Update app.py

app.py

@@ -1 +1,41 @@
-print(hello)
+import gradio as gr
+import requests
+import os
+import numpy as np
+import pandas as pd
+import io
+# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForSequenceClassification
+from question_generator.questiongenerator import QuestionGenerator
+
+qg = QuestionGenerator()
+# num_que = 5
+
+def generate_questions(article,num_que):
+    result = ''
+    if num_que == None or num_que == '':
+        num_que = 5
+    else:
+        num_que = num_que
+    generated_questions_list = qg.generate(article, num_questions=int(num_que))
+    summarized_data = {
+        "generated_questions" : generated_questions_list
+    }
+    generated_questions = summarized_data.get("generated_questions",'')
+    for q in generated_questions:
+        result = result + q + '\n'
+    return result
+
+## design 1
+inputs=gr.Textbox(lines=5, label="Article/Text",elem_id="inp_div")
+total_que = gr.Textbox(label="Number of Question want to generate",elem_id="inp_div")
+outputs=gr.Textbox(lines=5, label="Generated Questions",elem_id="inp_div")
+
+demo = gr.Interface(
+    generate_questions,
+    [inputs,total_que],
+    outputs,
+    title="Question Generation using T5",
+    description="Feel free to give your feedback", 
+    css=".gradio-container {background-color: lightgray} #inp_div {background-color: #7FB3D5;"
+)
+demo.launch(enable_queue = False)