3c498972ce
Rewrites android-cua-smoke.py to demonstrate the complete first-run journey
instead of the previous "ping" smoke test. The new structured multi-phase
flow covers: server connection setup, session list, new session creation,
TypeScript hello-world task submission (watching tool calls/file writes),
output verification, and Settings/model-selection screenshot.
Key changes:
- run_onboarding_showcase() orchestrates 6 sequential CUA phases with
per-phase goals, step budgets, and PASS/FAIL phase tracking
- run_cua_step() replaces run_cua() — accepts step_label, action_delay,
saves labeled screenshots (/tmp/cua_<phase>_<step>.png) for debugging
- Global --speed-multiplier flag scales all _sleep() calls (0.5 = 2x faster)
- Showcase is now the default mode; legacy --goal / --scenarios flags retained
for backwards compat and CI regression scenarios
- Tighter action_delay (0.7s) and trimmed history window (14 turns) vs
previous 1.0s / 12 turns
- Phase banner log lines ("STEP N: ...") narrate the video in real time
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01No3k1AEioE4PNUZg12TxQo
1050 lines
41 KiB
Python
Executable File
1050 lines
41 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Android Computer-Use Agent (CUA) smoke test for OpenCode Mobile.
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Full onboarding showcase — drives an Android emulator via ADB using an LLM vision loop:
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screenshot → vision model → action → repeat
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Demonstrates the complete first-run journey:
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1. App opens on connection screen (no saved connections)
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2. Configure opencode server URL
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3. Connect — session list loads
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4. Create new AI coding session
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5. Submit a TypeScript "hello world" task
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6. Watch opencode work (tool calls, file writes), wait for idle
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7. Verify output / success response
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8. Navigate to Settings — show model selection
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9. Screenshot settings screen
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Requirements:
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pip install openai
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ADB in PATH with a connected device/emulator.
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Usage:
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# Azure OpenAI (recommended — already configured via ~/.env.d/azure-openai.env)
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source ~/.env.d/azure-openai.env
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python scripts/android-cua-smoke.py --model gpt-5.4 --include-xml
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# OpenAI
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export OPENAI_API_KEY=sk-...
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python scripts/android-cua-smoke.py --model gpt-4o --include-xml
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# Run ONLY the onboarding showcase (default and primary flow):
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python scripts/android-cua-smoke.py --showcase
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# Custom goal (legacy / quick debugging):
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python scripts/android-cua-smoke.py --goal "Open settings and toggle dark mode"
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# Speed up for a demo video (tighter waits, fewer retries):
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python scripts/android-cua-smoke.py --speed-multiplier 0.5
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"""
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import argparse
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import base64
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import json
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import os
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import subprocess
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import sys
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import tempfile
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import time
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import threading
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import re
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import xml.etree.ElementTree as ET
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from functools import lru_cache
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from pathlib import Path
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try:
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from openai import OpenAI, AzureOpenAI
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except ImportError:
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sys.exit("openai package required: pip install openai")
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# ---------------------------------------------------------------------------
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# Constants
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# ---------------------------------------------------------------------------
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APP_PACKAGE = "cc.agentlabs.opencode"
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# Default opencode Tailscale dev server
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DEFAULT_OPENCODE_URL = "http://100.108.64.76:4096"
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# TypeScript task prompt sent to the AI coding session
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TYPESCRIPT_TASK = (
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"Write a TypeScript hello world app. "
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"Create a file hello.ts that prints 'Hello, World!' to the console."
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)
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# ---------------------------------------------------------------------------
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# Global state
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# ---------------------------------------------------------------------------
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_step_counter = 0
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_speed_multiplier = 1.0 # Set via --speed-multiplier; <1.0 = faster
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def _sleep(seconds: float) -> None:
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"""Interruptible sleep that respects the global speed multiplier."""
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time.sleep(max(0.2, seconds * _speed_multiplier))
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# ---------------------------------------------------------------------------
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# ADB helpers
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# ---------------------------------------------------------------------------
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def adb(*args: str) -> str:
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"""Run an adb command and return stdout."""
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result = subprocess.run(
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["adb", *args],
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capture_output=True, text=True, timeout=30,
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)
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if result.returncode != 0 and "Error" in result.stderr:
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raise RuntimeError(f"adb {' '.join(args)} failed: {result.stderr.strip()}")
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return result.stdout.strip()
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def _bounds_center(bounds: str) -> tuple[int, int] | None:
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match = re.match(r"\[(\d+),(\d+)\]\[(\d+),(\d+)\]", bounds or "")
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if not match:
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return None
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x1, y1, x2, y2 = map(int, match.groups())
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return ((x1 + x2) // 2, (y1 + y2) // 2)
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def current_foreground_package() -> str:
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"""Return resumed foreground package name when available."""
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out = adb("shell", "dumpsys", "activity", "activities")
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for line in out.splitlines():
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if "mResumedActivity" not in line:
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continue
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match = re.search(r"\s([a-zA-Z0-9_\.]+)/", line)
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if match:
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return match.group(1)
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return ""
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def ensure_app_foreground(package: str = APP_PACKAGE, retries: int = 3,
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verbose: bool = True) -> bool:
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"""Bring app to foreground before scenario start."""
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for attempt in range(retries):
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current = current_foreground_package()
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if current == package:
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return True
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adb("shell", "monkey", "-p", package, "-c", "android.intent.category.LAUNCHER", "1")
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_sleep(2.0)
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if verbose:
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seen = current or "unknown"
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print(f" [prep] foreground package was '{seen}', launched '{package}' (attempt {attempt + 1}/{retries})")
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return current_foreground_package() == package
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def maybe_dismiss_telemetry_consent(package: str = APP_PACKAGE,
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verbose: bool = True) -> bool:
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"""Dismiss first-launch telemetry consent modal when present."""
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xml = ui_dump()
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if not xml:
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return False
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try:
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root = ET.fromstring(xml)
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except ET.ParseError:
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return False
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consent_markers = (
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"help improve opencode",
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"share anonymous crash reports",
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)
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dismiss_markers = (
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"not now", "no thanks", "decline", "skip", "later",
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"don't allow", "dont allow", "deny", "continue without",
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"opt out", "cancel",
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)
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page_text = " ".join(
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" ".join(filter(None, [
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node.attrib.get("text", ""),
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node.attrib.get("content-desc", ""),
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])).lower()
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for node in root.iter()
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)
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if not any(marker in page_text for marker in consent_markers):
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return False
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candidates = []
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for node in root.iter():
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clickable = node.attrib.get("clickable") == "true"
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if not clickable:
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continue
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label = " ".join(filter(None, [
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node.attrib.get("text", ""),
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node.attrib.get("content-desc", ""),
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node.attrib.get("resource-id", ""),
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])).strip().lower()
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center = _bounds_center(node.attrib.get("bounds", ""))
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if not center:
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continue
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candidates.append((label, center))
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for label, (x, y) in candidates:
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if any(marker in label for marker in dismiss_markers):
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adb("shell", "input", "tap", str(x), str(y))
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_sleep(1.0)
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if verbose:
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print(f" [prep] dismissed telemetry consent via '{label or 'button'}' at ({x}, {y})")
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return True
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if verbose:
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print(" [prep] telemetry consent detected but dismiss button was not found")
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return False
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def screenshot_b64(label: str = "") -> str:
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"""Capture emulator screenshot and return as base64 PNG. Retries on timeout."""
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global _step_counter
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_step_counter += 1
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suffix = f"_{label}" if label else ""
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debug_path = f"/tmp/cua_step_{_step_counter:03d}{suffix}.png"
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for attempt in range(3):
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try:
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result = subprocess.run(
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["adb", "exec-out", "screencap", "-p"],
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capture_output=True, timeout=30,
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)
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if result.returncode == 0 and len(result.stdout) > 100:
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Path(debug_path).write_bytes(result.stdout)
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return base64.b64encode(result.stdout).decode()
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except subprocess.TimeoutExpired:
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if attempt < 2:
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_sleep(3)
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continue
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raise
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# Fallback: screencap on device then pull
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with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as f:
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path = f.name
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try:
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subprocess.run(["adb", "shell", "screencap", "-p", "/sdcard/_cua_screen.png"],
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capture_output=True, timeout=30)
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subprocess.run(["adb", "pull", "/sdcard/_cua_screen.png", path],
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capture_output=True, timeout=10)
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data = Path(path).read_bytes()
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Path(debug_path).write_bytes(data)
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return base64.b64encode(data).decode()
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finally:
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Path(path).unlink(missing_ok=True)
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# ---------------------------------------------------------------------------
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# Screen recording
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# ---------------------------------------------------------------------------
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def start_screen_recording(scenario_name: str) -> tuple:
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"""Start ADB screen recording. Returns (thread, stop_event, remote_path)."""
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remote_path = f"/sdcard/cua_{scenario_name}.mp4"
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stop_event = threading.Event()
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def _record():
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try:
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subprocess.run(
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["adb", "shell", f"screenrecord --time-limit 180 {remote_path}"],
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capture_output=True, timeout=200,
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)
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except Exception:
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pass
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thread = threading.Thread(target=_record, daemon=True)
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thread.start()
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_sleep(1.0)
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return thread, stop_event, remote_path
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def stop_screen_recording(thread: threading.Thread, remote_path: str,
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local_path: str) -> bool:
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"""Stop recorder, pull video to local_path. Returns True on success."""
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subprocess.run(
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["adb", "shell", "pkill", "-2", "screenrecord"],
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capture_output=True, timeout=10,
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)
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_sleep(2.0)
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thread.join(timeout=5)
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result = subprocess.run(
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["adb", "pull", remote_path, local_path],
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capture_output=True, timeout=30,
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)
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if result.returncode == 0 and Path(local_path).exists():
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print(f" [recording] saved to {local_path}")
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return True
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print(f" [recording] pull failed: {result.stderr.decode(errors='replace').strip()}")
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return False
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# ---------------------------------------------------------------------------
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# ArchiveBox upload
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# ---------------------------------------------------------------------------
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def upload_to_archivebox(video_path: str, scenario_name: str) -> bool:
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"""Upload video to ArchiveBox if ARCHIVEBOX_URL is configured."""
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url = os.environ.get("ARCHIVEBOX_URL", "").rstrip("/")
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api_key = os.environ.get("ARCHIVEBOX_API_KEY", "")
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if not url:
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print(" [archivebox] ARCHIVEBOX_URL not set — skipping upload")
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return False
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try:
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import urllib.request
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video_data = Path(video_path).read_bytes()
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boundary = "----CUAUploadBoundary"
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body_parts = []
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body_parts.append(f"--{boundary}\r\nContent-Disposition: form-data; name=\"url\"\r\n\r\nfile://{scenario_name}.mp4".encode())
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body_parts.append(
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f"--{boundary}\r\nContent-Disposition: form-data; name=\"file\"; filename=\"{scenario_name}.mp4\"\r\nContent-Type: video/mp4\r\n\r\n".encode()
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+ video_data
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)
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body_parts.append(f"--{boundary}--\r\n".encode())
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body = b"\r\n".join(body_parts)
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headers = {
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"Content-Type": f"multipart/form-data; boundary={boundary}",
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"Content-Length": str(len(body)),
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}
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if api_key:
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headers["X-API-Key"] = api_key
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req = urllib.request.Request(f"{url}/api/v1/add", data=body, headers=headers, method="POST")
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with urllib.request.urlopen(req, timeout=60) as resp:
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print(f" [archivebox] uploaded {scenario_name}.mp4 → {url} ({resp.status})")
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return True
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except Exception as exc:
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print(f" [archivebox] upload failed: {exc}")
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return False
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def ui_dump() -> str:
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"""Dump UI hierarchy XML and return as string."""
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adb("shell", "uiautomator", "dump", "/sdcard/_cua_ui.xml")
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result = subprocess.run(
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["adb", "pull", "/sdcard/_cua_ui.xml", "/tmp/_cua_ui.xml"],
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capture_output=True, timeout=10,
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)
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if result.returncode == 0:
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return Path("/tmp/_cua_ui.xml").read_text(errors="replace")
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return ""
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def execute_action(action: dict) -> str:
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"""Execute an action dict returned by the LLM. Returns status string."""
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act = action.get("type", "")
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if act == "tap":
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x, y = int(action["x"]), int(action["y"])
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adb("shell", "input", "tap", str(x), str(y))
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return f"tapped ({x}, {y})"
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elif act == "type":
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text = action.get("text", "")
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escaped = text.replace(" ", "%s").replace("&", "\\&").replace(";", "\\;")
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adb("shell", "input", "text", escaped)
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return f"typed '{text}'"
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elif act == "key":
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key = action.get("key", "")
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key_map = {
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"enter": "66", "back": "4", "home": "3",
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"delete": "67", "tab": "61",
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}
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code = key_map.get(key.lower(), key)
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adb("shell", "input", "keyevent", code)
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return f"pressed key {key}"
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elif act == "swipe":
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x1, y1 = int(action["x1"]), int(action["y1"])
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x2, y2 = int(action["x2"]), int(action["y2"])
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duration = int(action.get("duration", 300))
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adb("shell", "input", "swipe", str(x1), str(y1), str(x2), str(y2), str(duration))
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return f"swiped ({x1},{y1})->({x2},{y2})"
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elif act == "send":
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# Auto-locate send button: rightmost clickable button in the bottom input bar.
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_, screen_h = get_screen_size()
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bottom_threshold = int(screen_h * 0.75)
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xml = ui_dump()
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matches = re.findall(r'clickable="true"[^>]*bounds="\[(\d+),(\d+)\]\[(\d+),(\d+)\]"', xml)
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bottom_buttons = [(int(x1), int(y1), int(x2), int(y2)) for x1, y1, x2, y2 in matches if int(y1) > bottom_threshold]
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if bottom_buttons:
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send_btn = max(bottom_buttons, key=lambda b: (b[0] + b[2]) // 2)
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cx = (send_btn[0] + send_btn[2]) // 2
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cy = (send_btn[1] + send_btn[3]) // 2
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adb("shell", "input", "tap", str(cx), str(cy))
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return f"send button tapped ({cx}, {cy})"
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screen_w, _ = get_screen_size()
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fx = screen_w - 80
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fy = screen_h - 120
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adb("shell", "input", "tap", str(fx), str(fy))
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return f"send button tapped (fallback {fx}, {fy})"
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elif act == "wait":
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secs = float(action.get("seconds", 2))
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_sleep(secs)
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return f"waited {secs}s"
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elif act == "screenshot":
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# Explicit screenshot action — agent wants to observe current state
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label = action.get("label", "observe")
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screenshot_b64(label)
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return f"screenshot taken ({label})"
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elif act == "done":
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return "DONE"
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elif act == "fail":
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return "FAIL: " + action.get("reason", "unknown")
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else:
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return f"unknown action: {act}"
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# ---------------------------------------------------------------------------
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# LLM CUA loop
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# ---------------------------------------------------------------------------
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SYSTEM_PROMPT = """\
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You are an Android phone automation agent. You control the device by issuing actions.
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On each turn you receive a screenshot of the current Android screen.
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Respond with a JSON object for ONE action to take next.
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Available actions:
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{"type": "tap", "x": <int>, "y": <int>}
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{"type": "type", "text": "<string>"}
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{"type": "key", "key": "enter|back|home|delete|tab"}
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{"type": "swipe", "x1": <int>, "y1": <int>, "x2": <int>, "y2": <int>, "duration": <ms>}
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{"type": "send"} -- tap the send/submit button (auto-locates via UI hierarchy)
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{"type": "wait", "seconds": <float>}
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{"type": "screenshot", "label": "<tag>"} -- observe current state without acting
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{"type": "done", "summary": "<what was accomplished>"}
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{"type": "fail", "reason": "<why the goal cannot be achieved>"}
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Rules:
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- Issue exactly ONE action per turn as a JSON object. No markdown, no explanation outside JSON.
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- Coordinates are in pixels relative to the screenshot dimensions.
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- IMPORTANT: In this app, pressing "enter" inserts a newline — it does NOT send the message.
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To send a message use {"type": "send"} which auto-locates and taps the send/arrow button.
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After typing your message, press "back" to dismiss the keyboard, then use {"type": "send"}.
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- Be efficient: skip unnecessary waits, tap directly on visible targets.
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- When the goal is fully achieved respond with {"type": "done", "summary": "..."}.
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- If genuinely stuck after 5+ attempts on the same element respond with {"type": "fail", ...}.
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"""
|
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|
|
|
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def call_llm(client, model: str, system: str, history: list) -> str:
|
|
"""Call LLM via OpenAI-compatible API with retry on rate limit."""
|
|
for attempt in range(3):
|
|
try:
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|
response = client.chat.completions.create(
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|
model=model,
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messages=[{"role": "system", "content": system}] + history,
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|
max_completion_tokens=300,
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|
temperature=0,
|
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)
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return response.choices[0].message.content.strip()
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|
except Exception as e:
|
|
if "429" in str(e) and attempt < 2:
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|
wait = 15 * (attempt + 1)
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print(f" [rate limited, retrying in {wait}s...]")
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time.sleep(wait)
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|
continue
|
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raise
|
|
|
|
|
|
def make_client(model: str):
|
|
"""Create OpenAI client. Supports AZURE_OPENAI_*, AZURE_DEV_AI_*, OPENAI_API_KEY, GEMINI_API_KEY, XAI_API_KEY."""
|
|
if os.environ.get("AZURE_OPENAI_API_KEY"):
|
|
azure_model = os.environ.get("AZURE_OPENAI_MODEL", "gpt-5.4")
|
|
return AzureOpenAI(
|
|
api_key=os.environ["AZURE_OPENAI_API_KEY"],
|
|
azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
|
|
api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2024-08-01-preview"),
|
|
), azure_model
|
|
if os.environ.get("AZURE_DEV_AI_API_KEY"):
|
|
base_url = os.environ.get("AZURE_DEV_AI_BASE_URL", "https://vibe-dev-ai.cognitiveservices.azure.com/openai/v1")
|
|
azure_model = os.environ.get("AZURE_DEV_AI_MODEL", "gpt-4o-2024-11-20")
|
|
return OpenAI(api_key=os.environ["AZURE_DEV_AI_API_KEY"], base_url=base_url), azure_model
|
|
if os.environ.get("OPENAI_API_KEY"):
|
|
base = os.environ.get("OPENAI_BASE_URL")
|
|
return OpenAI(base_url=base) if base else OpenAI(), model
|
|
if os.environ.get("XAI_API_KEY"):
|
|
return OpenAI(
|
|
api_key=os.environ["XAI_API_KEY"],
|
|
base_url="https://api.x.ai/v1",
|
|
), "grok-2-vision-1212"
|
|
if os.environ.get("GEMINI_API_KEY"):
|
|
return OpenAI(
|
|
api_key=os.environ["GEMINI_API_KEY"],
|
|
base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
|
|
), "gemini-2.0-flash"
|
|
sys.exit("Set AZURE_OPENAI_API_KEY, AZURE_DEV_AI_API_KEY, OPENAI_API_KEY, XAI_API_KEY, or GEMINI_API_KEY")
|
|
|
|
|
|
@lru_cache(maxsize=1)
|
|
def get_screen_size() -> tuple[int, int]:
|
|
"""Return (width, height) of the connected device screen. Cached."""
|
|
try:
|
|
out = adb("shell", "wm", "size")
|
|
for line in out.splitlines():
|
|
if "size:" in line.lower():
|
|
dims = line.split(":")[-1].strip()
|
|
w, h = dims.split("x")
|
|
return int(w), int(h)
|
|
except Exception:
|
|
pass
|
|
return 1080, 1920
|
|
|
|
|
|
def run_cua_step(goal: str, max_steps: int = 30, model: str = "gpt-4o",
|
|
include_ui_xml: bool = False, verbose: bool = True,
|
|
step_label: str = "", action_delay: float = 0.8) -> dict:
|
|
"""Run the CUA loop for a single goal until done/fail/max_steps.
|
|
|
|
Args:
|
|
goal: Natural-language instruction for this step.
|
|
max_steps: Hard cap on LLM turns.
|
|
model: Vision model deployment name.
|
|
include_ui_xml: Append UI hierarchy XML to each prompt turn.
|
|
verbose: Print action log.
|
|
step_label: Short name shown in logs/screenshot filenames.
|
|
action_delay: Seconds to pause after each action (scaled by speed_multiplier).
|
|
"""
|
|
client, model = make_client(model)
|
|
history = []
|
|
screen_w, screen_h = get_screen_size()
|
|
label_prefix = f"[{step_label}] " if step_label else ""
|
|
|
|
for step in range(1, max_steps + 1):
|
|
img_b64 = screenshot_b64(label=f"{step_label}_{step:02d}" if step_label else f"{step:03d}")
|
|
|
|
content: list = [
|
|
{
|
|
"type": "text",
|
|
"text": (
|
|
f"{label_prefix}Step {step}/{max_steps}. "
|
|
f"Screen: {screen_w}x{screen_h}px. "
|
|
f"Goal: {goal}\n"
|
|
"What action should I take next?"
|
|
),
|
|
},
|
|
{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{img_b64}", "detail": "high"}},
|
|
]
|
|
|
|
if include_ui_xml:
|
|
xml = ui_dump()
|
|
if xml:
|
|
content.append({"type": "text", "text": f"UI hierarchy (truncated to 4000 chars):\n{xml[:4000]}"})
|
|
|
|
history.append({"role": "user", "content": content})
|
|
|
|
reply = call_llm(client, model, SYSTEM_PROMPT, history)
|
|
history.append({"role": "assistant", "content": reply})
|
|
|
|
# Parse action — tolerate markdown fences and multi-object responses
|
|
try:
|
|
clean = reply.strip()
|
|
if clean.startswith("```"):
|
|
clean = clean.split("\n", 1)[1].rsplit("```", 1)[0].strip()
|
|
m = re.search(r'\{[^{}]*\}', clean)
|
|
action = json.loads(m.group(0)) if m else json.loads(clean)
|
|
except json.JSONDecodeError:
|
|
if verbose:
|
|
print(f" {label_prefix}[step {step}] Failed to parse: {reply[:120]}")
|
|
continue
|
|
|
|
result = execute_action(action)
|
|
if verbose:
|
|
print(f" {label_prefix}[step {step}] {action.get('type', '?')} -> {result}")
|
|
|
|
if result == "DONE":
|
|
return {"status": "success", "steps": step, "summary": action.get("summary", "")}
|
|
if result.startswith("FAIL"):
|
|
return {"status": "fail", "steps": step, "reason": action.get("reason", "")}
|
|
|
|
# Trim history to keep context manageable
|
|
if len(history) > 14:
|
|
history = history[-14:]
|
|
|
|
_sleep(action_delay)
|
|
|
|
return {"status": "timeout", "steps": max_steps}
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Onboarding showcase — structured multi-phase flow
|
|
# ---------------------------------------------------------------------------
|
|
|
|
# Banner printed before each named phase so the video is narrated by log output
|
|
PHASE_BANNERS = {
|
|
"connect": "STEP 1-2: Opening app — configuring server connection",
|
|
"session_list": "STEP 3: Connected — viewing session list",
|
|
"new_session": "STEP 4: Creating a new AI coding session",
|
|
"typescript": "STEP 5-6: Submitting TypeScript task — watching opencode work",
|
|
"verify": "STEP 7: Verifying task output / success response",
|
|
"settings": "STEP 8-9: Navigating to Settings — showing model selection",
|
|
}
|
|
|
|
|
|
def _banner(key: str) -> None:
|
|
line = "=" * 64
|
|
msg = PHASE_BANNERS.get(key, key)
|
|
print(f"\n{line}")
|
|
print(f" {msg}")
|
|
print(f"{line}\n")
|
|
|
|
|
|
def run_onboarding_showcase(
|
|
opencode_url: str = DEFAULT_OPENCODE_URL,
|
|
model: str = "gpt-5.4",
|
|
include_ui_xml: bool = False,
|
|
verbose: bool = True,
|
|
max_steps_per_phase: int = 20,
|
|
) -> dict:
|
|
"""Execute the full first-run onboarding journey.
|
|
|
|
Each phase is a focused CUA sub-goal. Phases are run sequentially.
|
|
Returns a summary dict with per-phase results.
|
|
"""
|
|
|
|
results: dict[str, dict] = {}
|
|
|
|
def _run(key: str, goal: str, max_steps: int | None = None) -> bool:
|
|
"""Run one phase. Returns True if succeeded."""
|
|
_banner(key)
|
|
steps = max_steps or max_steps_per_phase
|
|
r = run_cua_step(
|
|
goal=goal,
|
|
max_steps=steps,
|
|
model=model,
|
|
include_ui_xml=include_ui_xml,
|
|
verbose=verbose,
|
|
step_label=key,
|
|
action_delay=0.7,
|
|
)
|
|
results[key] = r
|
|
ok = r["status"] == "success"
|
|
icon = "OK" if ok else "FAIL"
|
|
print(f"\n [{icon}] Phase '{key}': {r['status']} in {r['steps']} steps")
|
|
if r.get("summary"):
|
|
print(f" {r['summary']}")
|
|
if r.get("reason"):
|
|
print(f" reason: {r['reason']}")
|
|
return ok
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 1-2: Open app, configure server connection
|
|
# -----------------------------------------------------------------------
|
|
ok = _run(
|
|
"connect",
|
|
goal=(
|
|
f"You are on the OpenCode mobile app. "
|
|
"The screen shows either a connection screen (first launch) or an empty connections list. "
|
|
"Your goal: add a new connection to the opencode server. "
|
|
"Look for an 'Add Connection', '+', or 'New Connection' button and tap it. "
|
|
f"In the URL / Host field type '{opencode_url}'. "
|
|
"Leave username and password blank. "
|
|
"Tap 'Save', 'Connect', or 'Done' to save the connection. "
|
|
"Report done when you can see the connection has been saved or the app navigated away from the add-connection form."
|
|
),
|
|
max_steps=max_steps_per_phase,
|
|
)
|
|
if not ok:
|
|
return {"status": "fail", "phase": "connect", "results": results}
|
|
|
|
_sleep(2.0)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 3: Connect to server — view session list
|
|
# -----------------------------------------------------------------------
|
|
ok = _run(
|
|
"session_list",
|
|
goal=(
|
|
"The connection has been saved. "
|
|
"Now tap on the saved connection entry to connect to the server. "
|
|
"Wait up to 10 seconds for the session list screen to appear. "
|
|
"The session list may be empty (no sessions yet) — that is fine. "
|
|
"Report done when you can see the session list screen (even if empty)."
|
|
),
|
|
max_steps=15,
|
|
)
|
|
if not ok:
|
|
return {"status": "fail", "phase": "session_list", "results": results}
|
|
|
|
_sleep(1.5)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 4: Create new session
|
|
# -----------------------------------------------------------------------
|
|
ok = _run(
|
|
"new_session",
|
|
goal=(
|
|
"You are on the sessions list screen. "
|
|
"Tap the '+' button (usually top-right) to create a new AI coding session. "
|
|
"Wait up to 5 seconds for the new session / chat screen to open. "
|
|
"Report done once you see a text input field at the bottom of the screen "
|
|
"(the session chat/input view is open)."
|
|
),
|
|
max_steps=12,
|
|
)
|
|
if not ok:
|
|
return {"status": "fail", "phase": "new_session", "results": results}
|
|
|
|
_sleep(1.0)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 5-6: Type TypeScript task and wait for opencode to complete
|
|
# -----------------------------------------------------------------------
|
|
ok = _run(
|
|
"typescript",
|
|
goal=(
|
|
f"You are inside a new OpenCode session (chat view with a text input at the bottom). "
|
|
f"Tap the text input field. "
|
|
f"Type this exact message: {TYPESCRIPT_TASK!r} "
|
|
"Press back to dismiss the keyboard. "
|
|
"Use the send action to submit. "
|
|
"After sending, wait and watch — opencode will show tool calls and file writes as it works. "
|
|
"Wait up to 90 seconds total for the session to go idle/complete "
|
|
"(no new activity for at least 5 seconds, or a completion indicator appears). "
|
|
"Re-check every 15 seconds by looking at the screen. "
|
|
"Report done when opencode appears to have finished (idle, no spinners, last message is a summary or file was created)."
|
|
),
|
|
max_steps=25,
|
|
)
|
|
if not ok:
|
|
return {"status": "fail", "phase": "typescript", "results": results}
|
|
|
|
_sleep(2.0)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 7: Verify output / success
|
|
# -----------------------------------------------------------------------
|
|
ok = _run(
|
|
"verify",
|
|
goal=(
|
|
"The opencode session has finished. "
|
|
"Look at the chat to confirm the TypeScript hello world task succeeded. "
|
|
"You should see: a mention of 'hello.ts', 'Hello, World!', a file creation tool call, "
|
|
"or a success summary from the assistant. "
|
|
"Take a clear screenshot showing the result. "
|
|
"Report done with a brief summary of what you see as evidence of success. "
|
|
"Report fail only if the screen clearly shows an error with no recovery."
|
|
),
|
|
max_steps=8,
|
|
)
|
|
# Verify phase is informational — continue even on uncertain result
|
|
_sleep(1.5)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Phase 8-9: Navigate to Settings, show model selection
|
|
# -----------------------------------------------------------------------
|
|
_run(
|
|
"settings",
|
|
goal=(
|
|
"Navigate to the Settings screen of the OpenCode mobile app. "
|
|
"Look for a gear icon, 'Settings' tab in the bottom navigation bar, "
|
|
"or a hamburger menu that contains Settings. Tap it. "
|
|
"Once on the Settings screen, look for a 'Model' or 'AI Model' option and tap it "
|
|
"to show the model selection list. "
|
|
"Take a screenshot showing the model list or model setting. "
|
|
"You do NOT need to change the model — just show it is accessible. "
|
|
"Report done when the settings/model screen is visible in a screenshot."
|
|
),
|
|
max_steps=15,
|
|
)
|
|
|
|
# Overall status: success if connect + session + typescript all succeeded
|
|
critical = ["connect", "session_list", "new_session", "typescript"]
|
|
failed_critical = [k for k in critical if results.get(k, {}).get("status") != "success"]
|
|
overall = "success" if not failed_critical else "partial"
|
|
return {"status": overall, "phase_results": results}
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Legacy smoke scenarios (kept for backwards compat / --scenario flag)
|
|
# ---------------------------------------------------------------------------
|
|
|
|
SMOKE_SCENARIOS = [
|
|
{
|
|
"name": "send_message",
|
|
"goal": (
|
|
"You see the OpenCode mobile app. Tap the '+' button (top-right) to create a new session. "
|
|
"Tap the text input at the bottom. Type 'ping'. Press back to dismiss keyboard. "
|
|
"Use the send action. Wait 5 seconds, then take another screenshot. "
|
|
"If you don't yet see an assistant reply, wait another 10 seconds and re-check. "
|
|
"If still no assistant bubble, wait another 15 seconds and re-check one more time. "
|
|
"Report success if you see both a 'You' bubble and an 'Assistant' bubble. "
|
|
"Report failure only after at least 30 seconds of total waiting with no assistant bubble."
|
|
),
|
|
},
|
|
{
|
|
"name": "multi_turn",
|
|
"goal": (
|
|
"You see the OpenCode mobile app. Tap '+' (top-right) to create a new session. "
|
|
"Tap the text input. Type 'what is 2+2'. Press back. Use send action. "
|
|
"Wait up to 30 seconds for an assistant reply (re-check every 10 seconds). "
|
|
"Then tap the text input again, type 'and 3+3?'. Press back. Use send action. "
|
|
"Wait up to 30 seconds for the second assistant reply (re-check every 10 seconds). "
|
|
"Report success if you see two assistant reply bubbles."
|
|
),
|
|
},
|
|
{
|
|
"name": "verify_session_list",
|
|
"goal": (
|
|
"You see the OpenCode mobile app. Tap the '+' button (top-right) to create a new session. "
|
|
"Wait 2 seconds for the session to be created. "
|
|
"Navigate back to the sessions list by tapping the 'Sessions' tab or pressing back. "
|
|
"Wait 3 seconds for the session list to load. "
|
|
"Report success if you can see at least one session entry in the list. "
|
|
"Report failure if the sessions list appears empty or shows an error message."
|
|
),
|
|
},
|
|
]
|
|
|
|
|
|
def _connect_and_verify_sessions_goal(url: str) -> str:
|
|
return (
|
|
f"You see the OpenCode mobile app. "
|
|
"Go to the Connections tab (bottom navigation bar). "
|
|
"If a connection to the server already exists, tap it to make it active and skip to the next step. "
|
|
"Otherwise tap '+' or 'Add Connection', "
|
|
f"enter the URL '{url}', leave username/password blank, tap Save or Connect. "
|
|
"Wait 3 seconds. "
|
|
"Now navigate to the Sessions tab (bottom navigation bar). "
|
|
"Wait 5 seconds for sessions to load. "
|
|
"If the sessions list is empty or shows 'No sessions yet', tap the '+' button "
|
|
"(top-right) to create a new session, wait 3 seconds, then navigate back to the "
|
|
"Sessions tab and wait 3 seconds for the list to refresh. "
|
|
"Report SUCCESS if you see at least one session listed (a session title is visible). "
|
|
"Report FAILURE if the sessions list is still empty, shows 'No sessions yet', or shows an error."
|
|
)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# CLI entry point
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description="OpenCode Mobile Android CUA smoke test — full onboarding showcase",
|
|
formatter_class=argparse.RawDescriptionHelpFormatter,
|
|
epilog="""
|
|
Examples:
|
|
# Full onboarding showcase (default, recommended for demo video):
|
|
source ~/.env.d/azure-openai.env
|
|
python scripts/android-cua-smoke.py --model gpt-5.4 --include-xml
|
|
|
|
# Speed up for a faster demo (0.5 = half the wait times):
|
|
python scripts/android-cua-smoke.py --speed-multiplier 0.5
|
|
|
|
# Legacy single-goal mode:
|
|
python scripts/android-cua-smoke.py --goal "Open settings"
|
|
|
|
# Legacy named scenario:
|
|
python scripts/android-cua-smoke.py --scenarios send_message,verify_session_list
|
|
""",
|
|
)
|
|
|
|
# Showcase mode (new default)
|
|
parser.add_argument(
|
|
"--showcase",
|
|
action="store_true",
|
|
default=True,
|
|
help="Run the full onboarding showcase (default). Demonstrates connect → session → TypeScript task → settings.",
|
|
)
|
|
parser.add_argument(
|
|
"--opencode-url",
|
|
default=None,
|
|
help=f"OpenCode server URL (default: {DEFAULT_OPENCODE_URL}).",
|
|
)
|
|
|
|
# Speed control
|
|
parser.add_argument(
|
|
"--speed-multiplier",
|
|
type=float,
|
|
default=1.0,
|
|
metavar="FACTOR",
|
|
help="Scale all wait/sleep durations. 0.5 = twice as fast, 2.0 = twice as slow. Default: 1.0",
|
|
)
|
|
|
|
# Model / verbosity
|
|
parser.add_argument("--model", default="gpt-4o", help="Vision model deployment name.")
|
|
parser.add_argument("--max-steps", type=int, default=20, help="Max LLM steps per phase (showcase) or total (legacy).")
|
|
parser.add_argument("--include-xml", action="store_true", help="Include UI hierarchy XML in LLM context (more accurate, more tokens).")
|
|
parser.add_argument("--quiet", action="store_true")
|
|
|
|
# Legacy / compat flags
|
|
parser.add_argument("--goal", help="Legacy: single custom goal (disables showcase).")
|
|
parser.add_argument(
|
|
"--scenarios",
|
|
help="Legacy: comma-separated scenario names to run (disables showcase). "
|
|
"Valid: connect_and_verify_sessions, send_message, multi_turn, verify_session_list.",
|
|
)
|
|
parser.add_argument(
|
|
"--skip-connect-scenario", action="store_true",
|
|
help="Legacy: skip the connect-and-verify regression scenario.",
|
|
)
|
|
parser.add_argument(
|
|
"--only-connect-scenario", action="store_true",
|
|
help="Legacy: run ONLY the connect-and-verify-sessions scenario.",
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
|
|
# Apply speed multiplier globally
|
|
global _speed_multiplier
|
|
_speed_multiplier = args.speed_multiplier
|
|
if args.speed_multiplier != 1.0:
|
|
print(f"[speed] multiplier={args.speed_multiplier} — all waits scaled accordingly")
|
|
|
|
# Verify ADB
|
|
try:
|
|
devices = adb("devices")
|
|
if "device" not in devices.split("\n", 1)[-1]:
|
|
sys.exit("No ADB device connected. Start emulator first.")
|
|
except FileNotFoundError:
|
|
sys.exit("adb not found in PATH")
|
|
|
|
connect_url = args.opencode_url or os.environ.get("OPENCODE_URL") or DEFAULT_OPENCODE_URL
|
|
|
|
# -----------------------------------------------------------------------
|
|
# Determine run mode: showcase vs. legacy scenarios
|
|
# -----------------------------------------------------------------------
|
|
use_legacy = bool(args.goal or args.scenarios or args.only_connect_scenario)
|
|
|
|
if not use_legacy:
|
|
# ----------------------------------------------------------------
|
|
# NEW DEFAULT: Full onboarding showcase
|
|
# ----------------------------------------------------------------
|
|
print("\n" + "=" * 64)
|
|
print(" OpenCode Mobile — Full Onboarding Showcase")
|
|
print(f" Server: {connect_url}")
|
|
print(f" Model: {args.model}")
|
|
print(f" Speed: {_speed_multiplier}x")
|
|
print("=" * 64)
|
|
|
|
rec_thread, _stop_ev, remote_path = start_screen_recording("onboarding_showcase")
|
|
local_video = "/tmp/cua_onboarding_showcase.mp4"
|
|
|
|
try:
|
|
if not ensure_app_foreground(verbose=not args.quiet):
|
|
print("[prep] warning: could not confirm app in foreground")
|
|
maybe_dismiss_telemetry_consent(verbose=not args.quiet)
|
|
ensure_app_foreground(verbose=not args.quiet)
|
|
|
|
result = run_onboarding_showcase(
|
|
opencode_url=connect_url,
|
|
model=args.model,
|
|
include_ui_xml=args.include_xml,
|
|
verbose=not args.quiet,
|
|
max_steps_per_phase=args.max_steps,
|
|
)
|
|
finally:
|
|
stop_screen_recording(rec_thread, remote_path, local_video)
|
|
upload_to_archivebox(local_video, "onboarding_showcase")
|
|
|
|
print("\n" + "=" * 64)
|
|
print(f" Showcase result: {result['status'].upper()}")
|
|
if local_video and Path(local_video).exists():
|
|
print(f" Video: {local_video}")
|
|
print("=" * 64)
|
|
|
|
# Print per-phase summary table
|
|
phase_results = result.get("phase_results", {})
|
|
if phase_results:
|
|
print("\n Phase breakdown:")
|
|
for phase, pr in phase_results.items():
|
|
icon = "PASS" if pr["status"] == "success" else "FAIL"
|
|
print(f" [{icon}] {phase:20s} {pr['status']:8s} {pr['steps']} steps")
|
|
|
|
sys.exit(0 if result["status"] == "success" else 1)
|
|
|
|
# -----------------------------------------------------------------------
|
|
# LEGACY MODE: named/custom scenarios
|
|
# -----------------------------------------------------------------------
|
|
connect_scenario = {
|
|
"name": "connect_and_verify_sessions",
|
|
"goal": _connect_and_verify_sessions_goal(connect_url),
|
|
}
|
|
|
|
if args.scenarios:
|
|
catalog = {connect_scenario["name"]: connect_scenario}
|
|
for s in SMOKE_SCENARIOS:
|
|
catalog[s["name"]] = s
|
|
requested = [n.strip() for n in args.scenarios.split(",") if n.strip()]
|
|
unknown = [n for n in requested if n not in catalog]
|
|
if unknown:
|
|
sys.exit(f"Unknown scenario(s): {', '.join(unknown)}. Valid: {', '.join(catalog.keys())}")
|
|
scenarios = [catalog[n] for n in requested]
|
|
elif args.only_connect_scenario:
|
|
scenarios = [connect_scenario]
|
|
else:
|
|
scenarios = [{"name": "custom", "goal": args.goal}] if args.goal else list(SMOKE_SCENARIOS)
|
|
if not args.goal and not args.skip_connect_scenario:
|
|
scenarios.append(connect_scenario)
|
|
|
|
results = []
|
|
for scenario in scenarios:
|
|
if not args.quiet:
|
|
print(f"\n{'='*60}")
|
|
print(f"Scenario: {scenario['name']}")
|
|
print(f"Goal: {scenario['goal'][:80]}...")
|
|
print(f"{'='*60}")
|
|
|
|
rec_thread, _stop_ev, remote_path = start_screen_recording(scenario["name"])
|
|
local_video = f"/tmp/cua_{scenario['name']}.mp4"
|
|
|
|
try:
|
|
if not ensure_app_foreground(verbose=not args.quiet):
|
|
print(f" [prep] warning: could not confirm {APP_PACKAGE} in foreground")
|
|
maybe_dismiss_telemetry_consent(verbose=not args.quiet)
|
|
ensure_app_foreground(verbose=not args.quiet)
|
|
|
|
result = run_cua_step(
|
|
goal=scenario["goal"],
|
|
max_steps=args.max_steps,
|
|
model=args.model,
|
|
include_ui_xml=args.include_xml,
|
|
verbose=not args.quiet,
|
|
step_label=scenario["name"],
|
|
)
|
|
finally:
|
|
stop_screen_recording(rec_thread, remote_path, local_video)
|
|
upload_to_archivebox(local_video, scenario["name"])
|
|
|
|
result["scenario"] = scenario["name"]
|
|
result["video"] = local_video if Path(local_video).exists() else None
|
|
results.append(result)
|
|
|
|
if not args.quiet:
|
|
print(f"\nResult: {result['status']} in {result['steps']} steps")
|
|
if result.get("video"):
|
|
print(f"Video: {result['video']}")
|
|
if result.get("summary"):
|
|
print(f"Summary: {result['summary']}")
|
|
if result.get("reason"):
|
|
print(f"Reason: {result['reason']}")
|
|
|
|
failed = [r for r in results if r["status"] != "success"]
|
|
if failed:
|
|
print(f"\n{'!'*60}")
|
|
print(f"FAILED: {len(failed)}/{len(results)} scenarios")
|
|
sys.exit(1)
|
|
else:
|
|
print(f"\nAll {len(results)} scenarios passed.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|