What’s New
Amazon Bedrock AgentCore enables the building of a multimodal WhatsApp ordering assistant and provides a backend that integrates multiple channels (text, voice notes, calls). This solution uses the Meta WhatsApp Business Platform as the customer front, Amazon Nova 2 and Amazon Nova 2 Sonic for text and voice processing, and connects to the restaurant backend through the Model Context Protocol (MCP). (Source: aws.amazon.com)
How It Works
AgentCore allows for the addition or removal of channels without changing the backend by separating the channel and order logic. Specifically, it uses the AWS Cloud Development Kit (AWS CDK) to deploy the entire system and the Amazon Bedrock Converse API for text processing. Additionally, Amazon Nova 2 Lite handles text processing, and Amazon Nova 2 Sonic performs real-time voice processing. (Source: aws.amazon.com)
Memory Lifecycle Management
AgentCore’s memory lifecycle policy is a mechanism that prevents long-running agents from retaining old context. This solution uses AWS Step Functions and Amazon Bedrock to run a nightly lifecycle workflow, which scores, integrates, and deletes the agent’s memory to maintain response quality and compliance. (Source: aws.amazon.com)
Key Takeaways for Engineers
- Use AWS CDK to build a multimodal WhatsApp ordering assistant.
- Leverage the Model Context Protocol (MCP) to manage the agent’s memory lifecycle.
- Customize text processing using the Amazon Bedrock Converse API.
Summary
- Use AWS CDK to build a multimodal WhatsApp ordering assistant.
- Leverage MCP to manage the agent’s memory lifecycle.
- Use the Amazon Bedrock Converse API to customize text processing.