app.py

from fastapi import FastAPI, File, UploadFile
from fastapi.middleware.cors import CORSMiddleware
import joblib
import pandas as pd
import numpy as np
from datetime import datetime

app = FastAPI()

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Load the model
model = joblib.load('superkart_sales_model.joblib')

def preprocess_data(df):
    # Calculate Price_Weight_Ratio
    df['Price_Weight_Ratio'] = df['Product_MRP'] / df['Product_Weight']
    
    # Calculate Store_Age
    current_year = datetime.now().year
    df['Store_Age'] = current_year - df['Store_Establishment_Year']
    
    # Calculate Product_Year (assuming it's the same as Store_Establishment_Year for this example)
    df['Product_Year'] = df['Store_Establishment_Year']
    
    return df

@app.get("/")
async def root():
    return {"message": "SuperKart Sales Prediction API"}

@app.post("/predict")
async def predict(file: UploadFile = File(...)):
    try:
        # Read the uploaded CSV file
        df = pd.read_csv(file.file)
        
        # Preprocess the data
        df = preprocess_data(df)
        
        # Make predictions
        predictions = model.predict(df)
        
        return {"predictions": predictions.tolist()}
    except Exception as e:
        return {"error": str(e)}, 500

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)