AI-102 Implement generative AI solutions Practice Question
Exhibit
Refer to the exhibit.
{
"role": "system",
"content": "You are a helpful assistant that provides information about company policies. Only answer questions based on the provided context. If the answer is not in the context, say 'I do not know.'"
}You are using Azure OpenAI Service with the system message shown in the exhibit. The model sometimes answers questions using general knowledge even when the context does not contain the answer. Which modification should you make to enforce the behavior?
⚠ Common exam trap
Microsoft often tests the misconception that prompt engineering (like repeating instructions) or temperature adjustments can enforce strict data-only behavior, when in reality the 'strict' parameter in Azure OpenAI On Your Data is the specific mechanism designed for this purpose.
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
✓
Set the 'strict' parameter to true in Azure OpenAI On Your Data configuration
The 'strict' parameter in Azure OpenAI On Your Data configuration forces the model to rely exclusively on the provided data sources and refuse to answer when the context lacks the information. This directly enforces the desired behavior of not falling back on general knowledge.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a user message repeating the instruction
Why it's wrong here
Repetition may not be enforced; model can still ignore.
- ✗
Reduce the temperature to 0
Why it's wrong here
Temperature affects randomness, not adherence to context.
- ✗
Fine-tune the model with examples of refusing to answer
Why it's wrong here
Fine-tuning is not required; the feature exists in Azure OpenAI On Your Data.
- ✓
Set the 'strict' parameter to true in Azure OpenAI On Your Data configuration
Why this is correct
The strict setting forces the model to use only the provided context.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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