Parse visual regions

Parse a screenshot into text and icon regions with the optional perception extension, and let an external chooser such as jev-use pick bounded actions.

When a window's accessibility tree and browser state do not identify the target, parse_visual_regions turns one retained screenshot into text and icon regions. Cua Driver keeps capture and input authority; the regions are observations, not action recommendations.

Install the extension#

Inspect the catalog entry (version, hashes, licenses, provenance) before installing. Nothing is ever installed as a side effect: a parse on a default install returns not_installed.

cua-driver describe parse_visual_regions
cua-driver extension inspect cua-perception --catalog <catalog.json>
cua-driver extension install cua-perception --catalog <catalog.json>
cua-driver extension status cua-perception

Update with cua-driver extension update cua-perception --catalog <catalog.json> and remove with:

cua-driver extension remove cua-perception

Capture, parse, act once, reobserve#

Use one persistent MCP connection or SDK runtime for the whole loop. A one-shot cua-driver call process cannot resolve another process's capture_id.

state   = get_window_state({"pid":844,"window_id":10725})
regions = parse_visual_regions({
  "capture_id": state.capture_id,
  "options": {"kinds":["text","icon"], "min_confidence":0.5, "max_regions":100}
})
click({..., "x": <point in a region>, "y": ..., "capture_id": state.capture_id})
state   = get_window_state({"pid":844,"window_id":10725})

• Regions are half-open rectangles in the source PNG's pixels, origin top left. Map a point through the returned action-coordinate mapping; do not rescale yourself.
• Build the click locally with x, y, the exact target, delivery mode, and the same capture_id. At most one action per capture.
• Never strip capture_id to retry a stale capture as a plain coordinate click.
• Reobserve after every attempt, including timeouts and refusals, and verify the real postcondition. background_unavailable does not authorize a foreground retry.
• Prefer an accessibility element or browser ref when one names the same control.

The worker only receives the screenshot and parse options, never input, accessibility, browser, or credential access.

Let an external chooser pick the action#

To put a model such as TypeSafe Jev above this loop, build a small candidate table locally: opaque IDs, each mapped to one complete Driver action, plus reobserve and abstain. Send the chooser only the goal, the capture_id, compact regions, and candidate descriptions. Accept exactly one known ID and dispatch the prebuilt action unchanged. The chooser never sees tool names, arguments, screenshots, or credentials.

The jev-use example (public preview) does this for a local browser form. It needs Cua Driver 0.23.2 or later, a system-installed Chrome, Edge, or Chromium, uv, and, for the live run, a key from the TypeSafe console. On macOS, point it at the app binary with export CUA_DRIVER_BIN="/Applications/CuaDriver.app/Contents/MacOS/cua-driver". On Windows, run Driver and the terminal without elevation.

git clone --depth 1 https://github.com/trycua/cua.git cua-jev-use
cd cua-jev-use/libs/cua-driver/examples/jev-use
uv sync --frozen --python 3.12
 
# Fixed choices, no API key:
uv run --frozen python verify_setup.py --output-dir runs/connection-check
# Live Jev choices (prompts for TYPESAFE_API_KEY):
uv run --frozen python verify_setup.py --live --output-dir runs/jev-example

Each run ends with a line like this; the live run reports "checks": 2:

{"event": "setup_complete", "checks": 1, "fixture_closed": true}

In runs/jev-example/summary.json, look for "complete": true and "observed": {"submitted": "jev-guide-live"}, which comes from the test server, not the model. Add --typescript to run the TypeScript agent too (after npm ci; "checks": 4). To call only the chooser from your own loop:

uv run python/choose_action.py --mock < fixtures/jev-choice-request-v1.json

To adapt it, change the candidates (python/core.py), the goal and observations (python/jev_adapter.py), and the completion check (python/run.py). A failed or incomplete run may still have acted: read the action log before retrying.

Native desktop apps#

The same chooser loop works in native desktop apps. Candidates then come from the accessibility tree that Cua Driver reports through macOS Accessibility, Windows UI Automation, or Linux AT-SPI, not from a web page:

• An element becomes a candidate only when it is enabled, on screen, labeled, and part of the native app rather than embedded web content. Window chrome is skipped.
• Platform roles map to one vocabulary (button, toggle, checkbox, radio, popup, menu_item, link, text_input), and candidate IDs come from the role, the label, and the path of actionable ancestors, so the same task yields the same IDs on every platform.
• At most 24 actions are offered, plus reobserve and abstain. In a window with more controls, the ones that perform the task's declared steps are kept first, and the offered actions keep their accessibility-tree order. Risky labels (delete, send, purchase, close) are left out unless the task allows them, and typed text comes only from the task's parameters.
• When the tree offers nothing to act through (empty, missing a declared control, or only window chrome), the agent falls back to visual regions from the same capture. A visual target needs an exact, unique text match with OCR confidence of at least 0.8 unless the task lowers it.

Native requests use the cua.jev_choice_request_v2 contract, which adds a source (page, ax, or visual) to each candidate. The built-in tasks also send progress: each required step and how many times this run has performed it. The runner counts its own successful actions and never reads the count from the app. The example includes AppKit, WPF, WinUI3, GTK3, and custom-painted canvas test apps; each task passes only when the app's own state file shows the expected result:

bash ../../tests/fixtures/build/macos.sh --only appkit
uv run --frozen python verify_native.py --harness appkit --typescript --output-dir runs/native-mock
# Add --live for Jev choices, or --task counter to run one task.

Use --harness wpf (build with ..\..\tests\fixtures\build\windows.ps1 -Targets wpf) or --harness winui3 (build with -Targets winui3) on Windows and --harness gtk3 (build with bash ../../tests/fixtures/build/linux.sh --only gtk3, run with .venv/bin/python) on an X11 Linux session. --harness canvas needs the perception extension and proves the visual fallback. Tasks live in python/native_tasks.py and typescript/native_tasks.ts; the design is recorded in RFC 4268.