- import os
 - import re
 - import tiktoken
 - 
 - 
 - def singleton(cls, *args, **kw):
 -     instances = {}
 - 
 -     def _singleton():
 -         key = str(cls) + str(os.getpid())
 -         if key not in instances:
 -             instances[key] = cls(*args, **kw)
 -         return instances[key]
 - 
 -     return _singleton
 - 
 - 
 - def rmSpace(txt):
 -     txt = re.sub(r"([^a-z0-9.,]) +([^ ])", r"\1\2", txt, flags=re.IGNORECASE)
 -     return re.sub(r"([^ ]) +([^a-z0-9.,])", r"\1\2", txt, flags=re.IGNORECASE)
 - 
 - 
 - def findMaxDt(fnm):
 -     m = "1970-01-01 00:00:00"
 -     try:
 -         with open(fnm, "r") as f:
 -             while True:
 -                 l = f.readline()
 -                 if not l:
 -                     break
 -                 l = l.strip("\n")
 -                 if l == 'nan':
 -                     continue
 -                 if l > m:
 -                     m = l
 -     except Exception as e:
 -         pass
 -     return m
 - 
 -   
 - def findMaxTm(fnm):
 -     m = 0
 -     try:
 -         with open(fnm, "r") as f:
 -             while True:
 -                 l = f.readline()
 -                 if not l:
 -                     break
 -                 l = l.strip("\n")
 -                 if l == 'nan':
 -                     continue
 -                 if int(l) > m:
 -                     m = int(l)
 -     except Exception as e:
 -         pass
 -     return m
 - 
 - 
 - encoder = tiktoken.encoding_for_model("gpt-3.5-turbo")
 - 
 - def num_tokens_from_string(string: str) -> int:
 -     """Returns the number of tokens in a text string."""
 -     num_tokens = len(encoder.encode(string))
 -     return num_tokens
 - 
 - 
 - def truncate(string: str, max_len: int) -> int:
 -     """Returns truncated text if the length of text exceed max_len."""
 -     return encoder.decode(encoder.encode(string)[:max_len])
 
 
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