app.py

import streamlit as st
import joblib
import numpy as np

model = joblib.load("model/student_model.pkl")

st.set_page_config(
    page_title="Student Performance Predictor", page_icon="🎓", layout="centered"
)
st.title("🎓 Student Performance Prefictor")
st.markdown(
    "Predict whether a student will **pass or fail** based on scores and preparation."
)

st.divider()

# Input Form
with st.form("prediction_form"):
    col1, col2 = st.columns(2)

    with col1:
        gender = st.selectbox("👤 Gender", ["Female", "Male"])
        prep = st.selectbox("📘 Test Preparation", ["None", "Completed"])

    with col2:
        math = st.slider("📐 Math Score", 0, 100, 70)
        read = st.slider("📖 Reading Score", 0, 100, 70)
        write = st.slider("✍️ Writing Score", 0, 100, 70)

    submit = st.form_submit_button("🔍 Predict")

if submit:
    input_data = np.array(
        [
            [
                1 if gender == "Male" else 0,
                math,
                read,
                write,
                1 if prep == "Completed" else 0,
            ]
        ]
    )

    result = model.predict(input_data)[0]
    avg_score = round((math + read + write) / 3, 2)

    st.markdown("### 📊 Prediction Result")
    if result == 1:
        st.success(f"✅ Likely to Pass (Avg Score: {avg_score})")
        st.balloons()
    else:
        st.error(f"❌ May Fail (Avg Score: {avg_score})")
        st.warning("Encourage more practice or test preparation.")

st.divider()
st.caption("Made with ❤️ using Streamlit and scikit-learn")