| from toolbox import CatchException, update_ui |
| from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping |
| import requests |
| from bs4 import BeautifulSoup |
| from request_llm.bridge_all import model_info |
|
|
| def google(query, proxies): |
| query = query |
| url = f"https://www.google.com/search?q={query}" |
| headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36'} |
| response = requests.get(url, headers=headers, proxies=proxies) |
| soup = BeautifulSoup(response.content, 'html.parser') |
| results = [] |
| for g in soup.find_all('div', class_='g'): |
| anchors = g.find_all('a') |
| if anchors: |
| link = anchors[0]['href'] |
| if link.startswith('/url?q='): |
| link = link[7:] |
| if not link.startswith('http'): |
| continue |
| title = g.find('h3').text |
| item = {'title': title, 'link': link} |
| results.append(item) |
|
|
| for r in results: |
| print(r['link']) |
| return results |
|
|
| def scrape_text(url, proxies) -> str: |
| """Scrape text from a webpage |
| |
| Args: |
| url (str): The URL to scrape text from |
| |
| Returns: |
| str: The scraped text |
| """ |
| headers = { |
| 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36', |
| 'Content-Type': 'text/plain', |
| } |
| try: |
| response = requests.get(url, headers=headers, proxies=proxies, timeout=8) |
| if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding |
| except: |
| return "无法连接到该网页" |
| soup = BeautifulSoup(response.text, "html.parser") |
| for script in soup(["script", "style"]): |
| script.extract() |
| text = soup.get_text() |
| lines = (line.strip() for line in text.splitlines()) |
| chunks = (phrase.strip() for line in lines for phrase in line.split(" ")) |
| text = "\n".join(chunk for chunk in chunks if chunk) |
| return text |
|
|
| @CatchException |
| def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): |
| """ |
| txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 |
| llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行 |
| plugin_kwargs 插件模型的参数，暂时没有用武之地 |
| chatbot 聊天显示框的句柄，用于显示给用户 |
| history 聊天历史，前情提要 |
| system_prompt 给gpt的静默提醒 |
| web_port 当前软件运行的端口号 |
| """ |
| history = [] |
| chatbot.append((f"请结合互联网信息回答以下问题：{txt}", |
| "[Local Message] 请注意，您正在调用一个[函数插件]的模板，该模板可以实现ChatGPT联网信息综合。该函数面向希望实现更多有趣功能的开发者，它可以作为创建新功能函数的模板。您若希望分享新的功能模组，请不吝PR！")) |
| yield from update_ui(chatbot=chatbot, history=history) |
|
|
| |
| from toolbox import get_conf |
| proxies, = get_conf('proxies') |
| urls = google(txt, proxies) |
| history = [] |
|
|
| |
| max_search_result = 5 |
| for index, url in enumerate(urls[:max_search_result]): |
| res = scrape_text(url['link'], proxies) |
| history.extend([f"第{index}份搜索结果：", res]) |
| chatbot.append([f"第{index}份搜索结果：", res[:500]+"......"]) |
| yield from update_ui(chatbot=chatbot, history=history) |
|
|
| |
| i_say = f"从以上搜索结果中抽取信息，然后回答问题：{txt}" |
| i_say, history = input_clipping( |
| inputs=i_say, |
| history=history, |
| max_token_limit=model_info[llm_kwargs['llm_model']]['max_token']*3//4 |
| ) |
| gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( |
| inputs=i_say, inputs_show_user=i_say, |
| llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, |
| sys_prompt="请从给定的若干条搜索结果中抽取信息，对最相关的两个搜索结果进行总结，然后回答问题。" |
| ) |
| chatbot[-1] = (i_say, gpt_say) |
| history.append(i_say);history.append(gpt_say) |
| yield from update_ui(chatbot=chatbot, history=history) |
|
|
|
|
