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app.py

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+# Import necessary libraries
+import numpy as np
+import joblib  # For loading the serialized model
+import pandas as pd  # For data manipulation
+from flask import Flask, request, jsonify  # For creating the Flask API
+
+# Initialize Flask app with a name
+superkart_api = Flask("SuperKart Sales Predictor")
+
+# Load the trained churn prediction model
+model = joblib.load("best_sales_model.pkl")
+
+# Define a route for the home page
+@superkart_api.get('/')
+def home():
+    return "Welcome to the SuperKart System"
+
+# Define an endpoint to predict churn for a single customer
+@superkart_api.post('/v1/sales')
+def predict_sales():
+    # Get JSON data from the request
+    data = request.get_json()
+
+    # Extract relevant customer features from the input data
+    sample = {
+    'Product_Weight': data['Product_Weight'],
+    'Product_Sugar_Content': data['Product_Sugar_Content'],
+    'Product_Allocated_Area': data['Product_Allocated_Area'],
+    'Product_MRP': data['Product_MRP'],
+    'Store_Size': data['Store_Size'],
+    'Store_Location_City_Type': data['Store_Location_City_Type'],
+    'Store_Type': data['Store_Type'],
+    'Product_Id_char': data['Product_Id_char'],
+    'Store_Age': data['Store_Age'],
+    'Product_Type_Category': data['Product_Type_Category'],
+    'Store_Id': data['Store_Id']
+}
+
+    # Convert the extracted data into a DataFrame
+    input_data = pd.DataFrame([sample])
+
+    # Make a churn prediction using the trained model
+    prediction = model.predict(input_data).tolist()[0]
+
+    # Return the prediction as a JSON response
+    return jsonify({'Sales': prediction})
+
+
+# Run the Flask app in debug mode
+if __name__ == '__main__':
+    superkart_api.run(debug=True)

best_sales_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1e54bbb34d2ac12b359137b917fbcf267b4c191d7b05304baf174c7cf2b9eb25
+size 63810675

requirements.txt

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+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