# # Copyright 2024 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # 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.""" try: num_tokens = len(encoder.encode(string)) return num_tokens except Exception as e: pass return 0 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])