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import joblib
import pandas as pd
from flask import Flask, request, jsonify
# Initialize Flask app with a name
sales_predictor_api = Flask("SuperKart Sales Predictor")
# Load the trained SuperKart Sales prediction model
model = joblib.load("superkart_sales_model.pkl")
# Define a route for the home page
@sales_predictor_api.get('/')
def home():
return "Welcome to the SuperKart Sales Prediction API!"
# Define an endpoint to predict churn for a single customer
@sales_predictor_api.post('/v1/productsales')
def predict_sales():
try:
# Get JSON data
sales_data = request.get_json()
# Ensure input is a list of records
if isinstance(sales_data, dict):
sales_data = [sales_data]
# Convert to DataFrame
input_data = pd.DataFrame(sales_data)
# Predict
prediction = model.predict(input_data).tolist()[0]
return jsonify({"prediction": float(prediction)})
except Exception as e:
return jsonify({"error": str(e)})
# Run the Flask app in debug mode
if __name__ == '__main__':
sales_predictor_api.run(debug=True) |