Amazon Bedrock Flows Agent

Overview

The Bedrock Flows Agent is a specialized agent class in the Agent Squad that integrates directly with Amazon Bedrock Flows. This integration enables you to orchestrate your Bedrock Flows alongside other agent types (Bedrock Agent, Lex, Bedrock API…), providing a unified and flexible approach to agents orchestration.

Key Features

• Support for cross-region Bedrock Flows invocation
• Support for multiple flow input output type via flow input/output encoder/decoder callbacks

Creating a BedrockFlowsAgent

Python Package

If you haven’t already installed the AWS-related dependencies, make sure to install them:

pip install "agent-squad[aws]"

Basic Example

TypeScript

import { BedrockFlowsAgent } from 'agent-squad';

const techFlowAgent = new BedrockFlowsAgent({
  name: 'tech-flow-agent',
  description: 'Specialized in AWS services',
  flowIdentifier: 'AEXAMPLID',
  flowAliasIdentifier: 'AEXAMPLEALIASID',
  enableTrace:true
});

Python

from agent_squad.agents import BedrockFlowsAgent, BedrockFlowsAgentOptions

tech_flow_agent = BedrockFlowsAgent(BedrockFlowsAgentOptions(
    name="tech-flow-agent",
    description="Specializes in handling tech questions about AWS services",
    flowIdentifier='AEXAMPLID',
    flowAliasIdentifier='AEXAMPLEALIASID',
    enableTrace=True
))

Flow Input Encoder callback

Amazon Bedrock Flows Input supports multiple type of document output:

• String
• Number
• Boolean
• Object
• Array

In the default definition of the BedrockFlowsAgent, the output document type is a string. If you need to send an object, array, number or a boolean to your Flow input, you can use the flow input callback to transform the input payload based on your needs.

Here are an example for TS and python:

TypeScript

// implementation of the custom flowInputEncoder callback
const flowInputEncoder = (
agent: Agent,
input: string,
kwargs: {
userId?: string,
sessionId?: string,
chatHistory?: any[],
[key: string]: any  // This allows any additional properties
}
) => {
if (agent.name == 'tech-flow-agent'){
return {
  "question":input,
};
} else {
return input
}
}

// passing flowInputEncoder to our BedrockFlowsAgent
const techFlowAgent = new BedrockFlowsAgent({
name: 'tech-flow-agent',
description: 'Specialized in AWS services',
flowIdentifier: 'AEXAMPLID',
flowAliasIdentifier: 'AEXAMPLEALIASID',
flowInputEncoder: flowInputEncoder,
enableTrace: true
});

Python

# implementation of the custom flowInputEncoder callback
def flow_input_encoder(agent:Agent, input: str, **kwargs) -> Any:
  if agent.name == 'tech-flow-agent':
    # return a dict
    return {
      "question": input
    }
  else:
      return input #input as string

# passing flowInputEncoder to our BedrockFlowsAgent
tech_flow_agent = BedrockFlowsAgent(BedrockFlowsAgentOptions(
    name="tech-flow-agent",
    description="Specializes in handling tech questions about AWS services",
    flowIdentifier='AEXAMPLID',
    flowAliasIdentifier='AEXAMPLEALIASID',
    flow_input_encoder=flow_input_encoder,
    enableTrace=True
))

Sample Code

You can find sample code for using the BedrockFlowsAgent in both TypeScript and Python:

• TypeScript Sample
• Python Sample