Create App.py

App.py

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+from flask import Flask, request, jsonify
+import joblib
+import numpy as np
+import traceback
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Load model
+model = joblib.load("tuned_gradient_boosting_model.pkl")
+
+# Home route
+@app.route('/')
+def home():
+    return "Sales Prediction API is running."
+
+# Prediction route
+@app.route('/predict', methods=['POST'])
+def predict():
+    try:
+        # Parse JSON input
+        data = request.get_json(force=True)
+
+        # Extract features as a 2D array (expecting list or single sample dict)
+        features = np.array(data['features']).reshape(1, -1)
+
+        # Make prediction
+        prediction = model.predict(features)
+
+        # Return prediction as JSON
+        return jsonify({"predicted_sales": prediction[0]})
+
+    except Exception as e:
+        return jsonify({"error": str(e), "trace": traceback.format_exc()})
+
+if __name__ == '__main__':
+    app.run(debug=True, host='0.0.0.0', port=5000)