Microsoft AI-901 Exam Dumps

For vision-enabled Azure OpenAI / Microsoft Foundry model requests, image input can be provided by using an image URL or base64-encoded image data. Microsoft's Azure OpenAI REST API reference states that the image content part URL field can contain either a URL of the image or the base64 encoded image data. It also states that the Responses API input_image.image_url value can be a fully qualified URL or a base64 encoded image in a data URL.

When using the Azure OpenAI Responses API with a vision-enabled model, the image must be included as an input image content item. The correct content item type is:

{'type': 'input_image', 'image_url': image_url}

Microsoft's Azure OpenAI Responses API documentation states that the Responses API supports image inputs, and multimodal requests use structured input content items for the request.

Why the other options are incorrect:

A . image_base64 = Incorrect. Base64 data can be used as the image data format, but the content item type is still input_image. B . image_generation = Incorrect. This is related to generating images, not providing an image for analysis. C . output_image = Incorrect. This would refer to generated output, not image input. D . input_image = Correct.

To create an AI agent that follows a specific role and behavior, you configure system instructions. Microsoft Foundry Agent Service documentation states that agent instructions define goals, constraints, and behavior.

Option A. tokens per minute (TPM) controls throughput quota, not behavior. Option C. temperature controls response randomness/creativity, not the agent's role. Option D. max completion tokens controls response length, not the agent's role or behavioral rules.

Therefore, the correct answer is B. system instructions.

Microsoft's Foundry Agent Service documentation states that tool_choice provides deterministic control over tool calling:

auto means the model decides whether to call tools. required means the model must call one or more tools. none means the model does not call tools.

Therefore:

A . auto = Incorrect, because the model may or may not call the Azure function. B . none = Incorrect, because this prevents tool/function calls. C . required = Correct, because it forces the agent to call a tool.

The Azure OpenAI function-calling documentation also confirms that tool_choice='auto' lets the model decide whether to call a function, while tool_choice='none' forces a user-facing response without a tool call.

The correct text analysis technique is Named Entity Recognition (NER).

Microsoft defines NER as a feature that identifies and categorizes entities in unstructured text, including people, places, and organizations.

Sentiment analysis detects positive, negative, or neutral opinion. Summarization creates shorter versions of text. Key phrase extraction identifies important phrases, but it does not specifically classify mentions as people, organizations, or locations.