REA Computer-Use Environments
Collection
Real Linux desktop apps as agentenv computer environments built by REA. Agents use screen, mouse and keyboard; files are graded with no model. • 48 items • Updated
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
id: string
type: string
env_id: string
vs
environment: string
app_version: string
task: string
prompt: string
agent: string
model: string
agentenv_framework: string
witness: string
runs: list<item: struct<run: int64, verdict: string, turns: null, usd: double, checks: struct<add-milk: struct<score: double, results: list<item: struct<id: string, result: bool, description: string>>>>>>
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1876, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 830, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 689, in write_rows_on_file
table = pa.concat_tables(self.current_rows)
File "pyarrow/table.pxi", line 6268, in pyarrow.lib.concat_tables
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
id: string
type: string
env_id: string
vs
environment: string
app_version: string
task: string
prompt: string
agent: string
model: string
agentenv_framework: string
witness: string
runs: list<item: struct<run: int64, verdict: string, turns: null, usd: double, checks: struct<add-milk: struct<score: double, results: list<item: struct<id: string, result: bool, description: string>>>>>>
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | type string | env_id string | env_ids list | name string | depends_on list | prompt string | file_artifact_id null | verifier_id null |
|---|---|---|---|---|---|---|---|---|
env | deploy_env | mousepad | null | null | null | null | null | null |
agent | deploy_agent | null | [
"mousepad"
] | null | null | null | null | null |
skills | add_skills | null | [
"mousepad"
] | null | null | null | null | null |
record | start_computer_recording | mousepad | null | agent | [
"env"
] | null | null | null |
task | prompt_agent | null | null | null | [
"skills",
"record"
] | Add buy milk as a new line at the end of the to-do list open in Mousepad, then save it. | null | null |
check | env_outcome_verifier | mousepad | null | null | [
"task"
] | null | null | null |
end | end_computer_recording | null | null | agent | [
"task"
] | null | null | null |
env | deploy_env | mousepad | null | null | null | null | null | null |
null | null | null | null | null | null | Add buy milk as a new line at the end of the to-do list open in Mousepad, then save it. | null | null |
Mousepad: a computer-use environment
The real Mousepad 0.6 text 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.
Mousepad opens a shopping list. The agent has to add a new line, buy milk, at the end and save the file, without disturbing the rest of the list. It sees only the screen and acts only with the mouse and keyboard.
Watch
Each video is the computer's own screen recording at 10 frames per second.
The task
Add buy milk as a new line at the end of the to-do list open in Mousepad, then save it.
bundle/artifacts/add-milk-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 |
|---|---|---|
milk |
lines_present |
Documents/todo.txt |
bread |
lines_present |
Documents/todo.txt |
one-milk |
line_count |
Documents/todo.txt |
The checks read the saved list: buy milk is there exactly once, and buy bread is still there.
Results
3 of 3 runs passed, about $0.56 per run.
Run it
You need Docker. agentenv-framework builds the computer: Ubuntu 24.04 with the app installed from Ubuntu's archive (mousepad 0.6.1-1build2).
pip install agentenv-framework==0.9.1431
hf download earakely-scale/MousepadComputerEnv-REA --repo-type dataset --local-dir mousepad
agent-env run mousepad/bundle --task add-milk --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:
- Capture. REA launched Mousepad 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.
- 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. - Task. The task's checks were validated against the capture: they fail on the starting state and pass on the captured end state.
- Witness and runs. Scripted computer actions solved the task in a kept computer, and the verifier failed before and passed after. 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
- A simple task: it shows the environment working end to end rather than testing a strong agent.
- The computer uses the
mousepadversion in Ubuntu 24.04's archive at build time; it is not pinned. - Three runs is a small sample.
Licences
The bundle code, the task and the synthetic seed files are Apache-2.0. Mousepad itself is not included: the computer installs it from Ubuntu's archive (mousepad 0.6.1-1build2) at build time, under its own licence (GPL-2.0-or-later).
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