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app.py
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app.py
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from flask import Flask, render_template, request,session
#import keras.backend.tensorflow_backend as tb
#tb._SYMBOLIC_SCOPE.value = True
# from chatterbot import ChatBot
# from chatterbot.trainers import ChatterBotCorpusTrainer
import pickle
import psycopg2
import re
from jira.client import JIRA
from flask import current_app
from flask_mail import Mail
from flask_mail import Message
import threading
import datetime
import nltk
from nltk.chat.util import Chat, reflections
from nltk.stem import WordNetLemmatizer
lemmatizer = WordNetLemmatizer()
import pickle
import numpy as np
# from keras.models import load_model
# model = load_model('chatbot_model.h5')
import json
# import random
# intents = json.loads(open('intents.json').read())
# words = pickle.load(open('words.pkl','rb'))
# classes = pickle.load(open('classes.pkl','rb'))
app = Flask(__name__)
app.testing = False
app.secret_key = 'super secret key'
app.config['MAIL_SERVER']='smtp.gmail.com'
app.config['MAIL_PORT'] = 465
app.config['MAIL_USERNAME'] = 'sajasmine175@gmail.com'
app.config['MAIL_PASSWORD'] = 'stratapps'
app.config['MAIL_USE_TLS'] = False
app.config['MAIL_USE_SSL'] = True
app.config['MAIL_DEFAULT_SENDER'] = 'sajasmine175@gmail.com'
app.config['MAIL_ASCII_ATTACHMENTS'] = True
app.config['DEBUG'] = True
mail = Mail(app)
model_nltk = pickle.load(open("nltk.pkl", 'rb'))
# english_bot = ChatBot("Chatterbot", storage_adapter='chatterbot.storage.SQLStorageAdapter',
# logic_adapters=[
# {
# 'import_path': 'chatterbot.logic.BestMatch',
# 'default_response': 'I am sorry, but I do not understand. I am still learning.',
# 'maximum_similarity_threshold': 0.90
# }
# ]
# )
# trainer = ChatterBotCorpusTrainer(english_bot)
# trainer.train("./greetings.yml")
regex = '^[a-z0-9]+[\._]?[a-z0-9]+[@]\w+[.]\w{2,3}$'
def clean_up_sentence(sentence):
# tokenize the pattern - split words into array
sentence_words = nltk.word_tokenize(sentence)
# stem each word - create short form for word
sentence_words = [lemmatizer.lemmatize(word.lower()) for word in sentence_words]
return sentence_words
# return bag of words array: 0 or 1 for each word in the bag that exists in the sentence
# def bow(sentence, words, show_details=True):
# # tokenize the pattern
# sentence_words = clean_up_sentence(sentence)
# # bag of words - matrix of N words, vocabulary matrix
# bag = [0]*len(words)
# isFound = False
# for s in sentence_words:
# for i,w in enumerate(words):
# if w == s:
# # assign 1 if current word is in the vocabulary position
# bag[i] = 1
# if show_details:
# isFound = True
# print ("found in bag: %s" % w)
# if(isFound == True):
# return (np.array(bag))
# else:
# return -1000
# def predict_class(sentence, model):
# # filter out predictions below a threshold
# p = bow(sentence, words,show_details=True)
# print('res', isinstance(p, np.ndarray), p)
# if(not isinstance(p, np.ndarray) and p == -1000):
# return -1000
# else:
# res = model.predict(np.array([p]))[0]
# ERROR_THRESHOLD = 0.25
# results = [[i,r] for i,r in enumerate(res) if r>ERROR_THRESHOLD]
# # sort by strength of probability
# results.sort(key=lambda x: x[1], reverse=True)
# return_list = []
# for r in results:
# return_list.append({"intent": classes[r[0]], "probability": str(r[1])})
# return return_list
# def getResponse(ints, intents_json):
# if(ints == -1000):
# tag = 'noanswer'
# list_of_intents = intents_json['intents']
# for i in list_of_intents:
# if(i['tag']== tag):
# result = random.choice(i['responses'])
# break
# return result
# else:
# tag = ints[0]['intent']
# print('tag', tag)
# list_of_intents = intents_json['intents']
# for i in list_of_intents:
# if(i['tag']== tag):
# result = random.choice(i['responses'])
# break
# return result
# def chatbot_response(msg):
# print('msg',msg)
# ints = predict_class(msg, model)
# res = getResponse(ints, intents)
# return res
@app.route("/")
def home():
session['mail_id'] = ''
session['count'] = 0
session['name'] = ''
return render_template("index_new.html")
def send_async_email(app, msg):
with app.app_context():
mail.send(msg)
print ("sent")
def send_email(sub,id, to):
app = current_app._get_current_object()
msg = Message(subject=sub,
sender='sajasmine175@gmail.com', recipients=to)
msg.html=render_template('mail_content.html', issueLink='https://xamplify.atlassian.net/browse/'+str(id))
thr = threading.Thread(target=send_async_email, args=[app, msg])
thr.start()
return thr
# @app.route("/chatterbot")
# def get_bot_response():
# print(request)
# userText = request.args.get('msg')
# ts = datetime.datetime.now()
# print(session,session['count'], re.search(regex,userText))
# if(session['count'] == 0 and re.search(regex,userText)):
# print("mail id is entered")
# session['mail_id'] = userText
# session['count'] = 1
# return 'Thanks, how can I help you?'
# elif(session['count'] == 0 and re.search(regex,userText) == None):
# return 'Please enter valid email id'
# conn = psycopg2.connect(database="chatbotdb", user = "postgres", password = "postgres", host = 'localhost', port = "5432")
# print("*******", english_bot.get_response(userText))
# res = str(english_bot.get_response(userText))
# cursor = conn.cursor()
# s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,search_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s)", (session['mail_id'], userText, userText, 'human', ts))
# s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,resp_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s) ", (session['mail_id'], res, res, 'bot',ts ))
# print('s',s)
# conn.commit()
# cursor.close()
# conn.close()
# return res
@app.route("/createjira")
def create_jira():
print("############################################")
summaryText=request.args.get('summary')
descriptionText=request.args.get('description')
emailidText=request.args.get('emailid')
jira=JIRA(basic_auth=('agayatri@stratapps.com','ECCxYPP8gydsLlXR9lMKEC40'),
options={'headers': {'content-type': 'application/json'},'server': 'https://xamplify.atlassian.net/'})
new_issue = jira.create_issue(project={'key': 'XBI'}, summary= summaryText, description=descriptionText, issuetype={'name': 'Bug'})
print(new_issue)
send_email(summaryText, new_issue, ['graghavendra@stratapps.com' ,'kjasmine@stratapps.com', emailidText])
return str(new_issue)
@app.route("/chat-nltk")
def get_response():
userText = request.args.get('msg')
ts = datetime.datetime.now()
print(session,session['count'], re.search(regex,userText))
# if(session['count'] == 0 ):
# print("mail id is entered")
# session['mail_id'] = userText
# session['count'] = 1
# return 'Hi! Before we get started I have a few questions for you. First, we’ll need your email address in case we need to follow up with you about your question [SPLIT] Please enter your email'
# elif(session['count'] == 1 and re.search(regex,userText)):
# session['count'] = 2
# return 'Hi! My name is Jasmine, how can I help you today? [SPLIT] What is your name?'
# elif(session['count'] == 1 and re.search(regex,userText) == None ):
# return 'Please enter valid email id'
# elif(session['count'] == 2):
# session['count'] = 3
# session['name'] = userText
# return 'Welcome to xAmplify '+ userText+ ', how can we assist you today?'
res= str(model_nltk.respond(userText))
if(res == 'None'):
return 'Please provide more info'
else:
return res
@app.route("/save-in-db")
def save_db():
userText = request.args.get('userText')
res = request.args.get('msg')
print('res',res)
print('mail',request.args.get('mail'))
ts = datetime.datetime.now()
conn = psycopg2.connect(database="chatbotdb", user = "postgres", password = "postgres", host = 'localhost', port = "5432")
cursor = conn.cursor()
s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,search_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s)", (request.args.get('mail'), userText, userText, 'human', ts))
s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,resp_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s) ", (request.args.get('mail'), res, res, 'bot',ts ))
print('s',s)
conn.commit()
cursor.close()
conn.close()
return {}
# @app.route("/chat-dl")
# def get_response_dl():
# userText = request.args.get('msg')
# ts = datetime.datetime.now()
# print(session,session['count'], re.search(regex,userText))
# if(session['count'] == 0 and re.search(regex,userText)):
# print("mail id is entered")
# session['mail_id'] = userText
# session['count'] = 1
# return 'Thanks, how can I help you?'
# elif(session['count'] == 0 and re.search(regex,userText) == None):
# return 'Please enter valid email id'
# res= str(chatbot_response(userText))
# conn = psycopg2.connect(database="chatbotdb", user = "postgres", password = "postgres", host = 'localhost', port = "5432")
# cursor = conn.cursor()
# s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,search_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s)", (session['mail_id'], userText, userText, 'human', ts))
# s= cursor.execute("INSERT INTO chathistry (user_mail_id,text,resp_txt,persona,created_at) VALUES(%s, %s, %s, %s, %s) ", (session['mail_id'], res, res, 'bot',ts ))
# print('s',s)
# conn.commit()
# cursor.close()
# conn.close()
# return res
# @app.route("/get-intents")
# def get_intents():
# data_file = open('intents.json').read()
# intents = json.loads(data_file)
# return intents
# @app.route("/get-chats")
# def get_chats():
# chat = Chat(set_pairs, reflections)
# str1=json.dumps(chat)
# str1
# # data_file = open('intents.json').read()
# # intents = json.loads(data_file)
# # return intents
# # filename_model = 'nltk.pkl'
# # pickle.dump(chat, open(filename_model, 'wb'))
if __name__ == '__main__':
app.run(debug=False,threaded=False)