1. 使用到技术

1. OpenAI KEY
2. Serper KEY
3. Bing Search

2. 原理解析

使用Google和Bing的搜搜结果交由OpenAI处理并给出回答。

3. 代码实现

import requests from lxml import etree import os from openai import OpenAI  # 从环境变量中加载 API 密钥 os.environ["OPENAI_API_KEY"] = "sk-xxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" os.environ["SERPER_API_KEY"] = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" # 确保在执行代码前已经设置了环境变量 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") SERPER_API_KEY = os.getenv("SERPER_API_KEY")  def search_bing(query):     headers = {         'Referer': 'https://www.bing.com/',         'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36',     }     params = {         'q': query,         'mkt': 'zh-CN'     }      response = requests.get('https://www.bing.com/search', params=params, headers=headers)      html = etree.HTML(response.text)      li_list = html.xpath("//li[@class='b_algo']")      result = []      for index in range(len(li_list)):         title = ";".join(li_list[index].xpath("./h2/a/text()"))         link = li_list[index].xpath("./h2/a/@href")[0]         snippet = ";".join(li_list[index].xpath("./div/p/text()"))         position = index         print(title, link, snippet, position)         result.append({             'title': title,             'link': link,             'snippet': snippet,             'position': position,         })     return result  def search_serper(query):     """使用Serper API进行搜索并返回结果。"""     url = "https://google.serper.dev/search"     headers = {         "X-API-KEY": SERPER_API_KEY,         "Content-Type": "application/json",     }     params = {         'q': query,         'gl': "cn",         'hl': "zh-cn",     }      try:         response = requests.post(url, headers=headers, json=params)         response.raise_for_status()  # 检查HTTP请求状态         serper_data = response.json()         if not serper_data:             return "无法获取搜索结果", []         google_context = serper_data.get('organic', [])         google_other = serper_data.get('relatedSearches', [])         return google_context, google_other     except requests.RequestException as e:         print(f"请求失败: {e}")         return None  def search_openai(query, context):     """利用OpenAI API回答问题并引用相关上下文，并使用流的方式输出。"""     context_template = (         "你是GinLynn构建的大型语言AI助手。给你一个用户问题，请正确、简洁、准确的讲述这个问题的答案。"         "你会得到一组与问题相关的上下文，其中每个对象都是一个json字符串，"         "'snippet'字段表示片段，'title'字段表示标题，'link'字段表示链接，'position'字段表示位置。"         "请使用这些上下文并在每个句子的末尾引用上下文(如果适用)。"         "你的答案必须是正确、准确的，由专家以公正和专业的语气撰写。请限制为2048token。"         "不要给出任何与问题无关的信息，也不要重复。如果给定的上下文没有提供足够的信息，"         "那么在相关主题后面加上“information is missing on”。请以[position]的格式注明出处和参考编号。"         "以下是一组上下文:"     )      client = OpenAI(api_key=OPENAI_API_KEY)      try:         completion = client.chat.completions.create(             model="gpt-4o",             messages=[                 {"role": "system", "content": context_template + context},                 {"role": "user", "content": query}             ],             stream=True  # 启用流式响应         )          # 逐条打印流式输出的结果         for chunk in completion:             if chunk.choices[0].delta.content is not None:                 print(chunk.choices[0].delta.content, end="")          print()  # 输出换行         return "完成输出"      except Exception as e:         print(f"OpenAI API request failed: {e}")         return "无法完成请求", []   if __name__ == '__main__':     query = input("请输入查询: ")      if query.strip() == "":         query = "最新俄乌局势信息"      print("正在搜索...")     serper_context, other_queries = search_serper(query)     bing_context = search_bing(query)      context = []     if bing_context:         context.extend(bing_context)     if serper_context:         # 为Serper上下文的每个条目重置 position 值，以防止重复         for index, item in enumerate(serper_context, start=len(bing_context)):             item['position'] = index  # 从当前Bing结果的数量开始         context.extend(serper_context)      print("搜索结果:", context)     search_openai(query, str(context))      if other_queries:         print("相关搜索:", other_queries)  

4. 运行结果