import streamlit as st
from transformers import pipeline

st.set_page_config(page_title="Semantic Analyzer")

st.title("Semantic Analyzer")
st.write("Analyze the sentiment of your text using NLP.")

@st.cache_resource
def load_model():
    return pipeline(
        "sentiment-analysis",
        model="distilbert/distilbert-base-uncased-finetuned-sst-2-english",
        device=-1
    )

text = st.text_area("Enter a sentence or paragraph")

if st.button("Analyze"):
    if text.strip():
        with st.spinner("Analyzing text..."):
            model = load_model()
            result = model(text[:5000])[0]

        st.subheader("Result")
        st.write("Sentiment:", result["label"])
        st.write("Confidence:", f"{result['score']:.2%}")
    else:
        st.warning("Please enter some text.")