






"""simple docstring"""





import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


UpperCamelCase					=     """
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
"""







class 						_a  (		unittest.TestCase							,	lowercase_       ):





   '''simple docstring'''






   def __lowercase							(       self)			->   List[str]:




          '''simple docstring'''




          lowercase__:							List[Any]         =     load_tool("summarization")
          self.tool.setup()
          lowercase__:							List[str]         =     load_tool("summarization"					, remote=UpperCAmelCase_)





   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          lowercase__:							str         =     self.tool(UpperCAmelCase_)
          self.assertEqual(
              UpperCAmelCase_					, "Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."					, )





   def __lowercase							(       self)			->   Optional[Any]:




          '''simple docstring'''




          lowercase__:							Dict         =     self.remote_tool(UpperCAmelCase_)
          self.assertEqual(
              UpperCAmelCase_					, "Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."					, )





   def __lowercase							(       self)			->   Tuple:




          '''simple docstring'''




          lowercase__:							str         =     self.tool(text=UpperCAmelCase_)
          self.assertEqual(
              UpperCAmelCase_					, "Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."					, )





   def __lowercase							(       self)			->   Any:




          '''simple docstring'''




          lowercase__:							int         =     self.remote_tool(text=UpperCAmelCase_)
          self.assertEqual(
              UpperCAmelCase_					, "Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM."					, )














"""simple docstring"""





from dataclasses import dataclass

UpperCamelCase					=     """0.1"""
UpperCamelCase					=     """Lucia Harcekova"""







@dataclass
class 						_a  :





   '''simple docstring'''






   UpperCamelCase__     	=							42
   UpperCamelCase__     	=							42
   UpperCamelCase__     	=							42





   def __repr__(       self)			->   str:




          '''simple docstring'''




          return F"""({self.offset}, {self.length}, {self.indicator})"""







class 						_a  :





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_ = 13					, UpperCAmelCase_ = 6)			->   None:




          '''simple docstring'''




          lowercase__:							Union[str, Any]         =     window_size
          lowercase__:							Any         =     lookahead_buffer_size
          lowercase__:							Optional[Any]         =     self.window_size - self.lookahead_buffer_size





   def __lowercase							(       self					, UpperCAmelCase_)			->   list[Token]:




          '''simple docstring'''




          lowercase__:							Any         =     []
          lowercase__:							Union[str, Any]         =     ""

          # while there are still characters in text to compress
          while text:
                 # find the next encoding phrase
                 # - triplet with offset, length, indicator (the next encoding character)
                 lowercase__:							Optional[Any]         =     self._find_encoding_token(UpperCAmelCase_					, UpperCAmelCase_)

                 # update the search buffer:
                 # - add new characters from text into it
                 # - check if size exceed the max search buffer size, if so, drop the
                 #   oldest elements
                 search_buffer += text[: token.length + 1]
                 if len(UpperCAmelCase_) > self.search_buffer_size:
                        lowercase__:							List[Any]         =     search_buffer[-self.search_buffer_size :]

                 # update the text
                 lowercase__:							List[str]         =     text[token.length + 1 :]

                 # append the token to output
                 output.append(UpperCAmelCase_)

          return output





   def __lowercase							(       self					, UpperCAmelCase_)			->   str:




          '''simple docstring'''




          lowercase__:							int         =     ""

          for token in tokens:
                 for _ in range(token.length):
                        output += output[-token.offset]
                 output += token.indicator

          return output





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_)			->   Token:




          '''simple docstring'''




          if not text:
                 raise ValueError("We need some text to work with.")

          # Initialise result parameters to default values
          lowercase__    ,      lowercase__:							Optional[int]         =     0, 0

          if not search_buffer:
                 return Token(UpperCAmelCase_					, UpperCAmelCase_					, text[length])

          for i, character in enumerate(UpperCAmelCase_):
                 lowercase__:							Union[str, Any]         =     len(UpperCAmelCase_) - i
                 if character == text[0]:
                        lowercase__:							Optional[Any]         =     self._match_length_from_index(UpperCAmelCase_					, UpperCAmelCase_					, 0					, UpperCAmelCase_)
                        # if the found length is bigger than the current or if it's equal,
                        # which means it's offset is smaller: update offset and length
                        if found_length >= length:
                               lowercase__    ,      lowercase__:							Any         =     found_offset, found_length

          return Token(UpperCAmelCase_					, UpperCAmelCase_					, text[length])





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_)			->   int:




          '''simple docstring'''




          if not text or text[text_index] != window[window_index]:
                 return 0
          return 1 + self._match_length_from_index(
              UpperCAmelCase_					, window + text[text_index]					, text_index + 1					, window_index + 1)


if __name__ == "__main__":
  from doctest import testmod

  testmod()
  # Initialize compressor class
  UpperCamelCase					=     LZaaCompressor(window_size=13, lookahead_buffer_size=6)

  # Example
  UpperCamelCase					=     """cabracadabrarrarrad"""
  UpperCamelCase					=     lzaa_compressor.compress(TEXT)
  print(lzaa_compressor.compress("""ababcbababaa"""))
  UpperCamelCase					=     lzaa_compressor.decompress(compressed_text)
  assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."






