Free Databricks Databricks-Generative-AI-Engineer-Associate Exam Dumps Questions & Answers

All of the following are Python APIs used to query Databricks foundation models. When running in an interactive notebook, which of the following libraries does not automatically use the current session credentials?

• A.OpenAI client
• B.Databricks Python SDK
• C.REST API via requests library
• D.MLflow Deployments SDK

A Generative AI Engineer has deployed a customer-support agent in production that retrieves product documentation and generates responses. SMEs have been reviewing agent responses and providing feedback through a web interface that captures ratings of 1-5 stars and written comments. The engineer needs to systematically collect this feedback and use it to create an evaluation dataset that can be used to compare future agent versions against the current baseline performance.
Which approach should the engineer use to accomplish this task?

• A.Log the SME ratings and comments directly to a Delta table with the corresponding user queries and agent responses, then use MLflow to create an evaluation dataset from this table and register it for future agent evaluations.
• B.Export only the written SME comments to a text file and manually score them using a custom script, then use the script's output as the evaluation dataset for future agent comparisons.
• C.Use the customer review app to collect SME feedback, then directly deploy the highest-rated responses as the new agent baseline without storing them as a formal evaluation dataset.
• D.Use Unity Catalog to create a view that filters only 5-star-rated interactions, then register this view as the evaluation dataset to benchmark all future agent versions.

A Generative AI Engineer is managing prompt templates using MLflow v3.x for a document summarization pipeline. A regulatory audit requires the team to demonstrate exactly which prompt version was used to generate outputs on a specific date three months ago, including the exact prompt text and any variables used at that time.
Which combination of MLflow v3.x capabilities allows the engineer to satisfy this audit requirement?

• A.MLflow autologging and Delta Lake time travel on the inference table.
• B.MLflow Prompt Registry version history and logged runs that reference the prompt name and version used during inference.
• C.MLflow Model Registry webhooks and a downstream audit log stored in an external database.
• D.MLflow experiment tags and an automatically scripted changelog stored in a Databricks notebook.

A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in PDF format. These PDFs can contain both text and images. They want to develop a solution using the least amount of lines of code.
Which Python package should be used to extract the text from the source documents?

• A.flask
• B.beautifulsoup
• C.unstructured
• D.numpy

A team wants to serve a code generation model as an assistant for their software developers. It should support multiple programming languages. Quality is the primary objective.
Which of the Databricks Foundation Model APIs, or models available in the Marketplace, would be the best fit?

• A.Llama2-70b
• B.MPT-7b
• C.CodeLlama-34B
• D.BGE-large