Predictive Maintenance Agent

import pandas as pd
from sklearn.ensemble import RandomForestClassifier

def predict_failure(machine_id):
    telemetry = pd.read_sql("SELECT * FROM machine_telemetry WHERE machine_id = ?", machine_id)
    features = telemetry[['vibration','temperature','runtime_hours','cycle_count']]
    model = RandomForestClassifier()
    model.fit(features, telemetry['failure_within_30d'])
    risk = model.predict_proba(features.iloc[-1:])[0][1]
    return 'High' if risk > 0.7 else 'Medium' if risk > 0.4 else 'Low'