app.py

# -*- coding: utf-8 -*-
"""
Created on Mon Dec 25 18:18:27 2023

@author: alish
"""

import gradio as gr
import fitz  # PyMuPDF
import questiongenerator as qs
import random

from questiongenerator import QuestionGenerator
qg = QuestionGenerator()



def Extract_QA(qlist):
        i=0
        question_i= qlist[i]['question']
        Choices_ans= []
        Choice_is_correct=[]
        for j in range(4):
           Choices_ans= Choices_ans+ [qlist[i]['answer'][j]['answer']]
           Choice_is_correct= Choice_is_correct+ [qlist[i]['answer'][j]['correct']]
           
        Q=f"""
             Q: {question_i}
             A. {Choices_ans[0]}
             B. {Choices_ans[1]}
             C. {Choices_ans[2]}
             D. {Choices_ans[3]}   
            """
        xs=['A','B','C','D']
        result = [x for x, y in zip(xs, Choice_is_correct) if y ]
        A= f"""
            The rigth answer is: {result[0]}
            """
        return (Q,A)






def extract_text_from_pdf(pdf_file_path):
    # Read the PDF file
    global extracted_text
    text = []
    with fitz.open(pdf_file_path) as doc:
        for page in doc:
            text.append(page.get_text())
    extracted_text= '\n'.join(text)
    extracted_text= get_sub_text(extracted_text)
    
    return ("The pdf is uploaded Successfully from:"+ str(pdf_file_path))

qg = qs.QuestionGenerator()

def get_sub_text(TXT):
   sub_texts= qg._split_into_segments(TXT)
   if isinstance(sub_texts, list):
       return sub_texts
   else:
       return [sub_texts]

def pick_One_txt(sub_texts):
    global selected_extracted_text
    N= len(sub_texts)
    if N==1:
       selected_extracted_text= sub_texts[0] 
       return(selected_extracted_text)
    # Generate a random number between low and high
    random_number = random.uniform(0, N)    
    # Pick the integer part of the random number
    random_number = int(random_number)
    selected_extracted_text= sub_texts[random_number]
        
    return(selected_extracted_text)
 

def pipeline():
    global Q,A
    text= selected_extracted_text
    qlist= qg.generate(text, num_questions=1, answer_style="multiple_choice")
    Q,A= Extract_QA(qlist)
    A= A + '\n'+text
    return (Q,A)

def ReurnAnswer():
    return A

def GetQuestion():
    pick_One_txt(extracted_text)
    Q,A=pipeline()
    return Q

with gr.Blocks() as demo:
    
    with gr.Row():
        #input_file=gr.File(type="filepath", label="Upload PDF Document")
        input_file=gr.UploadButton(label='Select a file!', file_types=[".pdf"])
        #upload_btn = gr.Button(value="Upload File")
        #txt= extract_text_from_pdf(input_file)
    with gr.Row():
        with gr.Column():
            upload_btn = gr.Button(value="Upload the pdf File.")
            Gen_Question = gr.Button(value="Show the Question")
            Gen_Answer = gr.Button(value="Show the Answer")
            
        with gr.Column():
            file_stat= gr.Textbox(label="File Status")
            question = gr.Textbox(label="Question(s)")
            Answer = gr.Textbox(label="Answer(s)")

    
    upload_btn.click(extract_text_from_pdf, inputs=input_file, outputs=file_stat, api_name="QuestioGenerator")
    Gen_Question.click(GetQuestion, inputs=None, outputs=question, api_name="QuestioGenerator")
    Gen_Answer.click(ReurnAnswer, inputs=None, outputs=Answer, api_name="QuestioGenerator")
    #examples = gr.Examples(examples=["I went to the supermarket yesterday.", "Helen is a good swimmer."],
    #                       inputs=[english])

demo.launch()