app.py

import gradio as gr
import pandas as pd
import re
import os
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("potsawee/t5-large-generation-squad-QuestionAnswer")
model = AutoModelForSeq2SeqLM.from_pretrained("potsawee/t5-large-generation-squad-QuestionAnswer")

def generate_question_answer_pairs(input_text):
    if input_text is None:
        return "Please enter a text"

    d = {'Question':[],'Answer':[]}
    df = pd.DataFrame(data=d)

    sentences = re.split(r'(?<=[.!?])', input_text)
    question_answer_pairs = []

    for sentence in sentences:
        input_ids = tokenizer.encode(sentence, return_tensors="pt")
        outputs = model.generate(input_ids, max_length=100, num_return_sequences=1)
        question_answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
        question_answer_pairs.append(question_answer)

    result = ''

    for question_answer in question_answer_pairs:
        qa_parts = question_answer.split("?")
        if len(qa_parts) >= 2:
            question_part = qa_parts[0] + "?"
            answer_part = qa_parts[1].strip()
            new_data = {'Question': [question_part], 'Answer': [answer_part]}
            df = pd.concat([df, pd.DataFrame(new_data)], ignore_index=True)
            result += f"Question: {question_part}\nAnswer: {answer_part}\n\n"
            
    df.to_csv("QAPairs.csv")
    return result, "QAPairs.csv"

title = "Question-Answer Pairs Generation"
input_text = gr.Textbox(lines=4, label="Text:")
output_file = gr.File(label="Download as csv")
output_text = gr.Textbox()

interface = gr.Interface(
    fn=generate_question_answer_pairs,
    inputs=input_text,
    outputs=[output_text, output_file],
    title=title,
)
interface.launch()