app.py

import gradio as gr
import numpy as np
import joblib
import pandas as pd

# ------------------------------------------------------------
# AAC Participation Predictor (Gradio)
# - Loads sklearn preprocessor + model artifacts
# - Outputs Yes/No for the senior's likelihood to attend
# ------------------------------------------------------------

PREPROCESS_PATH = "aac_preprocess.joblib"
MODEL_PATH = "aac_mlp.joblib"

preprocess = joblib.load(PREPROCESS_PATH)
model = joblib.load(MODEL_PATH)

ACTIVITIES = [
    "Elastic Band Workout",
    "Chair Pilates",
    "Memory Game",
    "Digital Skills Workshop",
    "Chinese New Year Celebration",
]

def predict_participation(
    age: int,
    gender: str,
    single_household: str,
    health_score: float,
    mobility: str,
    last_cny_attendance: str,
    activity_type: str
):
    """Return Yes/No + probability."""
    # Build one-row dataframe matching training columns
    x = pd.DataFrame([{
        "Age": age,
        "Gender": "M" if gender == "Male" else "F",
        "Single Household (Y/N)": "Y" if single_household == "Yes" else "N",
        "Health Score (0-100)": float(health_score),
        "Mobility (Low/Medium/High)": mobility,
        "Last Chinese New Year Event Attendance": "Y" if last_cny_attendance == "Yes" else "N",
        "Activity Type": activity_type,
    }])

    X_t = preprocess.transform(x)
    prob = float(model.predict_proba(X_t)[:, 1][0])
    THRESHOLD = 0.5
    decision = "Yes" if prob >= THRESHOLD else "No"
    return decision, round(prob, 4)

demo = gr.Interface(
    fn=predict_participation,
    inputs=[
        gr.Slider(60, 100, step=1, label="Age", value=70),
        gr.Dropdown(["Male", "Female"], label="Gender"),
        gr.Radio(["Yes", "No"], label="Single Household?"),
        gr.Slider(0, 100, step=0.1, label="Health Score (0-100)", value=75.0),
        gr.Dropdown(["Low", "Medium", "High"], label="Mobility Level"),
        gr.Radio(["Yes", "No"], label="Attended last Chinese New Year event?"),
        gr.Dropdown(ACTIVITIES, label="Type of Activity")
    ],
    outputs=[
        gr.Textbox(label="Likely to Attend? (Yes/No)"),
        gr.Number(label="Predicted attendance probability (0–1)"),
    ],
    title="Senior Activity Participation Predictor (AAC)",
    description=(
        "Enter senior details + activity type to predict attendance likelihood. "
        "This demo loads a trained model and returns a Yes/No recommendation."
    )
)

if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        ssr_mode=False
    )