College_ML_Telegram_Bot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ol>\n",
    "    <li>First, Get the Input data, and classify them according to their intents</li>\n",
    "    <li>Then From that classifiar, we will predict the intent of user's query</li>\n",
    "    <li><strike>After getting the intent of user, we will apply the logic of data driven bot</li>\n",
    "    <li>According to intent, and the question, apply the TF-IDF Logic and find similarity between a particular answer and question</li>\n",
    "    <li>One with highest similarity will be given as response to the user</strike></li>\n",
    "</ol>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Classes\n",
    "#### 0. Admission Enquiry\n",
    "#### 1. Contact Info\n",
    "#### 2. About Courses and Programms\n",
    "#### 3. Campus Enquiry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk\n",
    "import numpy as np\n",
    "import re\n",
    "import string\n",
    "import pandas as pd\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from sklearn.svm import LinearSVC\n",
    "from sklearn.neural_network import MLPClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = [[\"Is Admission Open?\", 0], \\\n",
    "           [\"Is there any seat available in this college?\", 0], \\\n",
    "           [\"How many seats are available in this college?\", 0], \\\n",
    "           [\"Is there any seat available in Information Technology Department?\", 0], \\\n",
    "           [\"I want to take admission in Dental College, is there any seat available?\", 0], \\\n",
    "           [\"Can i take admission through GUJCET in this college?\", 0], \\\n",
    "           [\"What was the last year cut off for the admission?\", 0], \\\n",
    "           [\"I want Admission Cell email id for contact\", 1], \\\n",
    "           [\"I want admin contact number\", 1], \\\n",
    "           [\"I want admin department contact number\", 1], \\\n",
    "           [\"I want hostel contact information\", 1], \\\n",
    "           [\"I want toll free contact number\", 1], \\\n",
    "           [\"Give or send me your website link\", 1], \\\n",
    "           [\"What are the available programms in this university ?\", 2], \\\n",
    "           [\"What are the technical courses this university offer?\", 2], \\\n",
    "           [\"What are the medical courses this university offer?\", 2], \\\n",
    "           [\"What are the courses in the Engineering Department?\", 2], \\\n",
    "           [\"Is there any Fest being organized in the College?\", 2], \\\n",
    "           [\"Is there any special international program in the college?\", 2], \\\n",
    "           [\"I want to know about the college\", 3], \\\n",
    "           [\"I want to know about the parking facility in the college\", 3], \\\n",
    "           [\"What about Cafeteria,Is there any cafetaria in college or campus?\", 3], \\\n",
    "           [\"Is there any library in here?\", 3], \\\n",
    "           [\"Is there any Cafeteria in college?\", 3], \\\n",
    "           [\"What about Canteen in the college?\", 3], \\\n",
    "           [\"What about garden in the college?\", 3], \\\n",
    "           [\"How many books are there in library?\", 3] \\\n",
    "          ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Training the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "lemma = WordNetLemmatizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def LemWords(words):\n",
    "    return ' '.join(lemma.lemmatize(word) for word in words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocessSent(sent):\n",
    "    sent = sent.lower()\n",
    "    sent = sent.translate(remove_punct_dict)\n",
    "    words = nltk.word_tokenize(sent)\n",
    "    sent = LemWords(words)\n",
    "    return sent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset = [[preprocessSent(data[0]), data[1]] for data in dataset]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['is admission open', 0],\n",
       " ['is there any seat available in this college', 0],\n",
       " ['how many seat are available in this college', 0],\n",
       " ['is there any seat available in information technology department', 0],\n",
       " ['i want to take admission in dental college is there any seat available', 0],\n",
       " ['can i take admission through gujcet in this college', 0],\n",
       " ['what wa the last year cut off for the admission', 0],\n",
       " ['i want admission cell email id for contact', 1],\n",
       " ['i want admin contact number', 1],\n",
       " ['i want admin department contact number', 1],\n",
       " ['i want hostel contact information', 1],\n",
       " ['i want toll free contact number', 1],\n",
       " ['give or send me your website link', 1],\n",
       " ['what are the available programms in this university', 2],\n",
       " ['what are the technical course this university offer', 2],\n",
       " ['what are the medical course this university offer', 2],\n",
       " ['what are the course in the engineering department', 2],\n",
       " ['is there any fest being organized in the college', 2],\n",
       " ['is there any special international program in the college', 2],\n",
       " ['i want to know about the college', 3],\n",
       " ['i want to know about the parking facility in the college', 3],\n",
       " ['what about cafeteriais there any cafetaria in college or campus', 3],\n",
       " ['is there any library in here', 3],\n",
       " ['is there any cafeteria in college', 3],\n",
       " ['what about canteen in the college', 3],\n",
       " ['what about garden in the college', 3],\n",
       " ['how many book are there in library', 3]]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(dataset, columns = ['text', 'intent'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df['text']\n",
    "y = df['intent']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "tfidfVectorizer = TfidfVectorizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = tfidfVectorizer.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "classifier = LinearSVC(max_iter = 1000, C = 0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearSVC(C=0.1, class_weight=None, dual=True, fit_intercept=True,\n",
       "          intercept_scaling=1, loss='squared_hinge', max_iter=1000,\n",
       "          multi_class='ovr', penalty='l2', random_state=None, tol=0.0001,\n",
       "          verbose=0)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classifier.fit(X, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### From the Predicted class, Give response using NER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.chunk import tree2conlltags\n",
    "from nltk.chunk import ne_chunk\n",
    "from nltk import pos_tag, sent_tokenize, word_tokenize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "responses = {0 : \"\"\"Admission Desk is open till 20th July for Students like You😁, You can ask them questions anytime. \n",
    "There are some seats available in Engineering, Science, MCA and Dental Department.  \n",
    "You can take admission either via GUJCET Exam or JEE. \n",
    "Admission Process can be done either via Online Mode or Offline Mode.\n",
    "\"\"\", \\\n",
    "1 : \"\"\"You can reach Admission Cell, Email ID abc@xyz.com.\n",
    "You can reach Admission Cell, Mobile No 00000000000.\n",
    "Contact us on Toll Free Mobile, 11111111111.\n",
    "To Contact the Hostel Cell, Email on cdf@xyz.com.\n",
    "Sorry, We can't give you Admin Details😅.\n",
    "\"\"\", \\\n",
    "2 : \"\"\"This College provides various courses in Engineering like , Information Technology, Computer Science, Mechanical, Civil, Chemical.\n",
    "There is a Medical Science Department, which provides various types of Biology Courses.\n",
    "This College provides Special Global Student Exchange Program. \n",
    "Every Year, This College organizes Cultural Fest named 'Felicific' having a week of full of Excitement and Joy.\n",
    "\"\"\", \\\n",
    "3 : \"\"\" College Cafeteria is one of the largest in the city, and serves pure and hygenic food.\n",
    "Our Library has over 100000 books.\n",
    "College has parking lot for over 1000 vehicles.\n",
    "There are 3 Gardens and 1 Main Garden in this College.\n",
    "This College has a very vast Campus Infrastructor, containing Gardens, Library, Cricket and Football Ground etc.\n",
    "\"\"\", \\\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "entities = []\n",
    "for i in range(len(responses.keys())):\n",
    "    temp = []\n",
    "    for sent in sent_tokenize(responses[i]):\n",
    "        for chunk in ne_chunk(pos_tag(word_tokenize(sent))):\n",
    "            # print(tree2conlltags(ne_chunk(pos_tag(word_tokenize(sent)))))\n",
    "            if hasattr(chunk, 'label'):\n",
    "                temp.append([chunk[0][0], sent])\n",
    "                # print(chunk.label(), ' '.join(c[0] for c in chunk))\n",
    "                                          \n",
    "    entities.append(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# entities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def LemTokens(tokens):\n",
    "    return [lemma.lemmatize(token) for token in tokens]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Normalize(text): #Remove punctuation, then word tokenize, Then Lemmatize Each Token\n",
    "    return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def response(user_query): \n",
    "    robo_response = ''\n",
    "    # Predict the intent of the User_query\n",
    "    X_test = tfidfVectorizer.transform([user_query])\n",
    "    prediction = classifier.predict(X_test)\n",
    "    entity = entities[prediction[0]]\n",
    "    sents = []\n",
    "    # Try to find if the user_query contains any of the entity of that intent class or not\n",
    "    for item in entity:\n",
    "        if item[0].lower() in user_query.lower():\n",
    "            sents.append(item[1])\n",
    "            # robo_response += item[1] + '\\n'\n",
    "    \n",
    "    # If there is no entity in the user_query according to the prediction class\n",
    "    if len(sents) == 0:\n",
    "        resp = \"Sorry, I can't understand you.\\n😅Can you please rephrase the query Or For Any \"\n",
    "        if prediction[0] == 0:\n",
    "            resp += \"Admission Query\"\n",
    "        elif prediction[0] == 1:\n",
    "            resp += \"Contact Info\"\n",
    "        elif prediction[0] == 2:\n",
    "            resp += \"Courses and Programms related Query\"\n",
    "        elif prediction[0] == 3:\n",
    "            resp += \"Campus related Query\"\n",
    "        resp += \", You can Check our website for more information\"\n",
    "        return resp\n",
    "    \n",
    "    sents.append(user_query)\n",
    "    tfidf = TfidfVectorizer(tokenizer = Normalize, stop_words='english')\n",
    "    vect = tfidf.fit_transform(sents)\n",
    "    vals = cosine_similarity(vect[-1], vect)\n",
    "    idx = vals.argsort()[0][-2]\n",
    "    flat = vals.flatten()\n",
    "    flat.sort()\n",
    "    req = flat[-2]\n",
    "    if req!=0:\n",
    "        robo_response += sents[idx]\n",
    "    # robo_response += \"\\n\\n😄Please Check our website for more information.\"\n",
    "    return robo_response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = \"College?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'College has parking lot for over 1000 vehicles.'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "response(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import json\n",
    "\n",
    "class telegram_bot():\n",
    "    def __init__(self):\n",
    "        self.token = \"1365657286:AAF5fh9IaRG-dBmz10vp5mJRDpSGit6L0nE\"    #write your token here!  \n",
    "        self.url = f\"https://api.telegram.org/bot{self.token}\"\n",
    "\n",
    "    def get_updates(self,offset=None):\n",
    "        url = self.url+\"/getUpdates?timeout=100\"\n",
    "        if offset:\n",
    "            url = url+f\"&offset={offset+1}\"\n",
    "        url_info = requests.get(url)\n",
    "        return json.loads(url_info.content)\n",
    "\n",
    "    def send_message(self,msg,chat_id):\n",
    "        url = self.url + f\"/sendMessage?chat_id={chat_id}&text={msg}\"\n",
    "        if msg is not None:\n",
    "            requests.get(url)\n",
    "\n",
    "    def grab_token(self):\n",
    "        return tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "...\n",
      "[{'update_id': 312269594, 'message': {'message_id': 67, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625317, 'text': '/start', 'entities': [{'offset': 0, 'length': 6, 'type': 'bot_command'}]}}]\n",
      "312269594\n",
      "/start\n",
      "1143427314\n",
      "...\n",
      "[{'update_id': 312269595, 'message': {'message_id': 69, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625393, 'text': 'I want to take admission in engineering, is there any seat available?'}}]\n",
      "312269595\n",
      "I want to take admission in engineering, is there any seat available?\n",
      "1143427314\n",
      "...\n",
      "[{'update_id': 312269596, 'message': {'message_id': 71, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625417, 'text': 'Can I take admission through GUJCET?'}}]\n",
      "312269596\n",
      "Can I take admission through GUJCET?\n",
      "1143427314\n",
      "...\n",
      "[{'update_id': 312269597, 'message': {'message_id': 73, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625435, 'text': 'Tell me about campus infrastructure of the college'}}]\n",
      "312269597\n",
      "Tell me about campus infrastructure of the college\n",
      "1143427314\n",
      "...\n",
      "[]\n",
      "...\n",
      "[]\n",
      "...\n",
      "[{'update_id': 312269598, 'message': {'message_id': 75, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625574, 'text': 'Is there any special program for students?'}}]\n",
      "312269598\n",
      "Is there any special program for students?\n",
      "1143427314\n",
      "...\n",
      "[{'update_id': 312269599, 'message': {'message_id': 77, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625607, 'text': 'Is there any special international program for students?'}}]\n",
      "312269599\n",
      "Is there any special international program for students?\n",
      "1143427314\n",
      "...\n",
      "[{'update_id': 312269600, 'message': {'message_id': 79, 'from': {'id': 1143427314, 'is_bot': False, 'first_name': 'Jaimish', 'language_code': 'en'}, 'chat': {'id': 1143427314, 'first_name': 'Jaimish', 'type': 'private'}, 'date': 1594625631, 'text': 'Give me admission cell email id'}}]\n",
      "312269600\n",
      "Give me admission cell email id\n",
      "1143427314\n",
      "...\n",
      "[]\n",
      "...\n",
      "[]\n",
      "...\n",
      "[]\n",
      "...\n",
      "[]\n",
      "...\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-25-7a449333c254>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     16\u001b[0m \u001b[1;32mwhile\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     17\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"...\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 18\u001b[1;33m     \u001b[0mupdates\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtbot\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_updates\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moffset\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mupdate_id\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     19\u001b[0m     \u001b[0mupdates\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mupdates\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'result'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     20\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mupdates\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-24-066e0c18da82>\u001b[0m in \u001b[0;36mget_updates\u001b[1;34m(self, offset)\u001b[0m\n\u001b[0;32m     11\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0moffset\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m             \u001b[0murl\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;34mf\"&offset={offset+1}\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m         \u001b[0murl_info\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mrequests\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     14\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mjson\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl_info\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontent\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\requests\\api.py\u001b[0m in \u001b[0;36mget\u001b[1;34m(url, params, **kwargs)\u001b[0m\n\u001b[0;32m     74\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'allow_redirects'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 76\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mrequest\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'get'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     77\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     78\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\requests\\api.py\u001b[0m in \u001b[0;36mrequest\u001b[1;34m(method, url, **kwargs)\u001b[0m\n\u001b[0;32m     59\u001b[0m     \u001b[1;31m# cases, and look like a memory leak in others.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     60\u001b[0m     \u001b[1;32mwith\u001b[0m \u001b[0msessions\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0msession\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 61\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0msession\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     62\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     63\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\requests\\sessions.py\u001b[0m in \u001b[0;36mrequest\u001b[1;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[0;32m    528\u001b[0m         }\n\u001b[0;32m    529\u001b[0m         \u001b[0msend_kwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msettings\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 530\u001b[1;33m         \u001b[0mresp\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprep\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0msend_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    531\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    532\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mresp\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\requests\\sessions.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, request, **kwargs)\u001b[0m\n\u001b[0;32m    641\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    642\u001b[0m         \u001b[1;31m# Send the request\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 643\u001b[1;33m         \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0madapter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    644\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    645\u001b[0m         \u001b[1;31m# Total elapsed time of the request (approximately)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\requests\\adapters.py\u001b[0m in \u001b[0;36msend\u001b[1;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[0;32m    447\u001b[0m                     \u001b[0mdecode_content\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    448\u001b[0m                     \u001b[0mretries\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 449\u001b[1;33m                     \u001b[0mtimeout\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    450\u001b[0m                 )\n\u001b[0;32m    451\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\urllib3\\connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[1;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[0;32m    675\u001b[0m                 \u001b[0mbody\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    676\u001b[0m                 \u001b[0mheaders\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 677\u001b[1;33m                 \u001b[0mchunked\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mchunked\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    678\u001b[0m             )\n\u001b[0;32m    679\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\urllib3\\connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[1;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[0;32m    424\u001b[0m                     \u001b[1;31m# Python 3 (including for exceptions like SystemExit).\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    425\u001b[0m                     \u001b[1;31m# Otherwise it looks like a bug in the code.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 426\u001b[1;33m                     \u001b[0msix\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mraise_from\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    427\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mSocketTimeout\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mBaseSSLError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSocketError\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    428\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_raise_timeout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0me\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout_value\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mread_timeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\urllib3\\packages\\six.py\u001b[0m in \u001b[0;36mraise_from\u001b[1;34m(value, from_value)\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\site-packages\\urllib3\\connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[1;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[0;32m    419\u001b[0m                 \u001b[1;31m# Python 3\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    420\u001b[0m                 \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 421\u001b[1;33m                     \u001b[0mhttplib_response\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mconn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    422\u001b[0m                 \u001b[1;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    423\u001b[0m                     \u001b[1;31m# Remove the TypeError from the exception chain in\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\http\\client.py\u001b[0m in \u001b[0;36mgetresponse\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m   1352\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1353\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1354\u001b[1;33m                 \u001b[0mresponse\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbegin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1355\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mConnectionError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1356\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\http\\client.py\u001b[0m in \u001b[0;36mbegin\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    305\u001b[0m         \u001b[1;31m# read until we get a non-100 response\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    306\u001b[0m         \u001b[1;32mwhile\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 307\u001b[1;33m             \u001b[0mversion\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatus\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreason\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_read_status\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    308\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mstatus\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mCONTINUE\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    309\u001b[0m                 \u001b[1;32mbreak\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\http\\client.py\u001b[0m in \u001b[0;36m_read_status\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    266\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    267\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_read_status\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 268\u001b[1;33m         \u001b[0mline\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreadline\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_MAXLINE\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"iso-8859-1\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    269\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[0m_MAXLINE\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    270\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mLineTooLong\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"status line\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\socket.py\u001b[0m in \u001b[0;36mreadinto\u001b[1;34m(self, b)\u001b[0m\n\u001b[0;32m    584\u001b[0m         \u001b[1;32mwhile\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    585\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 586\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    587\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    588\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_timeout_occurred\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\ssl.py\u001b[0m in \u001b[0;36mrecv_into\u001b[1;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[0;32m   1010\u001b[0m                   \u001b[1;34m\"non-zero flags not allowed in calls to recv_into() on %s\"\u001b[0m \u001b[1;33m%\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1011\u001b[0m                   self.__class__)\n\u001b[1;32m-> 1012\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnbytes\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1013\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1014\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0msocket\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnbytes\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\ssl.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, len, buffer)\u001b[0m\n\u001b[0;32m    872\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Read on closed or unwrapped SSL socket.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    873\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 874\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    875\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mSSLError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    876\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mSSL_ERROR_EOF\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msuppress_ragged_eofs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mc:\\users\\administrator\\anaconda3\\envs\\madchatbot\\lib\\ssl.py\u001b[0m in \u001b[0;36mread\u001b[1;34m(self, len, buffer)\u001b[0m\n\u001b[0;32m    629\u001b[0m         \"\"\"\n\u001b[0;32m    630\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mbuffer\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 631\u001b[1;33m             \u001b[0mv\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    632\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    633\u001b[0m             \u001b[0mv\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "tbot = telegram_bot()\n",
    "\n",
    "update_id = None\n",
    "\n",
    "def make_reply(msg):\n",
    "    if msg is not None:\n",
    "        if 'website' in msg.lower():\n",
    "            return \"Our site link is, 'www.ddu.ac.in' .\"\n",
    "        if msg.lower() == 'bye' or msg.lower() == 'good bye':\n",
    "            return 'Good Bye'\n",
    "        if len(word_tokenize(msg)) == 1:\n",
    "            return 'Hello\\nWelcome to the unofficial Assistant of DDU College😄\\nWhat can I do for You?'    \n",
    "    reply = response(msg)\n",
    "    return reply\n",
    "flag = 0\n",
    "while True:\n",
    "    print(\"...\")\n",
    "    updates = tbot.get_updates(offset=update_id)\n",
    "    updates = updates['result']\n",
    "    print(updates)\n",
    "    if updates:\n",
    "        for item in updates:\n",
    "            update_id = item[\"update_id\"]\n",
    "            print(update_id)\n",
    "            try:\n",
    "                message = item[\"message\"][\"text\"]\n",
    "                print(message)\n",
    "            except:\n",
    "                message = None\n",
    "            from_ = item[\"message\"][\"from\"][\"id\"]\n",
    "            print(from_)\n",
    "\n",
    "            reply = make_reply(message)\n",
    "            tbot.send_message(reply,from_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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