Orchestrating Generative AI Applications With AWS Step Functions and Amazon Bedrock
By integrating AWS Step Functions with Amazon Bedrock, you can leverage generative AI in your workflows to create powerful AI-driven applications. These applications can be used to generate responses to user queries, automate tasks, and more.
Integrating Bedrock models into AWS Step Functions state machines also gives developers the ability to chain multiple model prompts together to generate more complex and coherent responses. This technique is known as AI prompt-chaining and is commonly used in chatbots to generate more human-like responses.
In this lab, you will work with the Amazon Bedrock integration in AWS Step Functions to interact with a foundation model and orchestrate an AI prompt-chaining workflow.
Learning objectives
Upon completion of this intermediate-level lab, you will be able to:
- Configure an Amazon Bedrock integration on an AWS Step Functions state machine
- Compile conversation history by leveraging the AWS Step Functions Pass state
- Orchestrate AI prompt-chaining workflows using AWS Step Functions
Intended audience
- Candidates for the AWS Certified Machine Learning Specialty certification
- Cloud Architects
- Software Engineers
Prerequisites
Familiarity with the following will be beneficial but is not required:
- Amazon Bedrock
- AWS Step Functions
The following content can be used to fulfill the prerequisites:
Environment before
Environment after
Jun is a Cloud Labs Developer with previous experience as a Software Engineer and Cloud Developer. He holds the AWS Certified Solutions Architect and DevOps Engineer Professional certifications. He also holds the AWS Certified Solutions Architect, Developer, and SysOps Administrator Associate certifications.
Jun is focused on giving back to the growing cloud community by sharing his knowledge and experience with students and creating engaging content.