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Tutorial: Build an Agentic AI Application with Agents for Amazon Bedrock
- This tutorial guides you on building an AI application with Agents for Amazon Bedrock to trigger a Lambda function for task execution.
- The application allows parents to book appointments with high school teachers using DynamoDB to store related data.
- The architecture includes components like Amazon Bedrock, Bedrock Agent, Action Group, Lambda Function, DynamoDB, and Jupyter Notebook.
- Prerequisites include using us-east-1, accessing Bedrock models, and setting up a SageMaker AI Domain.
- Building the application involves creating a SageMaker Notebook using a CloudFormation template and running commands in Jupyter Lab.
- Steps include installing required libraries, creating DynamoDB tables, setting up a Lambda function, and creating the agent and action group.
- Testing involves running prompts like checking teacher availability, booking appointments, and listing appointments.
- The agent uses reasoning and limited data to fulfill requests, showcasing its capabilities and limitations.
- Cleaning up at the end is crucial to avoid charges, including removing DynamoDB tables, Agent and Action Group, Lambda Function, and CloudFormation stack.
- Remember to run all clean-up steps to keep the cost below $1 for exploring the application.
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