import joblib
import pandas as pd
from extract_features import extract_features

# Load the trained model and feature list
model = joblib.load("final_model.pkl")  # Make sure it's your trained model
expected_features = joblib.load("expected_features.pkl")  # A list of 29 feature names used during training

# Set your test audio file here
file_path = "patient_1_healthy.wav"  # or patient_2_cognitive_decline.wav

# Extract features from the file
features = extract_features(file_path)

# Align features to training feature set
X = pd.DataFrame([features])
X = X.reindex(columns=expected_features, fill_value=0)

# Predict
prediction = model.predict(X)[0]
prob = model.predict_proba(X).max()

print(f"🧠 Predicted Cognitive Status: {prediction} (Confidence: {prob:.2f})")