Skip to main content

Toolkit for computer-use RL environments and benchmarks

Project description

cua-bench

Framework for benchmarking Computer-Use Agents with verifiable cross-platform environments.

Documentation - Installation, guides, and API reference.

Running Tests

The test suite covers the core gym interface, worker system, and benchmark runners.

Install dev dependencies

uv pip install -e ".[dev,browser,server,rl]"

Note: The browser extra installs Playwright for e2e tests with the simulated provider.

Run all tests

uv run --with pytest pytest cua_bench/tests/ -v

Run specific test modules

# Core gym interface (make, reset, step, evaluate)
uv run --with pytest pytest cua_bench/tests/test_gym_interface.py -v

# HTTP worker client (/reset, /step endpoints)
uv run --with pytest pytest cua_bench/tests/test_worker_client.py -v

# Worker server endpoints and action serialization
uv run --with pytest pytest cua_bench/tests/test_worker_server.py -v

# Benchmark runner functions
uv run --with pytest pytest cua_bench/tests/test_run_benchmark.py -v

# Worker manager (spawning/managing workers)
uv run --with pytest pytest cua_bench/tests/test_worker_manager.py -v

# Action parsing
uv run --with pytest pytest cua_bench/tests/test_actions.py -v

Run tests with coverage

uv run --with pytest --with pytest-cov pytest cua_bench/tests/ -v --cov=cua_bench --cov-report=term-missing

Test Structure

Test Module What it Tests Approach
test_gym_interface.py Core Environment API: make(), reset(), step(), evaluate() E2E - Real simulated (Playwright) environments
test_worker_client.py HTTP client for worker servers (CBEnvWorkerClient) Mock server - Uses @patch("requests.post") to mock HTTP responses
test_worker_server.py FastAPI endpoints and action serialization Unit - Action serialize/deserialize, request models, simple endpoints
test_run_benchmark.py run_benchmark(), run_single_task(), run_interactive() E2E - Real simulated (Playwright) environments
test_worker_manager.py Workers + dataloader training loop E2E - Real workers, real envs, mock model for actions
test_actions.py Action string parsing (repr_to_action()) Unit - Pure function tests

Test Approach Philosophy

  • E2E tests use real simulated (Playwright) environments. The simulated provider is fast enough for testing.
  • Mock server tests (test_worker_client.py) mock HTTP responses to test client logic in isolation.
  • Mock model (test_worker_manager.py) uses a mock model that returns simple actions to test the dataloader training loop without requiring a real ML model.

Infrastructure Benchmarking

Measure the throughput of the worker infrastructure:

uv run python -m cua_bench.scripts.benchmark_workers --num_workers 16 --num_steps 10

Options:

Flag Default Description
--num_workers 16 Number of parallel workers
--num_steps 10 Steps per worker
--task_path None Path to task directory (creates temp if empty)

Output:

  • Average reset time
  • Average step time
  • Average finish time
  • Step throughput (steps/sec)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cua_bench-0.2.7.tar.gz (13.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cua_bench-0.2.7-py3-none-any.whl (13.4 MB view details)

Uploaded Python 3

File details

Details for the file cua_bench-0.2.7.tar.gz.

File metadata

  • Download URL: cua_bench-0.2.7.tar.gz
  • Upload date:
  • Size: 13.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for cua_bench-0.2.7.tar.gz
Algorithm Hash digest
SHA256 f2faf40aa21fffc9ccf6e232bd3c457f5d33b11c35c30178aa091e79713cf148
MD5 e01524ab2881b535b6903ac0b19058c7
BLAKE2b-256 221a40e057215973db4d316a6d998b76fe113ea6b765f8f65534176dae325e69

See more details on using hashes here.

File details

Details for the file cua_bench-0.2.7-py3-none-any.whl.

File metadata

  • Download URL: cua_bench-0.2.7-py3-none-any.whl
  • Upload date:
  • Size: 13.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for cua_bench-0.2.7-py3-none-any.whl
Algorithm Hash digest
SHA256 68f21fe8e1d0659ecb09a03bacbe418c8d37303694ac356ce919e216460dd287
MD5 77c5998949ccee681f8bd91eaf250666
BLAKE2b-256 064c3c3bde2103dc46064898eecef5a3e680e819f963ce41cdb0708d31c782af

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page