Fetch.ai has dropped a new developer tutorial showing how to build an autonomous agent that generates images using Google’s Gemini 2.5 Flash Image model and distributes them through the platform’s decentralized infrastructure. It’s not a product launch. It’s a how-to guide, and that distinction matters more than you might think.
The tutorial walks developers through constructing what Fetch.ai calls a “mailbox agent,” a specialized piece of software built in Python using the uagents library. This agent takes text prompts, feeds them to Google’s image generation model, and uploads the resulting visuals to Agentverse ExternalStorage, where other agents and applications can access them.
How the integration actually works
The agent uses a chat protocol, meaning it can receive prompts and return generated images in a conversational format. Those images get packaged as ResourceContent messages, a standardized format that allows other participants in the Agentverse ecosystem, including the ASI:One application, to consume and display the visual content.
To get it running, developers need two things: a Google AI API key for accessing the Gemini model and an Agentverse API key for interacting with the storage and messaging infrastructure. The whole setup leans on Python and Fetch.ai’s open-source uagents library.
