Update app.py

app.py

@@ -1,22 +1,27 @@
 import streamlit as st
 from transformers import pipeline, AutoModelForQuestionAnswering, AutoTokenizer
+
 @st.cache(allow_output_mutation=True)
 def load_qa_model():
     model_name = "mrm8488/mobilebert-uncased-finetuned-squadv2"
     model = AutoModelForQuestionAnswering.from_pretrained(model_name)
     tokenizer = AutoTokenizer.from_pretrained(model_name)
     qa = pipeline("question-answering", model=model, tokenizer=tokenizer)
-    return qa
+    text_generator = pipeline("text-generation")
+    return qa, text_generator
 
-qa = load_qa_model()
+qa, text_generator = load_qa_model()
 st.title("Ask Questions about your Text")
 sentence = st.text_area('Please paste your article :', height=30)
-question = st.text_input("Questions from this article?")
-button = st.button("Get me Answers")
-max = st.sidebar.slider('Select max', 50, 500, step=10, value=150)
-min = st.sidebar.slider('Select min', 10, 450, step=10, value=50)
-do_sample = st.sidebar.checkbox("Do sample", value=False)
-with st.spinner("Discovering Answers.."):
+num_questions = st.number_input("Number of questions to generate:", min_value=1, max_value=10, value=3, step=1)
+num_answers = st.number_input("Number of answers per question:", min_value=1, max_value=5, value=1, step=1)
+button = st.button("Generate Questions and Answers")
+
+with st.spinner("Generating Questions and Answers.."):
     if button and sentence:
-        answers = qa(question=question, context=sentence)
-        st.write(answers['answer'])
+        generated_questions = text_generator(sentence, max_length=50, num_return_sequences=num_questions)
+        for question_index, question_output in enumerate(generated_questions):
+            st.subheader(f"Question {question_index + 1}: {question_output['generated_text']}")
+            answers = qa(question=question_output['generated_text'], context=sentence, topk=num_answers)
+            for answer_index, answer in enumerate(answers):
+                st.write(f"Answer {answer_index + 1}: {answer['answer']}")