cpuos

Recipe · browser base

Browser QA sandbox recipe

A Playwright recipe for repeatable web app checks, with deterministic fixtures, failure traces and separate browser contexts for each test.

When to use this profile

Browser QA differs from open-ended browsing: the goal is a repeatable assertion about your own app. Use a staging deployment or an isolated preview, seed known fixture data and collect traces only when a test fails. Give the agent selectors and assertions that describe user behavior, then compare the changed interface against those checks.

Prepare a repeatable environment

  • Match Playwright and browser versions and lock fonts and viewport settings for visual checks.
  • Prepare disposable test accounts and seed fixture data before each run.
  • Set retries deliberately and distinguish flaky infrastructure from an assertion failure.
Command inside a prepared Linux guest
pnpm --dir /work/project exec playwright test --workers=2

Return results the agent can use

  • A test report with passing and failing assertions.
  • Screenshots, videos or traces for failures.
  • A reviewable patch to tests and application code.

Run a deterministic login and navigation test, introduce a known UI regression and confirm the trace explains the failed assertion. Repeat to detect flaky results.

Resources and boundaries

Start with 4 vCPU and 8 GB of RAM, then measure peak memory and task duration on a representative fixture. These are workload planning values, not a benchmark or a provisioned configuration. Use the sandbox cost calculator to estimate running time and retained snapshots.

  • Each worker launches browser processes; two workers are a starting profile, not a throughput guarantee.
  • Trace files may contain authentication and customer data; sanitize artifacts before sharing.
  • Do not run destructive test actions against production accounts.

Keep model inference separate from this execution profile. A hosted model or gpuOS can decide the next action while the CPU environment runs it. The quickstart describes the account workflow and the proposed runtime contract.

Questions

Is this a separate built-in template?
This is a workload recipe based on the browser profile. It adds preparation and execution guidance, not a separate built-in image or a new backend runtime.
Can I run the command now?
The command runs in a Linux environment where the listed dependencies and input files are prepared. cpuOS SDK examples describe a proposed contract; confirm runtime access and package versions before integration.
How should I choose CPU and memory?
Use the starting profile to run a representative fixture, measure peak memory and elapsed time, and add room for package installation, worker processes and larger inputs. Enforce a task timeout separately.

Related guides

Plan your browser qa task

Create a workspace and choose a profile. Connect an execution backend before running code.

gpuOS · where models think

Need the model too? Run it on gpuOS

gpuOS serves open models on your own GPUs behind one OpenAI-compatible API. The model reasons on gpuOS, the agent acts in a cpuOS sandbox.