AWS Certified AI Practitioner
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An HR assistant model must answer employee policy questions based on the company handbook stored in an S3 bucket. The system retrieves relevant policy paragraphs and includes them in the prompt before generating the answer. Which prompting approach is being used?
Real Exam
Community
JJin
A
Few-shot Prompting
B
Contextual / Retrieval-Augmented Prompting (RAG)
C
Zero-shot Prompting
D
Chain-of-Thought Prompting
Explanation:
Explanation
This scenario describes Retrieval-Augmented Generation (RAG), which is a contextual prompting approach where:
- Retrieval Phase: The system retrieves relevant information from an external knowledge source (in this case, the company handbook stored in an S3 bucket)
- Augmentation Phase: The retrieved relevant policy paragraphs are included in the prompt as context
- Generation Phase: The model generates an answer based on the provided context
Why other options are incorrect:
- A) Few-shot Prompting: This involves providing examples of input-output pairs in the prompt, not retrieving external documents
- C) Zero-shot Prompting: This involves asking the model to perform a task without any examples or retrieved context
- D) Chain-of-Thought Prompting: This involves breaking down complex problems into intermediate reasoning steps, not retrieving external documents
Key characteristics of RAG:
- Uses external knowledge sources
- Retrieves relevant information at inference time
- Provides retrieved context in the prompt
- Particularly useful for domain-specific knowledge that may not be in the model's training data
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