ai-tinkerers-a2a-demo

A playground for experimenting with Google A2A (Agent-to-Agent) patterns, agent adapters, streaming, and push notification/callback workflows in Python.

A2A Example Types

1. Basic Echo Agent/Server

• Files: sample_a2a_subscribe_server.py, sample_a2a_subscribe_client.py
• Description: Minimal agent/server that echoes user queries. Demonstrates basic A2A server and client setup.

2. Push Notification/Callback (Subscribe) Example

• Files:
  • sample_a2a_subscribe_server.py (with custom task manager)
  • sample_a2a_subscribe_client.py (with FastAPI notification endpoint)
  • a2a_min_subscribe_task_manager.py, a2a_min_subscribe_client.py
• Description: Shows how a client can register a callback URL to receive asynchronous notifications from the server when tasks complete. Illustrates non-blocking task execution and HTTP callbacks.

3. Advanced News Riddle Agent

• Files: news_riddle_agent.py, news_riddle_server.py, news_riddle_client.py, gradio_app.py
• Description:
  • An advanced agent that generates riddles based on the latest news headlines, not just AI news. It uses LLMs and a web search tool to find recent news, then creates riddles and answers for them.
  • The agent is composed of two sub-agents: a news search agent and a riddle creation agent. The workflow is orchestrated via a CrewAI Crew object with two tasks: one for news search, one for riddle creation.
  • Example usage (from news_riddle_agent.py):

    agent = AINewsRiddleAgent()
    agent.llm.stream = False
    result = agent.crew.kickoff({"topic": "tarrifs"})
    for part in result:
        print(part)

  • The agent and tasks are now more general ("news" not just "AI news").
  • Supports both streaming and non-streaming LLM output.

Setup

1. Install uv
2. Run uv sync
3. Run the server/client of your choice by running uv run src/<file>.py

Running Examples

• See each script for specific instructions and requirements (e.g., FastAPI, Uvicorn for notification callback, Gradio for web UI).
• Make sure to set up any required environment variables (API keys, etc.).

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This repo is intended for prototyping and learning about agent-to-agent workflows, streaming, and async notification patterns in Python.