In this tutorial, we implement a QwenPaw workflow that provides a practical environment for building and testing an agent-powered assistant. We install and initialize QwenPaw, configure its working directory, set up authentication, connect optional model providers via Colab secrets, and create a structured workspace with custom skills and local knowledge files. We also launch the QwenPaw Console via a Colab-accessible URL, expose it through an optional Cloudflare tunnel, and test the streaming chat API programmatically, enabling us to use QwenPaw both as an interactive assistant and as an API-driven agent framework.

import os

import sys

import json

import time