Calling a Microsoft Foundry Generative AI Model

Implement generative AI apps and agents by using Foundry

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?

  1. The exported playground session history
  2. The model training dataset
  3. The Foundry project display name
  4. The model endpoint and authentication credentials Correct Answer
Answer Correct answer: D — The application must include the model endpoint and authentication credentials to successfully call the deployed generative AI model.

Community Insight

This question tests the technical requirements for programmatic API access to an AI service versus local testing artifacts like playground history.

To integrate a generative AI model deployed in Microsoft Foundry into an external application, the app must use the specific model endpoint and valid authentication credentials.

Learners often confuse the development environment tools (like the Playground session history) with the production deployment endpoints required for actual API calls.

Community Discussion (1 comments)

Tony5487 👍 1 Selected: D
call generative ai need model enpoint and auth credentials.

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Expert Analysis

Why the Answer Is Correct

To programmatically call a deployed generative AI model from an external application, two critical pieces of information are mandatory: the network address (endpoint URL) where the model resides, and the authentication credentials (such as API keys or Azure AD tokens) that authorize the request. Without these, the application cannot establish a connection or prove its identity to the service.

Why the Other Options Are Wrong

The exported playground session history (Option A) is useful for debugging or reproducing prompts but does not provide the connectivity details needed for live inference. The model training dataset (Option B) is used during the fine-tuning or training phase, not for serving predictions. The Foundry project display name (Option C) is a human-readable identifier within the management portal and has no function in network routing or API authorization.

Community Comment Notes

Community feedback strongly supports Option D, with users noting that "call generative ai need model enpoint and auth credentials." This aligns with standard cloud API practices where endpoints and keys are the primary interface for integration.

Exam Strategy

Always distinguish between development/testing tools (Playground, datasets) and operational/runtime components (Endpoints, Credentials). For any 'how to connect' question, look for the network and security identifiers first.

Frequently Asked Questions

Why can't I use the Playground session history to call the model?

Session history logs past interactions for review but does not contain the live API endpoint or security tokens needed to send new requests.

Is the project display name used in the API URL?

No, the display name is for human identification in the UI; the API uses a unique resource ID or specific endpoint URL for routing.

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