code.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0779343d",
   "metadata": {},
   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "2022-11-30 23:58:27.272849: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2022-11-30 23:58:27.407866: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
      "2022-11-30 23:58:27.407887: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n",
      "2022-11-30 23:58:27.433745: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
      "2022-11-30 23:58:28.108293: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2022-11-30 23:58:28.108339: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2022-11-30 23:58:28.108344: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "from keras.layers import Dense, Dropout, Embedding, LSTM, Bidirectional, SimpleRNN, GRU\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from sklearn.model_selection import train_test_split\n",
    "from transformers import BertTokenizer\n",
    "from keras.models import Sequential\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow_addons as tfa\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9724be29",
   "metadata": {},
   "source": [
    "## Loading the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a41b3ee9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>questionID</th>\n",
       "      <th>questionTitle</th>\n",
       "      <th>questionText</th>\n",
       "      <th>questionUrl</th>\n",
       "      <th>topics</th>\n",
       "      <th>therapistName</th>\n",
       "      <th>therapistUrl</th>\n",
       "      <th>answerText</th>\n",
       "      <th>upvotes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5566fab2a64752d71ec3ca69</td>\n",
       "      <td>Escalating disagreements between mother and wife</td>\n",
       "      <td>My wife and mother are having tense disagreeme...</td>\n",
       "      <td>https://counselchat.com/questions/escalating-d...</td>\n",
       "      <td>Family Conflict</td>\n",
       "      <td>Kristi King-Morgan, LMSW</td>\n",
       "      <td>https://counselchat.com/therapists/kristi-king...</td>\n",
       "      <td>&lt;p&gt;What you are describing is something psycho...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5566f94fa64752d71ec3ca64</td>\n",
       "      <td>I'm addicted to smoking. How can I stop?</td>\n",
       "      <td>I'm planning to have baby, so I have to quit s...</td>\n",
       "      <td>https://counselchat.com/questions/i-m-addicted...</td>\n",
       "      <td>Substance Abuse,Addiction</td>\n",
       "      <td>Rebecca Duellman</td>\n",
       "      <td>https://counselchat.com/therapists/rebecca-due...</td>\n",
       "      <td>&lt;p&gt;Hi. Good for you in planning ahead to do wh...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5567d26887a1cc0c3f3d8f46</td>\n",
       "      <td>Keeping secrets from my family</td>\n",
       "      <td>I have secrets in my mind, and I don't know wh...</td>\n",
       "      <td>https://counselchat.com/questions/keeping-secr...</td>\n",
       "      <td>Family Conflict</td>\n",
       "      <td>Jeevna Bajaj</td>\n",
       "      <td>https://counselchat.com/therapists/jeevna-bajaj</td>\n",
       "      <td>&lt;p&gt;It sounds like keeping the secrets has beco...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>556bed15c969ba5861709df5</td>\n",
       "      <td>The Underlying Causes of Being Possessive</td>\n",
       "      <td>I am extremely possessive in my relationships ...</td>\n",
       "      <td>https://counselchat.com/questions/the-underlyi...</td>\n",
       "      <td>Behavioral Change,Social Relationships</td>\n",
       "      <td>Rebecca Duellman</td>\n",
       "      <td>https://counselchat.com/therapists/rebecca-due...</td>\n",
       "      <td>&lt;p&gt;Hi there. It's great you are able to realiz...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>556ba115c969ba5861709de6</td>\n",
       "      <td>Can I control anxiety without medication?</td>\n",
       "      <td>I had a head injury a few years ago and my min...</td>\n",
       "      <td>https://counselchat.com/questions/can-i-contro...</td>\n",
       "      <td>Anxiety</td>\n",
       "      <td>Rebecca Duellman</td>\n",
       "      <td>https://counselchat.com/therapists/rebecca-due...</td>\n",
       "      <td>&lt;p&gt;You didn't say what or how many medications...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 questionID                                     questionTitle  \\\n",
       "0  5566fab2a64752d71ec3ca69  Escalating disagreements between mother and wife   \n",
       "1  5566f94fa64752d71ec3ca64          I'm addicted to smoking. How can I stop?   \n",
       "2  5567d26887a1cc0c3f3d8f46                    Keeping secrets from my family   \n",
       "3  556bed15c969ba5861709df5         The Underlying Causes of Being Possessive   \n",
       "4  556ba115c969ba5861709de6         Can I control anxiety without medication?   \n",
       "\n",
       "                                        questionText  \\\n",
       "0  My wife and mother are having tense disagreeme...   \n",
       "1  I'm planning to have baby, so I have to quit s...   \n",
       "2  I have secrets in my mind, and I don't know wh...   \n",
       "3  I am extremely possessive in my relationships ...   \n",
       "4  I had a head injury a few years ago and my min...   \n",
       "\n",
       "                                         questionUrl  \\\n",
       "0  https://counselchat.com/questions/escalating-d...   \n",
       "1  https://counselchat.com/questions/i-m-addicted...   \n",
       "2  https://counselchat.com/questions/keeping-secr...   \n",
       "3  https://counselchat.com/questions/the-underlyi...   \n",
       "4  https://counselchat.com/questions/can-i-contro...   \n",
       "\n",
       "                                   topics             therapistName  \\\n",
       "0                         Family Conflict  Kristi King-Morgan, LMSW   \n",
       "1               Substance Abuse,Addiction          Rebecca Duellman   \n",
       "2                         Family Conflict              Jeevna Bajaj   \n",
       "3  Behavioral Change,Social Relationships          Rebecca Duellman   \n",
       "4                                 Anxiety          Rebecca Duellman   \n",
       "\n",
       "                                        therapistUrl  \\\n",
       "0  https://counselchat.com/therapists/kristi-king...   \n",
       "1  https://counselchat.com/therapists/rebecca-due...   \n",
       "2    https://counselchat.com/therapists/jeevna-bajaj   \n",
       "3  https://counselchat.com/therapists/rebecca-due...   \n",
       "4  https://counselchat.com/therapists/rebecca-due...   \n",
       "\n",
       "                                          answerText  upvotes  \n",
       "0  <p>What you are describing is something psycho...        0  \n",
       "1  <p>Hi. Good for you in planning ahead to do wh...        0  \n",
       "2  <p>It sounds like keeping the secrets has beco...        0  \n",
       "3  <p>Hi there. It's great you are able to realiz...        0  \n",
       "4  <p>You didn't say what or how many medications...        0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_data = pd.read_csv(\"counselchat-data.csv\")\n",
    "chat_data = chat_data.dropna()\n",
    "chat_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "844bde5a",
   "metadata": {},
   "source": [
    "## Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6162f9a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1376, 9)"
      ]
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     "execution_count": 3,
     "metadata": {},
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    }
   ],
   "source": [
    "chat_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "afb0f4d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Family Conflict',\n",
       " 'Substance Abuse',\n",
       " 'Family Conflict',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Relationship Dissolution ',\n",
       " 'Anger Management',\n",
       " 'Sleep Improvement',\n",
       " 'Professional Ethics',\n",
       " 'Social Relationships',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Domestic Violence',\n",
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       " 'Anger Management',\n",
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       " 'Military Issues ',\n",
       " 'Relationships',\n",
       " 'Domestic Violence',\n",
       " 'Depression',\n",
       " 'Marriage',\n",
       " 'Grief and Loss',\n",
       " 'Family Conflict',\n",
       " 'Marriage',\n",
       " 'Grief and Loss',\n",
       " 'Trauma',\n",
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       " 'Relationships',\n",
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       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'Depression',\n",
       " 'Family Conflict',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'LGBTQ',\n",
       " 'Relationships',\n",
       " 'LGBTQ',\n",
       " 'Anger Management',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Depression',\n",
       " 'Domestic Violence',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Self-esteem',\n",
       " 'Social Relationships',\n",
       " 'Relationships',\n",
       " 'Self-esteem',\n",
       " 'Depression',\n",
       " 'Parenting',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Stress',\n",
       " 'Parenting',\n",
       " 'Intimacy',\n",
       " 'Human Sexuality',\n",
       " 'Addiction',\n",
       " 'Addiction',\n",
       " 'Family Conflict',\n",
       " 'Trauma',\n",
       " 'Depression',\n",
       " 'Trauma',\n",
       " 'Anxiety',\n",
       " 'Addiction',\n",
       " 'Anger Management',\n",
       " 'Depression',\n",
       " 'Relationships',\n",
       " 'Depression',\n",
       " 'Self-esteem',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Trauma',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Relationships',\n",
       " 'Anger Management',\n",
       " 'Behavioral Change',\n",
       " 'Relationships',\n",
       " 'Family Conflict',\n",
       " 'Anger Management',\n",
       " 'Parenting',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " 'Stress',\n",
       " 'Family Conflict',\n",
       " 'Trauma',\n",
       " 'Trauma',\n",
       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'Anxiety',\n",
       " 'Stress',\n",
       " 'Self-esteem',\n",
       " 'Spirituality',\n",
       " 'Spirituality',\n",
       " 'Anxiety',\n",
       " 'Stress',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Self-esteem',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Workplace Relationships',\n",
       " 'Sleep Improvement',\n",
       " 'Stress',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Human Sexuality',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Grief and Loss',\n",
       " 'Anger Management',\n",
       " 'Relationship Dissolution ',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Stress',\n",
       " 'Human Sexuality',\n",
       " 'Anxiety',\n",
       " 'Spirituality',\n",
       " 'Human Sexuality',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Anger Management',\n",
       " 'Relationships',\n",
       " 'Legal & Regulatory',\n",
       " 'Professional Ethics',\n",
       " 'Social Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Social Relationships',\n",
       " 'Marriage',\n",
       " 'Intimacy',\n",
       " 'Marriage',\n",
       " 'Social Relationships',\n",
       " 'Self-esteem',\n",
       " 'Social Relationships',\n",
       " 'Self-esteem',\n",
       " 'Family Conflict',\n",
       " 'Social Relationships',\n",
       " 'Family Conflict',\n",
       " 'Self-esteem',\n",
       " 'LGBTQ',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Social Relationships',\n",
       " 'Relationships',\n",
       " 'Social Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Grief and Loss',\n",
       " 'Family Conflict',\n",
       " 'Self-esteem',\n",
       " 'Anxiety',\n",
       " 'Social Relationships',\n",
       " 'Trauma',\n",
       " 'Anger Management',\n",
       " 'Anxiety',\n",
       " 'Social Relationships',\n",
       " 'LGBTQ',\n",
       " 'Self-esteem',\n",
       " 'Family Conflict',\n",
       " 'Human Sexuality',\n",
       " 'Self-esteem',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Anxiety',\n",
       " 'Legal & Regulatory',\n",
       " 'Anger Management',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Legal & Regulatory',\n",
       " 'Self-esteem',\n",
       " 'Relationships',\n",
       " 'Trauma',\n",
       " 'LGBTQ',\n",
       " 'Intimacy',\n",
       " 'Relationships',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Intimacy',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Family Conflict',\n",
       " 'LGBTQ',\n",
       " 'Trauma',\n",
       " 'Sleep Improvement',\n",
       " 'Domestic Violence',\n",
       " 'Domestic Violence',\n",
       " 'Trauma',\n",
       " 'Parenting',\n",
       " 'Grief and Loss',\n",
       " 'Family Conflict',\n",
       " 'Grief and Loss',\n",
       " 'Grief and Loss',\n",
       " 'Behavioral Change',\n",
       " 'Grief and Loss',\n",
       " 'Parenting',\n",
       " 'Human Sexuality',\n",
       " 'Human Sexuality',\n",
       " 'Anxiety',\n",
       " 'Intimacy',\n",
       " 'Grief and Loss',\n",
       " 'Anxiety',\n",
       " 'Intimacy',\n",
       " 'Self-esteem',\n",
       " 'Grief and Loss',\n",
       " 'Grief and Loss',\n",
       " 'Self-esteem',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Parenting',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Social Relationships',\n",
       " 'Social Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Social Relationships',\n",
       " 'Depression',\n",
       " 'LGBTQ',\n",
       " 'Social Relationships',\n",
       " 'Relationship Dissolution ',\n",
       " 'Relationship Dissolution ',\n",
       " 'LGBTQ',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Relationship Dissolution ',\n",
       " 'Relationship Dissolution ',\n",
       " 'Stress',\n",
       " 'Intimacy',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Family Conflict',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Intimacy',\n",
       " 'Anxiety',\n",
       " 'Workplace Relationships',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Stress',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Relationship Dissolution ',\n",
       " 'Workplace Relationships',\n",
       " 'Stress',\n",
       " 'Depression',\n",
       " 'Human Sexuality',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'LGBTQ',\n",
       " 'Parenting',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Behavioral Change',\n",
       " 'Human Sexuality',\n",
       " 'Social Relationships',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Sleep Improvement',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Sleep Improvement',\n",
       " 'Marriage',\n",
       " 'Social Relationships',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " \"Alzheimer's\",\n",
       " \"Alzheimer's\",\n",
       " 'Self-esteem',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Parenting',\n",
       " 'Human Sexuality',\n",
       " 'Social Relationships',\n",
       " 'Marriage',\n",
       " 'Stress',\n",
       " 'Family Conflict',\n",
       " 'Parenting',\n",
       " 'Depression',\n",
       " 'Behavioral Change',\n",
       " 'Behavioral Change',\n",
       " 'Relationships',\n",
       " 'Family Conflict',\n",
       " 'Behavioral Change',\n",
       " 'Family Conflict',\n",
       " 'Parenting',\n",
       " 'Relationships',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Relationships',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Depression',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Trauma',\n",
       " 'Family Conflict',\n",
       " 'Depression',\n",
       " 'Social Relationships',\n",
       " 'Depression',\n",
       " 'Parenting',\n",
       " 'Human Sexuality',\n",
       " 'Anger Management',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " 'Family Conflict',\n",
       " 'Behavioral Change',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Family Conflict',\n",
       " 'Self-esteem',\n",
       " 'Intimacy',\n",
       " 'Depression',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Intimacy',\n",
       " 'Self-esteem',\n",
       " 'Marriage',\n",
       " 'Family Conflict',\n",
       " 'LGBTQ',\n",
       " 'Marriage',\n",
       " 'Self-esteem',\n",
       " 'Relationships',\n",
       " 'Spirituality',\n",
       " 'Marriage',\n",
       " 'LGBTQ',\n",
       " 'Family Conflict',\n",
       " 'Depression',\n",
       " 'Spirituality',\n",
       " 'Spirituality',\n",
       " 'Trauma',\n",
       " 'Stress',\n",
       " 'Marriage',\n",
       " 'Spirituality',\n",
       " 'Anxiety',\n",
       " 'Spirituality',\n",
       " 'Family Conflict',\n",
       " 'Spirituality',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'LGBTQ',\n",
       " 'Family Conflict',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Anger Management',\n",
       " 'Behavioral Change',\n",
       " 'Depression',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Relationship Dissolution ',\n",
       " 'Marriage',\n",
       " 'Relationship Dissolution ',\n",
       " 'Relationship Dissolution ',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Behavioral Change',\n",
       " 'Self-esteem',\n",
       " 'Anxiety',\n",
       " 'Relationship Dissolution ',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Relationship Dissolution ',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Parenting',\n",
       " 'Self-esteem',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'LGBTQ',\n",
       " 'Social Relationships',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Social Relationships',\n",
       " 'Depression',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Stress',\n",
       " 'Self-esteem',\n",
       " 'Depression',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Family Conflict',\n",
       " 'Relationship Dissolution ',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Intimacy',\n",
       " 'Relationships',\n",
       " 'Parenting',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Parenting',\n",
       " 'LGBTQ',\n",
       " 'Trauma',\n",
       " 'Spirituality',\n",
       " 'Spirituality',\n",
       " 'Anxiety',\n",
       " 'Human Sexuality',\n",
       " 'Anxiety',\n",
       " 'Spirituality',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Relationship Dissolution ',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Relationship Dissolution ',\n",
       " 'Relationships',\n",
       " 'Intimacy',\n",
       " 'Self-esteem',\n",
       " 'Relationships',\n",
       " 'Social Relationships',\n",
       " 'Relationship Dissolution ',\n",
       " 'Family Conflict',\n",
       " 'Marriage',\n",
       " 'Spirituality',\n",
       " 'Social Relationships',\n",
       " 'Family Conflict',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Relationship Dissolution ',\n",
       " 'Social Relationships',\n",
       " 'LGBTQ',\n",
       " 'Addiction',\n",
       " 'Marriage',\n",
       " 'Marriage',\n",
       " 'Parenting',\n",
       " 'Spirituality',\n",
       " 'Human Sexuality',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " 'Human Sexuality',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Anxiety',\n",
       " 'Depression',\n",
       " 'Trauma',\n",
       " 'Self-esteem',\n",
       " 'Anxiety',\n",
       " 'Anger Management',\n",
       " 'Social Relationships',\n",
       " 'Anxiety',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Anger Management',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Parenting',\n",
       " 'Marriage',\n",
       " 'Family Conflict',\n",
       " 'Marriage',\n",
       " 'Diagnosis',\n",
       " 'Professional Ethics',\n",
       " 'Trauma',\n",
       " 'Diagnosis',\n",
       " 'Addiction',\n",
       " 'Legal & Regulatory',\n",
       " 'Relationships',\n",
       " 'Diagnosis',\n",
       " 'Marriage',\n",
       " 'Professional Ethics',\n",
       " 'Military Issues ',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Legal & Regulatory',\n",
       " 'Marriage',\n",
       " 'Legal & Regulatory',\n",
       " 'Substance Abuse',\n",
       " 'Marriage',\n",
       " 'Self-esteem',\n",
       " 'Relationships',\n",
       " 'Legal & Regulatory',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Human Sexuality',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Legal & Regulatory',\n",
       " 'Social Relationships',\n",
       " 'Legal & Regulatory',\n",
       " 'Marriage',\n",
       " 'Marriage',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Anxiety',\n",
       " 'Substance Abuse',\n",
       " 'Relationships',\n",
       " 'Human Sexuality',\n",
       " 'Marriage',\n",
       " 'Diagnosis',\n",
       " 'Self-esteem',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'Diagnosis',\n",
       " 'Relationships',\n",
       " 'Anxiety',\n",
       " 'Family Conflict',\n",
       " 'Family Conflict',\n",
       " 'Self-esteem',\n",
       " 'Behavioral Change',\n",
       " 'Anxiety',\n",
       " 'Marriage',\n",
       " 'Marriage',\n",
       " 'Intimacy',\n",
       " 'Behavioral Change',\n",
       " 'Depression',\n",
       " 'Relationships',\n",
       " 'Social Relationships',\n",
       " 'Behavioral Change',\n",
       " 'Parenting',\n",
       " 'Self-esteem',\n",
       " 'Self-esteem',\n",
       " 'Trauma',\n",
       " 'Trauma',\n",
       " 'Human Sexuality',\n",
       " 'Trauma',\n",
       " 'Trauma',\n",
       " 'Trauma',\n",
       " 'Depression',\n",
       " 'Marriage',\n",
       " 'Marriage',\n",
       " 'Marriage',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Marriage',\n",
       " 'Parenting',\n",
       " 'Family Conflict',\n",
       " 'Relationships',\n",
       " 'Marriage',\n",
       " 'Relationship Dissolution ',\n",
       " 'Human Sexuality',\n",
       " 'Legal & Regulatory',\n",
       " 'Anxiety',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Self-esteem',\n",
       " 'Self-esteem',\n",
       " 'Self-esteem',\n",
       " 'Self-esteem',\n",
       " 'Self-esteem',\n",
       " 'Trauma',\n",
       " 'Anxiety',\n",
       " 'Trauma',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " 'Relationships',\n",
       " ...]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topics = chat_data['topics']\n",
    "topics = list(map(lambda x: x.split(',')[0], topics))\n",
    "topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cad7e39c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "topic, counts = np.unique(topics, return_counts=True)\n",
    "\n",
    "fig = plt.figure(figsize=(10, 15))\n",
    "\n",
    "plt.barh(topic, counts, color='maroon')\n",
    "plt.xlabel('No. of topics')\n",
    "plt.ylabel('Topic')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50fe9367",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb08d98a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6284cbd8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a0b1633c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "203aa73c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e269f880",
   "metadata": {},
   "source": [
    "## Filtering the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "211ae67e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>questionTitle</th>\n",
       "      <th>questionText</th>\n",
       "      <th>answerText</th>\n",
       "      <th>topics</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1477</th>\n",
       "      <td>Is it healthy to embarrass a child as punishment?</td>\n",
       "      <td>My grandson's step-mother sends him to school ...</td>\n",
       "      <td>&lt;p&gt;Absolutely not!&amp;nbsp;&lt;/p&gt;&lt;p&gt;It is never in ...</td>\n",
       "      <td>Parenting,Family Conflict</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1478</th>\n",
       "      <td>How do I fix my relationship?</td>\n",
       "      <td>My boyfriend is in recovery from drug addictio...</td>\n",
       "      <td>&lt;p&gt;I'm sorry you have tension between you and ...</td>\n",
       "      <td>Relationships,Addiction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1479</th>\n",
       "      <td>What are the long term effects of losing one's...</td>\n",
       "      <td>The birth mother attempted suicide several tim...</td>\n",
       "      <td>&lt;p&gt;The true answer is, \"no one can really say ...</td>\n",
       "      <td>Family Conflict,Parenting,Children &amp; Adolescents</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1480</th>\n",
       "      <td>How do I help my 20 year old boyfriend who say...</td>\n",
       "      <td>I think adult life is making him depressed and...</td>\n",
       "      <td>&lt;p&gt;How do you help yourself to believe you req...</td>\n",
       "      <td>Relationships,Depression,Substance Abuse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1481</th>\n",
       "      <td>I'm worried about my new job.</td>\n",
       "      <td>I just took a job that requires me to travel f...</td>\n",
       "      <td>&lt;p&gt;hmm this is a tough one!&lt;/p&gt;</td>\n",
       "      <td>Anxiety,Career Counseling</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          questionTitle  \\\n",
       "1477  Is it healthy to embarrass a child as punishment?   \n",
       "1478                      How do I fix my relationship?   \n",
       "1479  What are the long term effects of losing one's...   \n",
       "1480  How do I help my 20 year old boyfriend who say...   \n",
       "1481                      I'm worried about my new job.   \n",
       "\n",
       "                                           questionText  \\\n",
       "1477  My grandson's step-mother sends him to school ...   \n",
       "1478  My boyfriend is in recovery from drug addictio...   \n",
       "1479  The birth mother attempted suicide several tim...   \n",
       "1480  I think adult life is making him depressed and...   \n",
       "1481  I just took a job that requires me to travel f...   \n",
       "\n",
       "                                             answerText  \\\n",
       "1477  <p>Absolutely not!&nbsp;</p><p>It is never in ...   \n",
       "1478  <p>I'm sorry you have tension between you and ...   \n",
       "1479  <p>The true answer is, \"no one can really say ...   \n",
       "1480  <p>How do you help yourself to believe you req...   \n",
       "1481                    <p>hmm this is a tough one!</p>   \n",
       "\n",
       "                                                topics  \n",
       "1477                         Parenting,Family Conflict  \n",
       "1478                           Relationships,Addiction  \n",
       "1479  Family Conflict,Parenting,Children & Adolescents  \n",
       "1480          Relationships,Depression,Substance Abuse  \n",
       "1481                         Anxiety,Career Counseling  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "desired_columns = ['questionTitle', 'questionText', 'answerText', 'topics']\n",
    "chat_data_new = chat_data[desired_columns].copy()\n",
    "chat_data_new = chat_data_new.dropna(axis = 0)\n",
    "chat_data_new.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ddee002",
   "metadata": {},
   "source": [
    "# Load the pre-trained BERT from transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2bd75cd4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "unit": "B",
       "unit_divisor": 1000,
       "unit_scale": true
      },
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b61d96e9173e40f294ce2e6cd07639ca",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Downloading:   0%|          | 0.00/232k [00:00<?, ?B/s]"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "12417452b6d740218d89892931051e8b",
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "unit": "B",
       "unit_divisor": 1000,
       "unit_scale": true
      },
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bd476c5c96224b6991924371964ef5e9",
       "version_major": 2,
       "version_minor": 0
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      "text/plain": [
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      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "#Load the bert tokenizer.\n",
    "bert_tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8d0cca77",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vocabulary Size: 30522\n"
     ]
    }
   ],
   "source": [
    "print('Vocabulary Size:', bert_tokenizer.vocab_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "32d1ea99",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Get the embeddings from the text corpus.\n",
    "def get_embeddings(sentences):\n",
    "    \n",
    "    tokenized_sentences = []\n",
    "    embeddings = []\n",
    "\n",
    "    for i in range(len(sentences)):\n",
    "        sentences[i] = \"[CLS] %s [SEP]\" % (sentences[i].strip(), )\n",
    "        tokenized_sentences.append(bert_tokenizer.tokenize(sentences[i]))\n",
    "        embeddings.append(bert_tokenizer.convert_tokens_to_ids(tokenized_sentences[-1]))\n",
    "\n",
    "    return embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ca33ad10",
   "metadata": {},
   "outputs": [],
   "source": [
    "idx = random.randint(0, len(chat_data_new))\n",
    "questionTitle = chat_data_new.loc[idx]['questionTitle']\n",
    "questionText = chat_data_new.loc[idx]['questionText']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9c43597c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Question Title:\n",
      "How can I help my fiancé accept and let go of my past?\n",
      "\n",
      "Question Title Embedding:\n",
      "[[101, 2129, 2064, 1045, 2393, 2026, 19154, 5138, 1998, 2292, 2175, 1997, 2026, 2627, 1029, 102]]\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Question Title:')\n",
    "print(questionTitle)\n",
    "print('')\n",
    "print('Question Title Embedding:')\n",
    "print(get_embeddings([questionTitle]))\n",
    "print('\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "37e41110",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Question Text:\n",
      "My fiancé and I come from a strong Christian background but both went off the \"straight and narrow\" once before. He is having a hard time accepting my past, especially  that I'm not a virgin. He has a hard time in general accepting himself and others. \r\n",
      "\r\n",
      "His insecurities are hurting our relationship. How can I help him let go of my past and decide to live in the present?\n",
      "\n",
      "Question Text Embedding:\n",
      "[[101, 2026, 19154, 1998, 1045, 2272, 2013, 1037, 2844, 3017, 4281, 2021, 2119, 2253, 2125, 1996, 1000, 3442, 1998, 4867, 1000, 2320, 2077, 1012, 2002, 2003, 2383, 1037, 2524, 2051, 10564, 2026, 2627, 1010, 2926, 2008, 1045, 1005, 1049, 2025, 1037, 6261, 1012, 2002, 2038, 1037, 2524, 2051, 1999, 2236, 10564, 2370, 1998, 2500, 1012, 2010, 16021, 8586, 29366, 2024, 11878, 2256, 3276, 1012, 2129, 2064, 1045, 2393, 2032, 2292, 2175, 1997, 2026, 2627, 1998, 5630, 2000, 2444, 1999, 1996, 2556, 1029, 102]]\n"
     ]
    }
   ],
   "source": [
    "print('Question Text:')\n",
    "print(questionText)\n",
    "print('')\n",
    "print('Question Text Embedding:')\n",
    "print(get_embeddings([questionText]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "457d479e",
   "metadata": {},
   "source": [
    "### Map the dataset to BERT embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b518eedd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_sentences_to_embeddings(data, column_1, column_2, max_len_1=128, max_len_2=16):\n",
    "    \n",
    "    sents_1 = data[column_1].tolist()\n",
    "    sents_2 = data[column_2].tolist()\n",
    "    entries = [str(sents_1[i] + sents_2[i]) for i in range(len(sents_1))]\n",
    "\n",
    "    encoded_1 = get_embeddings(sents_1)\n",
    "    encoded_2 = get_embeddings(sents_2)\n",
    "        \n",
    "    padded_1 = pad_sequences(encoded_1, padding='post', maxlen=max_len_1)\n",
    "    padded_2 = pad_sequences(encoded_2, padding='post', maxlen=max_len_2)\n",
    "    \n",
    "    return padded_1, padded_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3c3648bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab_size = bert_tokenizer.vocab_size\n",
    "X, y = map_sentences_to_embeddings(chat_data_new, 'questionTitle', 'questionText')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1268e4c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  101,  9686, 25015, ...,     0,     0,     0],\n",
       "       [  101,  1045,  1005, ...,     0,     0,     0],\n",
       "       [  101,  4363,  7800, ...,     0,     0,     0],\n",
       "       ...,\n",
       "       [  101,  2054,  2024, ...,     0,     0,     0],\n",
       "       [  101,  2129,  2079, ...,     0,     0,     0],\n",
       "       [  101,  1045,  1005, ...,     0,     0,     0]], dtype=int32)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "010bbac8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[18185,  2003, 23848, ...,  2079,  1029,   102],\n",
       "       [ 3241,  2055,  9422, ..., 13449,  1029,   102],\n",
       "       [ 2079,  1029,  2009, ...,  2033,  2041,   102],\n",
       "       ...,\n",
       "       [ 2054,  2453,  2022, ...,  2381,  1029,   102],\n",
       "       [ 2030,  2000, 15886, ...,  2032,  1029,   102],\n",
       "       [ 1996,  2346,  1012, ...,  2079,  1029,   102]], dtype=int32)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c39b72a8",
   "metadata": {},
   "source": [
    "## Building Bidirectional-LSTM model with 2 LSTM layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "de3990b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-11-30 23:58:45.244586: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory\n",
      "2022-11-30 23:58:45.244623: W tensorflow/stream_executor/cuda/cuda_driver.cc:263] failed call to cuInit: UNKNOWN ERROR (303)\n",
      "2022-11-30 23:58:45.244653: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (hp): /proc/driver/nvidia/version does not exist\n",
      "2022-11-30 23:58:45.246204: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "metrics = ['accuracy', tf.keras.metrics.Precision()]\n",
    "\n",
    "def bilstm_model(vocab_size, max_length, metrics):\n",
    "    \n",
    "    model = Sequential()\n",
    "    #first Embedding layer.\n",
    "    model.add(Embedding(vocab_size, 128, input_length=max_length))\n",
    "    \n",
    "    #first Bi-LSTM layer.\n",
    "    model.add(Bidirectional(LSTM(128, return_sequences=True)))\n",
    "    model.add(Dropout(0.75))\n",
    "    \n",
    "    #second Bi-LSTM layer.\n",
    "    model.add(Bidirectional(LSTM(128)))\n",
    "    model.add(Dropout(0.75))\n",
    "    \n",
    "    #outputllayer.\n",
    "    model.add(Dense(16, activation='softmax'))\n",
    "    \n",
    "    model.compile(optimizer='adam', metrics=metrics, loss='categorical_crossentropy')\n",
    "    \n",
    "    #print model summary.\n",
    "    model.summary()\n",
    "    \n",
    "    return model\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a9762002",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " embedding (Embedding)       (None, 128, 128)          3906816   \n",
      "                                                                 \n",
      " bidirectional (Bidirectiona  (None, 128, 256)         263168    \n",
      " l)                                                              \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 128, 256)          0         \n",
      "                                                                 \n",
      " bidirectional_1 (Bidirectio  (None, 256)              394240    \n",
      " nal)                                                            \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 256)               0         \n",
      "                                                                 \n",
      " dense (Dense)               (None, 16)                4112      \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 4,568,336\n",
      "Trainable params: 4,568,336\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "#build the model.\n",
    "model = bilstm_model(vocab_size, 128, metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "61951eab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n",
      "43/43 [==============================] - 26s 525ms/step - loss: 175922.2031 - accuracy: 0.0836 - precision: 0.9814 - val_loss: 131833.5781 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 2/15\n",
      "43/43 [==============================] - 21s 492ms/step - loss: 211827.4375 - accuracy: 0.0770 - precision: 0.9760 - val_loss: 137538.6250 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 3/15\n",
      "43/43 [==============================] - 21s 498ms/step - loss: 218663.3438 - accuracy: 0.0814 - precision: 0.9807 - val_loss: 139024.1562 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 4/15\n",
      "43/43 [==============================] - 22s 511ms/step - loss: 219947.0000 - accuracy: 0.0879 - precision: 0.9796 - val_loss: 143382.2031 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 5/15\n",
      "43/43 [==============================] - 21s 485ms/step - loss: 223921.2812 - accuracy: 0.0734 - precision: 0.9885 - val_loss: 148185.9531 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 6/15\n",
      "43/43 [==============================] - 21s 497ms/step - loss: 230709.9531 - accuracy: 0.0843 - precision: 0.9739 - val_loss: 155286.4844 - val_accuracy: 0.1570 - val_precision: 0.0000e+00\n",
      "Epoch 7/15\n",
      "43/43 [==============================] - 23s 537ms/step - loss: 235511.0000 - accuracy: 0.0843 - precision: 0.9787 - val_loss: 166364.4844 - val_accuracy: 0.0000e+00 - val_precision: 0.0000e+00\n",
      "Epoch 8/15\n",
      "43/43 [==============================] - 22s 524ms/step - loss: 247470.4844 - accuracy: 0.0501 - precision: 0.9777 - val_loss: 179067.5156 - val_accuracy: 0.0000e+00 - val_precision: 0.0000e+00\n",
      "Epoch 9/15\n",
      "43/43 [==============================] - 21s 483ms/step - loss: 257063.4219 - accuracy: 0.0741 - precision: 0.9740 - val_loss: 196128.9375 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 10/15\n",
      "43/43 [==============================] - 21s 487ms/step - loss: 270273.1875 - accuracy: 0.0523 - precision: 0.9709 - val_loss: 218479.1875 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 11/15\n",
      "43/43 [==============================] - 19s 455ms/step - loss: 287696.2188 - accuracy: 0.0436 - precision: 0.9670 - val_loss: 243480.6719 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 12/15\n",
      "43/43 [==============================] - 19s 447ms/step - loss: 307747.0000 - accuracy: 0.0276 - precision: 0.9693 - val_loss: 269157.1250 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 13/15\n",
      "43/43 [==============================] - 19s 450ms/step - loss: 325874.5000 - accuracy: 0.0262 - precision: 0.9617 - val_loss: 296160.0625 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 14/15\n",
      "43/43 [==============================] - 19s 453ms/step - loss: 345905.5312 - accuracy: 0.0276 - precision: 0.9646 - val_loss: 324651.2500 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n",
      "Epoch 15/15\n",
      "43/43 [==============================] - 19s 448ms/step - loss: 370196.2500 - accuracy: 0.0145 - precision: 0.9567 - val_loss: 354839.2812 - val_accuracy: 0.0000e+00 - val_precision: 0.9608\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(X, y, epochs=15, validation_data=(X, y))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec941cb8",
   "metadata": {},
   "source": [
    "## Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "83459562",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 4320x6480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "acc = history.history['accuracy']\n",
    "val_acc = history.history['val_accuracy']\n",
    "\n",
    "loss = history.history['loss']\n",
    "val_loss = history.history['val_loss']\n",
    "\n",
    "precision = history.history['precision']\n",
    "val_precision = history.history['val_precision']\n",
    "\n",
    "# precision = history.history['precision_4']\n",
    "# val_precision = history.history['val_precision_4']\n",
    "\n",
    "figure = plt.figure(figsize=(60, 90))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "760397be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Loss\n",
    "plt.plot(loss, label='Training Loss')\n",
    "plt.plot(val_loss, label='Validation Loss')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('Training and Validation Loss')\n",
    "plt.xlabel(\"epochs\")\n",
    "plt.ylabel(\"loss\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "77fb70af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Accuracy \n",
    "plt.plot(acc, label='Training Accuracy')\n",
    "plt.plot(val_acc, label='Validation Accuracy')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title('Training and Validation Accuracy')\n",
    "plt.xlabel(\"epochs\")\n",
    "plt.ylabel(\"accuracy\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "c113647d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Precision \n",
    "plt.plot(precision, label='Training Precision')\n",
    "plt.plot(val_precision, label='Validation Precision')\n",
    "plt.legend(loc='lower right')\n",
    "plt.title('Training and Validation Precision')\n",
    "plt.xlabel(\"epochs\")\n",
    "plt.ylabel(\"accuracy\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "6bf290ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "topics = chat_data_new.topics.unique().tolist()\n",
    "\n",
    "def predict_answer(query):\n",
    "    seqs = get_embeddings([query])\n",
    "    padded_seqs = pad_sequences(seqs, maxlen=128, padding='post')\n",
    "    prediction = model.predict(padded_seqs)\n",
    "    \n",
    "    topic_index = np.argmax(prediction)\n",
    "    \n",
    "    if topic_index > len(topics):\n",
    "        topic_index = len(topics) - 1\n",
    "    t = topics[topic_index]\n",
    "    \n",
    "    upper_bound = chat_data_new.groupby('topics').get_group(t).shape[0] # .get_group(output).shape[0]\n",
    "    r = np.random.randint(0,upper_bound)\n",
    "    responses = list(chat_data_new.groupby('topics').get_group(t).answerText)\n",
    "    print(responses[r])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "228461b5",
   "metadata": {},
   "source": [
    "### Sample query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "084ac568",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Given question: The Underlying Causes of Being Possessive\n",
      "\n",
      "\n",
      "Answer from the mode:\n",
      "1/1 [==============================] - 1s 872ms/step\n",
      "<p>I'm sorry you feel so alone and isolated, those feelings in and of themselves can lead to depression, stress and anxiety. &nbsp;So job one is finding someone you can talk to. &nbsp;A good friend or an open parent can be as helpful as a professional counselor, but if you don't have those, then by all means call your local Mental Health Association, suicide prevention, or go see your school counseling department. There are many of us now who do on-line, FaceTime, phone counseling so that is an option to consider in your situation. &nbsp;On the other hand, &nbsp;If you want to script a conversation with your parents (I'm a great believer in scripting) not that you're going to read it to them, but if you write down exactly what you want to say, read it over a few times before you're ready to have the conversation. &nbsp;Why? &nbsp;You'll be much more likely to do it if you're prepared, and you'll &nbsp;have a better chance of saying everything you want to say in a calm but forceful way. &nbsp;The same with your friends--you are probably a great listener and therefore attract people who want to talk--so you need to let these friends know you need something in return. &nbsp;If you practice asking for equal talk time, then perhaps these friends will respond and surprise you, or if you make those demands you'll start attracting people who are looking for equality in friendships. &nbsp;Now back to that script--first decide do you want to talk to both parents at once, or one at a time. &nbsp;Then begin to write down the points you want to make such as: &nbsp; I love you, and I know you love me but I don't feel as though I can trust your love to be unconditional enough to tell you who I really am, and how I really feel. &nbsp;Find your own words to describe your own feelings. &nbsp;If I can help, get in touch. You are right to reach out starting here, there are no prizes for suffering in silence and, as you already know, little joy in going it alone.&nbsp;</p>\n"
     ]
    }
   ],
   "source": [
    "query = 'The Underlying Causes of Being Possessive'\n",
    "\n",
    "print('Given question:', query)\n",
    "print('\\n')\n",
    "print('Answer from the mode:')\n",
    "predict_answer(query)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2067e7",
   "metadata": {},
   "source": [
    "## Real-time chatbot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4bcdd113",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter your query: The Underlying Causes of Being Possessive\n",
      "1/1 [==============================] - 0s 34ms/step\n",
      "<p>Hi there. Being 15 years old can be a very difficult time in your teenage life. I remember when I was 15 and how I often felt my parents weren’t listening to me. It’s even more difficult when you feel that you do not have a friend that you can confide in. </p><p>Having depression in the past and being able to get through it shows me that you can get through anything! Depression alone is a very difficult problem to work through. In addition to the communication problem with your parents, it appears that you are also struggling with stress and anxiety. We all have stress and anxiety in our lives. If we didn’t, none of us would be living. Anxiety &amp; stress keep us on our toes! Often, I have to remind myself of this as well. However, it is how we manage stress and anxiety, so it will not overcome our lives. </p><p>Are you familiar with relaxation techniques, such as: deep breathing exercises, meditation or yoga? Relaxation Techniques can help you tremendously in reducing your stress and anxiety. </p><p>Deep breathing exercises are helpful when you are on the go, such as school, shopping, out with friends or whatever extracurricular activities you engage in.  Most people do not take full advantage of their lung capacity. I know, that sounds silly. But, it’s true. You would be surprised how much air you lungs can hold. Imagine being in the Doctor’s office and taking deep breaths. This is what you want to do when you are feeling overwhelmed and/or stressed. Take a moment to take in at least 10 deep breaths and let them out slowly. You will be surprised how well you feel afterwards. </p><p>Meditation and Yoga are also healthy forms to working through stress and anxiety. You will need a quiet place for your meditation. You want to be “in the moment” and take in the peace and serenity. All it takes is a quiet place, closing your eyes and thinking of your “happy place.” Some people use meditation music as well. If you have access to this type of music and or the internet for more ways to practice meditation, please go for it! </p><p>Yoga on the other hand will take a little more work and practice. I would not suggest you learning this on your own, if you have never attempted yoga before. Find an experienced Yoga instructor to teach you the ropes and/or ask your school counselor about the possibility of getting someone to come to the school to teach the students. </p><p>Lastly, in regards to your parents it is very important to be able to have a relationship where you feel comfortable communicating. I would recommend writing a letter to them, if you are unable to express how you feel in person. A letter is more intimate and requires a little more effort on their end. If they are open on working on this relationship, maybe suggest family counseling to fully work on this issue.</p><p> I hope this was helpful for you and I wish you the best! </p>\n",
      "Enter your query: quit\n"
     ]
    }
   ],
   "source": [
    "while True:\n",
    "    \n",
    "    query = str(input('Enter your query: '))\n",
    "    query = query.strip().lower()\n",
    "    if query == 'quit':\n",
    "        break\n",
    "    \n",
    "    predict_answer(query)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7903c2d7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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