Implement generative AI solutions

Which TWO actions can you take to mitigate the risk of generating harmful content when using Azure OpenAI Service? (Choose two.)

You are testing an Azure OpenAI model with the parameters shown in the exhibit. The model generates very short responses. Which parameter should you modify to allow longer responses?

You are implementing a Retrieval Augmented Generation pattern with Azure AI Search and Azure OpenAI. Users complain that answers occasionally cite documents the user is not authorized to see, because the index contains all departments' content. You need to restrict retrieval so that each user only receives chunks from documents their identity permits. What should you do?

Your team is building a generative AI application on Azure OpenAI that must call an internal order-lookup REST API whenever a user asks about an order status. The model must decide when to call the API, and the application must execute the call and return the result to the model for the final answer. Which capability should you implement?

You need to provide a generative AI solution that can answer questions based on a large set of PDF documents stored in Azure Blob Storage. The solution must support natural language queries and return citations from the documents. Which Azure service combination should you use?

Your team is developing an AI-powered document summarization solution using Azure OpenAI. You need to ensure that the solution complies with Microsoft's Responsible AI principles, specifically transparency. Which configuration should you implement?

You are using Azure OpenAI Service to generate product descriptions. The output is often too verbose. You need to reduce the length of generated text without changing the model. Which parameter should you adjust?

A developer wants to use Azure OpenAI to generate text from a prompt. Which parameter controls the diversity of the generated output?

Which THREE are valid parameters when calling the Azure OpenAI Service chat completions API?

You are implementing a generative AI solution using Azure OpenAI Service. The solution must generate responses that are grounded in your organization's proprietary documents and must return citations that link back to the source documents. You need to configure the deployment to meet these requirements. Which two actions should you perform? (Choose two.)

A company uses Microsoft Copilot for Microsoft 365 to automate email responses. They want to ensure that the Copilot responses comply with their data governance policies and do not expose sensitive information. What should they configure?

You are developing a generative AI solution using Azure OpenAI Service. The solution must generate product descriptions based on a set of attributes provided by the user. You need to ensure the output adheres to a specific JSON schema. Which feature should you use to enforce the structure of the model's response?

A team is using Azure OpenAI Service to summarize long legal contracts. They observe that summaries sometimes miss clauses located near the end of the document. The contracts are far longer than the model's maximum context window. What should they implement to improve coverage of the entire document?

You are building a generative AI chatbot using Microsoft Copilot Studio. The chatbot must answer questions from a PDF document and a SQL database. Which THREE data sources can you configure? (Choose three.)

Refer to the exhibit. You are troubleshooting an Azure OpenAI API call that is returning incomplete responses. The response stops mid-sentence. Which parameter should you adjust?

You are deploying a generative AI solution that uses Azure OpenAI Service with your own data stored in Azure AI Search. Users report that answers are sometimes pulled from documents the user is not permitted to see, because the retrieval step searches the entire index. You need to ensure each user only receives answers grounded in documents they are authorized to access, without creating a separate index per user. What should you do?

You operate a RAG assistant on Azure OpenAI Service that answers questions over a product catalog. The index contains thousands of items, and users complain that answers mix details from unrelated products. You need retrieval to consider semantic meaning and handle paraphrased queries while returning only the most relevant items. What should you implement?

You are implementing a RAG (Retrieval-Augmented Generation) solution using Azure AI Search and Azure OpenAI Service. The solution is returning answers that are not relevant to the user query. What is the most likely cause?

You are building an internal knowledge assistant with Azure OpenAI Service. Responses must be grounded in a curated set of HR policy documents stored in Azure AI Search, and every response must include a citation to the specific source chunk. You already deployed a GPT-4o model and created the search index. You need to add the grounding layer with the least development effort. What should you do?

You run the Azure CLI command shown in the exhibit. After a few minutes, the deployment fails with a quota error. What is the most likely cause?

You are developing a generative AI application that must comply with responsible AI principles. Which Azure AI service should you use to detect and filter harmful content in both input prompts and output responses?

You are deploying a conversational AI solution using Microsoft Copilot Studio. The solution must comply with organizational data loss prevention (DLP) policies by preventing sensitive data from being sent to the underlying Azure OpenAI model. What should you configure?

Your team is building an internal knowledge assistant with Azure OpenAI Service. Legal requires that every generated answer include a traceable reference to the source document so reviewers can verify claims. The documents already live in Azure AI Search, and you want the service to return citation metadata alongside the generated text. Which feature should you configure?

You are designing a generative AI solution using Azure OpenAI Service. The solution must support multiple languages and provide consistent quality across languages. Which THREE actions should you take?

You need to generate a summary of a long article using Azure OpenAI. The article is 10,000 tokens long. What should you do to fit the article within the model's context window?

You deploy a GPT-4o model in Azure OpenAI Service for an internal assistant that summarizes long contracts. Legal requires that every generated summary be traceable to the exact source passages and that the assistant never answer from general world knowledge. You need the model to ground each statement in retrieved text and expose the supporting passages to the caller. What should you configure?

You are building a generative AI application with Azure OpenAI Service. The application must generate responses that are grounded in a specific set of internal documents stored in an Azure AI Search index. You want to use the built-in 'On Your Data' feature. Which configuration parameter should you set to ensure the model retrieves relevant documents before generating a response?

You are building an internal assistant on Azure OpenAI that must stream responses to a React web app while hiding the model endpoint key from the browser. The app already authenticates users with Microsoft Entra ID. You need the least-privilege approach that keeps the key out of client code. What should you do?

You are deploying a generative AI assistant on Azure OpenAI Service that must summarize user-supplied financial reports. Security policy requires that report contents never leave your Azure tenant and that the model must not be fine-tuned. You need to provision the resource so that prompt and completion data are not retained for human review and are not used to train any shared model. What should you configure?

You are using Azure OpenAI Service to generate marketing copy. You notice that the output sometimes contains factual inaccuracies about your company's products. Which action can you take to improve factual accuracy?

Which THREE factors should you consider when choosing between Azure OpenAI Service and Azure Machine Learning for deploying a generative AI model?

Which TWO actions are required to enable a custom chatbot built with Azure OpenAI to answer questions based on a company's internal PDF documents?

Which TWO are valid ways to manage cost when using Azure OpenAI Service in a production application?

Refer to the exhibit. You are deploying an Azure AI Services resource using an ARM template. After deployment, you cannot access the resource from any client, including the Azure portal. What is the most likely cause?

You are building a conversational AI system using Azure OpenAI Service. The system must maintain context across multiple user turns. Which parameter determines how many previous messages are considered for the next response?

Which TWO actions should you take to ensure that a generative AI model deployed on Azure Machine Learning is compliant with data privacy regulations?

Your team is using the Azure OpenAI Batch API to process 200,000 product-description rewrites overnight. The job must complete within a fixed window and cost as little as possible, and results are not needed interactively. A developer reports that the submitted batch job failed with an error about the input file. What is the most likely cause?

A company is using Azure OpenAI to generate customer support responses. They want to ensure the model does not use any personally identifiable information (PII) in its outputs. What should they implement?

You are using Azure OpenAI Service to summarize customer emails. The summaries must be concise and contain only key information. Which prompt engineering technique should you apply?

You are developing a generative AI application that uses Azure OpenAI Service to summarize large documents. The application experiences high latency when processing requests. You need to reduce the latency without changing the model. What should you do?

You are building a generative AI solution with Azure OpenAI Service that uses the GPT-4 model. The solution must process user requests and call external APIs to retrieve real-time data. You need to ensure the model can invoke the correct API based on user intent and return the results in a structured format. Which feature should you implement?

Which TWO Azure AI services can be used to build a conversational chatbot that uses generative AI? (Choose two.)

You are developing a solution that uses Azure OpenAI to generate customer support responses. You want to prevent the model from repeating the same phrases. Which parameter should you adjust?

You are reviewing an ARM template for deploying Azure OpenAI Service. The template includes a deployment for gpt-35-turbo with a capacity of 100. You need to ensure that the deployment uses provisioned throughput instead of standard. What should you modify?

You are building a generative AI application with Azure OpenAI Service. The application must use your own product catalog data stored in an Azure AI Search index to ground model responses. You need to configure the model deployment so that retrieved documents are automatically injected into the prompt without you manually assembling the context in application code. What should you configure on the model deployment?

You are developing a generative AI application using Azure OpenAI Service. The application must generate summaries of customer emails and then extract action items. You want to minimize the number of API calls and ensure the model outputs structured JSON. What should you do?

Refer to the exhibit. You are reviewing the configuration of an Azure OpenAI Service resource. The resource is configured with customer-managed keys for encryption. What is the primary benefit of this configuration?

You need to monitor usage and costs of your Azure OpenAI Service deployments. Which Azure tool should you use?

Your organization uses Azure AI Document Intelligence to extract data from invoices. The extraction accuracy for total amounts is low. You have a labeled dataset of 500 invoices. You need to improve the model's accuracy for the 'total amount' field. What should you do?

You run the Azure CLI command shown in the exhibit to create an online endpoint for a generative AI model. The deployment fails because the selected VM instance type is not available in the East US region. Which action should you take to resolve the issue?

You are building a generative AI application using Azure OpenAI Service. The application must provide factual answers based on your company's internal knowledge base. You need to minimize the risk of the model generating incorrect information (hallucinations). Which approach should you take?

You are deploying a generative AI chat application that calls an Azure OpenAI model deployment. The application must stream partial completions to the browser as tokens are produced and must reduce perceived latency for long answers. Which two request options should you configure? (Choose two.)

You are testing an Azure OpenAI chat completion. The response shown in the exhibit is returned. What does the finish_reason of 'content_filter' indicate?

Match each Azure Cognitive Search skill to its capability.

A developer is building a generative AI application with Azure OpenAI Service. The application must stream partial responses to users as tokens are generated, rather than waiting for the complete response. Which parameter should the developer set in the chat completion request?

You are using Azure OpenAI Service to generate product descriptions. You notice that the model occasionally outputs descriptions that contain factual inaccuracies about product specifications. You want to reduce these hallucinations without changing the model. What should you do?

You are deploying an Azure OpenAI model for a healthcare application. You need to ensure that the model does not generate medical advice and that all responses include a disclaimer. Which configuration should you use?

You are deploying a generative AI feature that drafts marketing copy with an Azure OpenAI GPT-4o deployment. The application must stream partial responses to the browser so users see text as it is generated, rather than waiting for the full completion. What should you enable in your API call?

You are building a generative AI application with Azure OpenAI Service that summarizes long legal contracts. Legal reviewers report that the summaries omit obligations buried in the middle of very long documents, even though the documents fit within the model's maximum context window. You need to improve recall of those mid-document clauses while minimizing added latency. What should you do first?

A company uses Azure OpenAI to generate product descriptions. They want to ensure that the descriptions are consistent in style and tone. Which strategy should they use?

You are building a solution to generate product descriptions using Azure OpenAI Service. You need to ensure that the output adheres to a specific tone (professional, friendly) and length (50-100 words). Which parameter should you adjust?

You are developing a customer support chatbot using Azure OpenAI Service. The chatbot must only answer questions related to the company's product catalog and policies. You want to minimize the risk of the chatbot generating harmful or off-topic responses. Which approach should you use?

Which TWO features of Azure AI Content Safety can help you moderate user-generated content in a social media application?

You are building a generative AI feature in an application using the Azure OpenAI SDK. The feature must stream tokens to the user as they are generated and must also capture the full response for logging. Which implementation approach satisfies both requirements?

You are deploying a generative AI model using Azure AI Foundry. The model must be accessible only from within a specific virtual network. Additionally, you need to monitor all API calls for auditing. Which two configurations are required? (Choose two.)

You are developing a solution that uses Azure Document Intelligence to extract data from invoices and then uses Azure OpenAI to summarize the extracted data. The solution occasionally produces summaries that omit key fields like the invoice total. What should you do to improve accuracy?

You are designing a generative AI solution using Azure OpenAI Service with your own data indexed in Azure AI Search. Which THREE components are essential for the retrieval-augmented generation (RAG) pattern?

You are developing a generative AI solution that uses Azure OpenAI Service. The solution must generate product descriptions in multiple languages. You need to ensure that the model consistently follows specific formatting rules, such as including a bullet list of features. Which strategy should you use?

You are developing a generative AI feature with Azure OpenAI Service. The feature must generate a structured JSON object that conforms to a specific schema so it can be consumed by a downstream application without post-processing. What should you use to constrain the model output to the schema?

You need to generate a poem using Azure OpenAI. The poem should be about nature and have a cheerful tone. Which parameter should you adjust to influence the tone?

You are developing a generative AI application that uses Azure OpenAI Service. You want to ensure that the application does not generate offensive content. Which Azure service should you use?

A company uses Azure OpenAI Service to generate product descriptions. They notice that the descriptions sometimes contain factually incorrect information. Which strategy should they use to reduce hallucinations?

You are building a generative AI assistant on Azure OpenAI that must call internal REST APIs to look up order status. You decide to use function calling. Which TWO actions are required to make the assistant reliably invoke the correct API and return a coherent answer? (Choose two.)

Your organization uses Azure OpenAI Service with a data source configured as 'Azure OpenAI on your data'. You notice that the responses include outdated information even though the underlying data source has been updated. What is the most likely cause?

You are developing a generative AI solution that uses Azure OpenAI Service. You need to control the creativity of the generated responses. Which parameter should you adjust?

You are preparing an Azure OpenAI deployment for a production generative AI application that must stream responses to a web front end and must limit the cost of overly long conversations. You need to configure parameters that control response length and streaming behavior. Which two parameters should you set? (Choose two.)

You are designing a solution that uses Azure AI Document Intelligence to extract data from invoices. The solution must classify invoices by vendor and extract line items. Which prebuilt model should you use?

Refer to the exhibit. You are configuring an Azure OpenAI Service deployment for document summarization. The current parameters produce summaries that are often too verbose. You need to make the summaries more concise while maintaining factual accuracy. Which parameter change should you make?

You are deploying a chatbot using Azure OpenAI Service with a custom dataset indexed in Azure AI Search. Users report that the chatbot frequently responds with 'I don't know' for questions that the dataset should cover. What is the most likely cause?

You are building a generative AI solution with Azure OpenAI Service. Prompts must be assembled from a system instruction, retrieved document chunks, and the user's question. You need a mechanism that automatically inserts the retrieved chunks into a designated placeholder in a prompt template before the request is sent to the model. What should you use?

A developer wants to integrate a pre-built AI model that can extract key information from invoices, such as vendor name, invoice date, and total amount. Which Azure AI service should they use?

Refer to the exhibit. You are deploying a generative AI model as an online endpoint in Azure Machine Learning. You receive complaints that the endpoint returns 503 errors during peak hours. What is the most likely cause?

You are deploying a generative AI assistant with Azure OpenAI Service. Company policy requires that the assistant must never output profanity, and that any attempt to elicit such content must be blocked at the service level rather than filtered in application code. You need the least administrative effort to enforce this. What should you do?

You are developing a chat application that uses Azure OpenAI Service to answer customer queries. The solution must ensure that the model does not generate harmful or offensive content. Which Azure AI service should you configure?

You are building a generative AI solution that uses Azure OpenAI function calling to let the model invoke backend APIs. During testing, the model sometimes invents parameter values that cause API errors. You need to make function invocation more reliable. What should you do?

A development team is building an Azure OpenAI chat application and wants the model to return structured JSON that matches a defined schema containing an 'intent' field and a 'confidence' field. The application will parse the response directly. Which deployment parameter should the team use to constrain the output format?

Your company uses Microsoft Copilot for Microsoft 365. You need to ensure that Copilot only accesses data from approved SharePoint sites and does not use any other organizational data. What should you configure?

You have configured a system message for an Azure OpenAI chat completion deployment as shown in the exhibit. Users are reporting that the assistant sometimes refuses to answer questions that are clearly within the scope of the provided data. What is the most likely issue?

Which TWO actions can you take to reduce the cost of using Azure OpenAI Service for a chat application?

You are building a generative AI feature that drafts marketing copy in English and must also produce accurate French and German versions. The team wants a single deployment that handles all three languages without maintaining separate prompt templates per language, and the translations must preserve the marketing tone. Which Azure OpenAI capability should the solution rely on?

You are building a generative AI feature where an Azure OpenAI model must call internal functions, such as looking up an order status and issuing a refund, based on the user's natural language request. You need the model to decide which function to invoke and to incorporate the function result into its answer. Which two actions should you take? (Choose two.)

You are using Azure OpenAI Service to generate code snippets. The output must be safe and free of security vulnerabilities. Which TWO practices should you follow? (Select TWO.)

Which THREE components are required to build a custom chat application using Azure OpenAI Service that can answer questions based on your own private data?

Your company wants to build a custom generative AI model that generates architectural designs. The model should be trained on the company's proprietary dataset of floor plans and designs. Which Azure service should you use?

You have deployed a generative AI model using Azure Machine Learning. The model is used for generating financial reports. You need to monitor the model's performance and detect data drift in the input data. What should you use?

Your company uses Azure AI Content Safety to moderate user-generated content in a chat application. You need to detect and block sexual content in multiple languages. Which pre-built category should you configure?

You need to generate realistic synthetic data using Azure OpenAI Service to train a machine learning model. The data must be diverse and cover edge cases. Which approach should you use?

You are deploying a solution that uses Azure OpenAI Service to generate financial reports. You need to ensure the outputs are accurate and consistent. Which TWO parameters should you adjust? (Choose two.)

You are a generative AI engineer at a financial services company. The company uses Azure OpenAI Service to generate investment summaries. You have deployed a GPT-4 model with a content filter set to 'Low' for hate speech. The model frequently generates summaries that include biased language against certain demographics. You need to reduce biased outputs while maintaining the ability to generate detailed financial analysis. You cannot afford to retrain the model. You have the following options: A) Change the content filter severity to 'High' for all categories, B) Add a system message instructing the model to avoid bias and provide examples of unbiased summaries in the prompt, C) Use the Azure AI Language service to detect bias in the output and regenerate if bias is found, D) Deploy a different model like GPT-3.5 which has less bias. Which course of action should you take?

You are developing a custom chatbot using Azure AI Bot Service and Language Understanding (CLU). The chatbot needs to escalate to a human agent when the user's sentiment is negative. Which component should you use to detect sentiment?

You are implementing a generative AI solution using Azure OpenAI. You need to ensure that the model's outputs do not contain certain inappropriate words or phrases. Which feature should you configure?

A developer uses the Azure OpenAI API to generate code. They want to ensure that the generated code is in Python. Which parameter should they set?

You are building a generative AI solution with Azure OpenAI Service that must produce concise, factual answers using only a supplied knowledge base. During testing, the model sometimes invents details not present in the knowledge base. You need to reduce hallucinations without retraining the model. What should you do?

A company wants to generate personalized product descriptions for its e-commerce site using Azure OpenAI. They need to ensure the model's output adheres to brand guidelines and does not generate prohibited content. Which approach should they use?

Refer to the exhibit. { "content_filters": [ { "type": "hate", "action": "block", "severity": "high" }, { "type": "sexual", "action": "block", "severity": "medium" }, { "type": "self_harm", "action": "block", "severity": "low" } ] } You deploy an Azure OpenAI model with the above content filter configuration. A user submits a prompt that the system rates as "hate" at severity level "medium". What happens?

You are deploying a generative AI solution that must produce structured JSON order confirmations from free-text customer emails. Downstream systems reject any response that is not valid JSON matching a fixed schema. Which approach best guarantees schema-conformant output from an Azure OpenAI chat completion?

You are building a generative AI solution using Azure OpenAI Service that must generate code snippets. The solution must ensure that the generated code does not include any known vulnerable patterns, such as SQL injection. You need to implement a safeguard. What should you do?

You are deploying a generative AI application using Azure OpenAI Service. The application must generate responses that are creative and varied for a marketing campaign. Which parameter should you adjust to increase the randomness of the model's output?

Which THREE components are required to build a custom copilot using Microsoft Copilot Studio that can answer questions from a SharePoint document library?

A company uses Azure OpenAI to generate product descriptions. They notice that the model occasionally produces descriptions that include false claims about product features. The company needs to reduce the frequency of these inaccuracies without changing the training data. Which parameter adjustment would be most effective?

You are building a generative AI application that must process large volumes of PDF documents and generate summaries using Azure OpenAI. The solution must be cost-effective and handle variable workloads. Which architecture should you recommend?

You are a cloud solution architect at a legal firm. The firm needs to automate the summarization of legal documents. They have a large corpus of past case summaries and legal documents stored in Azure Blob Storage. They want to use Azure OpenAI to generate summaries for new documents. The solution must ensure that the generated summaries are accurate and do not contain hallucinated legal facts. The firm also requires that the solution be serverless and minimize operational overhead. You need to design the solution. Option A: Use Azure OpenAI with a system message that instructs the model to be accurate. Deploy the model as a web app on Azure App Service and call it from Azure Functions triggered by new blob uploads. Option B: Use Azure OpenAI with Retrieval-Augmented Generation (RAG) by indexing the past case summaries in Azure AI Search. Use Azure Functions to process new documents, retrieve relevant cases, and pass them as context to the model. Store summaries in Azure Cosmos DB. Option C: Fine-tune an Azure OpenAI model on the past case summaries and deploy it as a managed endpoint. Use Azure Logic Apps to trigger summarization when new blobs are added. Option D: Use Azure OpenAI with the chat API and provide the entire document in the prompt. Use Azure Container Instances to run a service that calls the API and writes summaries back to Blob Storage. Which option should you choose?

A company is building a chatbot using Azure OpenAI Service to answer customer queries. The chatbot must not generate harmful or offensive content. Which Azure AI service should be integrated to filter inappropriate content?

A healthcare startup is developing a chatbot that uses Azure OpenAI to answer patient questions. They need to ensure that the chatbot only uses information from their verified medical database and does not generate unsupported medical advice. What is the best approach?

You are building a generative AI assistant with Azure OpenAI Service that must answer questions using a large corpus of internal product manuals. The manuals are updated weekly, and the assistant must reflect changes without retraining the model. You need to implement a retrieval-augmented generation (RAG) pattern. What should you use to index and retrieve relevant manual content?

You are deploying a retrieval-augmented generation chat solution on Azure OpenAI. During testing, users report that the model confidently answers questions using facts that are not in the indexed documents, and that retrieved chunks sometimes come from the wrong department's SharePoint site. You need to reduce these ungrounded answers without retraining the model. (Choose two.)

Your company wants to build a custom Copilot for customer support using Microsoft Copilot Studio. The support team needs to query a backend CRM system securely using the Copilot. Which authentication method should you configure for the custom connector to the CRM?

You are building an Azure OpenAI solution that must generate product descriptions from a small set of 40 curated examples that demonstrate your brand voice. You want the model to imitate the style without changing the model weights or incurring the cost of a fine-tuning job. What should you do?

You are implementing a generative AI chat solution on Azure OpenAI Service. The solution must ground its answers in a large internal knowledge base and return inline citations that link back to the exact source chunks. You want to minimize custom code and use a managed retrieval pipeline. Which Azure OpenAI feature should you configure?

You are developing a generative AI application using Azure OpenAI. The application must log all prompts and completions for auditing, but sensitive data such as personal health information (PHI) must be redacted before logging. Which approach should you use?

You have deployed a chatbot using Azure OpenAI with a system message as shown. The chatbot sometimes provides incorrect answers that are not supported by the sources. What is the most likely cause?

Which TWO actions should you take to reduce the cost of using Azure OpenAI for a chatbot that handles high traffic?

You are deploying a conversational AI solution using Microsoft Copilot Studio. The solution must provide responses based on data from an internal knowledge base stored in SharePoint. Which feature should you configure?

You are building a generative AI solution using Azure OpenAI. The solution must generate responses that include factual information from a set of internal documents that are updated frequently. You need to ensure the model uses the latest document versions without retraining. What should you do?

You are designing a generative AI assistant that must produce deterministic, repeatable answers for a compliance workflow. The assistant uses Azure OpenAI chat completions and must return the same output for identical prompts. Which parameter setting should you apply?

Refer to the exhibit. You are deploying a GPT-4 model using Azure OpenAI Service. The deployment uses the Standard scale type. Which statement is true about this deployment?

You are deploying an Azure OpenAI model for a public-facing FAQ assistant. The assistant must answer only questions covered by a fixed set of approved topics, and any off-topic question should receive a polite refusal. Which approach most directly enforces this behavior?

You are deploying a generative AI application using Azure OpenAI Service. The application must generate responses in multiple languages while maintaining high accuracy. You need to minimize token usage. Which approach should you recommend?

Refer to the exhibit. You are configuring a system message for an Azure OpenAI deployment. The assistant is still generating harmful code despite the instruction. Which additional measure should you implement?

A company wants to generate product descriptions for thousands of items using an Azure OpenAI GPT-4 model. They need to ensure the descriptions match a consistent brand voice. Which approach is most efficient and cost-effective?

Refer to the exhibit. A developer runs this PowerShell script to call Azure OpenAI. The script fails with an authentication error. What is the most likely cause?

Your team ships a generative assistant that calls a custom function to look up live order status. Users report that the assistant sometimes invents an order status instead of calling the function, and that when it does call the tool the arguments are occasionally malformed. You need to make tool invocation more reliable while keeping the existing model. What should you do?

Refer to the exhibit. You are using Microsoft Graph to retrieve user information for use in a Microsoft 365 Copilot extension. The response shows that the mail and mobilePhone fields are null. What is the most likely reason?

You need to deploy a generative AI model that can generate images from text descriptions. Which Azure service should you use?

You are deploying a conversational AI chatbot using Azure AI Language service. The chatbot must be able to switch between multiple intents in a single conversation without restarting the session. Which feature should you enable?

Your organization is deploying a generative AI chatbot using Azure OpenAI Service. The chatbot must answer questions based on internal documents stored in Azure Blob Storage. You need to implement a retrieval-augmented generation (RAG) solution. Which THREE components are required? (Select THREE.)

You are a machine learning engineer at a large retail company. The company has thousands of product descriptions that need to be updated regularly. They currently use a manual process. You propose using Azure OpenAI to generate new descriptions based on product attributes. You have a dataset of existing product descriptions and attributes stored in an Azure SQL Database. The solution must be cost-effective, scalable, and must not require retraining the model. You need to design the solution. You have the following options: Option A: Use Azure OpenAI with few-shot learning by including examples in the prompt for each product. Deploy the model on an Azure Kubernetes Service (AKS) cluster for high throughput. Option B: Use Azure OpenAI with prompt templates that include product attributes and call the API for each product. Use Azure Logic Apps to orchestrate the workflow and store results back to Azure SQL Database. Option C: Fine-tune a custom model on the existing product descriptions and deploy it as a managed endpoint. Use Azure Data Factory to batch process all products. Option D: Use Azure OpenAI with the batch API to generate descriptions for all products at once, using a single prompt that lists all products and attributes. Store the batch output in Azure Blob Storage and then import into Azure SQL Database. Which option should you choose?

You are a data scientist at a healthcare company. You have deployed a GPT-4 model using Azure OpenAI to answer patient inquiries about medical conditions. The model is configured with temperature=0.3 and max_tokens=200. Recently, the compliance team flagged that some responses contain contradictory information compared to the official medical guidelines. You need to ensure the model's answers align strictly with the provided medical documents (stored as PDFs in Azure Blob Storage). You have access to Azure Cognitive Search and Azure AI Document Intelligence. The solution must minimize hallucinations and not require retraining the model. What should you do?

You deploy a chat application using Azure OpenAI Service. Users report that the model sometimes generates inappropriate content. You need to implement a safety system that can be customized for your organization's policies. What should you use?

You are designing a generative AI solution that uses Azure OpenAI GPT-4 to answer customer support questions. The solution must comply with Microsoft's Responsible AI principles, particularly transparency and accountability. Which implementation approach best meets these requirements?

An organization is deploying a conversational AI solution using Azure OpenAI. They want to ensure the model's responses are grounded in their own knowledge base documents to reduce hallucinations. Which approach should they implement?

You are deploying a generative AI model using Azure AI Foundry. The model must be accessible only from a specific virtual network. Additionally, you need to monitor all API calls for auditing. Which two configurations are required? (Choose two.)

A marketing team uses Azure OpenAI Service to draft product descriptions. They report that outputs vary widely in tone and sometimes ignore the required brand voice. You need to make responses follow a fixed set of style rules consistently across all requests without changing the model deployment. What should you do?

Your company uses Microsoft 365 Copilot to generate meeting summaries. Some users report that summaries include information from meetings they did not attend. What is the most likely cause?

Your organization is building a chatbot using Azure OpenAI Service. The chatbot must provide citations from a set of internal documents stored in Azure Blob Storage. You need to configure the solution to minimize token usage while ensuring citations are accurate. Which approach should you use?

You are using Azure OpenAI to generate product descriptions. You notice that the descriptions are often too similar to each other. Which parameter should you adjust to increase diversity?

Refer to the exhibit. An administrator runs this Azure CLI command to deploy a GPT-4 model in Azure AI Foundry. The command fails with an error that the deployment name already exists. What should the administrator do to resolve the issue?

Which THREE components are required to implement a Retrieval-Augmented Generation (RAG) solution with Azure OpenAI Service? (Choose three.)

You are deploying a generative AI solution by using Azure OpenAI Service. The solution must ground model responses in a private Azure AI Search index that contains product manuals. You need to configure the model deployment so that the service automatically retrieves relevant chunks from the index and includes them in the prompt at inference time. Which configuration should you use?

You need to create a chatbot that uses Azure OpenAI to answer questions about your company's internal policies. The responses must be based only on the provided policy documents. Which approach should you use?

A team is prototyping an Azure OpenAI chat application and wants to iterate quickly on prompt wording without changing application code or redeploying. They also want to compare outputs from different prompt variants side by side. Which Azure AI Foundry feature should they use?

You are building a generative AI solution using Azure Machine Learning prompt flow. The solution must allow business analysts without coding experience to modify prompts and evaluate different model versions. What should you do?

A company uses Azure OpenAI to generate marketing copy. They want to ensure that the generated content does not contain offensive language. Which feature should they enable?

You are developing a generative AI application that uses Azure OpenAI Service. The application must generate responses that are grounded in a specific set of documents stored in Azure Blob Storage. You want to use the simplest approach that allows the model to reference these documents without building a custom retrieval pipeline. What should you use?

You are using Azure OpenAI Service to generate code snippets for a development team. You notice that the generated code sometimes contains security vulnerabilities. You need to minimize the risk of generating insecure code while maintaining productivity. What should you do?

You are using Azure AI Foundry to fine-tune a GPT-3.5 model on a dataset of customer service conversations. The fine-tuning job fails with an error indicating that the training data format is invalid. What is the most likely issue?

You are building a generative AI solution using Azure OpenAI Service. The application must retrieve information from a large private knowledge base. You need to ensure the model uses only relevant documents from the knowledge base to generate answers. Which feature should you configure?

You are using Azure OpenAI Service to generate marketing copy. The marketing team reports that the generated content sometimes contains factual inaccuracies. You need to improve the factual accuracy of the generated content. What should you do?

You are prototyping a chat experience on Azure OpenAI and want the model to produce structured JSON that matches a schema your application can deserialize reliably. Which feature should you configure?

You are deploying a chat application using Azure OpenAI. The application should only answer questions based on a specific set of internal documents. Which THREE features should you use?

You need to generate an image of a cat wearing a hat using Azure OpenAI. Which model should you use?

You need to deploy a generative AI model that can be used by multiple applications within your organization. The model must support real-time inference with low latency. Which Azure service should you use?

Refer to the exhibit. A developer received this response from an Azure OpenAI chat completion call. The prompt was "What is the capital of France?". The finish_reason is "stop". What does this indicate?

Which TWO statements about Azure OpenAI Service content filters are true?

You are building an application that uses the Azure OpenAI Assistants API. The assistant must maintain conversational context across multiple user turns and use a code interpreter to analyze uploaded CSV files. Which two actions should you perform? (Choose two.)

You are building a generative AI solution using Azure AI Foundry. The solution must meet compliance requirements that require all model inputs and outputs to be auditable for a minimum of one year. What should you enable?

Which THREE factors should you consider when selecting a model for a generative AI solution on Azure?

You need to generate realistic synthetic data for training a machine learning model while ensuring the data does not contain personally identifiable information (PII). Which Azure service should you use?

A financial services firm wants to use Azure OpenAI to generate investment advice summaries. They must ensure that the model does not produce any advice that could be interpreted as personalized financial advice. What is the most effective strategy?

You are configuring an Azure OpenAI deployment for a generative AI solution that summarizes long legal contracts. Users report that summaries sometimes omit clauses near the end of documents. The documents are up to 120 pages. You need to improve completeness without changing the model. What should you do?

A legal team wants an assistant that drafts contract summaries. Their policy requires that every generated summary include traceable references to the exact clauses used and that reviewers be able to see which source passages informed each statement. You are using Azure OpenAI with your own document index. Which approach best meets the traceability requirement?

You are designing a generative AI solution that uses Azure OpenAI Service. The solution must generate code snippets in Python and JavaScript. You need to ensure the model reliably outputs code in the correct language based on user input. Which approach should you use?

You are building a generative AI assistant on Azure OpenAI Service that must invoke backend business functions, such as checking order status and issuing refunds, in response to natural-language requests. You want the model to decide when a function is needed and to supply structured arguments, while your application retains control over execution. Which two actions should you take? (Choose two.)

You are building a generative AI assistant that must summarize long technical manuals stored in Azure Blob Storage. The manuals are often 300 pages, and the model must produce a concise summary with references to page numbers. Which approach should you use?