app.py

import streamlit as st
from transformers import pipeline

# Load the QA pipeline with the specified model
qa_pipeline = pipeline("question-answering", model="Suhaib-27/my_awesome_qa_model")

# Streamlit app
st.title("Question Answering for Comprehension Passages")
st.write("Enter the passage and the question, and the model will provide the answer.")

# Input fields for context and question
context = st.text_area("Context", height=200)
question = st.text_input("Question")

# If context and question are provided, perform the inference
if context and question:
    # Get the answer from the pipeline
    result = qa_pipeline(question=question, context=context)
    answer = result['answer']
    
    st.write("### Answer")
    st.write(answer)