Try and practice the latest Databricks : Databricks-Generative-AI-Engineer-Associate real questions & answers

A Generative AI Engineer is deploying a conversational agent that provides financial-analysis insights to internal analysts at a company. The company has standardized on Microsoft 365 for all internal communications and collaboration. The analysts are distributed across multiple time zones and primarily work within Microsoft Teams channels, where they already discuss financial data and share reports. The agent needs to integrate with the company's existing Azure Active Directory for authentication and must respect the company's data-governance policies. Users should be able to interact with the agent within their existing workflow without switching applications.
Which interface should the engineer implement for this agent deployment?

• A. Microsoft Teams integration to deploy the agent as a bot within Teams channels where analysts already collaborate.
• B. REST API endpoint with a custom frontend application hosted on the company's internal portal.
• C. Slack integration to enable the agent in a dedicated workspace for the financial-analysis team.
• D. Databricks Apps to create a custom web application that analysts can access through their browsers with SSO authentication.

A Generative AI Engineer is developing a chatbot designed to assist users with insurance-related queries. The chatbot is built on a large language model (LLM) and is conversational. However, to maintain the chatbot's focus and to comply with company policy, it must not provide responses to questions about politics. Instead, when presented with political inquiries, the chatbot should respond with a standard message:
"Sorry, I cannot answer that. I am a chatbot that can only answer questions around insurance." Which framework type should be implemented to solve this?

• A. Contextual Guardrail
• B. Security Guardrail
• C. Safety Guardrail
• D. Compliance Guardrail

Which of the following statements accurately identifies differences between the evaluation phase and the monitoring phase in the Generative AI application lifecycle within Databricks?

• A. The evaluation phase uses Mosaic AI Agent Evaluation and an evaluation dataset to assess an agent's performance metrics and traces, while the monitoring phase relies on inference tables as source data for creating a metrics profile.
• B. The evaluation phase uses all inference history to assess agent performance and readiness for production, while the monitoring phase uses only new inference-table records to monitor performance.
• C. The evaluation phase ensures the agent's responses comply with business rules in production, whereas the monitoring phase is focused on SLA and performance metrics.
• D. The evaluation phase logs and traces live API calls in production, while the monitoring phase runs metrics on inference tables containing those traces.

A Generative Al Engineer is setting up a Databricks Vector Search that will lookup news articles by topic within 10 days of the date specified An example query might be " Tell me about monster truck news around January 5th 1992 " . They want to do this with the least amount of effort.
How can they set up their Vector Search index to support this use case?

• A. Create separate indexes by topic and add a classifier model to appropriately pick the best index.
• B. Split articles by 10 day blocks and return the block closest to the query.
• C. pass the query directly to the vector search index and return the best articles.
• D. Include metadata columns for article date and topic to support metadata filtering.

A Generative AI Engineer has set up an endpoint with AI Guardrails turned on to block any incoming requests that divulge PII. They also have inference tables enabled for this endpoint. If an end user sends their phone number in their prompt, what will appear in the inference table for that record?

• A. The full answer that would have been sent without the PII block will appear in inference tables.
• B. The request will appear, but the response will be the error indicating that the request was blocked due to PII.
• C. The record will not appear in inference tables because it contains PII.
• D. The request will appear, but the response column will be blank.