risk_model.py

import numpy as np
import pandas as pd
from joblib import load

# ✅ Load model from simple relative path
model = load("heating_model_with_risk_score.joblib")

# Risk level mappings
reverse_map = {0: "Low", 1: "Moderate", 2: "High"}
alert_map = {"Low": "Safe", "Moderate": "Risk", "High": "High Risk"}

def predict_risk(temp, duration):
    input_data = pd.DataFrame([[temp, duration]], columns=["temperature", "duration"])
    pred = model.predict(input_data)[0]
    risk_level = reverse_map[pred]
    score_range = {"Low": (0, 40), "Moderate": (41, 70), "High": (71, 100)}
    risk_score = round(np.random.uniform(*score_range[risk_level]), 2)
    alert = alert_map[risk_level]
    return risk_level, risk_score, alert