app.py

# Import necessary libraries
import numpy as np
import pandas as pd
import joblib  # For loading the trained ML model
from flask import Flask, request, jsonify

# Initialize the Flask application
sales_forecast_api = Flask("SuperKart Sales Forecast API")

# Load the trained machine learning model
model = joblib.load("/content/drive/MyDrive/AIML Practice/Python Basics/deployment_files/superkart_prediction_model_v1_0.joblib")  # Ensure this file is present in the same directory

# Define a route for the home page (GET request)
@sales_forecast_api.get('/')
def home():
    """
    Handles GET requests to the root URL.
    Returns a welcome message.
    """
    return "Welcome to the SuperKart Sales Forecast API!"

# Define a route for single prediction (POST request)
@sales_forecast_api.post('/v1/forecast')
def predict_sales():
    """
    Handles POST requests to the '/v1/forecast' endpoint.
    Accepts product and store details in JSON format and returns the predicted sales revenue.
    """
    # Get JSON data from request body
    data = request.get_json()

    # Extract features for prediction
    sample = {
        'Product_Id': data['Product_Id'],
        'Product_Weight': data['Product_Weight'],
        'Product_Sugar_Content': data['Product_Sugar_Content'],
        'Product_Allocated_Area': data['Product_Allocated_Area'],
        'Product_Type': data['Product_Type'],
        'Product_MRP': data['Product_MRP'],
        'Store_Id': data['Store_Id'],
        'Store_Establishment_Year': data['Store_Establishment_Year'],
        'Store_Size': data['Store_Size'],
        'Store_Location_City_Type': data['Store_Location_City_Type'],
        'Store_Type': data['Store_Type']
    }

    # Convert to DataFrame
    input_df = pd.DataFrame([sample])

    # Make prediction
    predicted_sales = model.predict(input_df)[0]

    # Round off and convert to float
    predicted_sales = round(float(predicted_sales), 2)

    # Return response
    return jsonify({'Predicted_Sales_Revenue': predicted_sales})

# Run the Flask app
if __name__ == '__main__':
    sales_forecast_api.run(debug=True)