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
python
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
