Using Large Language Models on Amazon Bedrock for multi-step task execution

This article explores using Large Language Models (LLMs) on Amazon Bedrock for multi-step task execution, specifically demonstrating how to perform complex analytical queries using predefined API tools.

• Introduces a solution for breaking down complex queries into manageable steps
• Uses Synthetic Patient Generation dataset as an example
• Describes a two-stage approach: Plan and Execute
• Plan stage involves generating a structured JSON plan using API function signatures
• Execute stage programmatically carries out the planned steps
• Demonstrates ability to answer complex queries like finding the patient with the least number of vaccines

The solution showcases how LLMs can extend beyond text-based responses to provide actionable, context-aware outputs that can transform business analytics and decision-making processes.