SakuraFrp 自动签到（main + sakura_frp_auto_check + SakuraFrpQiandao），已排除 .env 与日志
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RRRosmontis
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import logging
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import time
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import random
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import json
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import re
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from typing import Optional, Dict
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from openai import OpenAI
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from playwright.sync_api import Page
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from playwright.sync_api import TimeoutError as PlaywrightTimeoutError
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from config import Config
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logger = logging.getLogger(__name__)
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class ModelApiError(Exception):
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"""模型 API 错误，属于不可重试错误。"""
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class CaptchaHandler:
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"""验证码处理器"""
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def __init__(self, config: Config):
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self.config = config
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self.client = OpenAI(
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base_url=config.base_url,
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api_key=config.api_key
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)
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def get_img(self, page: Page):
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try:
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# 获取验证码图片
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captcha_img_element = page.locator(".geetest_tip_img")
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captcha_img_element.wait_for(state="visible", timeout=10000)
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# 获取 CSS 属性
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bg_style = captcha_img_element.evaluate(
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"el => window.getComputedStyle(el).backgroundImage"
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)
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# 正则匹配
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match = re.search(r'url\(["\']?(.*?)["\']?\)', bg_style)
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if match:
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img_url = match.group(1)
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logger.info(f"成功获取验证码图片 URL: {img_url}")
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return img_url
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else:
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logger.error("无法提取验证码图片 URL")
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return ""
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except PlaywrightTimeoutError:
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logger.info("未检测到 GeeTest 验证码窗口")
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return False
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def handle_geetest_captcha(self, page: Page) -> bool:
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"""处理 GeeTest 九宫格验证码（带重试机制）"""
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logger.info("开始处理 GeeTest 验证码...")
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try:
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# 获取验证码图片
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img_url = self.get_img(page)
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if not img_url:
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logger.error("图片获取失败，刷新网页重试...")
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time.sleep(2)
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return False
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# 调用视觉模型识别，imagebase64 由配置控制
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recognition_result = self._recognize_captcha(img_url, imagebase64=self.config.image_as_base64)
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if not recognition_result:
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logger.warning("识别失败，刷新网页重试...")
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time.sleep(2)
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return False
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logger.info(f"验证码识别结果: {recognition_result}")
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# 根据识别结果点击相应的九宫格
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if not self._click_captcha_items(page, recognition_result):
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logger.warning("点击失败，刷新网页重试...")
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time.sleep(2)
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return False
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logger.warning("验证码流程完成，刷新网页验证是否成功...")
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time.sleep(2)
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return True
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except ModelApiError:
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raise
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except Exception as e:
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logger.error(f"处理验证码时发生错误: {e}", exc_info=True)
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return False
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def _recognize_captcha(self, img_url: str, imagebase64: bool = False) -> Optional[Dict]:
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"""使用视觉模型识别验证码，支持 imagebase64 方式"""
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try:
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prompt = (
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'这是一个九宫格验证码，请按从左到右、从上到下的顺序识别每个格子里的物品名称，'
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'最后识别左下角的参考图。输出格式为JSON：{"1":"名称", "2":"名称", ..., "10":"参考图名称"}。'
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'名称要简洁，参考图名称必须是九宫格里已有的名称。若有类似物品（如气球与热气球），请统一名称。'
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)
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image_url_value = img_url
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if imagebase64:
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import requests, base64
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try:
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resp = requests.get(img_url)
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resp.raise_for_status()
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img_bytes = resp.content
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img_b64 = base64.b64encode(img_bytes).decode('utf-8')
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image_url_value = f"data:image/jpeg;base64,{img_b64}"
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except Exception as e:
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logger.error(f"图片转base64失败: {e}")
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raise ModelApiError("图片转base64失败") from e
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response = self.client.chat.completions.create(
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model=self.config.model,
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messages=[{
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'role': 'user',
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'content': [
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{'type': 'text', 'text': prompt},
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{'type': 'image_url', 'image_url': {'url': image_url_value}}
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]
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}],
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stream=False
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)
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response_data = response.model_dump() if hasattr(response, "model_dump") else {}
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logger.debug(f"模型完整响应: {response_data}")
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for error_key in ("error", "errors"):
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if response_data.get(error_key):
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logger.error(f"模型 API 返回错误: {response_data[error_key]}")
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raise ModelApiError("模型 API 返回错误")
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choices = response_data.get("choices") or []
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if not choices:
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logger.error(f"模型 API 返回非标准成功响应，缺少 choices: {response_data}")
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raise ModelApiError("模型 API 返回非标准成功响应")
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result_content = choices[0].get("message", {}).get("content")
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if not result_content:
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logger.error(f"模型 API 响应缺少 message.content: {response_data}")
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raise ModelApiError("模型 API 响应缺少 message.content")
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logger.info(f"模型原始输出: {result_content}")
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json_text = self._extract_json(result_content)
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if not json_text:
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logger.error("无法从模型输出中提取有效 JSON")
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raise ModelApiError("模型输出不包含有效 JSON")
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cleaned_str = json_text.replace("'", '"').strip()
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result_dict = json.loads(cleaned_str)
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if isinstance(result_dict, dict) and result_dict.get("error"):
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logger.error(f"模型 API 返回错误: {result_dict['error']}")
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raise ModelApiError("模型 API 返回错误")
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return result_dict
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except json.JSONDecodeError as e:
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logger.error(f"JSON 解析失败: {e}")
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raise ModelApiError("模型输出 JSON 解析失败") from e
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except Exception as e:
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if isinstance(e, ModelApiError):
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raise
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status_code = getattr(e, "status_code", None)
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if status_code:
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logger.error(f"模型 API 调用失败，HTTP {status_code}: {e}")
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else:
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logger.error(f"模型 API 调用失败: {e}", exc_info=True)
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raise ModelApiError("模型 API 调用失败") from e
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@staticmethod
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def _extract_json(text: str) -> Optional[str]:
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"""从模型输出中提取 JSON，兼容代码块、Qwen box 标记和普通说明文本。"""
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if not isinstance(text, str):
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text = str(text)
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box_match = re.search(r'<\|begin_of_box\|>(.*?)<\|end_of_box\|>', text, flags=re.DOTALL)
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if box_match:
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return box_match.group(1).strip()
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code_block_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', text, flags=re.DOTALL)
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if code_block_match:
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return code_block_match.group(1).strip()
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start = text.find('{')
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if start == -1:
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return None
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stack = 0
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for i in range(start, len(text)):
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if text[i] == '{':
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stack += 1
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elif text[i] == '}':
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stack -= 1
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if stack == 0:
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return text[start:i + 1].strip()
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return None
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def _click_captcha_items(self, page: Page, recognition_result: Dict) -> bool:
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"""
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根据识别结果点击九宫格中匹配的格子
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九宫格布局（索引从1开始）：
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1 2 3
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4 5 6
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7 8 9
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第10个是参考图（左下角）
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"""
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try:
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# 获取参考图名称（第10个元素）
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target_name = recognition_result.get("10", "").strip()
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if not target_name:
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logger.error("未能从识别结果中获取参考图名称")
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return False
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logger.info(f"目标物品: {target_name}")
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# 获取所有九宫格元素（前9个）
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grid_items = page.locator(".geetest_item")
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item_count = grid_items.count()
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# 排除最后一个（参考图），只处理前9个
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if item_count < 9:
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logger.error(f"九宫格元素数量不足，只找到 {item_count} 个")
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return False
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# 遍历前9个格子，找到匹配的物品并点击
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clicked_count = 0
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for i in range(9):
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position = i + 1 # 位置索引从1开始
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item_name = recognition_result.get(str(position), "").strip()
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logger.info(f"位置 {position}: {item_name}")
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# 如果当前格子的物品名称匹配参考图
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if item_name and item_name == target_name:
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logger.info(f"找到匹配项！位置 {position} - {item_name}")
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# 点击该格子
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try:
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grid_items.nth(i).click()
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clicked_count += 1
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logger.info(f"已点击位置 {position}")
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# 点击后短暂等待，模拟人类操作
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time.sleep(random.uniform(0.3, 0.6))
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except Exception as e:
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logger.error(f"点击位置 {position} 时出错: {e}")
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if clicked_count == 0:
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logger.warning(f"未找到匹配 '{target_name}' 的格子")
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return False
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logger.info(f"共点击了 {clicked_count} 个匹配的格子")
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# 点击完成后，查找并点击确认按钮
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try:
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# 等待确认按钮变为可用状态（移除 geetest_disable 类）
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confirm_button = page.locator(".geetest_commit")
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confirm_button.wait_for(state="attached", timeout=5000)
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# 检查按钮是否可用（没有 geetest_disable 类）
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button_classes = confirm_button.get_attribute("class") or ""
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logger.info(f"确认按钮状态: {button_classes}")
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# 等待按钮变为可点击状态（最多等待3秒）
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max_wait = 3
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start = time.time()
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while "geetest_disable" in (confirm_button.get_attribute("class") or ""):
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if time.time() - start > max_wait:
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logger.warning("确认按钮未激活，但仍尝试点击")
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break
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time.sleep(0.2)
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logger.info("找到确认按钮，准备点击...")
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confirm_button.click(force=True)
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logger.info("已点击确认按钮")
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time.sleep(1)
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except PlaywrightTimeoutError:
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logger.info("未找到确认按钮，可能自动提交")
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return True
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except Exception as e:
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logger.error(f"点击验证码格子时发生错误: {e}", exc_info=True)
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return False
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def _refresh_captcha(self, page: Page) -> bool:
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"""刷新验证码"""
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try:
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logger.info("正在刷新验证码...")
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page.locator(".geetest_refresh").click()
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logger.info("已点击刷新按钮")
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time.sleep(1.5) # 等待新验证码加载
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return True
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except Exception as e:
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logger.error(f"刷新验证码失败: {e}")
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return False
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