app.py

import streamlit as st
from transformers import pipeline

# Load sentiment-analysis pipeline from Hugging Face
@st.cache_resource
def load_model():
    return pipeline("sentiment-analysis")

sentiment_pipeline = load_model()

# Streamlit UI
st.title("Smart Sentiment Analyzer 🤖")
st.markdown("Analyze your sentence using a real AI model (DistilBERT).")

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

if st.button("Analyze Sentiment"):
    if text.strip() == "":
        st.warning("Please enter some text.")
    else:
        result = sentiment_pipeline(text)[0]
        label = result["label"]
        score = round(result["score"] * 100, 2)

        st.success(f"**Sentiment:** {label}")
        st.info(f"**Confidence:** {score}%")