OpenClaw and Qwen3.7 Max setup on Ubuntu

This tutorial installs OpenClaw on an Ubuntu server and connects it to Qwen3.7 Max through Alibaba Cloud Model Studio. The agent runs on the server, while the model uses a cloud endpoint. This is not a demonstration of running model inference locally.

The setup uses an API key and an openclaw.json configuration pointing to the Singapore endpoint. The presenter enables thinking and tool capabilities, restarts the OpenClaw gateway, checks model authorization, and opens the terminal interface. He describes a one-million-token context window; the connected model listing shows 977k.

Two tasks follow. First, the AI agent inspects the server and produces a health report covering processes, CPU and memory use, filesystem details, network connections, SSH sessions, ports, and logs. The presenter recognizes several findings as data from his system and reviews suggested security actions. That assessment does not independently establish the report's completeness.

The second task asks the model to split a messy 80-line app.py with hardcoded passwords and missing error handling into a structured application. The presenter reports eight resulting files and reviews the structure, README, configuration, and comparison table in VS Code. He calls the output production ready, but the transcript shows no build or test results. Alibaba's claimed 35-hour autonomous runtime is also outside the scope of these two demonstrations.