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AWS Multi-Agent Orchestrator 

The AWS Multi-Agent Orchestrator is a flexible and powerful framework designed to manage multiple AI agents seamlessly while handling complex, multi-turn conversations. By intelligently routing queries and maintaining context across interactions, it empowers developers to build robust, scalable, and efficient AI solutions tailored to diverse needs.

Key Features and Benefits

  • Intelligent Query Routing: Analyzes user input to determine the most suitable agent for each task, ensuring accurate and contextually relevant responses.
  • Context Preservation: Maintains conversation history across interactions, enabling seamless multi-turn conversations.
  • Pre-built and Customizable Components: Comes with ready-to-use components for quick deployment while offering integration options for custom agents and storage solutions.
  • Scalability: Suitable for applications ranging from basic chatbots to complex AI systems, scaling effortlessly with your needs.

How It Works

AWS Multi-Agent Orchestrator 
AWS Multi-Agent Orchestrator 
  1. User Input Analysis: The system begins by analyzing the user’s query through a Classifier.
  2. Agent Selection: The Classifier evaluates agent characteristics and conversation history to select the most appropriate agent.
  3. Agent Processing: The chosen agent processes the query and generates a response.
  4. Context Update: The orchestrator updates the conversation history and stores the interaction.
  5. Response Delivery: The user receives the response, completing the cycle.

Demo Application

To provide hands-on experience, the Multi-Agent Orchestrator includes a Demo App with specialized agents. This interactive application showcases the orchestrator’s ability to handle diverse topics with ease.

Demo Agents in Action

  1. Travel Agent: Assists with flight bookings using an Amazon Lex Bot.
  2. Weather Agent: Provides weather updates through a Bedrock LLM Agent and the Open-Meteo API.
  3. Restaurant Agent: Offers dining suggestions powered by an Amazon Bedrock Agent.
  4. Math Agent: Solves mathematical problems using Bedrock LLM Agent tools.
  5. Tech Agent: Answers technical questions using a Bedrock LLM Agent.
  6. Health Agent: Addresses health-related queries with a Bedrock LLM Agent.

Watch the system effortlessly switch between topics, maintaining context and delivering precise responses—even for brief follow-ups.

Getting Started: Examples and Quick Start

Ready-to-Run Scripts

Explore standalone scripts in Python and TypeScript for quick experimentation.

Demo Applications

  • Chat Demo App: Interactive chat interface showcasing multi-agent orchestration.
  • E-commerce Support Simulator:
    • Automated responses for common queries.
    • Intelligent routing for complex issues.
    • Real-time communication with human-in-the-loop for exceptional cases.

Sample Projects

Discover various implementations:

  • Chat-Demo-App: Multi-agent chat application.
  • E-commerce Support Simulator: AI-driven customer support solution.
  • Chat-Chainlit-App: Chat application built with Chainlit.
  • Fast-API Streaming: Implementation with real-time streaming.
  • Text-to-Structured Output: Transform natural language into structured data.

All examples are available in both Python and TypeScript. Detailed documentation is provided for easy setup and customization.

Creative Implementations

The versatility of the Multi-Agent Orchestrator enables innovative solutions across industries:

Multilingual AI Chatbot for Flight Reservations

Create a chatbot that supports multiple languages using Amazon Lex and other agents, with minimal effort.

AI-Powered E-Commerce Support System

Design a customer support system that blends automated responses with human oversight for complex queries.

AI-Driven Call Center

Build a voice-enabled AI customer service platform using Amazon Connect, Lex, and Bedrock.

TypeScript Version: Quick Setup

Install the package with:

bashCopy codenpm install multi-agent-orchestrator

Example Usage

typescriptCopy codeimport { MultiAgentOrchestrator, BedrockLLMAgent, LexBotAgent } from "multi-agent-orchestrator";

const orchestrator = new MultiAgentOrchestrator();

// Add specialized agents
orchestrator.addAgent(
  new BedrockLLMAgent({
      name: "Tech Agent",
      description: "Specializes in technology-related topics.",
      streaming: true
  })
);

orchestrator.addAgent(
  new LexBotAgent({
      name: "Travel Agent",
      description: "Helps users book and manage flight reservations.",
      botId: process.env.LEX_BOT_ID,
      botAliasId: process.env.LEX_BOT_ALIAS_ID,
      localeId: "en_US"
  })
);

// Route a query
const response = await orchestrator.routeRequest("I want to book a flight", 'user123', 'session456');

// Handle the response
console.log(response);

Conclusion

The AWS Multi-Agent Orchestrator is a game-changing framework for managing AI agents. Its flexibility, scalability, and robust features make it ideal for building intelligent, responsive, and context-aware systems across a range of applications. Whether you’re developing a multilingual chatbot or a sophisticated e-commerce support system, this orchestrator provides the tools and capabilities to turn your vision into reality.

Explore the demo apps and dive into the documentation to get started today!

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