AI-102 Implement generative AI solutions Practice Question
You need to generate a summary of a long article using Azure OpenAI. The article is 10,000 tokens long. What should you do to fit the article within the model's context window?
⚠ Common exam trap
Many exam-takers confuse parameters that control output behavior (temperature, max_tokens) with the fundamental input token limit, leading them to incorrectly believe adjusting these parameters can bypass the context window restriction.
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
✓
Split the article into smaller sections and summarize each section separately.
The article exceeds the model's context window (typically 4096 or 8192 tokens for GPT-3.5/4). Splitting the article into smaller sections and summarizing each separately allows you to process the entire content within the token limits, then combine the summaries for a final coherent output. This is a standard chunking strategy for long documents when using Azure OpenAI.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Split the article into smaller sections and summarize each section separately.
Why this is correct
Chunking the input fits within the context window.
- ✗
Increase the temperature parameter.
Why it's wrong here
Temperature does not affect token limits.
- ✗
Use a model with a smaller context window.
Why it's wrong here
Smaller context window makes the problem worse.
- ✗
Set max_tokens to a lower value.
Why it's wrong here
max_tokens limits output length, not input.
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