AI-102 Implement generative AI solutions Practice Question
You are deploying an Azure OpenAI model for a public-facing FAQ assistant. The assistant must answer only questions covered by a fixed set of approved topics, and any off-topic question should receive a polite refusal. Which approach most directly enforces this behavior?
⚠ Common exam trap
A common mix-up: candidates confuse safety content filters with topical scope control, when filters only block harmful categories rather than off-topic questions.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure a system message that defines the allowed topics and instructs the model to refuse anything outside them.
The system message is the model's persistent instruction set, making it the natural place to declare allowed topics and refusal behavior. For a fixed FAQ scope, this directly shapes every response. The other settings influence sampling, safety categories, or capacity, none of which restrict the assistant to approved topics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Raise the frequency_penalty parameter to reduce repeated off-topic phrases.
Why it's wrong here
Frequency_penalty discourages repeating tokens that already appeared in the text. It does not define or enforce topic boundaries, so the model can still answer off-topic questions using fresh wording. This parameter affects stylistic repetition, not the scope of permissible content.
- ✗
Deploy the model with the lowest available quota tier to limit how many questions users can ask.
Why it's wrong here
Quota tiers constrain request volume and throughput, not the subject matter of responses. Users could still receive off-topic answers until the quota is exhausted, and throttling would harm legitimate use. Limiting capacity does not enforce the approved-topic boundary the scenario requires.
- ✗
Set the model deployment's content filter to block the 'violence' category at high severity.
Why it's wrong here
Content filters target harmful categories such as violence, hate, and sexual content. An off-topic but benign question about sports or weather would not trigger these filters, so the assistant would still answer it. Content filtering is a safety control, not a topical scope control.
- ✓
Configure a system message that defines the allowed topics and instructs the model to refuse anything outside them.
Why this is correct
The system message sets the model's operating instructions and persona for every turn in the conversation. Defining the permitted topics and the refusal behavior there gives the model a consistent boundary to apply across all user turns. This is the most direct, low-overhead way to constrain scope for a simple FAQ assistant.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.