Delete app_back.py
Browse files- app_back.py +0 -154
app_back.py
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# -*- coding: utf-8 -*-
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"""
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Created on Mon Dec 25 18:18:27 2023
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@author: alish
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"""
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import gradio as gr
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import fitz # PyMuPDF
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import questiongenerator as qs
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import random
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from questiongenerator import QuestionGenerator
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qg = QuestionGenerator()
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def Extract_QA(qlist):
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Q_All=''
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A_All=''
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for i in range(len(qlist)):
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question_i= qlist[i]['question']
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Choices_ans= []
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Choice_is_correct=[]
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for j in range(4):
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Choices_ans= Choices_ans+ [qlist[i]['answer'][j]['answer']]
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Choice_is_correct= Choice_is_correct+ [qlist[i]['answer'][j]['correct']]
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Q=f"""
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Q_{i+1}: {question_i}
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A. {Choices_ans[0]}
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B. {Choices_ans[1]}
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C. {Choices_ans[2]}
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D. {Choices_ans[3]}
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"""
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xs=['A','B','C','D']
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result = [x for x, y in zip(xs, Choice_is_correct) if y ]
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A= f"""
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Answer_{i+1}: {result[0]}
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"""
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Q_All= Q_All+Q
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A_All=A_All+ A
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return (Q_All,A_All)
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def extract_text_from_pdf(pdf_file_path):
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# Read the PDF file
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global extracted_text
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text = []
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with fitz.open(pdf_file_path) as doc:
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for page in doc:
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text.append(page.get_text())
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extracted_text= '\n'.join(text)
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extracted_text= get_sub_text(extracted_text)
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return ("The pdf is uploaded Successfully from:"+ str(pdf_file_path))
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qg = qs.QuestionGenerator()
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def get_sub_text(TXT):
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sub_texts= qg._split_into_segments(TXT)
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if isinstance(sub_texts, list):
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return sub_texts
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else:
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return [sub_texts]
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def pick_One_txt(sub_texts):
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global selected_extracted_text
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N= len(sub_texts)
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if N==1:
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selected_extracted_text= sub_texts[0]
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return(selected_extracted_text)
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# Generate a random number between low and high
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random_number = random.uniform(0, N)
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# Pick the integer part of the random number
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random_number = int(random_number)
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selected_extracted_text= sub_texts[random_number]
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return(selected_extracted_text)
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def pipeline(NoQs):
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global Q,A
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text= selected_extracted_text
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qlist= qg.generate(text, num_questions=NoQs, answer_style="multiple_choice")
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Q,A= Extract_QA(qlist)
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A= A + '\n'+text
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return (Q,A)
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def ReurnAnswer():
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return A
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def GetQuestion(NoQs):
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NoQs=int(NoQs)
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pick_One_txt(extracted_text)
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Q,A=pipeline(NoQs)
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return Q
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with gr.Blocks() as demo:
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with gr.Row():
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#input_file=gr.File(type="filepath", label="Upload PDF Document")
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input_file=gr.UploadButton(label='Select a file!', file_types=[".pdf"])
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#upload_btn = gr.Button(value="Upload File")
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#txt= extract_text_from_pdf(input_file)
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with gr.Row():
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with gr.Column():
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upload_btn = gr.Button(value="Upload the pdf File.")
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Gen_Question = gr.Button(value="Show the Question(s)")
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Gen_Answer = gr.Button(value="Show the Answer(s)")
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No_Qs= gr.Slider(minimum=1, maximum=5,step=1, label='No Questions')
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'''
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with gr.Accordion("Instruction"):
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gr.Markdown("Start by selecting a 'pdf' file using 'Select file' tab." )
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gr.Markdown("Upload the selceted 'pdf' file using 'Upload the pdf file' tab." )
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gr.Markdown("The code will randomly select a block of the text and generate N questions form it each time you push 'Show Question(s)" )
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'''
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gr.Markdown(""" **Instruction**
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* Start by selecting a 'pdf' file using 'Select file' tab.
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* Upload the selceted 'pdf' file using 'Upload the pdf file' tab.
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* The code will randomly select a block of the text and generate N questions form it each time you push 'Show Question(s)'. """ )
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gr.Image("PupQuizAI.png")
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with gr.Column():
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file_stat= gr.Textbox(label="File Status")
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question = gr.Textbox(label="Question(s)")
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Answer = gr.Textbox(label="Answer(s)")
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'''
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with gr.Accordion("Instruction"):
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gr.Markdown("Start by selecting a 'pdf' file using 'Select file' tab." )
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gr.Markdown("Upload the selceted 'pdf' file using 'Upload the pdf file' tab." )
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gr.Markdown("The code will randomly select a block of the text and generate N questions form it each time you push 'Show Question(s)" )
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'''
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upload_btn.click(extract_text_from_pdf, inputs=input_file, outputs=file_stat, api_name="QuestioGenerator")
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Gen_Question.click(GetQuestion, inputs=No_Qs, outputs=question, api_name="QuestioGenerator")
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Gen_Answer.click(ReurnAnswer, inputs=None, outputs=Answer, api_name="QuestioGenerator")
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#examples = gr.Examples(examples=["I went to the supermarket yesterday.", "Helen is a good swimmer."],
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# inputs=[english])
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demo.launch()
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