio streaming in client application and targets approximately 100 ms latency.
Which connection method should you use?
Answer: A
Explanation:
WebSockets is the best connection method for this application because it enables full-duplex, bi- directional streaming over a single TCP connection, meeting the strict ~100 ms latency requirement for real-time audio.
Reference:
https://www.chat-data.com/blog/implement-openai-realtime-api-for-chatgpt-voice
NEW QUESTION # 94
Hotspot Question
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
- Use a single key and endpoint to access multiple services.
- Consolidate billing for future services that you might use.
- Support the use of Azure Vision in Foundry Tools in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: PUT
Need to create a Cognitive Services Multi-Service resource using the PUT method. This specific resource type provides a single endpoint and key for multiple AI services, consolidates billing, and supports Azure Vision.
Box 2: CognitiveServices
Using the CognitiveServices kind creates a multi-service resource. This fulfills all the requirements by providing a single key and endpoint for multiple services, consolidating billing, and enabling access to features like Azure AI Vision and Text Analytics under one roof.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
NEW QUESTION # 95
You have a Microsoft Foundry project that contains an agent. The agent uses two tools to perform the following actions:
- Use Azure AI Search to retrieve answers from a private product
documentation index.
- Use the web search tool to retrieve public information on the
internet.
You need to ensure that for a specific run, the agent deterministically retrieves information only from the internet.
To what should you set tool_choice?
Answer: B
Explanation:
To force a specific run to exclusively use public information from the internet instead of your private documents, override the tool orchestration payload at the run level. Set the tool_choice directive specifically to the web grounding tool (e.g., bing_grounding or web_search) and constrain the tools array for that run.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/agents/how-to/tools/ai-search
NEW QUESTION # 96
......
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