Guide a first computer-use agent run from environment checks to a browser-only task and a viewer of the run history. Explain each stage so users can understand the output and review screenshots afterward.
Guide a new user through their first computer-use agent run (env check, safe browser-only task, then open the trajectory viewer).
Review the instructions the agent will receive before you install.
Walk the user through running this demo for the first time. Be conversational and pause for confirmation between phases; the goal is that they understand what each step does, not just that the commands succeed.
Briefly say what is about to happen: you will check their setup, run one safe browser-only task that does not touch their mouse or keyboard, and then open the trajectory viewer so they can see what the model saw.
Never read the contents of
.env. Do notcat,grep(without-q),Read, or otherwise display it — the user's API key must never appear in this conversation or in your context. Only check for its presence.
python -c "import computer_use, playwright; print('ok')". If that import
fails, point them at the Installation section of README.md and stop..env exists and the API key is set without ever printing it:
[ -f .env ] && grep -q '^ANTHROPIC_API_KEY=.' .env && echo 'API key: set' || echo 'API key: missing'
If missing, copy .env.example to .env and ask the user to open it in
their own editor and paste their key into it (do not ask them to paste
the key into chat, and do not edit .env for them). Wait until they confirm.python -c "from computer_use.preflight import check_and_warn; check_and_warn(require=False)"
and explain any warnings. These permissions are only needed for the desktop
computer tool, which the first task does not use, so it is fine to
continue without them for now.Explain that this task uses only the headless browser tool, so nothing on their screen will move. Then run:
CU_ENABLE_COMPUTER_USE_TOOLS=false python -m computer_use \
"Navigate to https://en.wikipedia.org/wiki/Special:Random three times, \
take a screenshot each time, then summarize what you saw."
While it runs, narrate what the streamed output means (dim thinking text, the
cyan tool-call lines, the yellow tool-result lines, the [usage] line). When
it finishes, point out the trajectory: runs/... path that was printed.
python -m streamlit run dev_ui/trajectory_viewer/app.py
Tell them to pick the newest run in the sidebar, expand the System prompt section to see exactly what the model was told, and scroll through the turns to see each screenshot inline.
Offer two follow-ups and let them choose:
python -m computer_use "open TextEdit and type hello world".
Warn them again that this will move their real mouse and keyboard.python -m uvicorn dev_ui.tool_panel.server:app --reload lets them call
each tool by hand without the model in the loop.End by pointing at the Configuration and Effective caching and context
pruning sections of README.md for the deeper material.
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Build and run computer-use-demo in Docker, then use Playwright to test its Streamlit interface without opening a visible browser. Save conversation transcripts, API exchanges, and screenshots to inspect behavior after changes.
Verify changes to the copilot-kit-ag-ui demo by building and running its server. Check API routing, cross-origin access settings, and build configuration, then use real credentials to confirm that a requested chart appears.