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41 lines
1.7 KiB
Python
41 lines
1.7 KiB
Python
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import processing
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import pandas as pd
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import gpt_alignment
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# paths to students andsewrs database
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studentAnswers1_path = "test_goldStandard/student/STSint.testinput.answers-students.sent1.txt"
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studentAnswers2_path = "test_goldStandard/student/STSint.testinput.answers-students.sent2.txt"
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studentAnsewrs_chunked_path1 = "test_goldStandard/student/STSint.testinput.answers-students.sent1.chunk.txt"
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studentAnsewrs_chunked_path2 = "test_goldStandard/student/STSint.testinput.answers-students.sent2.chunk.txt"
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studentsAnsewrs_alignment_path = "test_goldStandard/student/STSint.testinput.answers-students.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(studentAnsewrs_chunked_path1, studentAnsewrs_chunked_path2)
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goldstandard_alignment = processing.load_alignment(studentsAnsewrs_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 = processing.get_chunks_as_text(data)
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# generate a few examples
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#for i in range(1, 10):
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# print(processing.generate_alignment_format(data, i))
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# print("correct anwser for this is: ")
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# print(data["alignment_text"][i])
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# best prompt so far
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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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# Specify the file path
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file_path = "alignments_unformatted_student.txt"
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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')
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