server-2.py

# import Flask class from the flask module
from flask import Flask, request

import numpy as np
import pickle

# Create Flask object to run
app = Flask(__name__)

@app.route('/')
def home():
    return "Hi, Welcome to Flask!!"

@app.route('/predict')
def predict():

	# Get values from browser
	sepLen = request.args['sepal_length']
	sepWid = request.args['sepal_width']
	petLen = request.args['petal_length']
	petWid = request.args['petal_width']
	
	testData = np.array([sepLen, sepWid, petLen, petWid]).reshape(1,4)
	class_prediced = int(svmIrisModel.predict(testData)[0])
	output = "Predicted Iris Class: " + str(class_prediced)
	
	return (output)
	
# Load the pre-trained and persisted SVM model
# Note: The model will be loaded only once at the start of the server
def load_model():
	global svmIrisModel
	
	svmIrisFile = open('models/SVMModel.pckl', 'rb')
	svmIrisModel = pickle.load(svmIrisFile)
	svmIrisFile.close()

if __name__ == "__main__":
	print("**Starting Server...")
	
	# Call function that loads Model
	load_model()
	
	# Run Server
	app.run()

Thanks Socratesk.
I was trying to create a flask API app for an Iris dataset model and I had this error that has left me almost depressed and stucked for some days now.
Please kindly look into the codes and help me see what I'm doing wrong.

If need be I can push the codes to repo.
Thank you for your help.