Free Oracle 1Z0-1127-25 Exam Questions

Become Oracle Certified with updated 1Z0-1127-25 exam questions and correct answers

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Total 234 Questions | Updated On: Dec 07, 2025

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Question 1

How does the integration of a vector database into Retrieval-Augmented Generation (RAG)-based Large Language Models (LLMs) fundamentally alter their responses?

A : It transforms their architecture from a neural network to a traditional database system.

B : It shifts the basis of their responses from pretrained internal knowledge to real-time data retrieval.

C : It enables them to bypass the need for pretraining on large text corpora.

D : It limits their ability to understand and generate natural language.

Answer: B

Question 2

What is the purpose of Retrieval Augmented Generation (RAG) in text generation?

A : To generate text based only on the model-s internal knowledge without external data

B : To generate text using extra information obtained from an external data source

C : To store text in an external database without using it for generation

D : To retrieve text from an external source and present it without any modifications

Answer: B

Question 3

When considering the capabilities of code models, multi-modal LLMs, and language agents, which of the following scenarios would be LEAST likely?

A : A code model is used to generate code snippets based on natural language descriptions.

B : A multi-modal LLM is used to translate a spoken language conversation with image references.

C : A language agent helps a user troubleshoot an Oracle Cloud resource issue through a chat interface.

D : A standard LLM is used to write a creative poem based on a provided theme.

Answer: D

Question 4

What potential drawback can arise when using overly complex or lengthy prompts for LLMs?

A : The LLM might generate a more creative and interesting output.

B : The LLM might struggle to focus on the essential aspects of the task.

C : There is no downside; longer prompts always provide better results.

Answer: B

Question 5

Which component of Retrieval-Augmented Generation (RAG) evaluates and prioritizes the information retrieved by the retrieval system?

A : Encoder-decoder

B : Ranker

C : Generator

D : Retriever

Answer: B

Page: 1 / 47

Total 234 Questions | Updated On: Dec 07, 2025

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