earakely-scale/GeanyComputerEnv-REA

Geany: a computer-use environment

The real Geany 2.0 code editor running on an Ubuntu 24.04 desktop, as an agentenv computer environment. An agent completes the task only through screenshots, mouse and keyboard, and a verifier grades the saved files with no model.

Geany opens a small Python settings file for a corner shop. The agent has to find two settings in the editor, turn debug mode off and move the port from 8000 to 8080, then save. It sees only the screen and acts only with the mouse and keyboard.

Watch

• Agent runs (Claude Code with Claude Sonnet 5.5): run 1, run 2, run 3
• Scripted witness, which proves the task can be done through the computer: witness.mp4

Each video is the computer's own screen recording at 10 frames per second.

The task

In the shop's settings.py open in Geany, turn debug mode off and change the port to 8080, then save the file.

bundle/artifacts/debug-off-check/verify.py reads the app's files through the computer's data/get view and passes only if every check holds:

Check	Kind	File
changed	lines_present	Documents/shop/settings.py
old-gone	lines_absent	Documents/shop/settings.py
rest-kept	lines_present	Documents/shop/settings.py

The checks read the saved file line by line: the two new lines are present, the two old ones are gone, and the rest of the file is untouched.

Results

3 of 3 runs passed, about $0.63 per run.

Run	Outcome	Turns	Cost	Video
1	passed	9	$0.88	video
2	passed	9	$0.63	video
3	passed	9	$0.38	video

Run it

You need Docker. agentenv-framework builds the computer: Ubuntu 24.04 with the app installed from Ubuntu's archive (geany 2.0-1build2).

pip install agentenv-framework==0.9.1431
hf download earakely-scale/GeanyComputerEnv-REA --repo-type dataset --local-dir geany
agent-env run geany/bundle --task debug-off --agent claude-code --model <model>

The agent needs a model provider configured for agentenv. --task smoke only boots the computer, with no agent. bundle/README.md describes the bundle in detail.

How it was made

REA built this environment from a real session with the app:

1. Capture. REA launched Geany on a Linux desktop and recorded its package, windows and opened files while a scripted user made the edit. It also recorded the app's state folders before and after.
2. Export. REA turned the capture into an agentenv computer_app. It installs the app, seeds the starting files, starts the app, and waits for its main window. It also serves typed views of the app's files for verifiers.
3. Task. The task's checks were validated against the capture: they fail on the starting state and pass on the captured end state.
4. Witness and runs. Scripted computer actions solved the task in a fresh computer, and the verifier failed before, passed after and failed again after data/reset. Then an agent solved it 3 times, each run recorded.

What's inside

bundle/      the agentenv bundle: envs/ (app module, seed files), tasks/, artifacts/ (verifier), evals/
media/       witness and agent-run recordings (MP4) with short GIF previews
results.json the runs above, with each check's result

Limits

• The checks read whole lines, so an equivalent edit written differently (for example DEBUG=False without spaces) fails.
• The computer uses the geany version in Ubuntu 24.04's archive at build time; it is not pinned.
• Three runs is a small sample: the solve rate shows the task is solvable, not how hard it is.

Licences

The bundle code, the task and the synthetic seed files are Apache-2.0. Geany itself is not included: the computer installs it from Ubuntu's archive (geany 2.0-1build2) at build time, under its own licence (GPL-2.0-or-later).