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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) |