Q25 — AWS AIF-C01 Ch.2

Question 25 of 100 | ← Chapter 2

A company wants to use large language models (LLMs) from Amazon Bedrock to develop a chat interface for its product documentation, which is stored as PDF files. Which solution meets these requirements in the most cost-effective way?

• A. Use prompt engineering to include one PDF file as context in the user prompt when submitting to Amazon Bedrock.
• B. Use prompt engineering to include all PDF files as context in the user prompt when submitting to Amazon Bedrock.
• C. Fine-tune the model using all PDF documents via Amazon Bedrock, then use the fine-tuned model to process user prompts.
• D. Upload the PDF documents to an Amazon Bedrock knowledge base. When users submit prompts to Amazon Bedrock, leverage the knowledge base to provide contextual information. ✓

Correct Answer: D. Upload the PDF documents to an Amazon Bedrock knowledge base. When users submit prompts to Amazon Bedrock, leverage the knowledge base to provide contextual information.

Explanation

Option D uses the knowledge base to manage PDF documents and retrieve context on-demand, avoiding the context-length limitations inherent in embedding full documents directly in every prompt (Options A/B) and eliminating the high cost and complexity of model fine-tuning (Option C). Bedrock knowledge bases employ vectorized storage and semantic retrieval, charging only for the context actually retrieved and used—aligning with cost-effectiveness.