Create app.py

app.py

@@ -0,0 +1,25 @@
+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)