import streamlit as st
from transformers import pipeline

pipe = pipeline("text2text-generation", model="google/flan-t5-base")

def generate_answer(question):
    """Generates an answer to a question using the T5 language model."""

    answer = pipe(question, max_length=100, num_return_sequences=1)[0]
    return answer

st.markdown(
    f"""
    <style>
        body {{
            background-image: url("BK.jpg");
            background-size: cover;
        }}
    </style>
    """,
    unsafe_allow_html=True,
)


st.title("Question Answering App")

question = st.text_input("Ask me a question:")

if question:
    answer = generate_answer(question)

    st.markdown(f"**Answer:** {answer}")

else:
    st.markdown("Please ask me a question.")