code: import numpy as np
  from flask import Flask, request, jsonify, render_template
  import pickle
  
  app = Flask(__name__)
  model = pickle.load(open('model.pkl', 'rb'))
  
  
  @app.route('/')
  def home():
      return render_template('index.html')
  
  
  @app.route('/predict', methods=['GET', 'POST'])
  def predict():
      '''
      For rendering results on HTML GUI
      '''
      int_features = [int(x) for x in request.form.getlist('comp_select')]
      final_features = [np.array(int_features)]
      prediction = model.predict(final_features)
      # print(final_features)
      output = prediction[0]*10
  
      if (output <= 20):
          return render_template('index.html', prediction_text='Your symptoms match with {} % symptoms of the Covid Patients.\n You are at Low Risk of getting Covid-19.\n Please answer the questions below to predict again.'.format(output))
  
      elif (output > 20 and output <= 60):
          return render_template('index.html', prediction_text='Your symptoms match with {} % symptoms of the Covid Patients.\n You are at Medium Risk of getting Covid-19.\n We recommend you to have a Covid Test.\n Please answer the questions below to predict again.'.format(output))
  
      else:
          return render_template('index.html', prediction_text='Your symptoms match with {} % symptoms of the Covid Patients.\n You are at High Risk of getting Covid-19.\n We recommend you to have a Covid Test as soon as possible.\n Please answer the questions below to predict again.'.format(output))
  
  
  if __name__ == "__main__":
      app.run(debug=True)
  
apis: numpy.array