app.py

import streamlit as st
from transformers import pipeline

# Load the conversational pipeline
model_name = "./QAModel"
chatbot_pipeline = pipeline("conversational", model=model_name, tokenizer=model_name)

# Set the title for the Streamlit app
st.title("Movie Trivia Chatbot")

# Text input for the user
user_input = st.text_area("Ask a movie trivia question:")

def get_response(user_input):
    # Generate response
    conversation = chatbot_pipeline(user_input)
    return conversation[0]['generated_text']

if st.button("Get Answer"):
    if user_input:
        response = get_response(user_input)
        # Display the response
        st.subheader("Answer")
        st.write(response)
    else:
        st.warning("Please enter a question.")

# Optionally, add instructions or information about the app
st.write("""
    Enter a movie-related question above. The chatbot will provide an answer based on its training.
    """)