AI-103 Practice Test 14 — 15 Questions

Question 1

Which THREE actions occur when you 'deploy' an agent from Azure AI Foundry?

Accepted Answer

The agent's configuration is persisted as a versioned deployment.. Deployment makes the model/agent available as an endpoint, often configuring the model version and resource allocation.

Answer

The model is automatically retrained on new data.

Answer

All previous chat history is deleted from the server.

Question 2

In Azure AI Foundry, which tool would you use to measure the quality of your RAG application against a golden dataset?

Accepted Answer

Evaluation. Evaluation in Azure AI Foundry uses metrics to assess RAG pipelines.

Answer

Model Catalog

Answer

Deployment

Answer

Prompt Flow Tracing

Question 3

Which TWO of the following are valid ways to provide context to an agent in Prompt Flow?

Accepted Answer

Passing conversation history as part of the messages list. Static prompt text and dynamic vector store retrieval are standard methods.

Answer

Deploying the model in a different region

Answer

Increasing the model output length

Answer

Training a new model on the context

Question 4

You are developing an Azure AI Search index for a RAG application. You need to ensure that the search results include semantic relevance scores to improve the quality of the model's grounding. Which feature must you enable?

Accepted Answer

Enable Semantic Ranker on the search service. Semantic ranker is required to provide semantic relevance scores (semantic search) to rerank results.

Answer

Use Custom Analyzers

Answer

Enable Knowledge Store

Answer

Enable Hybrid Search with vectorization

Question 5

Which THREE features are provided by the Azure AI Foundry evaluation service?

Accepted Answer

Visualization of evaluation results. Built-in metrics, custom evaluation logic, and dataset visualization are key features.

Answer

Automated model fine-tuning based on failures

Answer

Automatic user interface generation

Question 6

You need to extract text lines, words, bounding polygons, and selection marks (such as radio buttons and checkboxes) from arbitrary documents without training. Which prebuilt model should you invoke?

Accepted Answer

Prebuilt Layout model. The Prebuilt Read model extracts text, layout structures, and selection marks across various document types without requiring any custom model training.

Answer

Prebuilt Business Card model

Answer

Prebuilt ID Document model

Answer

Custom Neural model

Question 7

Your custom extraction model is failing to identify fields on a new version of a document. You have labeled 50 documents. What is the most likely solution?

Accepted Answer

Add more training documents with the new layout. Adding more training samples that include the new document variations improves the model's robustness.

Answer

Change the API version to v2.1

Answer

Switch to a template model

Answer

Increase the confidence threshold

Question 8

Which THREE file types are supported for direct processing by the Document Intelligence API?

Accepted Answer

TIFF. PDF, JPEG, and TIFF (and PNG) are standard supported input formats.

Answer

DOCX

Answer

PPTX

Question 9

Which Azure AI Foundry feature helps identify drift in model performance after deployment?

Accepted Answer

Model Monitoring. Model monitoring tracks performance metrics over time to identify drift.

Answer

Data Drift Analysis via Compute

Answer

Prompt Flow Tracing

Answer

Model Catalog

Question 10

You are automating document processing. You want to trigger a workflow only after a Document Intelligence operation finishes. What is the standard way to implement this?

Accepted Answer

Poll the 'operation-location' URL. The Document Intelligence API returns a 'operation-location' URL; you poll this URL to check the status until completion.

Answer

Use a fixed-delay thread sleep

Answer

Use a WebSocket

Answer

Wait for a push notification

Question 11

Which THREE items are included in the JSON response from the Document Intelligence analyze operation?

Accepted Answer

PageResults (structure). The API response includes the read result (text), page information, and the extracted fields/entities.

Answer

UserPermissions

Answer

TrainingLogs

Question 12

Which THREE of the following are components of a standard Prompt Flow DAG (Directed Acyclic Graph)?

Accepted Answer

Inputs. Inputs, Tools (Nodes), and Outputs are fundamental to Prompt Flow structure.

Answer

Model Training Jobs

Answer

Data Labeling Projects

Question 13

You are designing a high-throughput document processing pipeline using Azure AI Document Intelligence. To optimize latency and cost, you want to extract only the text and layout structures (paragraphs, lines, words, and tables) from a multi-page PDF without performing key-value extraction or using custom models. Which model ID should you specify in your API request?

Accepted Answer

prebuilt-layout. The prebuilt layout model (prebuilt-layout) extracts document structures, tables, selection marks, and text without entity or custom key-value extraction.

Answer

prebuilt-invoice

Answer

prebuilt-read

Answer

prebuilt-document

Question 14

Which TWO file formats are natively supported as inputs for analysis in Azure AI Document Intelligence? (Choose TWO)

Accepted Answer

application/pdf. Document Intelligence supports standard document formats like PDF, JPEG, PNG, TIFF, and BMP.

Answer

text/html

Answer

application/zip

Answer

application/vnd.ms-excel

Question 15

Your application uses the Azure AI Document Intelligence Prebuilt Receipt model to process customer receipts. A receipt contains a custom tip amount that is not explicitly categorized by the default prebuilt schema. How should you extract this custom value?

Accepted Answer

Use the Prebuilt Layout model alongside custom regex rules or train a Custom model to capture the custom tip field.. When prebuilt models do not cover specific custom fields, you can combine the Prebuilt Read/Layout model output with custom parsing logic, or train a custom model if needed, but for prebuilt models, leveraging general key-value pairs or post-processing layout text is standard.

Answer

Call the Azure OpenAI service directly with the raw image to guess the tip amount.

Answer

Pass a custom JSON schema parameter in the Prebuilt Receipt API request body to extend its extraction fields.

Answer

Modify the prebuilt receipt model schema directly in the Azure Portal to add a new required field.