import streamlit as st
import joblib
from pathlib import Path

st.set_page_config(page_title="Sentiment Predictor", layout="centered")
st.title("Sentiment Predictor")

# Load the model pipeline
HERE = Path(__file__).resolve().parent
pipeline = joblib.load(HERE / "pipeline.joblib")  # expects pipeline.joblib in same folder (src/)

text = st.text_area("Enter text (one sentence per line)", "I love this\nThis is terrible", height=140)

if st.button("Predict"):
    lines = [t.strip() for t in text.splitlines() if t.strip()]
    if not lines:
        st.warning("Type at least one sentence.")
    else:
        preds = pipeline.predict(lines)
        st.subheader("Predictions")
        for s, p in zip(lines, preds):
            st.write(f"**{s}** → `{p}`")