Building Custom Amazon Bedrock Agents

In this detailed tutorial, Trevor Sullivan from StratusGrid walks viewers through the process of building custom Amazon Bedrock agents for automation. Amazon Bedrock is a managed service that simplifies the use of large language models (LLMs) by integrating them with AWS Lambda functions to perform actions based on user prompts. The video begins with an introduction to Amazon Bedrock and its capabilities, followed by an overview of the Bedrock agent workflow. Trevor explains how Bedrock agents can connect external tools to LLMs, enabling them to perform actions beyond just generating text responses. The core of the tutorial covers the creation of an OpenAPI specification, which defines the API endpoints and actions accessible to the LLM. Trevor demonstrates how to create a Bedrock agent, configure action groups, and implement Lambda functions to handle various tasks such as listing and deleting AWS CloudFormation stacks and adding tags to them. He walks through the entire process of setting up the Bedrock service, defining API routes, and writing Lambda function code to perform actions based on user prompts. The video also covers testing the agent, interpreting logs, and troubleshooting common issues. Trevor emphasizes the flexibility and power of Bedrock agents, highlighting their potential applications in various domains such as order management, retail inventory systems, and automated AWS account cleanup. The tutorial concludes with a discussion on integrating Bedrock agents with knowledge bases for retrieval-augmented generation (RAG) capabilities, allowing LLMs to query additional data sources. Overall, the video provides a comprehensive guide to building and deploying custom AI solutions using Amazon Bedrock agents.