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.ipynb_checkpoints/requirements-checkpoint.txt

@@ -0,0 +1,11 @@
+pandas==2.2.2
+numpy==2.0.2
+scikit-learn==1.6.1
+xgboost==2.1.4
+joblib==1.4.2
+Werkzeug==2.2.2
+flask==2.2.2
+gunicorn==20.1.0
+requests==2.28.1
+uvicorn[standard]
+streamlit==1.43.2

app.py

@@ -9,8 +9,10 @@ import os
 sales_forecast_predictor_api = Flask("Superkart sales forecast predictor")
 
 # Load the trained machine learning model
-model_path = os.path.join(os.path.dirname(__file__), "deployment_files", "store_sales_prediction_model_v1_0.joblib")
-model = joblib.load(model_path)
+# model_path = os.path.join(os.path.dirname(__file__), "store_sales_prediction_model_v1_0.joblib")
+# model = joblib.load(model_path)
+# Load the trained machine learning model
+model = joblib.load("rental_price_prediction_model_v1_0.joblib")
 
 # Define a route for the home page (GET request)
 @sales_forecast_predictor_api.get('/')
@@ -85,4 +87,4 @@ def predict_sales_batch():
 
 # Run the Flask application
 if __name__ == '__main__':
-    app.run(debug=True)
+    sales_forecast_predictor_api.run(debug=True)