import streamlit as st
from transformers import pipeline

# Load pipeline
@st.cache_resource
def load_pipeline():
    return pipeline("text-classification", model="distilbert/distilbert-base-uncased-finetuned-sst-2-english")

pipe = load_pipeline()

# Streamlit UI
st.title("Sentiment Analysis with DistilBERT")

text = st.text_area("Enter text to analyze sentiment:", height=150)
if st.button("Analyze"):
    if text.strip():
        result = pipe(text)[0]
        label = result['label']
        score = round(result['score'], 4)
        st.success(f"**Sentiment:** {label} ({score})")
    else:
        st.warning("Please enter some text.")