weilinliu55
cbdca1497c
- Extract device action execution into artemis/mcp action layer: typed ActionResult, capability manifest with startup validation, AdbActuator as the single physical implementation, in-memory ActionSession (replaces stdio subprocess MCP in validator), and McpActionExecutor preserving the legacy executor contract. adb_server keeps its external stdio/SSE surface unchanged and now reuses the actuator implementation; import-time side effects moved into configure_stdio_mode(). - Capability-gated prompt assembly (prompt_assembly.py): tool enums and teaching segments render per available backend tools; full-set output is byte-identical to the previous static text (locked by tests). - Admin console task queue: serial worker replaced by a per-device concurrent dispatcher (ARTEMIS_CONCURRENCY_MODE=global restores serial semantics), per-session cancellation, strict device binding on enqueue, unified stdio piping with tee to trace stdout.log, and shutdown cleanup of all active runs. Fix _pid_exists exception order so PermissionError is treated as alive. - mcp_server reliability: spawn watchdog kills runners stuck before interpreter startup and releases device reservations; task state reconcile uses psutil liveness, prefers runner-reported pids, and adds a 45s startup grace to stop false failure reports on Windows; conversation_id is now optional end-to-end; explicit device_serial is validated at submission. - CLI install now writes ~/.claude/rules/artemis.md for Claude Code and migrates/removes the legacy CLAUDE.md injection block; ~/.claude.json is never rewritten when it fails to parse. - Tests: Windows-portable stdio lifecycle and path assertions; new suites for action layer, prompt assembly, spawn watchdog, and task reconcile (895 passed, 3 skipped).
1269 lines
53 KiB
Python
1269 lines
53 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import asyncio
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import base64
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import difflib
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import json
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import math
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from pathlib import Path
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import re
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import time
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import traceback
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import uuid
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from uuid import UUID
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from langchain_core.messages import HumanMessage, SystemMessage
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from artemis.agents.validator.failure_analyzer import (
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FailureAnalyzer,
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ValidationErrorCategory,
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)
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from artemis.constants import (
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VALIDATOR_POLL_INTERVAL,
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VALIDATOR_POLL_TIMEOUT,
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VALIDATOR_UI_HIERARCHY_TIMEOUT,
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)
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from artemis.context import ArtemisContext
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from artemis.controllers.unified_controller import UnifiedMobileController
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from artemis.data_engine.trace import CURRENT_TRACE_ID, trace
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from artemis.graph.state import State
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from artemis.mcp.action_names import to_canonical_call
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from artemis.mcp.action_session import ActionSession, get_action_session
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from artemis.services.llm import get_llm
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from artemis.utils import image_diff, visualization
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from artemis.utils.decorators import wrap_with_callbacks
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from artemis.utils.logger import get_logger
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logger = get_logger(__name__)
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# Define actions that are permitted to succeed without a detected UI change
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ALLOW_NO_UI_CHANGE = {
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"wait_for_delay",
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"focus_and_clear_text",
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"launch_app",
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"stop_app",
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"press_key",
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"back",
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"erase_one_char",
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"swipe",
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}
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class ValidatorNode:
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"""Node responsible for executing actions on the device and verifying the results.
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Despite its name, this node handles:
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1. Parsing structured decisions from the Operator.
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2. Executing these actions via an MCP session (calling tools like tap,
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swipe, etc.).
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3. Verifying if the action resulted in a UI change.
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4. Triggering failure analysis and local repair if actions fail.
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In a more strict architecture, execution and validation might be split into
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separate nodes.
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"""
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def __init__(self, ctx: ArtemisContext):
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self.ctx = ctx
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async def _get_mcp_session(self) -> ActionSession:
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"""Returns the in-process unified action session (created lazily on ctx).
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The previous stdio-subprocess spawn -- and its local-controller fallback,
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which on Windows was the *only* path that ever ran -- is gone: the server now
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lives in-process, so there is no spawn to fail and exactly one execution path.
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"""
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return await get_action_session(self.ctx)
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def _parse_decisions(self, structured_decisions: str) -> tuple[list[dict] | None, str | None]:
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if not structured_decisions:
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return None, "No structured decisions found, nothing to execute."
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try:
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return json.loads(structured_decisions), None
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except json.JSONDecodeError as e:
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return None, f"Failed to parse structured decisions: {e}"
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async def _get_initial_screenshot(self, session, state: State) -> tuple[str, str | None]:
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screenshot_path = getattr(state, "latest_screenshot", None)
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if not screenshot_path:
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logger.error("No screenshot path found in state.latest_screenshot")
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raise ValueError("No screenshot path found in state.latest_screenshot")
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if not Path(screenshot_path).exists():
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logger.error(f"Screenshot file does not exist: {screenshot_path}")
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raise FileNotFoundError(f"Screenshot file does not exist: {screenshot_path}")
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try:
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with open(screenshot_path, "rb") as f:
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screenshot_b64 = base64.b64encode(f.read()).decode("utf-8")
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except Exception as e:
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logger.error(f"Failed to read screenshot from {screenshot_path}: {e}")
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raise e
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screenshot_name = Path(screenshot_path).stem
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return screenshot_b64, screenshot_name
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async def _poll_for_ui_change(
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self, session, pre_screenshot_b64, action_item
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) -> tuple[bool, str, str | None]:
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start_time = time.time()
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timeout = VALIDATOR_POLL_TIMEOUT
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ui_changed = False
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post_screenshot_b64 = None
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error_msg = ""
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while time.time() - start_time < timeout:
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try:
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content_img = await session.screenshot_b64()
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success_img = True
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except Exception as e:
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success_img, content_img = False, str(e)
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if success_img:
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post_screenshot_b64 = content_img
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img_before_bytes = base64.b64decode(pre_screenshot_b64)
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img_after_bytes = base64.b64decode(post_screenshot_b64)
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ui_changed = image_diff.check_ui_change(
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img_before_bytes, img_after_bytes, action_item
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)
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if ui_changed:
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logger.info("UI change detected during polling.")
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break
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else:
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logger.error(f"Failed to take screenshot via MCP: {content_img}")
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await asyncio.sleep(VALIDATOR_POLL_INTERVAL)
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if not ui_changed:
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error_msg = "Screen did not change"
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return ui_changed, error_msg, post_screenshot_b64
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async def _execute_validation_loop(self, state: State):
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actions, error_msg = self._parse_decisions(state.structured_decisions)
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if error_msg:
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return await state.asanitize_update(
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ctx=self.ctx,
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update={},
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agent="validator",
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)
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execution = []
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failed_action = None
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failure_reason = None
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actions_to_execute = list(actions)
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session = await self._get_mcp_session()
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try:
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last_screenshot_b64, last_screenshot_name = await self._get_initial_screenshot(
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session, state
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)
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# Preserve the turn-initial screenshot (what the operator saw when making decisions)
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decision_screenshot_b64 = last_screenshot_b64
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decision_screenshot_name = last_screenshot_name
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except Exception:
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return await state.asanitize_update(
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ctx=self.ctx,
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update={},
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agent="validator",
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)
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step_id = None
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if state.current_step_id:
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step_id = UUID(state.current_step_id)
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analysis_result = {}
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while actions_to_execute:
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action_item = actions_to_execute.pop(0)
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action_name = action_item.get("action")
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logger.info(f"Executing action: {action_name}")
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action_trace_id = uuid.uuid4()
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parent_id = CURRENT_TRACE_ID.get()
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token = CURRENT_TRACE_ID.set(action_trace_id)
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start_time = time.time()
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if self.ctx.data_engine and step_id:
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self.ctx.data_engine.record_trace(
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type="action",
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name=action_name,
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payload={"action": action_item, "status": "running"},
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status="running",
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parent_trace_id=parent_id,
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step_id=step_id,
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trace_id=action_trace_id,
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)
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try:
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pre_screenshot_b64 = last_screenshot_b64
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success = False
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error_msg = ""
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error_category = ValidationErrorCategory.GENERAL
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post_screenshot_b64 = None
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post_image_name = None
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action_item = dict(
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action_item
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) # Make a copy to avoid mutating original state actions
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attempts_log = []
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# 1. Pre-execution validation (Safety Net)
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original_coords = list(action_item.get("coordinates") or [])
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is_explorer_candidate = action_item.get("target_class") == "ExplorerCandidate"
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is_ocr_element = "[OCR]" in str(action_item.get("target_class") or "")
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has_index_metadata = bool(
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(
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action_item.get("target_text")
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or action_item.get("target_bounds")
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or action_item.get("target_resource_id")
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)
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and not is_explorer_candidate
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and not is_ocr_element
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)
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if has_index_metadata:
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# Index-based validation is fastest and safest when metadata is present
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(
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validation_passed,
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validation_category,
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validation_error,
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) = await self._validate_action_precondition(session, action_item, state=state)
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if not validation_passed:
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if validation_category == ValidationErrorCategory.XML_BYPASSED:
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logger.info(
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"Pre-execution XML-based validation bypassed"
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f" ({validation_error}). Falling back to"
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" Pixel-based validation..."
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)
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(
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validation_passed,
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validation_category,
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validation_error,
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) = await self._validate_action_precondition_pixel(
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session,
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action_item,
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pre_screenshot_b64,
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original_coords,
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state=state,
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)
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else:
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logger.info(
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"Pre-execution XML-based validation failed:"
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f" {validation_error}. Attempting Pixel-based"
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" validation fallback..."
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)
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(
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pixel_passed,
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pixel_category,
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pixel_error,
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) = await self._validate_action_precondition_pixel(
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session,
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action_item,
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pre_screenshot_b64,
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original_coords,
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state=state,
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)
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if pixel_passed and pixel_category == ValidationErrorCategory.NONE:
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logger.success(
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"Pixel-based validation fallback PASSED!"
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" Overriding XML validation failure."
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)
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validation_passed = True
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validation_category = ValidationErrorCategory.NONE
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validation_error = ""
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else:
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# Fall back to Pixel-based validation for pure coordinate/non-index interactions
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(
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validation_passed,
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validation_category,
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validation_error,
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) = await self._validate_action_precondition_pixel(
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session,
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action_item,
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pre_screenshot_b64,
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original_coords,
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state=state,
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)
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if not validation_passed:
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success = False
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error_msg = f"Pre-execution validation failed: {validation_error}"
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error_category = validation_category
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attempts_log.append(error_msg)
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# Capture the live mismatch screenshot to provide context for FailureAnalyzer
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try:
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post_screenshot_b64 = await session.screenshot_b64()
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except Exception as e:
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logger.error(f"Failed to capture live screenshot for failure analysis: {e}")
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post_screenshot_b64 = None
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else:
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# 2. Local execution attempts
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max_local_retries = 1 if action_name == "launch_app" else 2
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for attempt in range(max_local_retries):
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try:
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exec_success, exec_error = await self._exec_action(session, action_item)
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except Exception as e:
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exec_success = False
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exec_error = str(e)
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# Skip polling: assume execution success implies action success
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if exec_success:
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success = True
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error_msg = ""
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attempts_log.append("Success")
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break
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else:
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success = False
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error_msg = exec_error
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attempts_log.append(error_msg)
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if attempt < max_local_retries - 1:
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await asyncio.sleep(0.5)
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if not success and not post_screenshot_b64:
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logger.info("Action failed, capturing failure screenshot...")
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try:
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post_screenshot_b64 = await session.screenshot_b64()
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except Exception as e:
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logger.error(f"Failed to capture failure screenshot: {e!r}")
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post_screenshot_b64 = None
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# Enrich and record execution
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if len(attempts_log) > 1 or not success:
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action_item["attempts"] = list(attempts_log)
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execution.append(action_item)
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if post_screenshot_b64:
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decoded_bytes = base64.b64decode(post_screenshot_b64)
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last_screenshot_b64 = post_screenshot_b64
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logger.info(f"Successfully decoded post_screenshot_b64 ({len(decoded_bytes)} bytes)")
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if self.ctx.data_engine:
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post_image_name = self.ctx.data_engine.get_or_create_image(decoded_bytes)
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last_screenshot_name = post_image_name
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screenshot_path = str(self.ctx.data_engine.get_image_path(post_image_name))
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state.latest_screenshot = screenshot_path
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logger.info(
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f"Validator updated state.latest_screenshot to: {screenshot_path}"
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)
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# Update action trace with final results
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duration = time.time() - start_time
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if self.ctx.data_engine and step_id:
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relative_time = self.ctx.data_engine.get_relative_time(time.time())
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self.ctx.data_engine.record_trace(
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type="action",
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name=action_name,
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payload={
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"action": action_item,
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"success": success,
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"error_msg": error_msg,
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"post_screenshot": post_image_name,
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"timestamp": time.time(),
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"relative_time": relative_time,
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},
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status="success" if success else "failed",
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duration=duration,
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parent_trace_id=parent_id,
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step_id=step_id,
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trace_id=action_trace_id,
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)
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finally:
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CURRENT_TRACE_ID.reset(token)
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if not success:
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failed_action = action_item
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failure_reason = error_msg
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logger.warning(f"Action failed: {failed_action}. Triggering failure analysis.")
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analyzer = FailureAnalyzer(self.ctx)
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analysis_result = await analyzer.analyze(
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state,
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failed_action,
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failure_reason,
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pre_screenshot=decision_screenshot_b64,
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post_screenshot=post_screenshot_b64,
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pre_screenshot_name=decision_screenshot_name,
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post_screenshot_name=post_image_name,
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executed_actions=execution[:-1],
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unexecuted_actions=list(actions_to_execute),
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error_category=error_category,
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)
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action_item["repair"] = analysis_result.get("analysis", "No analysis provided.")
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status = analysis_result.get("status")
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if status == "fixed":
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logger.success("Failure repaired locally!")
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actions_to_execute = []
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# Reload the latest screenshot updated by FailureAnalyzer during repair
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try:
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screenshot_path = getattr(state, "latest_screenshot", None)
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if screenshot_path:
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if Path(screenshot_path).exists():
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with open(screenshot_path, "rb") as f:
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last_screenshot_b64 = base64.b64encode(f.read()).decode("utf-8")
|
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if self.ctx.data_engine:
|
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last_screenshot_name = self.ctx.data_engine.get_or_create_image(
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base64.b64decode(last_screenshot_b64)
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)
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logger.info(
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"Validator reloaded post-repair screenshot"
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f" from: {screenshot_path}"
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)
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except Exception as e:
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logger.error(f"Failed to reload post-repair screenshot: {e}")
|
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continue
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else:
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break
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|
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# Append any skipped actions to the execution log
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for skipped in actions_to_execute:
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skipped_copy = dict(skipped)
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skipped_copy["attempts"] = ["Skipped"]
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execution.append(skipped_copy)
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|
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report = {
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"execution": execution,
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"status": (
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"success"
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if success or (failed_action and analysis_result.get("status") == "fixed")
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else "failed"
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),
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"repair_status": (analysis_result.get("status") if failed_action else None),
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}
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|
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# Determine if a distinct post-action screenshot was captured
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distinct_post_image_name = (
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last_screenshot_name
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if (last_screenshot_name and last_screenshot_name != decision_screenshot_name)
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else None
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)
|
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|
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if self.ctx.data_engine and step_id:
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self.ctx.data_engine.update_step_execution_result(
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step_id, report, post_image_name=distinct_post_image_name
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)
|
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|
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return await state.asanitize_update(
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ctx=self.ctx,
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update={"last_execution_result": report},
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agent="validator",
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)
|
|
|
|
@wrap_with_callbacks(
|
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before=lambda: logger.info("Starting Validator Agent..."),
|
|
on_success=lambda _: logger.success("Validator Agent"),
|
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on_failure=lambda _: logger.error("Validator Agent"),
|
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)
|
|
@trace(type="agent", name="validator")
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|
async def __call__(self, state: State):
|
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|
|
step_id = None
|
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if state.current_step_id:
|
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step_id = UUID(state.current_step_id)
|
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|
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original_step_id = getattr(self.ctx.data_engine, "current_step_id", None)
|
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if self.ctx.data_engine and step_id:
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self.ctx.data_engine.current_step_id = step_id
|
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try:
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return await self._execute_validation_loop(state)
|
|
except asyncio.CancelledError:
|
|
# In-process session teardown happens in ArtemisContext.__aexit__; there
|
|
# is no subprocess left to kill.
|
|
logger.warning("Validator task cancelled (Stop requested).")
|
|
raise
|
|
except Exception as e:
|
|
err_stack = traceback.format_exc()
|
|
logger.critical(f"CRITICAL ERROR in Validator execution loop: {e}\n{err_stack}")
|
|
if self.ctx.data_engine and step_id:
|
|
try:
|
|
self.ctx.data_engine.update_step_execution_result(
|
|
step_id,
|
|
{
|
|
"status": "error",
|
|
"error_msg": str(e),
|
|
"traceback": err_stack,
|
|
},
|
|
)
|
|
except Exception:
|
|
pass
|
|
raise e
|
|
finally:
|
|
if self.ctx.data_engine:
|
|
self.ctx.data_engine.current_step_id = original_step_id
|
|
|
|
async def _exec_action(self, session: ActionSession, action_item: dict) -> tuple[bool, str]:
|
|
"""Executes one Operator action item through the unified action session.
|
|
|
|
The Operator's internal verbs (tap, long_press_on, focus_and_input_text, ...)
|
|
are translated to canonical tool calls in ``to_canonical_call`` using the
|
|
``normalized_coordinates`` the Operator already computed. Success comes from
|
|
the structured ``ActionResult.ok`` -- no string parsing.
|
|
"""
|
|
action_name = action_item.get("action")
|
|
|
|
if action_name == "wait_for_delay":
|
|
time_in_ms = action_item.get("time_in_ms", 0)
|
|
logger.info(f"Validator performing wait_for_delay for {time_in_ms}ms...")
|
|
await asyncio.sleep(time_in_ms / 1000.0)
|
|
return True, ""
|
|
|
|
width = getattr(self.ctx.device, "device_width", 1080) if self.ctx.device else 1080
|
|
height = getattr(self.ctx.device, "device_height", 2400) if self.ctx.device else 2400
|
|
|
|
try:
|
|
tool_name, wire_args = to_canonical_call(action_item, dims=(width, height))
|
|
except ValueError as e:
|
|
return False, str(e)
|
|
|
|
try:
|
|
res = await session.call(tool_name, wire_args)
|
|
except Exception as e:
|
|
return False, f"MCP call failed: {e}"
|
|
|
|
return (True, "") if res.ok else (False, res.message)
|
|
|
|
@trace(type="tool", name="safety_net_validation")
|
|
async def _validate_action_precondition(
|
|
self, session, action_item: dict, state: State | None = None
|
|
) -> tuple[bool, ValidationErrorCategory, str]:
|
|
"""Safety Net: Validates if the target element for interactive actions
|
|
|
|
is still present on the live screen and is substantially consistent,
|
|
with a short retry loop to accommodate screen transitions and loading
|
|
delays.
|
|
"""
|
|
max_pre_attempts = 3
|
|
pre_retry_delay = 0.4
|
|
|
|
passed = False
|
|
category = ValidationErrorCategory.NONE
|
|
reason = ""
|
|
|
|
for pre_attempt in range(1, max_pre_attempts + 1):
|
|
passed, category, reason = await self._validate_action_precondition_single(
|
|
session, action_item, state
|
|
)
|
|
if passed:
|
|
return True, category, reason
|
|
|
|
if category == ValidationErrorCategory.XML_BYPASSED:
|
|
# Do not retry on XML bypass/timeout; return immediately
|
|
# so it falls back to Pixel-based VLM validation
|
|
return False, category, reason
|
|
|
|
if pre_attempt < max_pre_attempts:
|
|
logger.info(
|
|
"Pre-execution validation failed on attempt"
|
|
f" {pre_attempt}/{max_pre_attempts}: {reason}. Retrying in"
|
|
f" {pre_retry_delay}s..."
|
|
)
|
|
await asyncio.sleep(pre_retry_delay)
|
|
else:
|
|
break
|
|
|
|
return passed, category, reason
|
|
|
|
async def _validate_action_precondition_single(
|
|
self, session, action_item: dict, state: State | None = None
|
|
) -> tuple[bool, ValidationErrorCategory, str]:
|
|
"""Safety Net: Validates if the target element for interactive actions
|
|
|
|
is still present on the live screen and is substantially consistent.
|
|
|
|
Returns (True, ValidationErrorCategory.NONE, "") if validation passes or
|
|
is skipped.
|
|
Returns (False, category, error_msg) if validation fails.
|
|
"""
|
|
action_name = action_item.get("action")
|
|
|
|
# 1. White-list filtering: Only validate interactive, element-focused actions
|
|
if action_name not in [
|
|
"tap",
|
|
"long_press_on",
|
|
"focus_and_input_text",
|
|
"focus_and_clear_text",
|
|
]:
|
|
return True, ValidationErrorCategory.NONE, ""
|
|
|
|
target_text = action_item.get("target_text")
|
|
target_bounds = action_item.get("target_bounds") # [l, t, r, b]
|
|
target_resource_id = action_item.get("target_resource_id")
|
|
|
|
width = 1080
|
|
height = 2400
|
|
operator_raw_data = getattr(state, "operator_raw_data", {}) or {}
|
|
w_raw = operator_raw_data.get("width")
|
|
h_raw = operator_raw_data.get("height")
|
|
if isinstance(w_raw, int) and isinstance(h_raw, int):
|
|
width = w_raw
|
|
height = h_raw
|
|
else:
|
|
device = getattr(self.ctx, "device", None)
|
|
if device:
|
|
width = getattr(device, "device_width", 1080)
|
|
height = getattr(device, "device_height", 2400)
|
|
|
|
# Calculate diagonal-based scale factor for resolution-independent thresholds
|
|
|
|
ref_diagonal = math.sqrt(1080**2 + 2400**2) # ~2631.8
|
|
current_diagonal = math.sqrt(width**2 + height**2)
|
|
scale_factor = current_diagonal / ref_diagonal
|
|
|
|
# 2. Skip validation if there's no target metadata to match against
|
|
if not target_text and not target_bounds and not target_resource_id:
|
|
return True, ValidationErrorCategory.NONE, ""
|
|
|
|
logger.info(
|
|
f"Pre-execution validation: checking target '{target_text}'"
|
|
f" ({target_resource_id}) at {target_bounds}..."
|
|
)
|
|
|
|
# 3. Pull live XML tree with strict timeout to avoid hanging the execution flow
|
|
|
|
try:
|
|
elements = None
|
|
try:
|
|
# The timeout must ride inside the session (MCP read timeout), never an
|
|
# outer asyncio.wait_for: cancelling call_tool mid-flight corrupts the
|
|
# in-memory transport and bricks the session for all later callers.
|
|
elements = await session.ui_hierarchy(timeout=VALIDATOR_UI_HIERARCHY_TIMEOUT)
|
|
except Exception as e:
|
|
logger.warning(
|
|
f"Failed to get live XML via MCP: {e!r}. Falling back to"
|
|
" Pixel-based validation."
|
|
)
|
|
return (
|
|
False,
|
|
ValidationErrorCategory.XML_BYPASSED,
|
|
f"XML hierarchy fetch timed out or errored: {e!r}",
|
|
)
|
|
|
|
if not elements or not isinstance(elements, list):
|
|
logger.warning(
|
|
"Live hierarchy empty or invalid. Falling back to Pixel-based validation."
|
|
)
|
|
return (
|
|
False,
|
|
ValidationErrorCategory.XML_BYPASSED,
|
|
"Live hierarchy empty or invalid.",
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(
|
|
f"Unexpected error during live XML fetch: {e}. Falling back to"
|
|
" Pixel-based validation."
|
|
)
|
|
return (
|
|
False,
|
|
ValidationErrorCategory.XML_BYPASSED,
|
|
f"Unexpected error during live XML fetch: {e}",
|
|
)
|
|
|
|
# 4. Matching Heuristics & Scoring
|
|
|
|
# Normalization Helper
|
|
def normalize_text(s: str | None) -> str:
|
|
if not s:
|
|
return ""
|
|
s = s.lower()
|
|
s = re.sub(r"\(\d+\+?\)", "", s)
|
|
s = re.sub(r"\[\d+\+?\]", "", s)
|
|
s = re.sub(r"[^\w\s\d]", "", s)
|
|
return s.strip()
|
|
|
|
# Recursive text aggregator for candidate container nodes
|
|
def aggregate_text(elem: dict) -> str:
|
|
text = (
|
|
elem.get("text") or elem.get("content-desc") or elem.get("accessibilityText") or ""
|
|
)
|
|
if not isinstance(text, str):
|
|
text = str(text)
|
|
children = elem.get("children") or []
|
|
if children:
|
|
for child in children:
|
|
if isinstance(child, dict):
|
|
text += " " + aggregate_text(child)
|
|
return text
|
|
|
|
norm_target_text = normalize_text(target_text)
|
|
|
|
candidates = []
|
|
for elem in elements:
|
|
if not isinstance(elem, dict):
|
|
continue
|
|
|
|
elem_bounds_str = elem.get("bounds")
|
|
elem_bounds = visualization.parse_bounds(elem_bounds_str)
|
|
if not elem_bounds:
|
|
continue
|
|
|
|
elem_raw_text = aggregate_text(elem)
|
|
elem_norm_text = normalize_text(elem_raw_text)
|
|
elem_res_id = elem.get("resource-id") or elem.get("resourceId") or ""
|
|
|
|
elem_cx, elem_cy = visualization.get_center_coordinates(*elem_bounds)
|
|
|
|
original_coords = action_item.get("coordinates") or [0, 0]
|
|
dist = math.sqrt(
|
|
(elem_cx - original_coords[0]) ** 2 + (elem_cy - original_coords[1]) ** 2
|
|
)
|
|
|
|
id_match = target_resource_id and elem_res_id and target_resource_id == elem_res_id
|
|
|
|
text_score = 0.0
|
|
if norm_target_text and elem_norm_text:
|
|
if norm_target_text == elem_norm_text:
|
|
text_score = 1.0
|
|
elif norm_target_text in elem_norm_text or elem_norm_text in norm_target_text:
|
|
text_score = 0.8
|
|
else:
|
|
text_score = difflib.SequenceMatcher(
|
|
None, norm_target_text, elem_norm_text
|
|
).ratio()
|
|
|
|
# Calculate bounds match (IoU)
|
|
bounds_score = 0.0
|
|
size_mismatch = False
|
|
if target_bounds and elem_bounds and len(target_bounds) == 4 and len(elem_bounds) == 4:
|
|
l1, t1, r1, b1 = target_bounds
|
|
l2, t2, r2, b2 = elem_bounds
|
|
|
|
# Check size ratio mismatch to prevent matching small widget to giant container
|
|
w1, h1 = r1 - l1, b1 - t1
|
|
w2, h2 = r2 - l2, b2 - t2
|
|
if w1 > 0 and h1 > 0 and w2 > 0 and h2 > 0:
|
|
size_ratio_w = max(w1, w2) / min(w1, w2)
|
|
size_ratio_h = max(h1, h2) / min(h1, h2)
|
|
if size_ratio_w > 2.5 or size_ratio_h > 2.5:
|
|
size_mismatch = True
|
|
|
|
li = max(l1, l2)
|
|
ti = max(t1, t2)
|
|
ri = min(r1, r2)
|
|
bi = min(b1, b2)
|
|
if ri > li and bi > ti:
|
|
inter_area = (ri - li) * (bi - ti)
|
|
union_area = (r1 - l1) * (b1 - t1) + (r2 - l2) * (b2 - t2) - inter_area
|
|
if union_area > 0:
|
|
bounds_score = inter_area / union_area
|
|
|
|
# Calculate Coordinate Containment
|
|
contains_coord = False
|
|
if (
|
|
original_coords
|
|
and len(original_coords) == 2
|
|
and elem_bounds
|
|
and len(elem_bounds) == 4
|
|
):
|
|
cx, cy = original_coords
|
|
l2, t2, r2, b2 = elem_bounds
|
|
contains_coord = l2 <= cx <= r2 and t2 <= cy <= b2
|
|
|
|
# Apply size mismatch penalty
|
|
if size_mismatch and not id_match:
|
|
text_score = 0.0
|
|
bounds_score = 0.0
|
|
contains_coord = False
|
|
|
|
# Define signal weights
|
|
W_id = 0.5
|
|
W_text = 0.4
|
|
W_bounds = 0.3
|
|
W_coord = 0.3
|
|
|
|
signals = []
|
|
weights = []
|
|
identity_signals = []
|
|
identity_weights = []
|
|
|
|
# 1. Resource ID Signal
|
|
if target_resource_id:
|
|
weights.append(W_id)
|
|
identity_weights.append(W_id)
|
|
if id_match:
|
|
signals.append(W_id * 1.0)
|
|
identity_signals.append(W_id * 1.0)
|
|
elif not elem_res_id:
|
|
signals.append(W_id * 0.3) # Soft penalty for missing ID
|
|
identity_signals.append(W_id * 0.3)
|
|
else:
|
|
signals.append(W_id * -0.5) # Hard penalty for mismatched ID
|
|
identity_signals.append(W_id * -0.5)
|
|
|
|
# 2. Text Signal
|
|
if target_text:
|
|
weights.append(W_text)
|
|
identity_weights.append(W_text)
|
|
if norm_target_text and elem_norm_text:
|
|
signals.append(W_text * text_score)
|
|
identity_signals.append(W_text * text_score)
|
|
elif not elem_norm_text:
|
|
signals.append(W_text * 0.0) # Penalty for missing expected text
|
|
identity_signals.append(W_text * 0.0)
|
|
|
|
# 3. Bounds Signal
|
|
if target_bounds:
|
|
weights.append(W_bounds)
|
|
signals.append(W_bounds * bounds_score)
|
|
|
|
# 4. Coordinate Containment Signal
|
|
if original_coords:
|
|
weights.append(W_coord)
|
|
signals.append(W_coord * (1.0 if contains_coord else 0.0))
|
|
|
|
if weights:
|
|
score = sum(signals) / sum(weights)
|
|
else:
|
|
score = 1.0
|
|
|
|
if identity_weights:
|
|
identity_score = sum(identity_signals) / sum(identity_weights)
|
|
else:
|
|
identity_score = 1.0
|
|
|
|
decay = max(0.5, 1.0 - (dist / 800.0))
|
|
score *= decay
|
|
|
|
candidates.append(
|
|
{
|
|
"element": elem,
|
|
"center": [elem_cx, elem_cy],
|
|
"bounds": elem_bounds,
|
|
"text": elem_raw_text,
|
|
"resource_id": elem_res_id,
|
|
"score": score,
|
|
"identity_score": identity_score,
|
|
"distance": dist,
|
|
"text_score": text_score,
|
|
"id_match": id_match,
|
|
}
|
|
)
|
|
|
|
if not candidates:
|
|
logger.warning(
|
|
"No candidates with valid bounds found. Falling back to Pixel-based validation."
|
|
)
|
|
return (
|
|
False,
|
|
ValidationErrorCategory.XML_BYPASSED,
|
|
"No candidates with valid bounds found.",
|
|
)
|
|
|
|
candidates.sort(key=lambda x: x["score"], reverse=True)
|
|
best = candidates[0]
|
|
|
|
passed = False
|
|
category = ValidationErrorCategory.NONE
|
|
reason = ""
|
|
|
|
threshold = 0.55 if best["distance"] <= 150 * scale_factor else 0.75
|
|
|
|
if best["score"] >= threshold:
|
|
passed = True
|
|
if best["distance"] <= 200 * scale_factor:
|
|
new_coords = best["center"]
|
|
old_coords = action_item.get("coordinates")
|
|
if old_coords != new_coords:
|
|
logger.success(
|
|
"Pre-execution validation SUCCESS"
|
|
f" (score={best['score']:.2f}). Target element"
|
|
f" '{target_text}' shifted by {best['distance']:.1f}px."
|
|
f" Self-healing: correcting coordinates {old_coords} ->"
|
|
f" {new_coords}."
|
|
)
|
|
action_item["coordinates"] = new_coords
|
|
# Drop the now-stale normalized coordinates so the canonical
|
|
# translation re-derives them from the healed pixel center.
|
|
action_item.pop("normalized_coordinates", None)
|
|
else:
|
|
logger.info(
|
|
"Pre-execution validation SUCCESS"
|
|
f" (score={best['score']:.2f}). Target element matched but"
|
|
f" shifted by {best['distance']:.1f}px"
|
|
f" (>{200 * scale_factor:.1f}px). Bypassing coordinate"
|
|
" self-healing to remain conservative."
|
|
)
|
|
else:
|
|
original_coords = action_item.get("coordinates")
|
|
|
|
# 1. Shifted Case: we must be conservative to avoid confusing disappearance as shift.
|
|
# Shift misclassification as disappeared is acceptable, but disappeared as shift
|
|
# causes errors.
|
|
is_valid_shift = False
|
|
|
|
# Enforce strict shift criteria (preferring disappeared over shifted)
|
|
max_allowed_distance = 100.0 * scale_factor
|
|
if best.get("id_match", False):
|
|
# Allow larger distance threshold only for strong resource ID matches
|
|
max_allowed_distance = 300.0 * scale_factor
|
|
|
|
if best["distance"] <= max_allowed_distance:
|
|
if best["identity_score"] >= 0.85:
|
|
# High confidence identity match (e.g. exact text or exact ID)
|
|
is_valid_shift = True
|
|
elif best["identity_score"] >= 0.5 and best.get("id_match", False):
|
|
# Moderate confidence with exact resource ID match
|
|
is_valid_shift = True
|
|
|
|
if is_valid_shift:
|
|
category = ValidationErrorCategory.TARGET_SHIFTED
|
|
reason = (
|
|
f"Target element '{target_text}' ({target_resource_id})"
|
|
f" expected at {original_coords} (bounds: {target_bounds})"
|
|
f" has shifted.\n- New location: {best['center']} (bounds:"
|
|
f" {best['bounds']})"
|
|
)
|
|
else:
|
|
# 2. Find the most specific element containing expected coordinates
|
|
occupant = None
|
|
if original_coords and len(original_coords) == 2:
|
|
orig_cx, orig_cy = original_coords
|
|
for elem in elements:
|
|
if not isinstance(elem, dict):
|
|
continue
|
|
elem_bounds_str = elem.get("bounds")
|
|
elem_bounds = visualization.parse_bounds(elem_bounds_str)
|
|
if elem_bounds:
|
|
left, top, right, bottom = elem_bounds
|
|
if left <= orig_cx <= right and top <= orig_cy <= bottom:
|
|
elem_area = (right - left) * (bottom - top)
|
|
if not occupant or elem_area < occupant[2]:
|
|
occupant = (elem, elem_bounds, elem_area)
|
|
|
|
def is_interactive(e: dict) -> bool:
|
|
clickable = e.get("clickable")
|
|
long_clickable = e.get("long-clickable") or e.get("longClickable")
|
|
focusable = e.get("focusable")
|
|
enabled = e.get("enabled")
|
|
|
|
def to_bool(v) -> bool:
|
|
if v is None:
|
|
return False
|
|
if isinstance(v, bool):
|
|
return v
|
|
return str(v).lower() == "true"
|
|
|
|
return (
|
|
to_bool(clickable)
|
|
or to_bool(long_clickable)
|
|
or to_bool(focusable)
|
|
or to_bool(enabled)
|
|
)
|
|
|
|
is_occupied = False
|
|
occupant_desc = "anonymous element"
|
|
occupant_bounds = None
|
|
|
|
if occupant:
|
|
elem, elem_bounds, _ = occupant
|
|
occupant_text = (
|
|
elem.get("text")
|
|
or elem.get("content-desc")
|
|
or elem.get("accessibilityText")
|
|
or ""
|
|
)
|
|
occupant_res_id = elem.get("resource-id") or elem.get("resourceId") or ""
|
|
occupant_bounds = elem_bounds
|
|
|
|
# Check if the occupant has content
|
|
has_content = bool(occupant_text or occupant_res_id)
|
|
|
|
# Check if this occupant or any container covering this point is interactive
|
|
coords_interactive = False
|
|
if original_coords and len(original_coords) == 2:
|
|
orig_cx, orig_cy = original_coords
|
|
for e in elements:
|
|
if not isinstance(e, dict):
|
|
continue
|
|
eb_str = e.get("bounds")
|
|
eb = visualization.parse_bounds(eb_str)
|
|
if eb:
|
|
e_left, e_top, e_right, e_bottom = eb
|
|
if e_left <= orig_cx <= e_right and e_top <= orig_cy <= e_bottom:
|
|
# Exclude full-screen root background elements
|
|
e_width = e_right - e_left
|
|
e_height = e_bottom - e_top
|
|
is_full_screen = (
|
|
e_width >= width - 10 and e_height >= height - 10
|
|
)
|
|
|
|
if is_interactive(e) and not is_full_screen:
|
|
coords_interactive = True
|
|
break
|
|
|
|
# Exclude full-screen or giant parent containers from being considered blockers
|
|
is_occupant_full_screen = False
|
|
if occupant_bounds:
|
|
o_w = occupant_bounds[2] - occupant_bounds[0]
|
|
o_h = occupant_bounds[3] - occupant_bounds[1]
|
|
is_occupant_full_screen = o_w >= width - 10 and o_h >= height - 10
|
|
|
|
# If target bounds are known, check if occupant is a giant container
|
|
if target_bounds:
|
|
t_w = target_bounds[2] - target_bounds[0]
|
|
t_h = target_bounds[3] - target_bounds[1]
|
|
t_area = t_w * t_h
|
|
o_area = o_w * o_h
|
|
if t_area > 0 and o_area > 3.0 * t_area:
|
|
is_occupant_full_screen = True
|
|
|
|
if (has_content or coords_interactive) and not is_occupant_full_screen:
|
|
is_occupied = True
|
|
occupant_desc = (
|
|
f"'{occupant_text}' ({occupant_res_id})"
|
|
if has_content
|
|
else "interactive anonymous element"
|
|
)
|
|
|
|
# If coordinates are occupied by a different active/labeled element
|
|
if is_occupied:
|
|
category = ValidationErrorCategory.TARGET_OCCUPIED
|
|
reason = (
|
|
f"The expected position {original_coords} for"
|
|
f" '{target_text}' ({target_resource_id}) is"
|
|
" occupied/intercepted by a different element:"
|
|
f" {occupant_desc} at bounds {occupant_bounds}."
|
|
)
|
|
else:
|
|
# 3. Completely Missing Case
|
|
category = ValidationErrorCategory.TARGET_DISAPPEARED
|
|
reason = (
|
|
f"Target element '{target_text}' ({target_resource_id})"
|
|
f" expected at {original_coords} (bounds:"
|
|
f" {target_bounds}) was not found on the screen."
|
|
)
|
|
|
|
return passed, category, reason
|
|
|
|
@trace(type="tool", name="safety_net_pixel_validation")
|
|
async def _validate_action_precondition_pixel(
|
|
self,
|
|
session,
|
|
action_item: dict,
|
|
pre_screenshot_b64: str,
|
|
original_coords: list[int] | None = None,
|
|
state: State | None = None,
|
|
) -> tuple[bool, ValidationErrorCategory, str]:
|
|
"""Pixel-level Safety Net: Validates if visual target button/component at
|
|
coordinates is still present, visible, and interactive on the live screen
|
|
compared to the original screenshot.
|
|
"""
|
|
action_name = action_item.get("action")
|
|
|
|
# 1. White-list filtering: Only validate interactive, element-focused actions
|
|
if action_name not in [
|
|
"tap",
|
|
"long_press_on",
|
|
"focus_and_input_text",
|
|
"input_text",
|
|
"click_coordinate",
|
|
"click",
|
|
"long_press",
|
|
]:
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
current_coords = action_item.get("coordinates")
|
|
orig_coords = original_coords or current_coords
|
|
|
|
if not orig_coords or len(orig_coords) != 2:
|
|
logger.info("Pixel safety net skipped: no valid coordinates.")
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
if not current_coords or len(current_coords) != 2:
|
|
current_coords = orig_coords
|
|
|
|
logger.info(
|
|
"Pre-execution pixel validation: checking target position"
|
|
f" {orig_coords} in original image vs {current_coords} on live"
|
|
" screen..."
|
|
)
|
|
|
|
# 2. Decode and crop the static reference (original) image ONCE outside the loop to save CPU
|
|
|
|
try:
|
|
orig_bytes = base64.b64decode(pre_screenshot_b64)
|
|
orig_crop_bytes = visualization.crop_and_annotate_target(
|
|
orig_bytes, orig_coords, crop_size=None, dot_radius=15
|
|
)
|
|
except Exception as e:
|
|
logger.error(
|
|
f"Failed to prepare original crop for pixel safety net: {e}. Bypassing check."
|
|
)
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
# 3. Get LLM Configuration once outside the loop
|
|
|
|
try:
|
|
try:
|
|
llm = get_llm(self.ctx, name="validator_pixel_safety_net")
|
|
except Exception:
|
|
llm = get_llm(self.ctx, name="validator")
|
|
|
|
# Load prompt template once
|
|
prompt_path = Path(__file__).parent.joinpath("pixel_safety_net.md")
|
|
prompt = prompt_path.read_text(encoding="utf-8")
|
|
except Exception as e:
|
|
logger.error(
|
|
f"Failed to initialize LLM/prompt for pixel safety net: {e}. Bypassing check."
|
|
)
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
# 4. Start high-precision execution validation retry loop
|
|
max_attempts = 3
|
|
retry_delay_seconds = 0.3
|
|
last_error = None
|
|
|
|
for attempt in range(1, max_attempts + 1):
|
|
logger.info(f"Pre-execution pixel validation: Attempt {attempt}/{max_attempts}...")
|
|
try:
|
|
# A. Take fresh live screenshot (captures state changes / dynamic loading settling)
|
|
live_screenshot_b64 = None
|
|
try:
|
|
live_screenshot_b64 = await session.screenshot_b64()
|
|
success_img = True
|
|
except Exception:
|
|
success_img, live_screenshot_b64 = False, None
|
|
|
|
if not success_img or not live_screenshot_b64:
|
|
raise Exception("Failed to acquire live screenshot from controller/MCP tool.")
|
|
|
|
# B. Decode and crop the live screen target
|
|
live_bytes = base64.b64decode(live_screenshot_b64)
|
|
live_crop_bytes = visualization.crop_and_annotate_target(
|
|
live_bytes, current_coords, crop_size=None, dot_radius=15
|
|
)
|
|
|
|
orig_b64 = base64.b64encode(orig_crop_bytes).decode("utf-8")
|
|
live_b64 = base64.b64encode(live_crop_bytes).decode("utf-8")
|
|
|
|
# C. Formulate multi-modal verification message
|
|
user_content = [
|
|
{"type": "text", "text": "[Image 1 (Reference)]"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": f"data:image/jpeg;base64,{orig_b64}"},
|
|
},
|
|
{"type": "text", "text": "[Image 2 (Current State)]"},
|
|
{
|
|
"type": "image_url",
|
|
"image_url": {"url": f"data:image/jpeg;base64,{live_b64}"},
|
|
},
|
|
]
|
|
if state:
|
|
thoughts = []
|
|
native_thought = getattr(state, "operator_native_thinking", None)
|
|
if native_thought and native_thought.strip():
|
|
thoughts.append(native_thought.strip())
|
|
raw_thought = getattr(state, "operator_raw_thinking", None)
|
|
if raw_thought and raw_thought.strip():
|
|
thoughts.append(raw_thought.strip())
|
|
|
|
operator_thought = "\n\n".join(thoughts)
|
|
if operator_thought.strip():
|
|
context_text = (
|
|
"[Planned Action & Original Thinking]\nAction:"
|
|
f" {action_name}\nOriginal"
|
|
f" Thinking:\n{operator_thought.strip()}"
|
|
)
|
|
user_content.append({"type": "text", "text": f"\n{context_text.strip()}"})
|
|
|
|
messages = [
|
|
SystemMessage(content=prompt),
|
|
HumanMessage(content=user_content),
|
|
]
|
|
|
|
# D. Invoke Universal VLM
|
|
response = await llm.ainvoke(messages)
|
|
output = response.content if isinstance(response.content, str) else ""
|
|
if isinstance(response.content, list):
|
|
output = "".join(
|
|
b.get("text", "")
|
|
for b in response.content
|
|
if isinstance(b, dict) and "text" in b
|
|
)
|
|
|
|
if output.startswith("```"):
|
|
code_match = re.search(r"```(?:json)?\s*([\s\S]*?)\s*```", output)
|
|
if code_match:
|
|
output = code_match.group(1).strip()
|
|
|
|
res_json = json.loads(output)
|
|
reasoning = res_json.get("reasoning", "")
|
|
is_present = res_json.get("is_present", True)
|
|
confidence = res_json.get("confidence", 1.0)
|
|
|
|
logger.info(
|
|
f"Pixel validation attempt {attempt}/{max_attempts} result:"
|
|
f" is_present={is_present}, confidence={confidence:.2f}, reasoning={reasoning}"
|
|
)
|
|
|
|
# E. Branching based on outcome
|
|
if is_present:
|
|
logger.info(f"Pixel validation SUCCESS on attempt {attempt}/{max_attempts}.")
|
|
return True, ValidationErrorCategory.NONE, ""
|
|
|
|
# Target not present: fail or bypass based on confidence without retry!
|
|
if confidence >= 0.7:
|
|
reason_msg = (
|
|
f"Pixel-level validation failed: {reasoning}"
|
|
if reasoning
|
|
else (
|
|
"Pixel-level validation failed: The target UI"
|
|
" element at the exact coordinates has disappeared,"
|
|
" changed, or is blocked."
|
|
)
|
|
)
|
|
return (
|
|
False,
|
|
ValidationErrorCategory.PIXEL_TARGET_DISAPPEARED,
|
|
reason_msg,
|
|
)
|
|
else:
|
|
logger.warning(
|
|
"Pixel validation failed but confidence"
|
|
f" ({confidence:.2f}) is below 0.7. Bypassing check."
|
|
)
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
except Exception as attempt_err:
|
|
logger.warning(
|
|
f"Error during pixel validation attempt {attempt}/{max_attempts}: {attempt_err}"
|
|
)
|
|
last_error = attempt_err
|
|
if attempt < max_attempts:
|
|
await asyncio.sleep(retry_delay_seconds)
|
|
continue
|
|
else:
|
|
logger.error(
|
|
"Pixel validation repeatedly failed with errors. Last"
|
|
f" error: {last_error}. Bypassing check to avoid"
|
|
" blocking flow."
|
|
)
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|
|
|
|
return True, ValidationErrorCategory.PIXEL_BYPASSED, ""
|