AI-900 Describe features of generative AI workloads on Azure Practice Test 2 — 15 Questions

Question 1

A quality assurance team at a software company uses Azure OpenAI Service to generate compliance reports. They need the model to produce the exact same output for a given prompt every time the API is called, to ensure reproducibility during testing. Which parameter should they set to achieve this deterministic behavior?

Accepted Answer

Set temperature to 0. Setting temperature to 0 forces the model to choose the most likely token at each step, eliminating randomness and producing deterministic outputs for the same prompt. This is essential for reproducibility in testing scenarios where identical results are required across API calls.

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Set frequency penalty to 1

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Set top_p to 1

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Set max_tokens to the expected output length

Question 2

A developer uses Azure OpenAI Service to generate creative marketing copy. The API costs are based on the total number of tokens processed (input + output). To minimize costs, the developer wants to ensure that the generated text is as brief as possible while still being effective. Which parameter should the developer adjust in the API request?

Accepted Answer

max_tokens. Option C (max_tokens) is correct because this parameter directly controls the maximum number of tokens the model can generate in a single response. By setting a lower max_tokens value, the developer caps the length of the output, which reduces the total tokens processed (input + output) and thus lowers API costs. Other parameters influence the style or diversity of the output but do not directly limit the length of the generated text.

Answer

temperature

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top_p

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frequency_penalty

Question 3

A developer uses Azure OpenAI Service to generate product descriptions. Each description must be concise and not exceed 50 words. Which parameter should the developer set in the API request to control the output length?

Accepted Answer

max_tokens. The `max_tokens` parameter in the Azure OpenAI API directly controls the maximum number of tokens (words or subwords) in the generated output. By setting `max_tokens` to a value that corresponds to 50 words, the developer ensures the model stops generating once the limit is reached, producing concise descriptions.

Answer

Temperature

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top_p

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frequency_penalty

Question 4

A marketing team uses Azure OpenAI Service to generate social media posts. They want the generated text to be more creative and diverse, with unexpected word choices. Which parameter should they increase?

Accepted Answer

temperature. Increasing the temperature parameter makes the model more creative and diverse by raising the probability of sampling lower-probability tokens, leading to unexpected word choices. Temperature controls the randomness of token selection, with higher values (e.g., 0.9) producing more varied outputs, which aligns with the team's goal of generating creative social media posts.

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frequency_penalty

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presence_penalty

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top_p

Question 5

A marketing team uses Azure OpenAI Service to generate tagline options for a new product. They notice that the model often generates very similar taglines for the same prompt, lacking creativity. To increase the diversity and variety of the output, which parameter should they increase?

Accepted Answer

Temperature. Increasing the temperature parameter makes the model's output more random and diverse by scaling the probability distribution over possible next tokens. A higher temperature (e.g., 0.9) flattens the distribution, giving lower-probability tokens a better chance to be selected, which directly addresses the lack of creativity and variety in the generated taglines.

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Top P

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Frequency penalty

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Max tokens

Question 6

A financial analyst uses Azure OpenAI Service to generate summaries of quarterly earnings reports. The analyst provides the raw text of the report in the prompt and wants the summary to stick strictly to the facts presented in that text, without adding any external information or speculation. Which technique should the analyst employ to minimize the risk of the model inventing information?

Accepted Answer

Use grounding by including the report text in the prompt and explicitly instructing the model to base the summary only on that text.. Option B is correct because grounding the model with the source text and explicitly instructing it to base the summary solely on that text is the most direct way to reduce hallucination. Azure OpenAI Service relies on the prompt for context; by providing the raw report and a strict instruction, the model is constrained to extract facts from the provided content rather than generating novel information.

Answer

Set the temperature parameter to a high value.

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Set the frequency penalty to the maximum allowed value.

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Set the max_tokens parameter to a very small number.

Question 7

A writer uses Azure OpenAI Service to generate story ideas. The current configuration uses a temperature setting of 0, causing the model to produce identical outputs for the same prompt. The writer wants more creative and diverse outputs. Which parameter should be increased?

Accepted Answer

temperature. Temperature controls the randomness of the model's output. A temperature of 0 makes the model deterministic, always choosing the most likely next token, which leads to identical outputs for the same prompt. Increasing the temperature (e.g., to 0.7 or higher) introduces more randomness, allowing the model to sample from less likely tokens and produce more creative, diverse story ideas.

Answer

max_tokens

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top_p

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frequency_penalty

Question 8

A developer uses Azure OpenAI Service to generate code snippets. They need the model to produce the most likely completion each time, with no randomness or creativity. Which parameter should they set?

Accepted Answer

temperature = 0. Setting temperature = 0 forces the model to always select the token with the highest probability at each step, eliminating randomness and ensuring deterministic, most-likely completions. This is ideal for tasks like code generation where consistency and predictability are required, as it disables the sampling randomness that higher temperature values introduce.

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temperature = 1

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top_p = 0.5

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frequency_penalty = 0.5

Question 9

A developer uses Azure OpenAI Service to generate product reviews for an e-commerce site. The developer notices that the model often repeats the same phrases within the same review, making the output sound unnatural. Which parameter should the developer adjust to reduce this repetition?

Accepted Answer

Frequency_penalty. The frequency_penalty parameter reduces the likelihood of the model repeating the same phrases by penalizing tokens that have already appeared in the generated text. A higher frequency_penalty value (e.g., 0.5 to 1.0) discourages the model from reusing the same words or phrases, making the output more diverse and natural. This directly addresses the issue of repetitive phrasing in product reviews.

Answer

Temperature

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Top_p

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Max_tokens

Question 10

A developer uses Azure OpenAI Service to generate multiple alternative product slogans. The developer wants to get exactly 5 different slogan options in a single API call, each being a separate piece of text. Which parameter should the developer set to control the number of completions returned?

Accepted Answer

n. The 'n' parameter in Azure OpenAI Service specifies the number of completions (candidate responses) to generate for each API call. Setting n=5 returns exactly five distinct slogan options as separate text strings, fulfilling the requirement of a single request producing multiple alternatives.

Answer

temperature

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max_tokens

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stop

Question 11

A developer uses the Azure OpenAI Service to generate product descriptions for an e-commerce catalog. The developer notices that the generated text is often too long, exceeding the desired word count. Which parameter should the developer set in the API request to strictly limit the length of the generated output?

Accepted Answer

Max_tokens. Option D (max_tokens) is correct because it directly controls the maximum number of tokens (words or subwords) the model can generate in a single response. By setting this parameter to a specific value, the developer enforces a hard limit on output length, preventing the generated product descriptions from exceeding the desired word count.

Answer

Temperature

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Top_p

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Frequency_penalty

Question 12

A social media company uses Azure OpenAI Service to automatically generate captions for user-uploaded images. The company has a strict content policy that prohibits any generated captions containing profanity, hate speech, or self-harm references. Which feature of the Azure OpenAI Service should the company configure to automatically block such harmful content?

Accepted Answer

Content filtering. Content filtering is the correct feature because it is specifically designed to detect and block harmful content such as profanity, hate speech, and self-harm references in both input prompts and generated outputs. Azure OpenAI Service's content filtering system uses multi-class classification models to enforce responsible AI policies automatically, without requiring custom training or manual moderation.

Answer

Temperature parameter

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Top-p parameter

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Max-tokens parameter

Question 13

A developer uses Azure OpenAI Service to generate marketing copy. They want the model to produce more focused and deterministic responses, reducing the variety of outputs for the same prompt. Which parameter should the developer decrease?

Accepted Answer

Temperature. Temperature controls the randomness of the model's output. Lowering temperature (e.g., from 1.0 to 0.2) makes the model more deterministic and focused, reducing output variety for the same prompt. This is the correct parameter to adjust for more consistent marketing copy.

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Max tokens

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Top P

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Frequency penalty

Question 14

A legal research firm uses Azure OpenAI Service to answer questions about specific case law documents. They want the model to base its answers exclusively on the content of the provided documents, without using any external knowledge from its training. Which approach should they use?

Accepted Answer

Use the 'Azure OpenAI on your data' feature with a 'Search' data source containing the documents. Option C is correct because the 'Azure OpenAI on your data' feature with a 'Search' data source allows the model to retrieve and ground its answers exclusively on the content of the provided documents. This approach uses a search index (e.g., Azure Cognitive Search) to fetch relevant document chunks and inject them into the prompt, ensuring the model does not rely on its pre-trained knowledge. It is the only method that enforces strict document-based grounding without external knowledge leakage.

Answer

Increase the 'temperature' parameter to 0.0

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Use the system message to instruct the model to only use provided documents

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Set the 'max_tokens' parameter to a low value

Question 15

A developer uses Azure OpenAI Service to generate short product descriptions. The developer notices that the model sometimes produces nonsensical or very low-probability words that make the output less coherent. The developer wants to reduce the chance of such outputs while still allowing some creative variability. Which parameter should the developer adjust in the API request?

Accepted Answer

Set the top_p parameter to a value like 0.9. Option B is correct because setting `top_p` to 0.9 (nucleus sampling) instructs the model to consider only the tokens whose cumulative probability mass reaches 90%, thereby cutting off very low-probability (nonsensical) tokens while still allowing creative variability from the top 90% of likely tokens. This directly addresses the developer's goal of reducing incoherent outputs without fully deterministic generation.

Answer

Decrease the temperature parameter to 0.1

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Increase the stop parameter to include more stop sequences

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Increase the max_tokens parameter to allow longer descriptions