app.py

from flask import Flask, request, render_template
import joblib
import pandas as pd

# Initialize Flask app
app = Flask(__name__, template_folder="templates", static_folder="static")

# Load model and preprocessor
model = joblib.load("insurance_model.pkl")
preprocessor = joblib.load("preprocessor.pkl")

@app.route("/", methods=["GET", "POST"])
def index():
    prediction = None
    if request.method == "POST":
        try:
            # Get form inputs
            age = float(request.form["age"])
            sex = request.form["sex"]
            bmi = float(request.form["bmi"])
            children = int(request.form["children"])
            smoker = request.form["smoker"]
            region = request.form["region"]

            # Create DataFrame for prediction
            user_input = pd.DataFrame([[age, sex, bmi, children, smoker, region]],
                                      columns=["age", "sex", "bmi", "children", "smoker", "region"])

            # Transform input
            user_input_processed = preprocessor.transform(user_input)

            # Predict
            pred = model.predict(user_input_processed)
            prediction = round(pred[0], 2)
        except Exception as e:
            prediction = f"Error: {str(e)}"

    return render_template("index.html", prediction=prediction)

if __name__ == "__main__":
    app.run(debug=True)