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180 lines
7.2 KiB
180 lines
7.2 KiB
# coding=utf-8
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import asyncio
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import re
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from functools import partial, wraps
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from json import JSONDecodeError
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from glom import glom
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from playwright.async_api import Browser
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from abs_spider import AbstractAiSeoSpider
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from domain.ai_seo import AiAnswer, AiSearchResult
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from utils import create_logger, parse_nested_json
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from utils.image_utils import crop_image_left
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logger = create_logger(__name__)
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class TongyiSpider(AbstractAiSeoSpider):
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async def do_check_session(self) -> bool:
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pass
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def __init__(self, browser: Browser, prompt: str, keyword: str, think: bool = False):
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super().__init__(browser, prompt, keyword, think)
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self.__listen_response = self.handle_listen_response_error(self.__listen_response)
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def get_home_url(self) -> str:
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return 'https://tongyi.aliyun.com'
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async def _do_spider(self) -> AiAnswer:
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# 初始化信息
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self._init_data()
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await self.browser_page.goto(self.get_home_url(), timeout=600000)
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if self.think:
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search_btn = self.browser_page.locator("div:text('深度思考')")
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if await search_btn.is_visible():
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await search_btn.click()
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await asyncio.sleep(1)
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else:
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search_btn = self.browser_page.locator("div:text('联网搜索')")
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if await search_btn.is_visible():
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await search_btn.click()
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await asyncio.sleep(1)
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# 开始操作
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# chat_input_element = self.browser_page.locator("//textarea[@placeholder='千事不决问通义']")
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chat_input_element = self.browser_page.locator("//textarea[contains(@class, 'ant-input')]")
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await chat_input_element.click()
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# 输入提问词
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await self.browser_page.keyboard.type(self.prompt)
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await asyncio.sleep(2)
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await self.browser_page.keyboard.press('Enter')
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# 监听请求
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self.browser_page.on('response', partial(self.__listen_response))
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await asyncio.sleep(2)
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await self.completed_event.wait()
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# 报错检查
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if self.fail_status:
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raise self.fail_exception
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# # 获取回答元素
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answer_element = self.browser_page.locator("//div[contains(@class, 'answerItem')]").nth(-1)
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box = await answer_element.bounding_box()
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logger.debug(f'answer_element: {box}')
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view_port_height = box['height'] + 500
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# 调整视口大小
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await self.browser_page.set_viewport_size({
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'width': 1920,
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'height': int(view_port_height)
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})
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# 打开搜索结果
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search_list_element = self.browser_page.locator("//div[contains(@class, 'linkTitle')]").nth(-1)
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if await search_list_element.is_visible():
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await search_list_element.click()
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await asyncio.sleep(2)
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# 关闭侧边栏
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side_console_element = self.browser_page.locator("//span[contains(@class, 'sc-frniUE')]")
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if await side_console_element.is_visible():
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await side_console_element.click()
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# 截图
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screenshot_path = self._get_screenshot_path()
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await self.browser_page.screenshot(path=screenshot_path)
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# 切割图片
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crop_image_left(screenshot_path, 340)
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self.ai_answer.screenshot_file = screenshot_path
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return self.ai_answer
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async def __listen_response(self, response):
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if '/dialog/conversation' not in response.url:
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return
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# 读取流式数据
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data = {}
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stream = await response.body()
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response_text = stream.decode('utf-8')
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datas = response_text.split("\n")
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# print("datas:",datas)
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# 合规数据转成字典
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for data_str in datas:
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if not data_str or data_str == 'data: [DONE]':
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continue
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data_str = data_str.replace('data: ', '')
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try:
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data = parse_nested_json(data_str)
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except JSONDecodeError as e:
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continue
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logger.debug(f"结果: {data}")
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# 获取结果
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contents = data.get('contents', [])
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# 保存搜索内容
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ai_search_result_list = []
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search_result_list = list()
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for content in contents:
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content_type = content.get('contentType', '')
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if content_type == 'plugin':
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logger.debug(f"获取到联网搜索结果")
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if self.think:
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search_result_list = glom(content, 'content.pluginResult.links', default=[])
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else:
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search_result_list = glom(content, 'content.pluginResult.links.-1.search_results', default=[])
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# for search_result in search_result_list:
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# url = search_result.get('url', '')
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# title = search_result.get('title', '')
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# body = search_result.get('body', '')
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# host_name = search_result.get('host_name', '未知')
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# publish_time = search_result.get('time', 0)
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# logger.debug(f"ai参考资料: [{host_name}]{title}({url})")
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# ai_search_result_list.append(
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# AiSearchResult(title=title, url=url, body=body, host_name=host_name, publish_time=publish_time)
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# )
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if content_type == 'think':
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logger.debug(f'获取到ai回复结果')
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answer = content.get('content', '').get('content', '')
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logger.debug(f"ai回复: {answer}")
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self.ai_answer.answer = answer
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pattern = r'ty-reference]\((\d+)\)'
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index_data = list(set(re.findall(pattern, self.ai_answer.answer)))
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for index, search_result in enumerate(search_result_list):
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url = search_result.get('url', '')
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title = search_result.get('title', '')
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body = search_result.get('body', '')
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host_name = search_result.get('host_name', '未知')
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publish_time = search_result.get('time', 0)
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if str(index+1) in index_data:
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is_referenced = "1"
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else:
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is_referenced = "0"
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logger.debug(f"ai参考资料: [{host_name}]{title}({url})")
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ai_search_result_list.append(
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AiSearchResult(title=title, url=url, body=body, host_name=host_name, publish_time=publish_time , is_referenced=is_referenced)
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)
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if ai_search_result_list:
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self.ai_answer.search_result = ai_search_result_list
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self.completed_event.set()
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def handle_listen_response_error(self, func):
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"""
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装饰器 用于处理请求回调中的异常
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:param func:
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:return:
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"""
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@wraps(func)
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async def wrapper(*args, **kwargs):
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try:
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return await func(*args, **kwargs)
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except Exception as e:
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logger.error(f"{self.get_platform_name()}响应异常: {e}", exc_info=True)
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# 标记失败状态 记录异常
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self.fail_status = True
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self.fail_exception = e
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self.completed_event.set()
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return wrapper
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def get_platform_id(self) -> int:
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return 2
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def get_platform_name(self) -> str:
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return 'TongYi'
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