File size: 3,065 Bytes
7f92d2c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | from typing import List, Dict, Any, Optional
from openai import OpenAI
import re
from urllib.parse import urlparse
import time
def extract_url_root_domain(url):
"""
从 URL 中提取根域名
例如:
- https://www.example.com/path -> example.com
- sub.example.co.uk -> example.co.uk
"""
# 确保 URL 包含协议，如果没有则添加
if not url.startswith(('http://', 'https://')):
url = 'http://' + url
# 使用 urlparse 解析 URL
parsed = urlparse(url).netloc
if not parsed:
parsed = url
# 移除端口号(如果存在)
parsed = parsed.split(':')[0]
# 分割域名部分
parts = parsed.split('.')
# 处理特殊的二级域名，如 .co.uk, .com.cn 等
if len(parts) > 2:
if parts[-2] in ['co', 'com', 'org', 'gov', 'edu', 'net']:
if parts[-1] in ['uk', 'cn', 'jp', 'br', 'in']:
return '.'.join(parts[-3:])
# 返回主域名部分（最后两部分）
return '.'.join(parts[-2:])
def get_clean_content(line):
clean_line = re.sub(r'^[\*\-•#\d\.]+\s*', '', line).strip()
clean_line = re.sub(r'^[\'"]|[\'"]$', '', clean_line).strip()
if (clean_line.startswith('"') and clean_line.endswith('"')) or \
(clean_line.startswith("'") and clean_line.endswith("'")):
clean_line = clean_line[1:-1]
return clean_line
def get_content_from_tag(content, tag, default_value=None):
# 说明：
# 1) (.*?) 懒惰匹配，尽量少匹配字符
# 2) (?=(</tag>|<\w+|$)) 使用前瞻，意味着当后面紧跟 </tag> 或 <任意单词字符开头的标签> 或文本结束时，都停止匹配
# 3) re.DOTALL 使得点号 . 可以匹配换行符
pattern = rf"<{tag}>(.*?)(?=(</{tag}>|<\w+|$))"
match = re.search(pattern, content, re.DOTALL)
if match:
return match.group(1).strip()
return default_value
def get_response_from_llm(
messages: List[Dict[str, Any]],
client: OpenAI,
model: str,
stream: Optional[bool] = False,
temperature: Optional[float] = 0.6,
depth: int = 0
):
try:
response = client.chat.completions.create(
model=model,
messages=messages,
temperature=temperature,
stream=stream
)
if hasattr(response.choices[0].message, 'content') and response.choices[0].message.content:
content = response.choices[0].message.content
return {
"content": content.strip()
}
except Exception as e:
print(f"LLM API error: {e}")
if "Input data may contain inappropriate content" in str(e):
return {
"content": ""
}
if "Error code: 400" in str(e):
return {
"content": ""
}
if depth < 512:
time.sleep(1)
return get_response_from_llm(messages=messages, client=client, model=model, stream=stream, temperature=temperature, depth=depth+1)
raise e
|