1Z0-1127-25 Using OCI Generative AI Service Practice Test 3 — 15 Questions

Question 1

An organization wants to use OCI Generative AI to summarize long legal documents. They need to ensure the summary is concise and retains key information. Which model parameter should they set to control the length of the summary?

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

Accepted Answer

max_tokens. The `max_tokens` parameter directly controls the maximum number of tokens (words or subwords) the model can generate in its response. By setting a lower value for `max_tokens`, the organization can enforce a concise summary, ensuring the output length is capped while retaining key information. Other parameters like `temperature` or `top_p` affect randomness or diversity, not output length.

Answer

frequency_penalty

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top_p

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temperature

Question 2

An enterprise wants to use OCI Generative AI to generate personalized email campaigns. They have a large customer database with preferences and past purchase history. Which design is best for high relevance and scalability?

Accepted Answer

Use a pipeline: retrieve relevant customer data and inject into prompt.. It implements a retrieval-augmented generation (RAG) pattern, which is the recommended approach for personalizing outputs at scale in OCI Generative AI. By retrieving only the relevant customer data (e.g., recent purchases, preferences) and injecting it into the prompt, you keep the context window efficient, reduce token costs, and avoid exceeding model limits. This design also allows the model to generate unique, context-aware emails without the overhead of fine-tuning per customer or the rigidity of rule-based systems.

Answer

Use a single prompt with all customer details as context.

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Fine-tune a model on each customer's history separately.

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Use a rule-based engine with AI-generated templates.

Question 3

Which TWO configuration steps are required to enable OCI Generative AI service in a tenancy? (Select two.)

Accepted Answer

Subscribe to the service in the tenancy.. Both options D and E are correct. To use OCI Generative AI service, you must first subscribe to the service at the tenancy level (option D) and then create an IAM policy to grant users or groups access to the service (option E). Simply enabling the service in the console is not a step; the service is enabled through subscription. Networking components like a VCN or service gateway are not prerequisites, and dynamic groups are not required for basic access.

Answer

Enable the generative AI service in the console.

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Set up a VCN with service gateway.

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Create a dynamic group.

Question 4

Which THREE OCI Generative AI service features help in controlling the cost of API calls? (Select three.)

Accepted Answer

Using a smaller model. Using a smaller model (Option A) reduces cost because OCI Generative AI service pricing is based on model size and compute resources required. Smaller models have fewer parameters, leading to lower per-token inference costs, making them ideal for simpler tasks where high accuracy is not critical.

Answer

Increasing temperature

Answer

Enabling response streaming

Question 5

Refer to the exhibit. A user in group GenAIUsers tries to use the `oci generative-ai model chat` command but gets 'not authorized'. Why?

Accepted Answer

The statement should be 'use' instead of 'read'.. The OCI IAM policy for Generative AI requires the 'use' verb to allow inference operations like chat, not the 'read' verb. The 'read' verb only grants permission to view metadata and list resources, not to invoke the model for chat completions. The error 'not authorized' occurs because the policy statement incorrectly uses 'read' instead of 'use', which is the required permission for the `oci generative-ai model chat` command.

Answer

The policy is not active yet.

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The command requires managing the model.

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The group is not in the correct compartment.

Question 6

Refer to the exhibit. The API Gateway fails to invoke the Generative AI service. What is the most likely missing configuration?

Accepted Answer

The API Gateway is not in the same VCN as the service's private endpoint.. The API Gateway must be in the same VCN as the Generative AI service's private endpoint to invoke the service. Private endpoints are accessible only within the same VCN or via VCN peering; if the gateway is in a different VCN, the request will fail due to network routing restrictions. This is a common misconfiguration when deploying OCI API Gateway with private endpoints for Generative AI.

Answer

The API Gateway does not have an internet gateway.

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The JWT token is expired.

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The Generative AI model is not deployed.

Question 7

A company wants to use OCI Generative AI service to generate email summaries for customer support. They need to ensure low latency and data residency in Frankfurt. What should they use?

Accepted Answer

Use the managed serving endpoint in Frankfurt region.. Managed serving endpoints in OCI Generative AI are pre-deployed, fully managed endpoints that provide low-latency inference and are available in specific regions, including Frankfurt. This ensures data residency in Frankfurt while meeting the latency requirements for real-time email summarization.

Answer

Use the playground in US region.

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Use OCI AI Quick Actions.

Answer

Create a dedicated AI cluster in Frankfurt.

Question 8

A developer receives a 403 error when calling the OCI GenAI API from a function. They have set up policies for the function's dynamic group. What is the most likely cause?

Accepted Answer

Missing IAM policy for GenAI service.. A 403 error when calling the OCI GenAI API from a function indicates an authorization failure. Even if the function's dynamic group is correctly configured, the IAM policy must explicitly grant the dynamic group permission to invoke the GenAI service. Without a policy statement like 'Allow dynamic-group [name] to use generative-ai-family in compartment [name]', the API call is denied, resulting in a 403 Forbidden.

Answer

The request body format is incorrect.

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The model is not available in the region.

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The API key is invalid.

Question 9

A company notices that their OCI GenAI managed serving endpoint returns incomplete responses for long prompts. What is the most likely cause?

Accepted Answer

The model's context window is exceeded.. When a prompt exceeds the model's context window, the model cannot process the entire input, leading to truncated or incomplete responses. OCI GenAI managed serving endpoints enforce a maximum context length (e.g., 4096 tokens for many models), and any prompt longer than this limit will be cut off, causing incomplete output.

Answer

The max tokens parameter is set too high.

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The top_p value is too low.

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The temperature is set too high.

Question 10

An architect is designing a GenAI solution for document summarization that must meet GDPR compliance. The data should not leave the EU. OCI GenAI models are available in Frankfurt, London, and Paris. Which is the best approach?

Accepted Answer

Deploy a dedicated AI cluster in Frankfurt and upload data to Object Storage in Frankfurt.. Deploying a dedicated AI cluster in Frankfurt ensures that all data processing and storage remain within the EU, meeting GDPR compliance. By using Object Storage in the same region, data never leaves the EU boundary, and the dedicated cluster provides full control over data residency and processing, unlike managed endpoints that may route data through other regions.

Answer

Use the managed serving endpoint in Frankfurt.

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Use the playground in any EU region.

Answer

Use a pre-trained model from OCI's catalog.

Question 11

Which TWO actions are required to enable a user to access OCI Generative AI service?

Accepted Answer

Subscribe to the GenAI service in the OCI Console.. To use OCI Generative AI service, a user must first subscribe to the service in the OCI Console. This subscription step activates the service for the tenancy, making it available for use. Without this explicit subscription, the service remains disabled and inaccessible, even if other prerequisites like IAM policies are in place.

Answer

Create a dedicated AI cluster.

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Enable the GenAI service in the region's service limits.

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Install the OCI SDK.

Question 12

A company uses OCI Generative AI service for customer support summarization. They notice the model frequently misses key details and generates hallucinations. What should they do first?

Accepted Answer

Adjust the prompt to be more specific and include few-shot examples.. Adjusting the prompt to be more specific and including few-shot examples is the first and most effective step to reduce hallucinations and improve detail capture in OCI Generative AI. Prompt engineering directly guides the model's attention and output format without altering core parameters or models, addressing the root cause of missing key details.

Answer

Increase the temperature parameter.

Answer

Use a different base model.

Answer

Increase the max tokens.

Question 13

A financial institution wants to use OCI Generative AI to analyze sensitive customer documents. They need to ensure no data leaves OCI and the model is fine-tuned on their proprietary data. Which deployment option should they choose?

Accepted Answer

Dedicated AI cluster with private endpoint.. A Dedicated AI cluster with private endpoint ensures that all data processing and model fine-tuning occur within OCI's network boundary, with no data egress to the public internet. This deployment option provides a fully isolated environment where the model can be fine-tuned on proprietary customer data while meeting strict data residency and security requirements.

Answer

Serverless inference with data isolation.

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OCI Functions with GPU.

Answer

OCI Data Science notebook session.

Question 14

Which TWO are benefits of using OCI Generative AI service's dedicated AI cluster?

Accepted Answer

Ability to fine-tune models on custom data.. Dedicated AI clusters in OCI Generative AI service provide isolated compute resources that allow you to fine-tune foundation models on your own custom datasets. This is a key benefit over the serverless offering, which only supports inference and does not permit model customization. Fine-tuning enables domain-specific optimization, improving accuracy for specialized tasks. Option E is correct because dedicated clusters offer lower latency compared to serverless endpoints. With dedicated resources, there is no resource contention or cold start delays, resulting in more consistent and faster inference responses, which is critical for real-time applications.

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Automatic scaling to handle large workloads.

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Built-in content filtering for all outputs.

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No need to provide any training data.

Question 15

Which THREE factors should be considered when choosing a model for a summarization task using OCI Generative AI?

Accepted Answer

Number of parameters.. The number of parameters (B) is a key factor because it directly correlates with the model's capacity to learn complex patterns and generate coherent summaries. Larger parameter models generally produce higher-quality summaries but require more resources. The context window size (D) determines how much text the model can consider at once, which is critical for summarizing long documents. Supported languages (E) ensure the model can handle the input language appropriately. These three factors are directly relevant to summarization task performance in OCI Generative AI.

Answer

Inference endpoint location.

Answer

Model training data cut-off date.