52 lines
3.3 KiB
Python
52 lines
3.3 KiB
Python
"""Read-only production asset rendering; synthetic state and blocked networking."""
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import os
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os.environ['QT_QPA_PLATFORM'] = 'offscreen'
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import json, sys
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from pathlib import Path
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from PySide6.QtCore import QEventLoop, QTimer, QUrl
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from PySide6.QtWidgets import QApplication
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from PySide6.QtWebEngineWidgets import QWebEngineView
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from PySide6.QtWebEngineCore import QWebEnginePage, QWebEngineUrlRequestInterceptor
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DEST = Path(__file__).parent
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class DenyNetwork(QWebEngineUrlRequestInterceptor):
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def interceptRequest(self, info):
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if info.requestUrl().scheme() in ('http','https','ws','wss'):
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info.block(True)
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class Page(QWebEnginePage):
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def javaScriptConsoleMessage(self, level, message, line, source):
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print('JS:', str(message), flush=True)
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app=QApplication([])
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view=QWebEngineView(); page=Page(view); view.setPage(page)
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blocker=DenyNetwork(page); page.profile().setUrlRequestInterceptor(blocker)
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view.resize(1440,1000);view.show()
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def wait(ms):
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loop=QEventLoop();QTimer.singleShot(ms,loop.quit);loop.exec()
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def js(code):
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values=[];loop=QEventLoop()
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def done(value): values.append(value);loop.quit()
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page.runJavaScript(code,done);QTimer.singleShot(10000,loop.quit);loop.exec()
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if not values: raise RuntimeError('JS callback timeout')
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return values[0]
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loop=QEventLoop();loaded=[]
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view.loadFinished.connect(lambda ok:(loaded.append(ok),loop.quit()))
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view.load(QUrl.fromLocalFile(r'C:\wechat_rpa\assets\ui\zhenyang-ai-console.html'))
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QTimer.singleShot(15000,loop.quit);loop.exec()
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assert loaded==[True],loaded
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state={'view':'automation','ready':True,'demo':False,'automation':{'transport':'protocol','reviewAssistant':{
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'supported':True,'ready':True,'enabled':False,'busy':False,'accountId':'168800000000001','accountName':'合成账号',
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'recipient':{'id':'S:168800000000001_10001','name':'合成医疗助理','label':'企业微信客户 · 联系编号10001','kind':'企业微信客户','peerId':'10001'},
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'notification':{'message':'等待人工直接回复客户'},'preview':'【合成审核提醒内容】仅渲染测试，不发送消息'}}}
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js('window.applyState('+json.dumps(state)+');render("automation");fit();')
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metrics=[]
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for ms in (50,700,2000):
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wait(ms)
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dom=json.loads(js('JSON.stringify({visibility:document.visibilityState,view:STATE.view,mainText:document.querySelector("#main").textContent.length,mainRect:document.querySelector("#main").getBoundingClientRect().toJSON(),screenRect:document.querySelector(".screen").getBoundingClientRect().toJSON(),opacity:getComputedStyle(document.querySelector(".screen")).opacity,transform:getComputedStyle(document.querySelector("#stage")).transform,window:[innerWidth,innerHeight],toggleRect:document.querySelector("[data-action=review-assistant-toggle]").getBoundingClientRect().toJSON()})'))
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shot=view.grab();path=DEST/f'assistant-settings-independent-{ms}.png';assert shot.save(str(path))
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image=shot.toImage();pixels=set(image.pixelColor(x,y).name() for x in range(240,1350,9) for y in range(30,970,9))
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dom.update(wait_ms=ms,pixel_colors_main=len(pixels),path=str(path));metrics.append(dom)
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(DEST/'assistant-render-metrics.json').write_text(json.dumps(metrics,ensure_ascii=False,indent=2),encoding='utf-8')
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print(json.dumps(metrics,ensure_ascii=False,indent=2),flush=True)
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view.close();app.processEvents()
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os._exit(0)
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