# app.py
import streamlit as st
from transformers import pipeline

st.title("🤗 Sentiment Detection (Hugging Face Model)")

# Load model once
@st.cache_resource
def load_model():
    return pipeline("sentiment-analysis")

model = load_model()

text = st.text_area("Enter text:")

if st.button("Analyze"):
    if text.strip():
        result = model(text)[0]
        st.write(f"**Sentiment:** {result['label']} ({round(result['score']*100, 2)}%)")
    else:
        st.warning("Please enter some text.")