1Z0-1127-25 Practice Test 43 — 15 Questions

Question 1

A developer is using the OCI Generative AI Agents service to build a RAG application. They have uploaded policy PDFs to an OCI Object Storage bucket. What is the next step to make the documents searchable?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Create a knowledge base from the Object Storage bucket. In OCI Generative AI Agents, you create a knowledge base from data sources like Object Storage. The agent then uses this knowledge base to retrieve relevant information for answering questions. Creating a dedicated cluster or fine-tuning is not required for RAG with agents.

Answer

Create a dedicated AI cluster to host the documents

Answer

Use the Embeddings API to embed each PDF manually

Answer

Fine-tune a model on the PDFs

Question 2

Which OCI Generative AI model is designed to rerank and improve the relevance of documents retrieved by a search system?

Accepted Answer

Cohere Rerank. Cohere Rerank is specifically designed for reranking documents to improve relevance ranking.

Answer

Cohere Embed

Answer

Cohere Command R

Answer

Meta Llama 3

Question 3

A user wants to quickly test different prompts and parameters (temperature, max tokens) with various OCI Generative AI models without writing any code. Which tool should they use?

Accepted Answer

The OCI Generative AI Playground. The OCI Generative AI Playground provides an interactive web UI to test models and adjust parameters.

Answer

The InferenceClient SDK in Python

Answer

OCI CLI with generative-ai commands

Answer

OCI Cloud Shell

Question 4

Which OCI Generative AI model is specifically designed to generate embeddings for English text?

Accepted Answer

Cohere embed-english-v3.0. Cohere embed-english-v3.0 is the embedding model for English text. The other options are either generative models or multilingual embedding models.

Answer

Meta Llama 3 8B

Answer

Cohere embed-multilingual-v3.0

Answer

Cohere Command R

Question 5

An OCI Generative AI user wants to host a fine-tuned model with guaranteed low latency for a production application. Which option should they choose?

Accepted Answer

Provision a Dedicated AI Cluster with model units for the fine-tuned model. A Dedicated AI Cluster provides dedicated inference capacity with low latency, ideal for production fine-tuned models. Shared infrastructure may have variable latency.

Answer

Use the Chat API with a base model

Answer

Use the on-demand shared inference endpoint

Answer

Use the OCI Generative AI Playground

Question 6

A developer is using the Embedding API to create embeddings for a clustering task. They want to ensure the embeddings are optimized for clustering similar documents. Which input type should they specify?

Accepted Answer

clustering. The input type 'clustering' optimizes embeddings for clustering tasks.

Answer

search_query

Answer

search_document

Answer

classification

Question 7

A prompt engineer is testing a new prompt for a Q&A system. The prompt includes ambiguous wording that causes the model to answer inconsistently. Which TWO steps should the engineer take to resolve this? (Choose two.)

Accepted Answer

Test the prompt with a diverse set of inputs to identify remaining ambiguities. Clarifying the prompt removes ambiguity. Testing with diverse inputs helps uncover edge cases. A/B testing would compare variants but does not directly fix ambiguity. Temperature reduction does not clarify instructions.

Answer

Use A/B testing between the original and rewritten prompt to measure improvement

Answer

Increase the temperature to encourage diverse responses

Answer

Reduce the max tokens to force shorter answers

Question 8

A prompt engineer wants to generate a poem in a specific rhyming scheme (ABAB). Which combination of prompt components is LEAST likely to succeed?

Accepted Answer

Only task instruction: 'Write a poem'. Providing only a task instruction ('Write a poem') without specifying the rhyme scheme or giving examples leaves the model to choose its own structure. The other options give explicit formatting or examples.

Answer

Task instruction: 'Write a poem' and output format specification: 'Use ABAB rhyme scheme'

Answer

Task instruction: 'Write a poem in ABAB rhyme scheme' and an example stanza

Answer

Task instruction: 'Write a poem' with a few-shot example of an ABAB poem

Question 9

Which parameter controls the randomness of the model's output by adjusting the probability distribution of the next token?

Accepted Answer

Temperature. Temperature adjusts the logits before softmax, making lower values (e.g., 0.1) more deterministic and higher values (e.g., 0.9) more random.

Answer

Frequency penalty

Answer

Top-p

Answer

Max tokens

Question 10

Which TWO are best practices for securing a generative AI endpoint on OCI? (Select TWO)

Accepted Answer

Store API keys in OCI Vault. OCI Vault provides a secure, centralized service for storing and managing API keys used to authenticate requests to generative AI endpoints. Storing keys in Vault prevents hardcoding them in application code or configuration files, reducing the risk of exposure and enabling automated rotation and access control via IAM policies.

Answer

Enable OCI Logging for audit

Answer

Use a public endpoint with IP restrictions

Answer

Disable authentication for internal use

Question 11

Which prompt engineering technique asks the model to explain its reasoning process step-by-step before arriving at the final answer?

Accepted Answer

Chain-of-thought prompting. Chain-of-thought prompting explicitly instructs the model to think step by step, improving reasoning accuracy.

Answer

Tree-of-thought prompting

Answer

Self-consistency

Answer

Zero-shot prompting

Question 12

A developer is using a Cohere Command model via OCI Generative AI. They want the model to generate responses strictly in JSON format for a specific task, but the model sometimes outputs additional explanatory text. Which prompt engineering technique is MOST effective?

Accepted Answer

Add a preamble: 'You are a JSON generator. Output only valid JSON. Do not include any other text.'. Using a system prompt to set the persona (e.g., 'You are a JSON generator') and including a step-by-step instruction reduces unwanted text. Cohere's preamble works like a system prompt to enforce constraints.

Answer

Include a single example of a JSON output in the user message

Answer

Set the temperature to 0.0 to make the model deterministic

Answer

Use a stop sequence '}' to force the model to stop after the JSON

Question 13

Which prompting technique involves providing the model with a few examples of input-output pairs within the prompt to guide its behavior?

Accepted Answer

Few-shot prompting. Few-shot prompting includes several demonstrations of the desired task, helping the model understand the expected output format and reasoning.

Answer

Zero-shot prompting

Answer

Self-consistency prompting

Answer

Chain-of-thought prompting

Question 14

A prompt engineer is refining a prompt that currently produces outputs with excessive repetition. Which TWO parameters can be adjusted to reduce repetition? (Choose two.)

Accepted Answer

Frequency penalty. Frequency penalty discourages tokens that have already appeared, and presence penalty discourages tokens that have appeared at all. Both reduce repetition. Temperature and max tokens do not directly target repetition.

Answer

Temperature

Answer

Max tokens

Answer

Top-p

Question 15

A prompt engineer is designing a system to answer customer queries using OCI Generative AI. They want to ensure the model's responses are concise, accurate, and consistent. Which TWO prompt engineering practices should they implement? (Select two.)

Accepted Answer

Include a system prompt specifying 'You are a customer support agent. Answer concisely in two sentences.'. Setting a low temperature reduces randomness (consistency). Including a system prompt with tone and length constraints directly addresses conciseness and format.

Answer

Remove any context from the prompt to avoid biasing the model

Answer

Use the tree-of-thought technique for every query

Answer

Set temperature to 0.9 to encourage creative responses