Amazon Bedrock is a service that provides foundational models from companies like Anthropic, Cohere, and Meta. It has various features that allow us to build generative AI applications. You can also use Amazon Bedrock to build knowledge bases using the foundational models available and then create AI agents using third-party platforms such as CrewAI, a framework that allows us to create, coordinate, and manage AI agents.
In this Cloud Lab, you’ll create an S3 bucket and upload data about a hypothetical company. You’ll then create an Aurora cluster and use it as a vector store of the knowledge base. You’ll also use AWS Secrets Manager to store Aurora cluster credentials. After this, you’ll enable the Amazon Titan foundational model and use it to create a knowledge base in Amazon Bedrock. Finally, you’ll create CrewAI agents that will use the knowledge base you created to reply to user queries and test these agents by assigning them different tasks.
After completing this lab, you’ll be well-equipped to use Bedrock Knowledge Bases and base models in your AI applications and will be able to build CrewAI agents integrated with Amazon Bedrock. The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
