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1. 使用到技术
- OpenAI KEY
- Serper KEY
- 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
