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Integrating Semantic Kernel Python with Google’s A2A Protocol

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Table of Contents

  1. Task Routing and Delegation
  2. Agent Discovery
  3. Example Scenario
  4. Prerequisites
  5. Setup & Running
  6. Share Your Feedback

Task Routing and Delegation

The TravelManager dynamically routes tasks to specialized agents configured as plugins within the TravelManager. This ensures efficient handling of requests by directing them to the most suitable agents based on context.

Agent Discovery

Agents advertise their capabilities through structured "Agent Cards," allowing client agents to identify and select the most appropriate agent for a given task. This facilitates seamless communication using the A2A protocol.

Example Scenario

In this scenario, a user requests a budget-friendly trip plan with currency conversion. The TravelManager detects the currency needs and invokes the CurrencyExchangeAgent to fetch rates from Frankfurter for conversion.

Prerequisites

  • Python 3.10 or higher
  • Package manager
  • Valid OpenAI credentials
  • Optional: Frankfurter API key

Setup & Running

  1. Navigate to the Semantic Kernel sample in the A2A sample directory.
  2. Create a .env file.
  3. Set up the environment by specifying your Python version.
  4. Run the Semantic Kernel Agent.
  5. Run the A2A Client in a separate terminal.

After following these steps, the server will be up and running, and you can start interacting with the Semantic Kernel Travel Agent Manager.

Share Your Feedback

Explore this sample in the A2A repository and provide your insights and feedback to help us improve the integration of Semantic Kernel agents with Google's A2A protocol.