app.py

import pickle
from unittest import registerResult
from flask import Flask, request,app,jsonify,url_for,render_template
import numpy as np
import pandas as pd
import json


app = Flask(__name__)
## Load model
regmodel = pickle.load(open("regmodel.pkl", "rb"))
scalar = pickle.load(open("scaling.pkl", "rb"))

@app.route('/')
def home():
    return render_template("home.html")

@app.route('/predict_api', methods = ["POST"])
def predict_api():
    data = request.json['data']
    print(data)
    print(np.array(list(data.values())).reshape(1, -1))
    new_data = scalar.transform(np.array(list(data.values())).reshape(1, -1))
    output = regmodel.predict(new_data)
    print(output[0])
    return jsonify(output[0])

@app.route('/predict', methods = ["POST"])
def predict():
    data = [float(x) for x in request.form.values()]
    final_input = scalar.transform(np.array(data).reshape(1,-1))
    print(final_input)
    output = regmodel.predict(final_input)[0]
    return render_template("home.html", prediction_text = f"The house price prediction is {output}")

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