mirror of
https://github.com/kuhyx/WUT_Computer_Science.git
synced 2026-07-04 18:23:15 +02:00
314 lines
12 KiB
Python
314 lines
12 KiB
Python
from openai import OpenAI
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import os
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import re
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def sentence_loop(sentences):
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# Process each sentence
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chunked_sentences = []
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for sentence in sentences:
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chunked_sentences = process_sentence(sentence, chunked_sentences)
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if chunked_sentences == False:
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return
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return chunked_sentences
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def is_correct_format(s):
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# Regular expression to match sequences of '[ some words ]'
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pattern = r'^(\[\s*[^]]+\s*\]\s*)+$'
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# Check if the string matches the pattern
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return bool(re.match(pattern, s))
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def check_format(input_data):
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# Check if the input is a string, and if so, process it directly
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if isinstance(input_data, str):
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return is_correct_format(input_data)
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# If the input is a list, process each element in the list
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elif isinstance(input_data, list):
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return [is_correct_format(string) for string in input_data]
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# Return None or raise an error if the input is neither a string nor a list
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else:
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return None
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def reformat_list(strings):
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result = []
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for string in strings:
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# Remove leading numbering like '1. '
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string = re.sub(r'^\d+\.\s*', '', string)
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# Check if the string contains partially formatted brackets
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if '[' in string and ']' in string:
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# Splitting the string into parts that are enclosed in square brackets
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parts = re.findall(r'\[[^\]]*\]', string)
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# Check for trailing punctuation after the last bracket and add it to the last part
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trailing_punctuation = re.search(r'\]\s*([.!?])\s*$', string)
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if trailing_punctuation and parts:
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parts[-1] = parts[-1][:-1] + trailing_punctuation.group(1) + ']'
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result.extend(parts)
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# Handle strings without square brackets
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else:
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# Splitting based on the dashed pattern and removing the numbering
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parts = re.split(r'\s*-\s*', string)
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parts = [part.strip() for part in parts if part.strip()]
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# Enclosing each part in square brackets
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for part in parts:
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result.append(f'[ {part} ]')
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return ' '.join(result)
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def reformat_square_not_full(input_string):
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# Split the string into parts that are either in brackets or not
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parts = re.split(r'(\[[^\]]*\])', input_string)
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formatted_parts = []
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for part in parts:
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if part: # Ignore empty strings
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# For parts not in brackets, remove trailing period, trim spaces, and enclose in brackets
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if not part.startswith('['):
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part = re.sub(r'\.\s*$', '', part).strip()
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formatted_parts.append(f"[ {part} ]")
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else:
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# For parts already in brackets, add spaces inside
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formatted_parts.append(re.sub(r'\[([^]]+)\]', r'[ \1 ]', part))
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return ' '.join(formatted_parts)
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def reformat_slash(input_string):
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# Split the string on slashes and strip spaces
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parts = [part.strip() for part in input_string.split('/')]
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# Enclose each part in square brackets
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formatted_parts = [f"[ {part} ]" for part in parts]
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return ' '.join(formatted_parts)
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def reformat_pipe(input_string):
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# Split the string on ' | ' and strip spaces
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parts = [part.strip() for part in input_string.split('|')]
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# Enclose each part in square brackets
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formatted_parts = [f"[ {part} ]" for part in parts]
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return ' '.join(formatted_parts)
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def is_pipe_format(s):
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# Regular expression to check for ' | ' pattern
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pattern = r'^(?:[^|]+\|)+[^|]+$'
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return bool(re.match(pattern, s))
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def is_numbered_line_format(s):
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# Regular expression to match lines starting with 'number. word/phrase \n'
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pattern = r'^(?:\d+\.\s+.+\n?)+$'
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# Check if the input is a list of strings
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if isinstance(s, list):
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return [bool(re.match(pattern, string)) for string in s]
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# If the input is a single string, process it directly
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return bool(re.match(pattern, s))
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def reformat_ists(input_string):
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# Use regular expression to find all occurrences of the iSTS pattern and extract the text
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parts = re.findall(r'\(iSTS \d+\)\s*([^)]+)', input_string)
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# Enclose each extracted part in square brackets
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formatted_parts = [f"[ {part.strip()} ]" for part in parts]
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return ' '.join(formatted_parts)
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def is_ists_format(s):
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# Regular expression to check for the iSTS pattern
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pattern = r'^(?:\(iSTS \d+\)\s*[^)]+\s*)+$'
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return bool(re.match(pattern, s))
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def reformat_with_sections(input_string):
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# Use regular expression to extract text following the section labels
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parts = re.split(r'\s*\[\s*S\d+\s*\]\s*', input_string)
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# Remove empty strings and enclose each part in square brackets
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formatted_parts = [f"[ {part.strip()} ]" for part in parts if part.strip()]
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return ' '.join(formatted_parts)
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def is_section_format(s):
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# Regular expression to check for the section label pattern
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pattern = r'^(?:\s*\[\s*S\d+\s*\]\s*.+)+$'
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return bool(re.match(pattern, s))
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def is_chunk_format(s):
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# Regular expression to check for both 'Chunk X: text' and '[Chunk X] text' patterns
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pattern = r'^(Chunk \d+:\s*.+?|\[\s*Chunk \d+\s*\]\s*.+?)(\s+(Chunk \d+:\s*.+?|\[\s*Chunk \d+\s*\]\s*.+?))*$'
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return bool(re.match(pattern, s))
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def reformat_chunks(input_string):
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# Find all occurrences of both chunk patterns and extract the text
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parts = re.findall(r'Chunk \d+:\s*(.+?)(?=\s*Chunk \d+:|$)|\[\s*Chunk \d+\s*\]\s*(.+?)(?=\s*\[\s*Chunk \d+\s*\]|$)', input_string)
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# Flatten the list of tuples and remove empty strings
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flattened_parts = [item for sublist in parts for item in sublist if item]
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# Enclose each extracted part in square brackets
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formatted_parts = [f"[ {part.strip()} ]" for part in flattened_parts]
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return ' '.join(formatted_parts)
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def reformat_ists_markers(input_string):
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# Split the string at '[ iSTS ]', remove empty strings, and enclose each part in square brackets
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parts = [part.strip() for part in re.split(r'\[\s*iSTS\s*\]', input_string) if part.strip()]
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formatted_parts = [f"[ {part} ]" for part in parts]
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return ' '.join(formatted_parts)
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def is_ists_marker_format(s):
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# Regular expression to check for the pattern with '[ iSTS ]'
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pattern = r'^(?:\[\s*iSTS\s*\].+)+$'
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return bool(re.match(pattern, s))
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def reformat_with_dashes(input_string):
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# Split the string on ' - ', remove empty strings, and enclose each part in square brackets
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parts = [part.strip() for part in input_string.split('-') if part.strip()]
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formatted_parts = [f"[ {part} ]" for part in parts]
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return ' '.join(formatted_parts)
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def is_dash_format(s):
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# Regular expression to check for the pattern with ' - '
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pattern = r'^[^-]+(?:\s*-\s*[^-]+)+$'
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return bool(re.match(pattern, s))
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def preliminary_reformat(input_string):
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input_string = input_string.strip("iSTS chunks:")
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input_string = input_string.strip("Here are the iSTS chunks for the given sentence:")
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return input_string
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def reformat_brackets_and_text(input_string):
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# Remove the trailing dot if present
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input_string = re.sub(r'\.$', '', input_string)
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# Split the string into parts that are either in brackets or not
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parts = re.split(r'(\[[^\]]*\])', input_string)
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formatted_parts = []
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for part in parts:
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if part: # Ignore empty strings
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# Remove commas and trim spaces for parts not in brackets
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if not part.startswith('['):
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part = re.sub(r',\s*', ' ', part).strip()
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# Enclose the non-bracket part in brackets
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formatted_parts.append(f"[ {part} ]")
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else:
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# Directly append the part in brackets
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formatted_parts.append(part)
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return ' '.join(formatted_parts)
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def is_brackets_and_text_format(s):
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# Regular expression to check the pattern
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pattern = r'^(\[[^\]]*\]|\s*[^[\]]+\s*)(,\s*|\s+|$)+$'
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return bool(re.match(pattern, s))
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def reformat(input_string):
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input_string = preliminary_reformat(input_string)
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if check_format(input_string):
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return input_string
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# Check if the string is of the first type (numbered list)
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if is_numbered_line_format(input_string):
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print("formated by reformat_list", input_string)
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return reformat_list(input_string)
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elif is_brackets_and_text_format(input_string):
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print("is_brackets_and_text_format")
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return reformat_brackets_and_text(input_string)
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# Check if the string is of the second type (already contains square brackets)
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elif '[' in input_string and ']' in input_string:
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print("formated by reformat_square_not_full")
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return reformat_square_not_full(input_string)
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# Check for the new type with slashes
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elif '/' in input_string:
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print("formated by reformat_slash")
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return reformat_slash(input_string)
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elif is_pipe_format(input_string):
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print("formated by reformat_pipe")
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return reformat_pipe(input_string)
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elif is_ists_format(input_string):
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print("formated by reformat_ists")
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return reformat_ists(input_string)
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elif is_section_format(input_string):
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print("formated by is_section_format")
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return reformat_with_sections(input_string)
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elif is_chunk_format(input_string):
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print("formated by reformat_chunks")
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return reformat_chunks(input_string)
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elif is_ists_marker_format(input_string):
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print("formated by reformat ists markers")
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return reformat_ists_markers(input_string)
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# Return the original string if it does not match either type
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elif is_dash_format(input_string):
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print("formated by reformat with dashes")
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return reformat_with_dashes(input_string)
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print("ERROR! reformat did not recognize the format of string! ", input_string)
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return False
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def remove_empty_brackets(input_string):
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# Regular expression to match empty brackets (with any number of spaces)
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pattern = r'\[\s*\]'
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# Replace empty brackets with an empty string
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cleaned_string = re.sub(pattern, '', input_string)
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# Remove any extra spaces that might be left after removing brackets
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cleaned_string = re.sub(r'\s{2,}', ' ', cleaned_string).strip()
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return cleaned_string
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def reformat_brackets(input_string):
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formatted_string = re.sub(r'\[\s*(.*?)\s*\]', r'[ \1 ]', input_string)
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return formatted_string
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def process_sentence(sentence, chunked_sentences):
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# Define the instruction with line breaks to ensure each line is within 80 characters
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instruction = (
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"Please divide the following sentence into iSTS chunks. Try to return chunks as a string in format [chunk 1] [chunk 2] [chunk 3] and so on... Here is the sentence: " + sentence
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)
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# API call with the instruction variable
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response = client.chat.completions.create(
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messages=[{
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"role": "user",
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"content": instruction,
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}],
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model="gpt-3.5-turbo",
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)
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chunked_sentence = response.choices[0].message.content
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chunked_sentence = chunked_sentence.strip()
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reformated = reformat(chunked_sentence)
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if reformated == False:
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print("ERROR! failed to reformat! ", chunked_sentence, reformated)
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return False
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reformated = reformated.strip(',')
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if not is_correct_format(reformated):
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print("ERROR! wrong format ", chunked_sentence, reformated)
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return False
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print("after reformation: ", reformated)
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reformated = remove_empty_brackets(reformated)
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reformated = reformat_brackets(reformated)
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chunked_sentences.append(reformated)
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return chunked_sentences
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def chunk_sentences(file_path, output_path):
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# Read the sentences from the file
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with open(file_path, 'r') as file:
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sentences = file.readlines()
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# Process each sentence
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chunk_sentences = sentence_loop(sentences)
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print(chunk_sentences)
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# Write the chunked sentences to a new file
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with open(output_path, 'w') as output_file:
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for sentence in chunk_sentences:
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output_file.write(sentence + '\n')
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# Usage
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file_path = 'test_goldStandard/student/STSint.testinput.answers-students.sent1.txt'
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output_path = 'output.txt'
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# Change me to os.environ['API_KEY']
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client = OpenAI(api_key='REDACTED_OPENAI_API_KEY')
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chunk_sentences(file_path, output_path)
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