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app.py

@@ -1,6 +1,16 @@
 import joblib
 import pandas as pd
 from flask import Flask, request, jsonify
+
+# Libraries different ensemble classifiers
+from sklearn.ensemble import (
+    BaggingRegressor,
+    RandomForestRegressor,
+    AdaBoostRegressor,
+    GradientBoostingRegressor,
+)
+import xgboost as xgb
+
 # Initialize Flask app
 app = Flask("Supermarket Product Price Predictor")
 loaded_model  = joblib.load("predict_product_price_v1_0.joblib")

requirements.txt

@@ -7,3 +7,4 @@ flask==2.2.2
 gunicorn==20.1.0
 requests==2.28.1
 uvicorn[standard]
+xgboost