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In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to enable nested event loops, then configure your Gemini API key and instantiate the GenAI client.
Next, we’ll define our communication contracts, Question and Answer Pydantic models, and spin up two UAgents: one “gemini_agent” that listens for incoming Question messages, invokes the Gemini “flash” model to generate responses, and emits Answer messages; and one “client_agent” that triggers a query upon startup and handles the incoming answer. Finally, we’ll learn how to run these agents concurrently using Python’s multiprocessing utility and gracefully shut down the event loop once the exchange is complete, illustrating UAgents’ seamless orchestration of inter-agent messaging.
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