app.py

from flask import Flask, request, jsonify
import joblib
import numpy as np

# Load the scaler and models
scaler = joblib.load('scaler.joblib')
models = {target: joblib.load(f'svm_model_{target}.joblib') for target in ['processing', 'perception', 'input', 'understanding']}

app = Flask(__name__)

@app.route('/predict', methods=['POST'])
def predict():
    data = request.json.get('user_input')
    if not data:
        return jsonify({"error": "No input provided"}), 400
    
    user_input_array = np.array(data).reshape(1, -1)
    user_input_scaled = scaler.transform(user_input_array)

    predictions = {target: model.predict(user_input_scaled)[0] for target, model in models.items()}
    
    return jsonify(predictions)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)