AI-102 Implement generative AI solutions Practice Question
You are developing a customer support chatbot using Azure OpenAI Service. The chatbot must only answer questions related to the company's product catalog and policies. You want to minimize the risk of the chatbot generating harmful or off-topic responses. Which approach should you use?
⚠ Common exam trap
It's easy for candidates to confuse content filtering parameters (temperature, top_p, max_tokens) with instruction-based control, assuming that reducing randomness or output length can prevent off-topic responses, when in fact only explicit system-level instructions can enforce domain constraints.
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
✓
Use a system message that instructs the model to only answer product-related questions.
A system message sets the foundational behavior of the model by providing high-level instructions that guide all subsequent responses. By explicitly instructing the model to only answer product-related questions, you establish a clear boundary that minimizes off-topic or harmful outputs. This approach leverages the model's instruction-following capability, which is more effective than parameter tuning alone for content restriction.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the max_tokens parameter to 100.
Why it's wrong here
Max_tokens only limits response length, not topic.
- ✓
Use a system message that instructs the model to only answer product-related questions.
Why this is correct
System messages define the assistant's behavior and constraints.
- ✗
Set the temperature parameter to 0.
Why it's wrong here
Temperature controls randomness, not topic adherence.
- ✗
Set the top_p parameter to 0.1.
Why it's wrong here
Top_p controls nucleus sampling, not topic restriction.
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