app.py

import os
from flask import Flask, render_template, request, redirect, url_for, jsonify
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.multiclass import *
from sklearn.svm import *
import pandas

app = Flask(__name__)
global Classifier
global Vectorizer

# load data
data = pandas.read_csv('spam.csv', encoding='latin-1')
train_data = data[:4400] # 4400 items
test_data = data[4400:] # 1172 items

# train model
Classifier = OneVsRestClassifier(SVC(kernel='linear', probability=True))
Vectorizer = TfidfVectorizer()
vectorize_text = Vectorizer.fit_transform(train_data.v2)
Classifier.fit(vectorize_text, train_data.v1)


@app.route('/', methods=['GET'])
def index():
    message = request.args.get('message', '')
    error = ''
    predict_proba = ''
    predict = ''

    global Classifier
    global Vectorizer
    try:
        if len(message) > 0:
          vectorize_message = Vectorizer.transform([message])
          predict = Classifier.predict(vectorize_message)[0]
          predict_proba = Classifier.predict_proba(vectorize_message).tolist()
    except BaseException as inst:
        error = str(type(inst).__name__) + ' ' + str(inst)
    return jsonify(
              message=message, predict_proba=predict_proba,
              predict=predict, error=error)

if __name__ == '__main__':
    port = int(os.environ.get('PORT', 5000))
    app.run(host='0.0.0.0', port=port, debug=True, use_reloader=True)