Weekend Experiment: Free Qwen as a Personal API. Here Is What Actually Happened.

Found a cool service - , my Chrome extension for reading articles. Or just as a personal AI backend with no subscription and no token limits.

But honestly - the idea came first, the reason came later. Not the other way around.

So the task: a client sends a request, Qwen on Kaggle processes it, the response comes back. For free. The first problem showed up five minutes in.

The Problem: Kaggle Has No Inbound Traffic

Kaggle is a Jupyter notebook on a cloud GPU. No public IP. No incoming connections. You can't just spin up a Flask server and hand out a URL.

First idea: ngrok. Creates a public tunnel to a local server. Problem: ToS grey area on Kaggle. Could get the account banned.

Second idea: flip the architecture. Kaggle doesn't accept requests - it makes them.

The notebook connects to a Cloudflare Worker via WebSocket on startup. The Worker receives a request from the client, pushes the task into the open socket, Kaggle processes it and sends the result back. From Kaggle's side, these are just regular outgoing HTTP requests - no ToS issues.

Kaggle notebook + CF Worker + README. About 10 minutes to set up.

What would you change in this setup? And where do you see a use case for this pattern - Kaggle as a free AI backend via CF Worker?