AI-103 Implement Generative AI And Agentic Solutions — All Questions With Answers

Question 1hardmultiple choice

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You are implementing Retrieval-Augmented Generation (RAG) using Azure AI Search and Azure OpenAI. Users report that when searching for technical product specifications, the system occasionally retrieves outdated product manuals because newer versions share similar titles. What configuration change should you make to improve retrieval accuracy?

Question 2easymultiple choice

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You are configuring an Azure OpenAI Service deployment in Microsoft AI Foundry portal. You need to ensure that the deployed model meets your enterprise compliance requirements for data privacy, ensuring that prompt and completion data are not used to train Microsoft base models. Which deployment type should you select?

Question 3hardmultiple choice

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You are building an agentic workflow in Microsoft Foundry using Semantic Kernel. The agent needs to call an external enterprise API to retrieve customer billing data. The API requires OAuth 2.0 user-delegated tokens. How should you configure the plugin registration to securely pass the user context?

Question 4mediummultiple choice

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You are building an agent using Azure AI Agent Service that needs to maintain long-term conversational memory across multiple sessions with a user. Which feature should you utilize to store and retrieve past user interactions?

Question 5mediummultiple choice

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You are developing a generative AI application that uses Azure OpenAI. You want to track token consumption per user department for chargeback purposes. Which feature should you enable and utilize?

Question 6mediummultiple choice

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You are configuring automatic evaluation in Azure AI Foundry using the groundedness metric. The evaluation pipeline requires a source context and an LLM-generated response. What does the groundedness metric assess?

Question 7mediummultiple choice

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You are deploying an open-source model (such as Llama 3) via Model Catalog in Azure AI Foundry. You want to optimize inference latency and throughput for high-concurrency requests. Which deployment type should you select?

Question 8hardmulti select

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You are implementing responsible AI practices in Azure AI Foundry for a public-facing chatbot. Which THREE safety evaluations or controls should you implement to protect users and the organization? (Choose THREE)

Question 9mediummulti select

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When designing a Responsible AI evaluation workflow in Azure AI Foundry, which TWO metrics are specifically used to assess content safety and potential harms? (Choose two.)

Question 10mediummulti select

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You are designing an agentic workflow in Azure AI Foundry that needs to perform multiple tasks sequentially. Which THREE components are essential for defining the orchestration logic?

Question 11mediummultiple choice

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You are developing an agent using Azure AI Agent Service and notice that the model consistently refuses to answer queries about company-internal technical specifications despite the documentation being uploaded to the vector index. Which action should you prioritize?

Question 12hardmultiple choice

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An agent is prone to 'hallucinations' when responding to specific niche queries. What is the most effective way to reduce these hallucinations using RAG?

Question 13easymultiple choice

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You need to evaluate the performance of your prompt engineering for a summarization task. Which tool in Azure AI Foundry allows you to run multiple prompt variants against a dataset to compare outputs?

Question 14hardmultiple choice

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You are designing an agent that needs to access user-specific data from OneDrive. How should you handle the authentication for this tool call?

Question 15easymultiple choice

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Which role is responsible for ensuring the ethical deployment of an AI agent within an organization?

Question 16mediummulti select

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Which TWO features in Azure AI Foundry help you manage the lifecycle of your AI agents?

Question 17easymulti select

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Which TWO resources are required to set up an Azure AI Foundry project?

Question 18mediummulti select

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Which THREE metrics should you monitor to evaluate the effectiveness of a RAG-based agent?

Question 19hardmulti select

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You are troubleshooting a Prompt Flow and suspect the issue lies in the input processing. Which THREE tools or techniques can you use?

Question 20hardmulti select

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

Question 21easymultiple choice

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You are building a customer service agent in Azure AI Foundry. The agent needs to call an external inventory management REST API when customers ask about stock levels. Which feature of Azure AI Agent Service should you implement to allow the agent to interact with this external API?

Question 22mediummultiple choice

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You are designing a RAG solution using Azure AI Search and Azure OpenAI. Users report that when querying technical documentation, the system misses highly relevant paragraphs because the exact keywords do not match the user's conversational query. How should you configure Azure AI Search to improve retrieval accuracy?

Question 23mediummultiple choice

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You are developing a multi-agent orchestration solution using Azure AI Agent Service and want to ensure that user inputs are safely evaluated before they are passed to the model. Which component should you configure to inspect and filter incoming prompts for malicious content and restricted topics?

Question 24mediummultiple choice

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You are evaluating an agentic workflow in Azure AI Foundry that performs multi-step reasoning. The agent occasionally enters an infinite loop, repeatedly calling the same tool with identical arguments. Which architectural pattern or configuration should you apply to prevent this behavior?

Question 25hardmultiple choice

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You are designing a RAG solution in Azure AI Foundry where sensitive enterprise documents must be retrieved. Users should only see search results corresponding to their security clearance level. How should you implement document-level access control in Azure AI Search?

Question 26easymultiple choice

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You are writing a system prompt for an Azure OpenAI model deployed in Azure AI Foundry. You want to ensure the model responds only using the provided context and refuses to answer if the context is insufficient. What technique should you use?

Question 27hardmultiple choice

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You are optimizing a RAG pipeline in Azure AI Foundry. Users complain that answers are missing key numerical details because important tables within PDF documents are being split across chunk boundaries during ingestion. What is the recommended remediation?

Question 28easymultiple choice

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You are deploying an Azure OpenAI model in Azure AI Foundry and want to evaluate its performance and safety against a validation dataset before moving to production. Which tool should you use?

Question 29mediummultiple choice

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You are designing an agentic workflow where an orchestrator agent delegates sub-tasks to specialized worker agents (e.g., a research agent and a coding agent). Which framework or service native to Azure AI supports multi-agent orchestration patterns?

Question 30hardmultiple choice

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You are implementing indirect prompt injection protection for an agent that reads emails and summarizes them. An incoming email contains malicious instructions designed to trick the agent into exfiltrating user data. Which Azure AI feature should you configure to detect this threat?

Question 31easymultiple choice

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You are configuring a connection between Azure AI Foundry and an Azure OpenAI resource. Which credential type is recommended for secure, keyless authentication between services in Azure?

Question 32mediummultiple choice

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You are building a RAG application where documents are updated frequently. You need to ensure that the Azure AI Search index reflects document deletions and updates in near real-time without performing full re-indexing. How should you design the ingestion pipeline?

Question 33easymultiple choice

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You are designing a generative AI solution in Azure AI Foundry. You need to ensure that user data sent to Azure OpenAI is not used to train Microsoft's foundational models. What is Microsoft's default data privacy policy for Azure OpenAI?

Question 34hardmultiple choice

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You are tuning the prompt for a generative AI application in Azure AI Foundry. The model frequently hallucinates when asked complex multi-part questions. You decide to use chain-of-thought (CoT) prompting. How should you structure the prompt to implement CoT effectively?

Question 35hardmultiple choice

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You are building an advanced agentic RAG solution. When a user asks a complex question, the agent needs to generate multiple search queries, execute them in parallel against Azure AI Search, synthesize the findings, and then formulate a final answer. Which agent pattern are you implementing?

Question 36hardmultiple choice

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You are building an agent that needs to execute Python code safely to calculate financial projections requested by users. Which tool in Azure AI Agent Service should you enable to allow the agent to write and run code in an isolated environment?

Question 37easymultiple choice

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You are designing a generative AI application in Azure AI Foundry and want to categorize user queries into predefined intent classes before routing them to specific agents. Which prompt engineering technique should you apply?

Question 38mediummultiple choice

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You are implementing a RAG solution where documents contain complex hierarchical headings. To ensure search chunks retain sufficient context about which section they belong to, what chunking strategy should you adopt?

Question 39hardmultiple choice

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You are monitoring an Azure OpenAI deployment in Azure AI Foundry and notice an increase in HTTP 429 (Too Many Requests) errors. Your application needs to handle these rate limit spikes gracefully. What is the recommended architectural solution?

Question 40easymultiple choice

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You are creating a custom prompt template in Azure AI Foundry. You want to insert the user's input safely while preventing prompt injection vulnerabilities. How should you design the template structure?

Question 41hardmultiple choice

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You are designing a multi-agent solution in Azure AI Foundry where agents collaborate asynchronously. One agent produces an intermediate JSON payload that must be strictly validated before being consumed by the next agent. What feature should you implement?

Question 42mediummultiple choice

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You are integrating Azure AI Search with Azure OpenAI for grounded chat generation. Users report that the generated answers are accurate, but the citations returned to the user point to raw internal file paths rather than user-friendly web URLs. How should you resolve this?

Question 43mediummultiple choice

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You are building a generative AI application that summarizes long legal documents. Users complain that summaries omit important clauses located in the middle of the document due to the model's attention limitations over extremely long texts. What phenomenon does this represent, and how can you mitigate it?

Question 44easymultiple choice

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You are managing prompt assets in Azure AI Foundry. Your team collaborates on developing, testing, and versioning system prompts. Which feature in Azure AI Foundry should you use to store and manage these prompt templates?

Question 45hardmultiple choice

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You are implementing an agentic workflow where an agent needs to search a vector database, inspect the retrieved results, and if the results are insufficient, reformulate the query and search again before answering. What agent design pattern are you implementing?

Question 46mediummultiple choice

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You are building a chat application with Azure OpenAI. To improve perceived latency for users, you want to stream the model's response token-by-token to the client interface. Which API parameter or client SDK feature should you enable?

Question 47easymultiple choice

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You are designing an AI application and want to test different foundation models (e.g., GPT-4o vs. Llama 3) side-by-side using the same prompt and test dataset. Which feature in Azure AI Foundry should you use?

Question 48mediummultiple choice

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You are developing a RAG solution using Azure AI Search. Users are searching using domain-specific acronyms that are not well-represented in standard embedding models, resulting in poor retrieval scores. What feature should you enable in Azure AI Search to improve keyword matching for exact acronyms?

Question 49hardmultiple choice

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You are implementing an agentic workflow where an agent executes tools that modify corporate data. To adhere to Responsible AI principles, you must ensure a human reviewer approves sensitive tool actions before they are executed. What design pattern should you implement in Azure AI Agent Service?

Question 50mediummultiple choice

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You are configuring model fine-tuning for an Azure OpenAI model in Azure AI Foundry. You have prepared a JSONL training dataset. Which evaluation approach is recommended to verify that fine-tuning successfully improved model performance without causing catastrophic forgetting?

Question 51mediummulti select

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You are designing a RAG solution using Azure AI Search and Azure OpenAI. Which TWO factors significantly influence the effectiveness of chunking documents during the ingestion phase? (Choose TWO)

Question 52mediummulti select

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You are configuring an agent in Azure AI Agent Service that needs to utilize tools. Which TWO types of tools are natively supported by Azure AI Agent Service? (Choose TWO)

Question 53hardmulti select

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You are troubleshooting a RAG application in Azure AI Foundry where retrieved search results are irrelevant to user queries. Which THREE actions should you take to diagnose and improve retrieval quality? (Choose THREE)

Question 54mediummulti select

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When designing prompt engineering strategies for complex reasoning tasks in Azure OpenAI, which TWO techniques help reduce hallucinations and improve output reliability? (Choose TWO)

Question 55mediummulti select

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You are evaluating generative AI model outputs in Azure AI Foundry. Which TWO automated evaluation metrics assess the quality and correctness of RAG responses against source data? (Choose TWO)

Question 56hardmulti select

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You are deploying an enterprise RAG application in Azure AI Foundry. You need to ensure data security and compliance across all components. Which THREE security practices should you implement? (Choose THREE)

Question 57mediummulti select

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You are optimizing an Azure OpenAI deployment in Azure AI Foundry for high-throughput batch processing. Which TWO strategies or configurations should you consider? (Choose TWO)

Question 58hardmulti select

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When designing agentic workflows in Azure AI Foundry, what are THREE key characteristics or components of agentic design compared to traditional single-turn prompt completion? (Choose THREE)

Question 59hardmulti select

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You are designing a secure RAG retrieval pipeline in Azure AI Search. Which THREE indexing or search configurations are essential when handling confidential documents? (Choose THREE)

Question 60mediummulti select

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When implementing prompt engineering for generative AI applications in Azure AI Foundry, which TWO practices are considered best practices for maintaining prompt maintainability and security? (Choose TWO)

Question 61mediummulti select

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You are preparing a dataset for fine-tuning an Azure OpenAI model in Azure AI Foundry. Which TWO data formatting and preparation requirements must you follow? (Choose TWO)

Question 62hardmulti select

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You are building an advanced agentic solution in Azure AI Foundry that integrates with external line-of-business systems. Which THREE architectural patterns or features should you incorporate to ensure robustness and safety? (Choose THREE)

Question 63hardmulti select

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You are designing a generative AI application in Azure AI Foundry that supports multi-turn conversations with memory. Which THREE components are required to properly maintain conversational state and context? (Choose THREE)

Question 64mediummulti select

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When implementing grounding in a RAG application using Azure AI Foundry, which TWO practices help minimize hallucinations in model outputs? (Choose TWO)

Question 65hardmulti select

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When configuring vector embeddings and search indexes in Azure AI Search for RAG, which THREE factors directly impact vector search performance and recall accuracy? (Choose THREE)

Question 66hardmulti select

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You are troubleshooting a multi-agent workflow in Azure AI Foundry where an agent fails to invoke an external API tool correctly. Which THREE debugging steps should you perform? (Choose THREE)

Question 67mediummulti select

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You are monitoring an Azure OpenAI model deployed in Azure AI Foundry. Which TWO Azure diagnostic metrics or logs should you analyze to track operational health and performance? (Choose TWO)

Question 68mediummulti select

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When designing an Azure AI Foundry project architecture, which TWO resources are typically linked to the Azure AI Hub to enable full model deployment and search capabilities? (Choose TWO)

Question 69hardmulti select

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You are implementing indirect prompt injection defenses in a RAG application where documents are ingested from public web pages. Which THREE mitigation strategies should you deploy? (Choose THREE)

Question 70mediummulti select

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When designing an evaluation pipeline in Azure AI Foundry for generative AI applications, which TWO metrics are commonly used to assess safety and risk? (Choose TWO)

Question 71hardmulti select

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You are optimizing an enterprise RAG application in Azure AI Foundry for high accuracy and minimal latency. Which THREE advanced retrieval techniques should you consider implementing? (Choose THREE)

Question 72mediummulti select

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When configuring role-based access control (RBAC) in Azure AI Foundry and Azure OpenAI, which TWO built-in Azure roles are commonly assigned to developers and services? (Choose TWO)

Question 73easymultiple choice

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You are configuring a Microsoft Foundry project to deploy a multimodal model. You need to ensure that the model deployment scales automatically based on request volume while minimizing management overhead. Which deployment type should you select?

Question 74hardmultiple choice

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You are implementing Retrieval-Augmented Generation (RAG) using Azure AI Search as the retriever and Azure OpenAI as the generator. Users report that the generated responses frequently miss critical context located in the middle of long retrieved documents. Which grounding optimization technique should you apply?

Question 75mediummultiple choice

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You are building an agentic workflow in Azure AI Foundry using the Semantic Kernel framework. The agent needs to call external APIs dynamically based on user intent. Which component should you register with the kernel to enable this capability?

Question 76easymultiple choice

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You are designing a customer service chatbot using Azure OpenAI. You need to ensure that the model refuses to answer questions outside the scope of your company's products. Where should you define this boundary instruction?

Question 77mediummultiple choice

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You are integrating Azure OpenAI into an enterprise application. You need to prevent prompt injection attacks where users attempt to override the system instructions. Which approach provides the most robust defense?

Question 78hardmultiple choice

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You are orchestrating a multi-agent system in Microsoft Foundry where Agent A generates code and Agent B reviews it. Agent B frequently gets stuck in a loop trying to optimize minor syntax formatting. How should you design the agentic workflow to prevent this infinite refinement loop?

Question 79easymultiple choice

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You are evaluating a generative AI application in Azure AI Foundry using automated metrics. You need to measure how well the generated answers are supported by the retrieved source documents. Which evaluation metric should you use?

Question 80hardmultiple choice

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You are designing an agentic workflow where an agent needs to maintain conversational context and remember user preferences across multiple disparate sessions over several weeks. Which architectural component should you implement?

Question 81mediummultiple choice

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You are configuring an Azure AI Search index for use with Azure OpenAI On Your Data. The index contains technical documentation with complex nested tables. Which search configuration will yield the best retrieval performance for semantic queries?

Question 82easymultiple choice

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You are preparing a prompt template for a summarization task. You want to provide three distinct examples of input text and expected summaries before asking the model to process the target text. What is this prompting technique called?

Question 83hardmultiple choice

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You are implementing a RAG pipeline where documents are chunked before embedding generation. You notice that semantic sentences are frequently split across chunk boundaries, resulting in degraded retrieval quality. Which chunking strategy should you implement to resolve this?

Question 84mediummultiple choice

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You are deploying an Azure OpenAI model in Azure AI Foundry and need to restrict access so that only specific virtual networks within your enterprise can invoke the model endpoint. Which feature should you configure?

Question 85easymultiple choice

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You are configuring an agent in Azure AI Foundry that needs to perform mathematical calculations accurately. Large language models often make arithmetic errors. How should you equip the agent to handle calculations reliably?

Question 86mediummultiple choice

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You are designing a generative AI application that processes user uploaded documents. You must ensure that Personally Identifiable Information (PII) such as Social Security numbers are automatically redacted before the text is sent to the Azure OpenAI model. Which service should you integrate into your pipeline?

Question 87easymultiple choice

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You are monitoring your Azure OpenAI deployment in Azure AI Foundry. You notice an increase in HTTP 429 status codes. What does this error indicate?

Question 88hardmultiple choice

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You are building an agentic application that uses function calling. The model frequently hallucinates arguments for complex tool schemas. Which technique should you apply to improve function calling reliability?

Question 89hardmulti select

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You are designing an enterprise RAG solution using Azure AI Search and Azure OpenAI. You need to ensure data security and compliance across different user permission tiers. Which TWO actions should you implement? (Choose two.)

Question 90mediummultiple choice

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You are implementing a multi-turn conversational agent in Azure AI Foundry. As the conversation grows longer, API latency and costs increase significantly. Which strategy should you implement to manage the conversation history effectively?

Question 91mediummulti select

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You are configuring prompt engineering practices for a generative AI application in Azure AI Foundry. Which THREE practices should you follow to ensure high output quality and reliability? (Choose three.)

Question 92hardmulti select

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You are troubleshooting an Azure OpenAI deployment in Azure AI Foundry where agents are failing to complete tasks due to excessive timeouts. Which THREE diagnostic steps should you take? (Choose three.)

Question 93hardmulti select

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You are building an autonomous agentic workflow using Microsoft Foundry and Semantic Kernel. You need to ensure the agent operates safely and adheres to human oversight requirements. Which THREE design patterns should you apply? (Choose three.)

Question 94mediummulti select

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Which TWO factors directly influence the embedding quality and retrieval relevance in an Azure AI Search vector retrieval pipeline? (Choose two.)

Question 95hardmulti select

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You are optimizing an agentic workflow in Azure AI Foundry. The agent needs to solve complex reasoning problems by breaking them down into distinct sub-tasks, executing them iteratively, and reflecting on intermediate results. Which THREE architectural frameworks or patterns support this behavior? (Choose three.)

Question 96mediummultiple choice

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You are developing a customer support agent using Microsoft Foundry. The agent needs to call a custom weather API tool when a user asks about local conditions. How should you define this capability in the agent configuration?

Question 97mediummulti select

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When configuring Azure OpenAI Custom Model Evaluation in Azure AI Foundry, which TWO metrics can be computed using LLM-as-a-judge evaluators? (Choose two.)

Question 98easymultiple choice

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You are implementing Retrieval-Augmented Generation (RAG) in Azure AI Foundry using Azure AI Search as the grounding data source. Which indexing feature should you enable to ensure the system can perform semantic ranking alongside traditional keyword search?

Question 99hardmultiple choice

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You are designing an agentic workflow in Azure AI Agent Service where multiple specialized agents need to collaborate to solve complex, multi-step financial analysis tasks. One agent manages the workflow state and decides which sub-agent to invoke next. What architectural pattern is best suited for this implementation?

Question 100mediummultiple choice

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You are configuring content safety filters in Azure AI Foundry for a public-facing generative AI application. You need to ensure that the application detects and blocks potential jailbreak attempts and protected material text. Which component should you configure?

Question 101mediummultiple choice

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You are configuring a code interpreter tool for an AI agent in Azure AI Agent Service. The agent needs to analyze a CSV dataset uploaded by a user. How does the agent execute this task securely?

Question 102hardmulti select

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You are designing an advanced agentic solution in Azure AI Foundry that requires tool integration and state management. Which TWO practices should you implement to ensure robust agent reliability and security? (Choose two)

Question 103easymultiple choice

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When engineering prompts for Azure OpenAI models, you want to guide the model's output format and persona effectively. Which practice represents the most reliable prompt engineering technique?

Question 104mediummulti select

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When implementing Retrieval-Augmented Generation (RAG) using Azure AI Search and Azure OpenAI, which THREE strategies help optimize chunk retrieval relevance and reduce noise? (Choose three)

Question 105hardmultiple choice

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You are implementing a grounded RAG solution in Azure AI Foundry. Users report that the model occasionally hallucinates answers even when relevant documents are retrieved by Azure AI Search. What is the most effective prompt engineering strategy to mitigate this grounding failure?

Question 106easymulti select

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As part of responsible AI practices in Azure AI Foundry, which TWO actions should you perform to evaluate and mitigate model fairness and safety risks before deployment? (Choose two)

Question 107mediummultiple choice

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You are building an agent in Azure AI Foundry that requires access to a private internal database. Which component should you configure to ensure the agent retrieves data securely without exposing the database endpoint publicly?

Question 108hardmultiple choice

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You are optimizing a RAG pipeline in Azure AI Foundry. The model is hallucinating when retrieving documents from a large corpus. Which strategy should you implement to improve grounding accuracy?

Question 109easymultiple choice

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You are deploying an LLM in Azure AI Foundry and need to monitor for toxicity and jailbreak attempts in real-time. Which feature should you enable?

Question 110mediummulti select

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You are designing an agentic workflow in Prompt Flow. Which TWO components are required to define a tool-based agent? (Choose two)

Question 111mediummultiple choice

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You are building an agent in Azure AI Foundry that needs to retrieve information from a company SharePoint site. Which component should you implement to ground the agent?

Question 112easymultiple choice

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You are deploying a model in Azure AI Foundry. You need to ensure that the model endpoint is protected by a virtual network. Which configuration should you use?

Question 113hardmultiple choice

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You are implementing prompt engineering for a customer support agent. To minimize hallucinations when the model lacks information, which Prompt Flow technique is most effective?

Question 114mediummultiple choice

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You are building an agent in Azure AI Foundry using a prompt flow. You need to ensure that the agent only uses company-approved documentation for its responses. Which feature should you implement to meet this requirement?

Question 115hardmultiple choice

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You are designing an agentic workflow in Azure AI Foundry that requires the agent to call an external REST API. Which component should you use to define the tool interface?

Question 116hardmulti select

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You are auditing a generative AI application for responsible AI compliance. Which THREE practices should you implement to mitigate risks? (Choose 3)

Question 117hardmultiple choice

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You are building an agentic workflow in Azure AI Foundry. You need the agent to perform a multi-step task: search a database, summarize results, and then send an email. Which component is best suited to manage this orchestration?

Question 118mediummultiple choice

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You are configuring an agent that must call a REST API to get current stock prices. Where must you define this integration to ensure the agent can reliably call the tool?

Question 119easymultiple choice

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You want to monitor the cost and latency of your agentic application in production. Which service should you integrate with your Azure AI Foundry project?

Question 120mediummultiple choice

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A user asks a question that triggers a 'Blocked' response from Azure AI Content Safety, even though the query seems harmless. What is the best step to investigate this?

Question 121easymultiple choice

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What is the primary purpose of a 'Vector Store' in a RAG-based agentic application?

Question 122hardmultiple choice

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An agent is performing poorly on multi-hop reasoning tasks. What architectural pattern should you implement to improve performance?

Question 123mediummultiple choice

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You are configuring a Prompt Flow to use a custom Python tool. Which configuration is required to ensure the environment has the necessary libraries?

Question 124mediummultiple choice

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When using Prompt Flow, you notice that your flow is failing at the 'aggregate' node. What is the most likely cause?

Question 125mediummultiple choice

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You are using Azure AI Foundry to deploy an agent. You want to ensure that the agent only uses approved data sources. Which feature should you configure?

Question 126easymultiple choice

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Which Azure AI Foundry feature allows you to visualize the execution path of an agentic workflow?

Question 127mediummultiple choice

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You need to ensure that your agent's response is formatted as valid JSON. How should you approach this?

Question 128hardmultiple choice

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Your team is implementing 'Human-in-the-loop' (HITL) for an agent that performs account updates. Which mechanism should you use to pause the agent and wait for approval?

Question 129mediummultiple choice

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You are testing an agent in the Azure AI Foundry playground. You observe that the agent answers questions about its internal prompt. What is the most effective way to prevent this?

Question 130easymultiple choice

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What is the purpose of 'Batch Inference' in Azure AI Foundry?

Question 131hardmultiple choice

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You need to optimize the retrieval performance of your RAG agent. You find that the search engine returns too many irrelevant documents. What should you adjust?

Question 132hardmultiple choice

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You are experiencing high latency in your RAG agent. You confirm the model response time is fine, but the retrieval step is slow. What should you investigate?

Question 133mediummultiple choice

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You want to add a new tool to an agent. Which step is required to link the tool to the model?

Question 134easymultiple choice

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Which of the following is a core principle of Responsible AI in Azure AI Foundry?

Question 135easymultiple choice

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When evaluating an AI agent, what does the 'Coherence' metric measure?

Question 136mediummultiple choice

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How do you handle sensitive user data when using an Azure AI Agent?

Question 137mediummultiple choice

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You need to ensure that your agent is compliant with regional data residency requirements. Where should you check this?

Question 138mediummultiple choice

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You are using Prompt Flow to iterate on an agent. What is the benefit of using 'Environment Variables' in your flow?

Question 139hardmultiple choice

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An agent is designed to summarize meeting transcripts but keeps including internal meeting notes in the final summary. What is the most effective way to address this?

Question 140mediummulti select

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Which TWO actions should you take to ensure your agentic solution is 'Responsible'?

Question 141hardmulti select

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When designing a RAG-based agent, which THREE factors directly influence the quality of the retrieved information?

Question 142hardmulti select

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You are configuring tool integration for an agent. Which THREE aspects must be clearly defined in the tool definition for the agent to correctly use it?

Question 143mediummulti select

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Which THREE types of tools can be integrated into an Azure AI Agent?

Question 144easymulti select

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Which TWO components are essential for creating an effective system prompt?

Question 145hardmulti select

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Which TWO strategies are recommended to prevent 'Model Over-Reliance' or 'Automation Bias' in agents?

Question 146mediummulti select

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Which THREE settings in the Azure AI Foundry playground can directly affect the 'creativity' of an agent's response?

Question 147mediummultiple choice

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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?

Question 148hardmultiple choice

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You are building an agent in Azure AI Foundry using a prompt flow. You need to ensure that the agent only accesses specific internal documents and avoids hallucinating outside the provided context. Which grounding technique should you implement?

Question 149easymultiple choice

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When designing an agentic workflow in Azure AI Foundry, which component is used to manage the execution order and decision-making logic of multiple agents?

Question 150mediummultiple choice

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You are implementing a tool call in a Prompt Flow. The tool needs to interact with an external REST API. What is the recommended way to manage the API credentials securely?

Question 151hardmultiple choice

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You notice your Azure AI agent is producing offensive content. You need to configure a guardrail that intercepts the model output before it is sent to the user. Which service should you integrate?

Question 152easymultiple choice

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Which component in Azure AI Foundry allows you to visualize and debug the execution path of a model call, including input/output mapping?

Question 153mediummultiple choice

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You are building a RAG solution and observe that the model retrieves the correct documents but fails to use the information accurately. What is the most effective approach to improve performance?

Question 154mediummultiple choice

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

Question 155hardmultiple choice

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You are automating document ingestion for a RAG pipeline. Which feature allows you to automatically split large documents into smaller chunks during indexing?

Question 156easymultiple choice

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

Question 157mediummultiple choice

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You are deploying an LLM in Azure AI Foundry and want to restrict access to the endpoint to a specific virtual network. What should you configure?

Question 158hardmultiple choice

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You need to ensure that an LLM-based agent in your application follows a specific output schema (JSON) for downstream processing. What is the most reliable way to enforce this?

Question 159easymultiple choice

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When sharing a Prompt Flow with a teammate, which action allows them to run the flow without having to recreate the connections?

Question 160easymultiple choice

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What is the primary benefit of using the Model Catalog in Azure AI Foundry?

Question 161hardmultiple choice

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You are performing Retrieval-Augmented Generation. You need to ensure the retrieved data includes metadata for filtering. Where should this metadata be defined?

Question 162mediummulti select

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Which TWO of the following are valid methods to improve the quality of retrieved data in a RAG system?

Question 163hardmulti select

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

Question 164mediummulti select

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Which TWO criteria are typically used to evaluate the grounding of an LLM-based application?

Question 165hardmulti select

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Which THREE of the following are best practices for Responsible AI when using Generative AI solutions?

Question 166mediummulti select

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

Question 167hardmulti select

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

Question 168mediummultiple choice

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You are building an AI agent in Microsoft Foundry that must answer questions grounded exclusively in a set of internal PDF policy documents. The agent must cite the exact page of the source document in every response, and the documents are updated weekly. You want the least operational overhead while keeping citations accurate. What should you do?

Question 169mediummultiple choice

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You are building an Azure AI Foundry agent that answers employee benefits questions from an HR policy PDF set. Legal requires that every response cite the exact source page, and that unsupported answers are refused. You must maximize groundedness while keeping the existing PDFs unchanged. Which approach should you implement?

Question 170hardmulti select

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You are configuring a function-calling agent in Microsoft Foundry. The agent must call an internal order-status REST API. Security review requires that the agent never receives the API key directly and that calls are auditable per user. You also need the agent to recover gracefully when the API returns a transient 503. (Choose two.)

Question 171hardmultiple choice

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You are implementing a function-calling flow in an Azure AI Foundry agent. The agent must call a get_order_status function, but during testing it sometimes invents an order ID and calls the function with a fabricated value instead of asking the user. You need the agent to request the missing order ID from the user before invoking the function. What should you do?

Question 172easymultiple choice

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You are deploying a generative AI chat application on Azure OpenAI. Product owners want the model's responses to follow a strict JSON schema so the front end can render structured cards. You need the highest possible reliability that outputs conform to the schema. What should you configure?

Question 173easymultiple choice

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A developer on your team is configuring an Azure AI Foundry agent that must answer questions about a product catalog stored in Azure Cosmos DB for NoSQL. The agent must retrieve the current price and stock for a given product SKU at query time. Which tool should the agent use?

Question 174hardmultiple choice

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You are building an agentic solution in Microsoft Foundry where a planner agent delegates subtasks to several specialist agents. During testing, the planner repeatedly loses track of completed subtasks and re-delegates work, causing duplicate API calls and inflated costs. You need the planner to maintain reliable state across turns without exceeding the context window. What should you implement?

Question 175mediummulti select

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You are deploying a generative AI chat application built on Azure OpenAI in Azure AI Foundry. The application must stream tokens to the browser, and you need to configure it so that responses begin appearing to users as quickly as possible while remaining correct. Which two actions should you take? (Choose two.)

Question 176hardmultiple choice

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You are using Azure AI Foundry to evaluate a generative AI assistant that summarizes customer call transcripts. Reviewers complain that some summaries include details never present in the transcript. You need an automated metric that quantifies this specific defect during evaluation runs. Which metric should you use?