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| 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}`") | |