AWS Certified AI Practitioner (AIF-C01) · Objective 2.1
Choosing a context window
2.1Standard
Summarize and compare long contracts.
Choose how to process the full document.
Choose two decisions.
Hint 1: Focus on the requirement
Compare model context capacity with cost, latency, and information loss, using staged processing when a source is too large.
Hint 2: Key terms
Review context windows and hierarchical summarization.
Context window
The token range a model can process for one request's input and output.
Output reservation
Capacity held for the generated response after input tokens are counted.
Hierarchical summarization
Summarizing sections first and then combining those summaries into a larger summary.
Information loss
Important meaning, conditions, or exceptions omitted during compression.
× Incorrect
Measure document tokens, reserved output, cost, latency, and quality, and evaluate chunking, retrieval, or staged summaries when a single context is insufficient.
Detailed explanation
A
CorrectEvaluate chunking, retrieval, and staged summaries for boundary information loss
Long documents can be handled within limits.
B
IncorrectConcatenate documents without bounds
Limits, cost, and exposure are ignored.
C
IncorrectA longer context guarantees accurate understanding
Length and quality are different.
D
CorrectMeasure document tokens, reserved output, cost, latency, and quality
Model fit is based on actual constraints.
Check official documentation
Compare the following points with the official documentation.
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