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37 lines
1.5 KiB
Python
37 lines
1.5 KiB
Python
import processing
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import pandas as pd
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import gpt_alignment
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# Specify the output file path
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file_path = "alignments_unformatted_headlines.txt"
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# paths to students answers database
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#chunked_path1 = "test_goldStandard/student/STSint.testinput.answers-students.sent1.chunk.txt"
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#chunked_path2 = "test_goldStandard/student/STSint.testinput.answers-students.sent2.chunk.txt"
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#alignment_path = "test_goldStandard/student/STSint.testinput.answers-students.wa"
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# paths to headlines
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chunked_path1 = "test_goldStandard/headlines/STSint.testinput.headlines.sent1.chunk.txt"
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chunked_path2 = "test_goldStandard/headlines/STSint.testinput.headlines.sent1.chunk.txt"
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alignment_path = "test_goldStandard/headlines/STSint.testinput.headlines.wa"
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# load data
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#studentAnserws = processing.load_sentences(studentAnswers1_path, studentAnswers1_path)
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goldstandard_chunked = processing.load_chunked(chunked_path1, chunked_path2)
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goldstandard_alignment = processing.load_alignment(alignment_path)
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# get a nice anwser-student table
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data = pd.merge(goldstandard_chunked, goldstandard_alignment, left_index=True, right_index=True)
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#print(data)
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data_for_chat, indexes = processing.get_chunks_as_text(data)
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client = gpt_alignment.createGPT()
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responses = []
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for i in range(0, len(data_for_chat)):
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responses.append(gpt_alignment.callApi(client, data_for_chat[i]))
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# Writing to the file with repr() to preserve "\n" characters
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with open(file_path, 'w') as file:
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for string in responses:
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file.write(repr(string) + '\n') |