AI-103試験無料問題集「Microsoft Developing AI Apps and Agents on Azure 認定」
You are designing a solution that will answer questions about human resources (HR) policies stored in the PDF format.
You need to ensure that the identical answer to a specific question is returned every time. The solution must minimize development effort.
Which service should you include in the solution?
You need to ensure that the identical answer to a specific question is returned every time. The solution must minimize development effort.
Which service should you include in the solution?
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
Hotspot Question
You have a Microsoft Foundry project that contains an internal Q&A agent.
Users report the following issues when they ask the agent questions:
- An increase in the following response: "No relevant information
found"
- Periodic HTTP 429 rate limit exceeded errors during peak hours
You need to identify whether each issue is caused by model unavailability, resource limits, or inference failures.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You have a Microsoft Foundry project that contains an internal Q&A agent.
Users report the following issues when they ask the agent questions:
- An increase in the following response: "No relevant information
found"
- Periodic HTTP 429 rate limit exceeded errors during peak hours
You need to identify whether each issue is caused by model unavailability, resource limits, or inference failures.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Hotspot Question
You have a Python application that redacts sensitive information before sending prompt text to a language model. The application has the following code:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
You have a Python application that redacts sensitive information before sending prompt text to a language model. The application has the following code:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Box 1: No
The audit list will not include entity records for "Contact" and "SSN" because neither word is a target PII entity type defined in the configuration.
The code limits scanning to Person and PhoneNumber via the piiCategories list.
"Contact" Definition: This is a regular English verb/noun, not a person's name or a telephone number.
"SSN" Definition: While "SSN" is a text label that points to sensitive data, it is a descriptor rather than an actual Social Security Number.
Box 2: Yes
For the given sample_text, text_for_model will include both or [email protected] and 859-
98-0987 completely unredacted.
The payload explicitly restricts the Personally Identifiable Information (PII) recognition to only two specific categories by setting piiCategories: ["Person", "PhoneNumber"].
Email Address Excluded: Because the Email category is omitted from the configuration list, the service bypasses the email address ([email protected]) and leaves it fully intact.
SSN Excluded: Similarly, because the USSSN (or equivalent Social Security Number) category is not specified in the piiCategories array, the SSN (859-98-0987) is completely ignored by the redaction policy and remains visible.
Box 3: Yes
text_for_model will contain entity type masks for "John Doe" and "312-555-1234", but only for those two specific items.
The piiCategories array explicitly requests Person and PhoneNumber.
Applied Redaction: The Azure AI Language service will replace "John Doe" and "312-555-1234" with masks like * or entity labels (depending on exact policy settings).
Skipped Data: The email ([email protected]) and the SSN (859-98-0987) will not be redacted because their categories (Email and USSSN) were omitted from your piiCategories list.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/concepts/conversations-entity-categories
Hotspot Question
You are creating an enrichment pipeline that will use Azure AI Search. The knowledge store contains unstructured JSON data and the text from scanned PDF documents.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You are creating an enrichment pipeline that will use Azure AI Search. The knowledge store contains unstructured JSON data and the text from scanned PDF documents.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Box 1: Object projection
For the unstructured JSON data, you must use object projection, and for the extracted text data from the scanned PDF documents, you must use file projection.
Object Projection: Projects your data as a full JSON representation. It is ideal for maintaining the original structure alongside any applied AI enrichments within a single JSON document inside Azure Blob Storage.
Box 2: File projection
File Projection: Captures the binary or image extraction layer required during Optical Character Recognition (OCR) processing. It isolates and outputs raw text and graphic details directly from unstructured physical binary files into a designated container Reference:
https://learn.microsoft.com/en-us/azure/search/cognitive-search-concept-image-scenarios
You have an Azure subscription that contains an Azure Al Foundry instance named AI1.
You have an app that automatically triages and resolves issues presented in the log files of a system.
You create an incident manager agent and a DevOps agent that collaborate to resolve the issues.
You need to ensure that the incident manager agent can assign work to the DevOps agent. The solution must minimize development effort.
What should you do?
You have an app that automatically triages and resolves issues presented in the log files of a system.
You create an incident manager agent and a DevOps agent that collaborate to resolve the issues.
You need to ensure that the incident manager agent can assign work to the DevOps agent. The solution must minimize development effort.
What should you do?
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
Drag and Drop Question
You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools.
The solution must meet the following requirements:
- Include a pipeline named Pipeline1 that supports cost-effective,
high-volume processing of standalone PDF invoices.
- Include a pipeline named Pipeline2 that supports cross-document
validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration may be used once, more than once, of 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.
You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools.
The solution must meet the following requirements:
- Include a pipeline named Pipeline1 that supports cost-effective,
high-volume processing of standalone PDF invoices.
- Include a pipeline named Pipeline2 that supports cross-document
validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration may be used once, more than once, of 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.
正解：
You have an Azure subscription that contains an Azure OpenAI resource.
You deploy the GPT-4 model to the resource.
You need to ensure that you can upload files that will be used as grounding data for the model.
Which two types of resources should you create? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You deploy the GPT-4 model to the resource.
You need to ensure that you can upload files that will be used as grounding data for the model.
Which two types of resources should you create? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
正解：A,E
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解説: (GoShiken メンバーにのみ表示されます)
You have a Microsoft Foundry project that contains a customer support agent. The agent calls an internal knowledge API tool before generating responses.
Users report the following issues:
- Some requests take more than 15 seconds to complete.
- Some responses are incorrect, even when the knowledge API returns the expected data.
You need to inspect individual agent runs to view the ordered sequence of large language model (LLM) calls, tool invocations, and timing information.
Which observability capability should you use?
Users report the following issues:
- Some requests take more than 15 seconds to complete.
- Some responses are incorrect, even when the knowledge API returns the expected data.
You need to inspect individual agent runs to view the ordered sequence of large language model (LLM) calls, tool invocations, and timing information.
Which observability capability should you use?
正解：A
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解説: (GoShiken メンバーにのみ表示されます)
You have a Microsoft Foundry project that contains an agent.
The agent uses Azure AI Search for Retrieval Augmented Generation (RAG).
You plan to ingest and index PDF product manuals.
You need to build a solution that supports semantic similarity matching. The solution must ensure that the agent retrieves relevant data when user questions use different wording than the product manuals.
Which indexing approach should you use?
The agent uses Azure AI Search for Retrieval Augmented Generation (RAG).
You plan to ingest and index PDF product manuals.
You need to build a solution that supports semantic similarity matching. The solution must ensure that the agent retrieves relevant data when user questions use different wording than the product manuals.
Which indexing approach should you use?
正解：D
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解説: (GoShiken メンバーにのみ表示されます)