app.py

import gradio as gr
import transformers

import os
import sys
import openai
from openai import Completion as complete

qa_gen_prompt = str("""You are a highly intelligent & complex question-answer generative model. 
  You take a passage as an input and generate 5 high-quality and diverse multiple-choice questions 
  with four choices each from the given passage by imitating the way a human asks questions and give answers. 
  Your output format is only 
    [{\"Q\": Question, \"A1\": Answer, \"A2\": Answer,\"A3\": Answer, \"A4\": Answer}, ...]\") }} form, no other form. \n The passage: """)
end_prompt = "the QA pairs:"

openai.api_key = os.environ["openai_api_key"]
access_code = os.environ["access_code"]

def convert_questions_to_html(qapairs):
  qapairs_template = []
  for qapair in qapairs:

    result = "<problem>\n<choiceresponse>  \n<label>" + qapair['Q'] + "</label>\n<checkboxgroup>"

    for key, value in qapair.items():
        if key != "Q":
            result += "\n    <choice correct=\"false\">" + value + "</choice>"
    result+="\n"
    result += "  </checkboxgroup>\n</choiceresponse>\n</problem>"
    qapairs_template.append(result)
  return "".join([qa + "\n\n" for qa in qapairs_template])


def convert_questions_to_template(qapairs):
  qapairs_template = []
  for qapair in qapairs:

    result = ">>" + qapair['Q'] + " <<\n\n"
    choices = [qapair['A1'], qapair['A2'], qapair['A3'], qapair['A4']]
    for i, choice in enumerate(choices):
      result += "[ ] " + choice + "\n"
      
    qapairs_template.append(result)

  return "".join([qa + "\n\n" for qa in qapairs_template])


def list_of_dicts_to_str(qapairs, indent=0):
    result = ''
    for d in qapairs:
        for key, value in d.items():
            if key.startswith("A"):
                result += ' ' * (indent + 4) + str(key) + ': ' + str(value) + '\n'
            else:
                result += ' ' * indent + str(key) + ': ' + str(value) + '\n'
    return result


def generate_questions(context, credentials):
    """
    Generate questions by calling davinci-003.
    """
    if credentials != access_code:
        return "Code d'accès incorrect. Veuillez réessayer.", "Code d'accès incorrect. Veuillez réessayer.", "Code d'accès incorrect. Veuillez réessayer."

    prompt = qa_gen_prompt + context + end_prompt
    
    try:
        completion = complete.create(model="text-davinci-003", prompt=prompt, max_tokens=1875)
        q_dict = eval(completion.choices[0].text)
        return list_of_dicts_to_str(q_dict), convert_questions_to_html(q_dict), convert_questions_to_template(q_dict)
    except Exception as e:
        # return str(e)
        # return python version
        return str(sys.version)


with gr.Blocks() as demo:

    # with gr.Row():
        
    #     with gr.Column():


    with gr.Row():
        
        with gr.Column():   
            gr.Markdown("## Générateur de questions à choix multiples")    
            gr.Markdown("Pour créer des questions à choix multiples, insérez un texte dans la boîte à gauche, puis cliquez sur 'Générer des questions.' Attention! N'oubliez pas le code d'accès.")

        with gr.Column():

            quiz_button = gr.Button("Générer cinq questions.", variant="primary")   
            credentials = gr.Textbox(placeholder="Code d'accès", lines=1, label="")
            

    with gr.Row():
        context = gr.Textbox(placeholder="insérez le texte ici.", lines=8, label="Texte")
        
        with gr.Tab("brut"):
            qa_pairs = gr.Textbox(placeholder="Les questions apparaîtront ici.", lines=19, label="Paires question-réponse")
        with gr.Tab("format html"):
            qa_pairs_html = gr.Textbox(placeholder="Les questions apparaîtront ici.", lines=19, label="Paires question-réponse, format html")
        with gr.Tab("format edulib"):
            qa_pairs_edulib = gr.Textbox(placeholder="Les questions apparaîtront ici.", lines=19, label="Paires question-réponse, format edulib")

        #todo: test generating with just one phrase for one MCQ with smaller models

    quiz_button.click(fn= generate_questions,
                          inputs=[context, credentials],	
                          outputs=[qa_pairs, qa_pairs_html, qa_pairs_edulib]
                     )
    

if __name__ == "__main__":
    demo.launch()