chatbot_project.ipynb

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        "# StackOverflow assistant bot\n",
        "\n",
        "The goal of this notebook is to help us construct a *dialogue chat bot*, which will be able to:\n",
        "\n",
        "* answer programming-related questions (using StackOverflow dataset);\n",
        "* chit-chat and simulate dialogue on all non programming-related questions.\n",
        "\n",
        "For a chit-chat mode we will use a pre-trained neural network engine available from [ChatterBot](https://github.com/gunthercox/ChatterBot).\n"
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        "! wget https://raw.githubusercontent.com/hse-aml/natural-language-processing/master/setup_google_colab.py -O setup_google_colab.py"
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      "execution_count": 0,
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            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2330 (2.3K) [text/plain]\n",
            "Saving to: ‘setup_google_colab.py’\n",
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        "import setup_google_colab"
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      "source": [
        "### Data description\n",
        "\n",
        "To detect *intent* of users questions we will need two text collections:\n",
        "- `tagged_posts.tsv` � StackOverflow posts, tagged with one programming language (*positive samples*).\n",
        "- `dialogues.tsv` � dialogue phrases from movie subtitles (*negative samples*).\n"
      ]
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 * Copyright (c) 2014 Dan Le Van
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    opacity: 0.6;
}

 .widget-text input[type="text"], .widget-text input[type="number"], .widget-textarea textarea {
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    border: 1px solid #9E9E9E;
    background-color: white;
    color: rgba(0, 0, 0, .8);
    font-size: 13px;
    padding: 4px 8px;
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    min-width: 0; /* This makes it possible for the flexbox to shrink this input */
    -ms-flex-negative: 1;
        flex-shrink: 1;
    outline: none !important;
}

 .widget-textarea textarea {
    height: inherit;
    width: inherit;
}

 .widget-text input:focus, .widget-textarea textarea:focus {
    border-color: #64B5F6;
}

 /* Widget Slider */

 .widget-slider .ui-slider {
    /* Slider Track */
    border: 1px solid #BDBDBD;
    background: #BDBDBD;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    position: relative;
    border-radius: 0px;
}

 .widget-slider .ui-slider .ui-slider-handle {
    /* Slider Handle */
    outline: none !important; /* focused slider handles are colored - see below */
    position: absolute;
    background-color: white;
    border: 1px solid #9E9E9E;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    z-index: 1;
    background-image: none; /* Override jquery-ui */
}

 /* Override jquery-ui */

 .widget-slider .ui-slider .ui-slider-handle:hover, .widget-slider .ui-slider .ui-slider-handle:focus {
    background-color: #2196F3;
    border: 1px solid #2196F3;
}

 .widget-slider .ui-slider .ui-slider-handle:active {
    background-color: #2196F3;
    border-color: #2196F3;
    z-index: 2;
    -webkit-transform: scale(1.2);
            transform: scale(1.2);
}

 .widget-slider  .ui-slider .ui-slider-range {
    /* Interval between the two specified value of a double slider */
    position: absolute;
    background: #2196F3;
    z-index: 0;
}

 /* Shapes of Slider Handles */

 .widget-hslider .ui-slider .ui-slider-handle {
    width: 16px;
    height: 16px;
    margin-top: -7px;
    margin-left: -7px;
    border-radius: 50%;
    top: 0;
}

 .widget-vslider .ui-slider .ui-slider-handle {
    width: 16px;
    height: 16px;
    margin-bottom: -7px;
    margin-left: -7px;
    border-radius: 50%;
    left: 0;
}

 .widget-hslider .ui-slider .ui-slider-range {
    height: 8px;
    margin-top: -3px;
}

 .widget-vslider .ui-slider .ui-slider-range {
    width: 8px;
    margin-left: -3px;
}

 /* Horizontal Slider */

 .widget-hslider {
    width: 300px;
    height: 28px;
    line-height: 28px;

    /* Override the align-items baseline. This way, the description and readout
    still seem to align their baseline properly, and we don't have to have
    align-self: stretch in the .slider-container. */
    -webkit-box-align: center;
        -ms-flex-align: center;
            align-items: center;
}

 .widgets-slider .slider-container {
    overflow: visible;
}

 .widget-hslider .slider-container {
    height: 28px;
    margin-left: 6px;
    margin-right: 6px;
    -webkit-box-flex: 1;
        -ms-flex: 1 1 148px;
            flex: 1 1 148px;
}

 .widget-hslider .ui-slider {
    /* Inner, invisible slide div */
    height: 4px;
    margin-top: 12px;
    width: 100%;
}

 /* Vertical Slider */

 .widget-vbox .widget-label {
    height: 28px;
    line-height: 28px;
}

 .widget-vslider {
    /* Vertical Slider */
    height: 200px;
    width: 72px;
}

 .widget-vslider .slider-container {
    -webkit-box-flex: 1;
        -ms-flex: 1 1 148px;
            flex: 1 1 148px;
    margin-left: auto;
    margin-right: auto;
    margin-bottom: 6px;
    margin-top: 6px;
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-orient: vertical;
    -webkit-box-direction: normal;
        -ms-flex-direction: column;
            flex-direction: column;
}

 .widget-vslider .ui-slider-vertical {
    /* Inner, invisible slide div */
    width: 4px;
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    margin-left: auto;
    margin-right: auto;
}

 /* Widget Progress Styling */

 .progress-bar {
    -webkit-transition: none;
    transition: none;
}

 .progress-bar {
    height: 28px;
}

 .progress-bar {
    background-color: #2196F3;
}

 .progress-bar-success {
    background-color: #4CAF50;
}

 .progress-bar-info {
    background-color: #00BCD4;
}

 .progress-bar-warning {
    background-color: #FF9800;
}

 .progress-bar-danger {
    background-color: #F44336;
}

 .progress {
    background-color: #EEEEEE;
    border: none;
    -webkit-box-shadow: none;
            box-shadow: none;
}

 /* Horisontal Progress */

 .widget-hprogress {
    /* Progress Bar */
    height: 28px;
    line-height: 28px;
    width: 300px;
    -webkit-box-align: center;
        -ms-flex-align: center;
            align-items: center;

}

 .widget-hprogress .progress {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    margin-top: 4px;
    margin-bottom: 4px;
    -ms-flex-item-align: stretch;
        align-self: stretch;
    /* Override bootstrap style */
    height: auto;
    height: initial;
}

 /* Vertical Progress */

 .widget-vprogress {
    height: 200px;
    width: 72px;
}

 .widget-vprogress .progress {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    width: 20px;
    margin-left: auto;
    margin-right: auto;
    margin-bottom: 0;
}

 /* Select Widget Styling */

 .widget-dropdown {
    height: 28px;
    width: 300px;
    line-height: 28px;
}

 .widget-dropdown > select {
    padding-right: 20px;
    border: 1px solid #9E9E9E;
    border-radius: 0;
    height: inherit;
    -webkit-box-flex: 1;
        -ms-flex: 1 1 148px;
            flex: 1 1 148px;
    min-width: 0; /* This makes it possible for the flexbox to shrink this input */
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    outline: none !important;
    -webkit-box-shadow: none;
            box-shadow: none;
    background-color: white;
    color: rgba(0, 0, 0, .8);
    font-size: 13px;
    vertical-align: top;
    padding-left: 8px;
	appearance: none;
	-webkit-appearance: none;
	-moz-appearance: none;
    background-repeat: no-repeat;
	background-size: 20px;
	background-position: right center;
    background-image: url("data:image/svg+xml;base64,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");
}

 .widget-dropdown > select:focus {
    border-color: #64B5F6;
}

 .widget-dropdown > select:disabled {
    opacity: 0.6;
}

 /* To disable the dotted border in Firefox around select controls.
   See http://stackoverflow.com/a/18853002 */

 .widget-dropdown > select:-moz-focusring {
    color: transparent;
    text-shadow: 0 0 0 #000;
}

 /* Select and SelectMultiple */

 .widget-select {
    width: 300px;
    line-height: 28px;

    /* Because Firefox defines the baseline of a select as the bottom of the
    control, we align the entire control to the top and add padding to the
    select to get an approximate first line baseline alignment. */
    -webkit-box-align: start;
        -ms-flex-align: start;
            align-items: flex-start;
}

 .widget-select > select {
    border: 1px solid #9E9E9E;
    background-color: white;
    color: rgba(0, 0, 0, .8);
    font-size: 13px;
    -webkit-box-flex: 1;
        -ms-flex: 1 1 148px;
            flex: 1 1 148px;
    outline: none !important;
    overflow: auto;
    height: inherit;

    /* Because Firefox defines the baseline of a select as the bottom of the
    control, we align the entire control to the top and add padding to the
    select to get an approximate first line baseline alignment. */
    padding-top: 5px;
}

 .widget-select > select:focus {
    border-color: #64B5F6;
}

 .wiget-select > select > option {
    padding-left: 4px;
    line-height: 28px;
    /* line-height doesn't work on some browsers for select options */
    padding-top: calc(28px - var(--jp-widgets-font-size) / 2);
    padding-bottom: calc(28px - var(--jp-widgets-font-size) / 2);
}

 /* Toggle Buttons Styling */

 .widget-toggle-buttons {
    line-height: 28px;
}

 .widget-toggle-buttons .widget-toggle-button {
    margin-left: 2px;
    margin-right: 2px;
}

 .widget-toggle-buttons .jupyter-button:disabled {
    opacity: 0.6;
}

 /* Radio Buttons Styling */

 .widget-radio {
    width: 300px;
    line-height: 28px;
}

 .widget-radio-box {
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-orient: vertical;
    -webkit-box-direction: normal;
        -ms-flex-direction: column;
            flex-direction: column;
    -webkit-box-align: stretch;
        -ms-flex-align: stretch;
            align-items: stretch;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    margin-bottom: 8px;
}

 .widget-radio-box label {
    height: 20px;
    line-height: 20px;
    font-size: 13px;
}

 .widget-radio-box input {
    height: 20px;
    line-height: 20px;
    margin: 0 8px 0 1px;
    float: left;
}

 /* Color Picker Styling */

 .widget-colorpicker {
    width: 300px;
    height: 28px;
    line-height: 28px;
}

 .widget-colorpicker > .widget-colorpicker-input {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    -ms-flex-negative: 1;
        flex-shrink: 1;
    min-width: 72px;
}

 .widget-colorpicker input[type="color"] {
    width: 28px;
    height: 28px;
    padding: 0 2px; /* make the color square actually square on Chrome on OS X */
    background: white;
    color: rgba(0, 0, 0, .8);
    border: 1px solid #9E9E9E;
    border-left: none;
    -webkit-box-flex: 0;
        -ms-flex-positive: 0;
            flex-grow: 0;
    -ms-flex-negative: 0;
        flex-shrink: 0;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    -ms-flex-item-align: stretch;
        align-self: stretch;
    outline: none !important;
}

 .widget-colorpicker.concise input[type="color"] {
    border-left: 1px solid #9E9E9E;
}

 .widget-colorpicker input[type="color"]:focus, .widget-colorpicker input[type="text"]:focus {
    border-color: #64B5F6;
}

 .widget-colorpicker input[type="text"] {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    outline: none !important;
    height: 28px;
    line-height: 28px;
    background: white;
    color: rgba(0, 0, 0, .8);
    border: 1px solid #9E9E9E;
    font-size: 13px;
    padding: 4px 8px;
    min-width: 0; /* This makes it possible for the flexbox to shrink this input */
    -ms-flex-negative: 1;
        flex-shrink: 1;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
}

 .widget-colorpicker input[type="text"]:disabled {
    opacity: 0.6;
}

 /* Date Picker Styling */

 .widget-datepicker {
    width: 300px;
    height: 28px;
    line-height: 28px;
}

 .widget-datepicker input[type="date"] {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    -ms-flex-negative: 1;
        flex-shrink: 1;
    min-width: 0; /* This makes it possible for the flexbox to shrink this input */
    outline: none !important;
    height: 28px;
    border: 1px solid #9E9E9E;
    background-color: white;
    color: rgba(0, 0, 0, .8);
    font-size: 13px;
    padding: 4px 8px;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
}

 .widget-datepicker input[type="date"]:focus {
    border-color: #64B5F6;
}

 .widget-datepicker input[type="date"]:invalid {
    border-color: #FF9800;
}

 .widget-datepicker input[type="date"]:disabled {
    opacity: 0.6;
}

 /* Play Widget */

 .widget-play {
    width: 148px;
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-align: stretch;
        -ms-flex-align: stretch;
            align-items: stretch;
}

 .widget-play .jupyter-button {
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    height: auto;
}

 .widget-play .jupyter-button:disabled {
    opacity: 0.6;
}

 /* Tab Widget */

 .jupyter-widgets.widget-tab {
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-orient: vertical;
    -webkit-box-direction: normal;
        -ms-flex-direction: column;
            flex-direction: column;
}

 .jupyter-widgets.widget-tab > .p-TabBar {
    /* Necessary so that a tab can be shifted down to overlay the border of the box below. */
    overflow-x: visible;
    overflow-y: visible;
}

 .jupyter-widgets.widget-tab > .p-TabBar > .p-TabBar-content {
    /* Make sure that the tab grows from bottom up */
    -webkit-box-align: end;
        -ms-flex-align: end;
            align-items: flex-end;
    min-width: 0;
    min-height: 0;
}

 .jupyter-widgets.widget-tab > .widget-tab-contents {
    width: 100%;
    -webkit-box-sizing: border-box;
            box-sizing: border-box;
    margin: 0;
    background: white;
    color: rgba(0, 0, 0, .8);
    border: 1px solid #9E9E9E;
    padding: 15px;
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    overflow: auto;
}

 .jupyter-widgets.widget-tab > .p-TabBar {
    font: 13px Helvetica, Arial, sans-serif;
    min-height: 25px;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tab {
    -webkit-box-flex: 0;
        -ms-flex: 0 1 144px;
            flex: 0 1 144px;
    min-width: 35px;
    min-height: 25px;
    line-height: 24px;
    margin-left: -1px;
    padding: 0px 10px;
    background: #EEEEEE;
    color: rgba(0, 0, 0, .5);
    border: 1px solid #9E9E9E;
    border-bottom: none;
    position: relative;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tab.p-mod-current {
    color: rgba(0, 0, 0, 1.0);
    /* We want the background to match the tab content background */
    background: white;
    min-height: 26px;
    -webkit-transform: translateY(1px);
            transform: translateY(1px);
    overflow: visible;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tab.p-mod-current:before {
    position: absolute;
    top: -1px;
    left: -1px;
    content: '';
    height: 2px;
    width: calc(100% + 2px);
    background: #2196F3;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tab:first-child {
    margin-left: 0;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tab:hover:not(.p-mod-current) {
    background: white;
    color: rgba(0, 0, 0, .8);
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-mod-closable > .p-TabBar-tabCloseIcon {
    margin-left: 4px;
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-mod-closable > .p-TabBar-tabCloseIcon:before {
    font-family: FontAwesome;
    content: '\f00d'; /* close */
}

 .jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tabIcon,
.jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tabLabel,
.jupyter-widgets.widget-tab > .p-TabBar .p-TabBar-tabCloseIcon {
    line-height: 24px;
}

 /* Accordion Widget */

 .p-Collapse {
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-orient: vertical;
    -webkit-box-direction: normal;
        -ms-flex-direction: column;
            flex-direction: column;
    -webkit-box-align: stretch;
        -ms-flex-align: stretch;
            align-items: stretch;
}

 .p-Collapse-header {
    padding: 4px;
    cursor: pointer;
    color: rgba(0, 0, 0, .5);
    background-color: #EEEEEE;
    border: 1px solid #9E9E9E;
    padding: 10px 15px;
    font-weight: bold;
}

 .p-Collapse-header:hover {
    background-color: white;
    color: rgba(0, 0, 0, .8);
}

 .p-Collapse-open > .p-Collapse-header {
    background-color: white;
    color: rgba(0, 0, 0, 1.0);
    cursor: default;
    border-bottom: none;
}

 .p-Collapse .p-Collapse-header::before {
    content: '\f0da\00A0';  /* caret-right, non-breaking space */
    display: inline-block;
    font: normal normal normal 14px/1 FontAwesome;
    font-size: inherit;
    text-rendering: auto;
    -webkit-font-smoothing: antialiased;
    -moz-osx-font-smoothing: grayscale;
}

 .p-Collapse-open > .p-Collapse-header::before {
    content: '\f0d7\00A0'; /* caret-down, non-breaking space */
}

 .p-Collapse-contents {
    padding: 15px;
    background-color: white;
    color: rgba(0, 0, 0, .8);
    border-left: 1px solid #9E9E9E;
    border-right: 1px solid #9E9E9E;
    border-bottom: 1px solid #9E9E9E;
    overflow: auto;
}

 .p-Accordion {
    display: -webkit-box;
    display: -ms-flexbox;
    display: flex;
    -webkit-box-orient: vertical;
    -webkit-box-direction: normal;
        -ms-flex-direction: column;
            flex-direction: column;
    -webkit-box-align: stretch;
        -ms-flex-align: stretch;
            align-items: stretch;
}

 .p-Accordion .p-Collapse {
    margin-bottom: 0;
}

 .p-Accordion .p-Collapse + .p-Collapse {
    margin-top: 4px;
}

 /* HTML widget */

 .widget-html, .widget-htmlmath {
    font-size: 13px;
}

 .widget-html > .widget-html-content, .widget-htmlmath > .widget-html-content {
    /* Fill out the area in the HTML widget */
    -ms-flex-item-align: stretch;
        align-self: stretch;
    -webkit-box-flex: 1;
        -ms-flex-positive: 1;
            flex-grow: 1;
    -ms-flex-negative: 1;
        flex-shrink: 1;
    /* Makes sure the baseline is still aligned with other elements */
    line-height: 28px;
    /* Make it possible to have absolutely-positioned elements in the html */
    position: relative;
}

/*# 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 */",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "text/css"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 116
        }
      },
      "source": [
        "import sys\n",
        "sys.path.append(\"..\")\n",
        "from common.download_utils import download_project_resources\n",
        "\n",
        "download_project_resources()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "060e33cb934243329aed277f74921afd",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=18012894), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "aee3ea543c8040b59ddf396d16bad197",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=145677870), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wLi4N0WuRBLr",
        "colab_type": "text"
      },
      "source": [
        "For those questions, that have programming-related intent, we will proceed as follow predict programming language (only one tag per question allowed here) and rank candidates within the tag using embeddings.\n",
        "For the ranking part, you will need:\n",
        "- `word_embeddings.tsv` � word embeddings, that are trained with StarSpace."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MsM2UdfNRBLs",
        "colab_type": "text"
      },
      "source": [
        "As a result of this notebook, you should obtain the following new objects that you will then use in the running bot:\n",
        "\n",
        "- `intent_recognizer.pkl` � intent recognition model;\n",
        "- `tag_classifier.pkl` � programming language classification model;\n",
        "- `tfidf_vectorizer.pkl` � vectorizer used during training;\n",
        "- `thread_embeddings_by_tags` � folder with thread embeddings, arranged by tags.\n",
        "    "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KpD4_1zeRBLt",
        "colab_type": "text"
      },
      "source": [
        "Some functions will be reused by this notebook and the scripts, so we put them into *utils.py* file. Don't forget to open it and fill in the gaps!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WM4gfenvb4Qr",
        "colab_type": "code",
        "outputId": "05f4981f-6c50-498f-b721-902a79abf937",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        }
      },
      "source": [
        "!ls"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "boost_1_63_0.zip  dialogue_manager.py  sample_data\t      utils.py\n",
            "common\t\t  main_bot.py\t       setup_google_colab.py\n",
            "data\t\t  __pycache__\t       Starspace\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hebjNMwP9Fyu",
        "colab_type": "code",
        "outputId": "7225e246-ba5d-4bc7-886a-70c412a67979",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "!ls data"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "dialogues.tsv  tagged_posts.tsv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oS_K0aFCncrz",
        "colab_type": "code",
        "outputId": "1b008f0c-621e-4dae-8a8c-d237dd28e856",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        }
      },
      "source": [
        "! pip install pydrive\n",
        "from pydrive.auth import GoogleAuth\n",
        "from pydrive.drive import GoogleDrive \n",
        "from google.colab import auth \n",
        "from oauth2client.client import GoogleCredentials\n",
        "# 1. Authenticate and create the PyDrive client.\n",
        "auth.authenticate_user()\n",
        "gauth = GoogleAuth()\n",
        "gauth.credentials = GoogleCredentials.get_application_default()\n",
        "drive = GoogleDrive(gauth)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pydrive\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/52/e0/0e64788e5dd58ce2d6934549676243dc69d982f198524be9b99e9c2a4fd5/PyDrive-1.3.1.tar.gz (987kB)\n",
            "\u001b[K    100% |████████████████████████████████| 993kB 20.7MB/s \n",
            "\u001b[?25hRequirement already satisfied: google-api-python-client>=1.2 in /usr/local/lib/python3.6/dist-packages (from pydrive) (1.6.7)\n",
            "Requirement already satisfied: oauth2client>=4.0.0 in /usr/local/lib/python3.6/dist-packages (from pydrive) (4.1.3)\n",
            "Requirement already satisfied: PyYAML>=3.0 in /usr/local/lib/python3.6/dist-packages (from pydrive) (3.13)\n",
            "Requirement already satisfied: six<2dev,>=1.6.1 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client>=1.2->pydrive) (1.11.0)\n",
            "Requirement already satisfied: uritemplate<4dev,>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client>=1.2->pydrive) (3.0.0)\n",
            "Requirement already satisfied: httplib2<1dev,>=0.9.2 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client>=1.2->pydrive) (0.11.3)\n",
            "Requirement already satisfied: pyasn1>=0.1.7 in /usr/local/lib/python3.6/dist-packages (from oauth2client>=4.0.0->pydrive) (0.4.5)\n",
            "Requirement already satisfied: rsa>=3.1.4 in /usr/local/lib/python3.6/dist-packages (from oauth2client>=4.0.0->pydrive) (4.0)\n",
            "Requirement already satisfied: pyasn1-modules>=0.0.5 in /usr/local/lib/python3.6/dist-packages (from oauth2client>=4.0.0->pydrive) (0.2.4)\n",
            "Building wheels for collected packages: pydrive\n",
            "  Building wheel for pydrive (setup.py) ... \u001b[?25ldone\n",
            "\u001b[?25h  Stored in directory: /root/.cache/pip/wheels/fa/d2/9a/d3b6b506c2da98289e5d417215ce34b696db856643bad779f4\n",
            "Successfully built pydrive\n",
            "Installing collected packages: pydrive\n",
            "Successfully installed pydrive-1.3.1\n",
            "\n",
            "WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
            "For more information, please see:\n",
            "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
            "  * https://github.com/tensorflow/addons\n",
            "If you depend on functionality not listed there, please file an issue.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PPkubBXoXYXP",
        "colab_type": "text"
      },
      "source": [
        "### Downloading starspace embeddings generated earlier specifically from the dataset containing stackoverflow posts. Refer the notebook Starspace_embeddings_Stackoverflow.ipynb"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AQaIsrQrngNW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "downloaded = drive.CreateFile({'id': '1fl64k63LFUOuMZKxGzE1KVvMT5nwmlOU'})\n",
        "downloaded.GetContentFile('my_starspace_embeddings_0612.tsv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DPoEaSpCnlQd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "cp my_starspace_embeddings_0612.tsv data/word_embeddings.tsv"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LnLL5uqSEX6N",
        "colab_type": "text"
      },
      "source": [
        "**We need to update utils.py. So here i am removing utils.py downloaded from project resources and uploading my utils.py \"updated\" with necessary functions!!!**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jJ3hya2Rnred",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!rm utils.py"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8ir2njeKn7eI",
        "colab_type": "code",
        "outputId": "e5557148-fc04-44d8-e389-1ab0234363c9",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 112
        }
      },
      "source": [
        "from google.colab import files\n",
        "files.upload() "
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-1ca80913-eaf3-4587-9049-b825d2d0b4c0\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-1ca80913-eaf3-4587-9049-b825d2d0b4c0\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving utils.py to utils.py\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'utils.py': b'\\nimport nltk\\nimport pickle\\nimport re\\nimport numpy as np\\n\\nnltk.download(\\'stopwords\\')\\nfrom nltk.corpus import stopwords\\n\\n# Paths for all resources for the bot.\\nRESOURCE_PATH = {\\n    \\'INTENT_RECOGNIZER\\': \\'intent_recognizer.pkl\\',\\n    \\'TAG_CLASSIFIER\\': \\'tag_classifier.pkl\\',\\n    \\'TFIDF_VECTORIZER\\': \\'tfidf_vectorizer.pkl\\',\\n    \\'THREAD_EMBEDDINGS_FOLDER\\': \\'thread_embeddings_by_tags\\',\\n    \\'WORD_EMBEDDINGS\\': \\'word_embeddings.tsv\\',\\n}\\n\\n\\ndef text_prepare(text):\\n    \"\"\"Performs tokenization and simple preprocessing.\"\"\"\\n    \\n    replace_by_space_re = re.compile(\\'[/(){}\\\\[\\\\]\\\\|@,;]\\')\\n    bad_symbols_re = re.compile(\\'[^0-9a-z #+_]\\')\\n    stopwords_set = set(stopwords.words(\\'english\\'))\\n\\n    text = text.lower()\\n    text = replace_by_space_re.sub(\\' \\', text)\\n    text = bad_symbols_re.sub(\\'\\', text)\\n    text = \\' \\'.join([x for x in text.split() if x and x not in stopwords_set])\\n\\n    return text.strip()\\n\\n\\ndef load_embeddings(embeddings_path):\\n    \"\"\"Loads pre-trained word embeddings from tsv file.\\n\\n    Args:\\n      embeddings_path - path to the embeddings file.\\n\\n    Returns:\\n      embeddings - dict mapping words to vectors;\\n      embeddings_dim - dimension of the vectors.\\n    \"\"\"\\n    \\n    # Hint: you have already implemented a similar routine in the 3rd assignment.\\n    # Note that here you also need to know the dimension of the loaded embeddings.\\n    # When you load the embeddings, use numpy.float32 type as dtype\\n\\n    ########################\\n    #### YOUR CODE HERE ####\\n    starspace_embeddings={}\\n    for line in open(embeddings_path):\\n      li = line.strip().split(\\'\\\\t\\')\\n      if li[0] not in starspace_embeddings:\\n        starspace_embeddings[li[0]] = np.array(li[1:], dtype=np.float32)\\n    ########################\\n    embeddings_dim=list(starspace_embeddings[list(starspace_embeddings.keys())[250]].shape)[0]\\n    \\n    return starspace_embeddings, embeddings_dim\\n\\ndef question_to_vec(question, embeddings, dim):\\n    \"\"\"Transforms a string to an embedding by averaging word embeddings.\"\"\"\\n    \\n    # Hint: you have already implemented exactly this function in the 3rd assignment.\\n\\n    ########################\\n    #### YOUR CODE HERE ####\\n    \"\"\"\\n        question: a string\\n        embeddings: dict where the key is a word and a value is its\\' embedding\\n        dim: size of the representation\\n\\n        result: vector representation for the question\\n    \"\"\"\\n    ######################################\\n    ######### YOUR CODE HERE #############\\n    ######################################\\n    ans=np.zeros((dim,))\\n    new_vector =  []\\n    counter = 0\\n    my_word_list = question.split()\\n    for x in range(len(my_word_list)):\\n      if my_word_list[x] in embeddings:\\n        counter += 1\\n        new_vector.append(list(embeddings[my_word_list[x]]))\\n        \\n    if counter != 0:\\n      ans=np.mean(new_vector,axis=0)\\n    \\n    return ans\\n    ########################\\n\\n    \\n\\ndef unpickle_file(filename):\\n    \"\"\"Returns the result of unpickling the file content.\"\"\"\\n    with open(filename, \\'rb\\') as f:\\n        return pickle.load(f)'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dMB6ERNoRBLu",
        "colab_type": "code",
        "outputId": "75f90cde-738e-4041-d17e-2f41bf72f0a5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "from utils import *"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s4pxV5wLBCvv",
        "colab_type": "code",
        "outputId": "e0b9ea97-7b2a-4eb3-848f-d66b159b0069",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 86
        }
      },
      "source": [
        "!ls"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "adc.json\t  dialogue_manager.py\t\t    sample_data\n",
            "boost_1_63_0.zip  main_bot.py\t\t\t    setup_google_colab.py\n",
            "common\t\t  my_starspace_embeddings_0612.tsv  Starspace\n",
            "data\t\t  __pycache__\t\t\t    utils.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pi397t8nBZhM",
        "colab_type": "code",
        "outputId": "4a34204c-ee28-4af0-effe-785e5baf8b5a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "!ls data"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "dialogues.tsv  tagged_posts.tsv  word_embeddings.tsv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mM9LnJT5RBLy",
        "colab_type": "text"
      },
      "source": [
        "## Part I. Intent and language recognition"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-Dqi3vmBRBLy",
        "colab_type": "text"
      },
      "source": [
        "We want to write a bot, which will not only **answer programming-related questions**, but also will be able to **maintain a dialogue**. We would also like to detect the *intent* of the user from the question (we could have had a 'Question answering mode' check-box in the bot, but it wouldn't fun at all, would it?). So the first thing we need to do is to **distinguish programming-related questions from general ones**.\n",
        "\n",
        "It would also be good to predict which programming language a particular question referees to. By doing so, we will speed up question search by a factor of the number of languages (10 here), and exercise our *text classification* skill a bit. :)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IT4ehbI4RBL0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import pickle\n",
        "import re\n",
        "\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZhjRXZADRBL4",
        "colab_type": "text"
      },
      "source": [
        "### Data preparation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OEj3pkjcRBL4",
        "colab_type": "text"
      },
      "source": [
        "In the first assignment (Predict tags on StackOverflow with linear models), you have already learnt how to preprocess texts and do TF-IDF tranformations. Reuse your code here. In addition, you will also need to [dump](https://docs.python.org/3/library/pickle.html#pickle.dump) the TF-IDF vectorizer with pickle to use it later in the running bot."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UpSpE358RBL5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def tfidf_features(X_train, X_test, vectorizer_path):\n",
        "    \"\"\"Performs TF-IDF transformation and dumps the model.\"\"\"\n",
        "    \n",
        "    # Train a vectorizer on X_train data.\n",
        "    # Transform X_train and X_test data.\n",
        "    \n",
        "    # Pickle the trained vectorizer to 'vectorizer_path'\n",
        "    # Don't forget to open the file in writing bytes mode.\n",
        "    \n",
        "    ######################################\n",
        "    ######### YOUR CODE HERE #############\n",
        "    tfidf_vectorizer = TfidfVectorizer(min_df=5, max_df=0.9, token_pattern = '(\\S+)', ngram_range=(1, 2))\n",
        "    X_train = tfidf_vectorizer.fit_transform(X_train)\n",
        "    ######################################\n",
        "    \n",
        "    X_test = tfidf_vectorizer.transform(X_test)\n",
        "    ######################################\n",
        "    \n",
        "    file_Name = vectorizer_path\n",
        "    # open the file for writing\n",
        "    fileObject = open(file_Name,'wb') \n",
        "\n",
        "    # this writes the object a to the\n",
        "    # file named 'testfile'\n",
        "    pickle.dump(tfidf_vectorizer,fileObject)   \n",
        "\n",
        "    # here we close the fileObject\n",
        "    fileObject.close()\n",
        "    \n",
        "    ######################################\n",
        "    \n",
        "    return X_train, X_test"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "54S66FIwRBL8",
        "colab_type": "text"
      },
      "source": [
        "Now, load examples of two classes. Use a subsample of stackoverflow data to balance the classes. You will need the full data later."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zu0wqq1cRBL9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sample_size = 200000\n",
        "\n",
        "dialogue_df = pd.read_csv('data/dialogues.tsv', sep='\\t').sample(sample_size, random_state=0)\n",
        "stackoverflow_df = pd.read_csv('data/tagged_posts.tsv', sep='\\t').sample(sample_size, random_state=0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ftzmmx5FRBMB",
        "colab_type": "text"
      },
      "source": [
        "Check how the data look like:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hMK1lTDpRBMD",
        "colab_type": "code",
        "outputId": "7810f05f-69be-487d-f876-1c4497797018",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "dialogue_df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>text</th>\n",
              "      <th>tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>82925</th>\n",
              "      <td>Donna, you are a muffin.</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48774</th>\n",
              "      <td>He was here last night till about two o'clock....</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55394</th>\n",
              "      <td>All right, then make an appointment with her s...</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90806</th>\n",
              "      <td>Hey, what is this-an interview? We're supposed...</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107758</th>\n",
              "      <td>Yeah. He's just a friend of mine I was trying ...</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                     text       tag\n",
              "82925                            Donna, you are a muffin.  dialogue\n",
              "48774   He was here last night till about two o'clock....  dialogue\n",
              "55394   All right, then make an appointment with her s...  dialogue\n",
              "90806   Hey, what is this-an interview? We're supposed...  dialogue\n",
              "107758  Yeah. He's just a friend of mine I was trying ...  dialogue"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HlFCSTARRBMG",
        "colab_type": "code",
        "outputId": "57178987-a914-4896-eff6-6ce74a5409b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "stackoverflow_df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>tag</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2168983</th>\n",
              "      <td>43837842</td>\n",
              "      <td>Efficient Algorithm to compose valid expressio...</td>\n",
              "      <td>python</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1084095</th>\n",
              "      <td>15747223</td>\n",
              "      <td>Why does this basic thread program fail with C...</td>\n",
              "      <td>c_cpp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1049020</th>\n",
              "      <td>15189594</td>\n",
              "      <td>Link to scroll to top not working</td>\n",
              "      <td>javascript</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200466</th>\n",
              "      <td>3273927</td>\n",
              "      <td>Is it possible to implement ping on windows ph...</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1200249</th>\n",
              "      <td>17684551</td>\n",
              "      <td>GLSL normal mapping issue</td>\n",
              "      <td>c_cpp</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          post_id                                              title  \\\n",
              "2168983  43837842  Efficient Algorithm to compose valid expressio...   \n",
              "1084095  15747223  Why does this basic thread program fail with C...   \n",
              "1049020  15189594                  Link to scroll to top not working   \n",
              "200466    3273927  Is it possible to implement ping on windows ph...   \n",
              "1200249  17684551                          GLSL normal mapping issue   \n",
              "\n",
              "                tag  \n",
              "2168983      python  \n",
              "1084095       c_cpp  \n",
              "1049020  javascript  \n",
              "200466           c#  \n",
              "1200249       c_cpp  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FXQZlDjKRBMJ",
        "colab_type": "text"
      },
      "source": [
        "Apply *text_prepare* function to preprocess the data:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pI57xaakRBMK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from utils import text_prepare"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WdPpH_p-RBMN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dialogue_df['text'] = [text_prepare(x) for x in list(dialogue_df['text'])]\n",
        "stackoverflow_df['title'] = [text_prepare(x) for x in list(stackoverflow_df['title'])]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uij8nUFgb0ix",
        "colab_type": "code",
        "outputId": "86e6a3d6-f856-4a41-8d02-fd933263155f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "dialogue_df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\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>text</th>\n",
              "      <th>tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>82925</th>\n",
              "      <td>donna muffin</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48774</th>\n",
              "      <td>last night till two oclock hear really got stu...</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55394</th>\n",
              "      <td>right make appointment see</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90806</th>\n",
              "      <td>hey thisan interview supposed making love</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>107758</th>\n",
              "      <td>yeah hes friend mine trying help</td>\n",
              "      <td>dialogue</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                     text       tag\n",
              "82925                                        donna muffin  dialogue\n",
              "48774   last night till two oclock hear really got stu...  dialogue\n",
              "55394                          right make appointment see  dialogue\n",
              "90806           hey thisan interview supposed making love  dialogue\n",
              "107758                   yeah hes friend mine trying help  dialogue"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gmeIAiNOb6g3",
        "colab_type": "code",
        "outputId": "d86934b1-ed3b-45d4-d1c5-d56fff0e3c21",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "stackoverflow_df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>post_id</th>\n",
              "      <th>title</th>\n",
              "      <th>tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2168983</th>\n",
              "      <td>43837842</td>\n",
              "      <td>efficient algorithm compose valid expressions ...</td>\n",
              "      <td>python</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1084095</th>\n",
              "      <td>15747223</td>\n",
              "      <td>basic thread program fail clang pass g++</td>\n",
              "      <td>c_cpp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1049020</th>\n",
              "      <td>15189594</td>\n",
              "      <td>link scroll top working</td>\n",
              "      <td>javascript</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200466</th>\n",
              "      <td>3273927</td>\n",
              "      <td>possible implement ping windows phone 7</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1200249</th>\n",
              "      <td>17684551</td>\n",
              "      <td>glsl normal mapping issue</td>\n",
              "      <td>c_cpp</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          post_id                                              title  \\\n",
              "2168983  43837842  efficient algorithm compose valid expressions ...   \n",
              "1084095  15747223           basic thread program fail clang pass g++   \n",
              "1049020  15189594                            link scroll top working   \n",
              "200466    3273927            possible implement ping windows phone 7   \n",
              "1200249  17684551                          glsl normal mapping issue   \n",
              "\n",
              "                tag  \n",
              "2168983      python  \n",
              "1084095       c_cpp  \n",
              "1049020  javascript  \n",
              "200466           c#  \n",
              "1200249       c_cpp  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B1skeW8wRBMP",
        "colab_type": "text"
      },
      "source": [
        "### Intent recognition"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TmTSSgRHRBMR",
        "colab_type": "text"
      },
      "source": [
        "We will do a binary classification on TF-IDF representations of texts. Labels will be either `dialogue` for general questions or `stackoverflow` for programming-related questions. First, prepare the data for this task:\n",
        "- concatenate `dialogue` and `stackoverflow` examples into one sample\n",
        "- split it into train and test in proportion 9:1, use *random_state=0* for reproducibility\n",
        "- transform it into TF-IDF features"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CjiGhppWRBMS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jZeG5JBuRBMV",
        "colab_type": "code",
        "outputId": "117bfcd2-8999-46e1-b478-423b18ccd2a6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "X = np.concatenate([dialogue_df['text'].values, stackoverflow_df['title'].values])\n",
        "y = ['dialogue'] * dialogue_df.shape[0] + ['stackoverflow'] * stackoverflow_df.shape[0]\n",
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=0)\n",
        "print('Train size = {}, test size = {}'.format(len(X_train), len(X_test)))\n",
        "\n",
        "X_train_tfidf, X_test_tfidf = tfidf_features(X_train, X_test, RESOURCE_PATH['TFIDF_VECTORIZER'])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train size = 360000, test size = 40000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "scJD2N59RBMZ",
        "colab_type": "text"
      },
      "source": [
        "Train the **intent recognizer** using LogisticRegression on the train set with the following parameters: *penalty='l2'*, *C=10*, *random_state=0*. Print out the accuracy on the test set to check whether everything looks good."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O47N32u5RBMb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6bppcP_6RBMg",
        "colab_type": "code",
        "outputId": "041caa69-b3fe-4909-981d-4199ef3290b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        }
      },
      "source": [
        "######################################\n",
        "intent_recognizer = LogisticRegression(penalty='l2', C=10, random_state=0)\n",
        "intent_recognizer.fit(X_train_tfidf, y_train)\n",
        "######################################"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LogisticRegression(C=10, class_weight=None, dual=False, fit_intercept=True,\n",
              "          intercept_scaling=1, max_iter=100, multi_class='warn',\n",
              "          n_jobs=None, penalty='l2', random_state=0, solver='warn',\n",
              "          tol=0.0001, verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ltZa9TuDRBMn",
        "colab_type": "code",
        "outputId": "4bfaa3b5-4b01-4237-8d7f-442944ce3502",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Check test accuracy.\n",
        "y_test_pred = intent_recognizer.predict(X_test_tfidf)\n",
        "test_accuracy = accuracy_score(y_test, y_test_pred)\n",
        "print('Test accuracy = {}'.format(test_accuracy))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test accuracy = 0.991575\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wu8zhxf5RBMq",
        "colab_type": "text"
      },
      "source": [
        "Dump the classifier to use it in the running bot."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "porv30NmRBMs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pickle.dump(intent_recognizer, open(RESOURCE_PATH['INTENT_RECOGNIZER'], 'wb'))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "quh8VWErRBMu",
        "colab_type": "text"
      },
      "source": [
        "### Programming language classification "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ISo_DsZJRBMv",
        "colab_type": "text"
      },
      "source": [
        "We will train one more classifier for the programming-related questions. It will predict exactly one tag (=programming language) and will be also based on Logistic Regression with TF-IDF features. \n",
        "\n",
        "First, let us prepare the data for this task."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9eQtlN5xRBMw",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X = stackoverflow_df['title'].values\n",
        "y = stackoverflow_df['tag'].values"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "acYPw3xqRBMz",
        "colab_type": "code",
        "outputId": "ba7ba313-93e2-4e8c-d12c-b9a51b2f6aa3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)\n",
        "print('Train size = {}, test size = {}'.format(len(X_train), len(X_test)))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train size = 160000, test size = 40000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1k2ibuJ2RBM4",
        "colab_type": "text"
      },
      "source": [
        "Let us reuse the TF-IDF vectorizer that we have already created above. It should not make a huge difference which data was used to train it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zxHDnouLRBM5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "vectorizer = pickle.load(open(RESOURCE_PATH['TFIDF_VECTORIZER'], 'rb'))\n",
        "\n",
        "X_train_tfidf, X_test_tfidf = vectorizer.transform(X_train), vectorizer.transform(X_test)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hwne-NANRBM9",
        "colab_type": "text"
      },
      "source": [
        "Train the **tag classifier** using OneVsRestClassifier wrapper over LogisticRegression. Use the following parameters: *penalty='l2'*, *C=5*, *random_state=0*."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JiB8SXzvRBM9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.multiclass import OneVsRestClassifier"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gvbn85uWRBNA",
        "colab_type": "code",
        "outputId": "dd899abc-20b1-4873-fde8-84175258c897",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 158
        }
      },
      "source": [
        "######################################\n",
        "tag_classifier = OneVsRestClassifier(LogisticRegression(penalty='l2', C=5, random_state=0))\n",
        "tag_classifier.fit(X_train_tfidf, y_train)\n",
        "######################################"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.\n",
            "  FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "OneVsRestClassifier(estimator=LogisticRegression(C=5, class_weight=None, dual=False, fit_intercept=True,\n",
              "          intercept_scaling=1, max_iter=100, multi_class='warn',\n",
              "          n_jobs=None, penalty='l2', random_state=0, solver='warn',\n",
              "          tol=0.0001, verbose=0, warm_start=False),\n",
              "          n_jobs=None)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GOF4K8hDRBND",
        "colab_type": "code",
        "outputId": "26e3c1c7-d86d-42ed-86de-4c79aa3a74ea",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "# Check test accuracy.\n",
        "y_test_pred = tag_classifier.predict(X_test_tfidf)\n",
        "test_accuracy = accuracy_score(y_test, y_test_pred)\n",
        "print('Test accuracy = {}'.format(test_accuracy))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test accuracy = 0.800725\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B1ReHD9dRBNH",
        "colab_type": "text"
      },
      "source": [
        "Dump the classifier to use it in the running bot."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mz6gsvz5RBNI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "pickle.dump(tag_classifier, open(RESOURCE_PATH['TAG_CLASSIFIER'], 'wb'))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S65vDfVlRBNR",
        "colab_type": "text"
      },
      "source": [
        "## Part II. Ranking  questions with embeddings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9gdEomxwRBNS",
        "colab_type": "text"
      },
      "source": [
        "To find a relevant answer (a thread from StackOverflow) on a question you will use vector representations to calculate similarity between the question and existing threads. We will need to use `question_to_vec` function prepared and made availabe in *utils.py* , which can create such a representation based on word vectors. \n",
        "\n",
        "However, it would be costly to compute such a representation for all possible answers in *online mode* of the bot (e.g. when bot is running and answering questions from many users). This is the reason why you will create a *database* with pre-computed representations. These representations will be arranged by non-overlaping tags (programming languages), so that the search of the answer can be performed only within one tag each time. This will make our bot even more efficient and allow not to store all the database in RAM. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BsYcj0s2RBNU",
        "colab_type": "text"
      },
      "source": [
        "Load StarSpace embeddings which were trained on Stack Overflow posts. These embeddings were trained in *supervised mode* for duplicates detection on the same corpus that is used in search. We can account on that these representations will allow us to find closely related answers for a question. \n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D3ridHbMRBNV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "starspace_embeddings, embeddings_dim = load_embeddings('data/word_embeddings.tsv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SrPSasPJRBNc",
        "colab_type": "text"
      },
      "source": [
        "Since we want to precompute representations for all possible answers, we need to load the whole posts dataset, unlike we did for the intent classifier:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m_KLq32YRBNe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "posts_df = pd.read_csv('data/tagged_posts.tsv', sep='\\t')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m9LyaYwxRBNf",
        "colab_type": "text"
      },
      "source": [
        "Look at the distribution of posts for programming languages (tags) and find the most common ones. \n",
        "You might want to use pandas [groupby](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html) and [count](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.count.html) methods:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UhPBnRdouxLD",
        "colab_type": "code",
        "outputId": "a08905e8-3a3a-47bf-eee8-dfd428c700c7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        }
      },
      "source": [
        "posts_df.head(5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>post_id</th>\n",
              "      <th>title</th>\n",
              "      <th>tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>9</td>\n",
              "      <td>Calculate age in C#</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>16</td>\n",
              "      <td>Filling a DataSet or DataTable from a LINQ que...</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>39</td>\n",
              "      <td>Reliable timer in a console application</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>42</td>\n",
              "      <td>Best way to allow plugins for a PHP application</td>\n",
              "      <td>php</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>59</td>\n",
              "      <td>How do I get a distinct, ordered list of names...</td>\n",
              "      <td>c#</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   post_id                                              title  tag\n",
              "0        9                                Calculate age in C#   c#\n",
              "1       16  Filling a DataSet or DataTable from a LINQ que...   c#\n",
              "2       39            Reliable timer in a console application   c#\n",
              "3       42    Best way to allow plugins for a PHP application  php\n",
              "4       59  How do I get a distinct, ordered list of names...   c#"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1gpiU5A3RBNg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "counts_by_tag = posts_df.groupby('tag').count()['title']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "74I2pJX_vETA",
        "colab_type": "code",
        "outputId": "c62aa0ee-43e4-4eec-b89c-a2eb3985e66f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        }
      },
      "source": [
        "counts_by_tag"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tag\n",
              "c#            394451\n",
              "c_cpp         281300\n",
              "java          383456\n",
              "javascript    375867\n",
              "php           321752\n",
              "python        208607\n",
              "r              36359\n",
              "ruby           99930\n",
              "swift          34809\n",
              "vb             35044\n",
              "Name: title, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1UbgFciJRBNj",
        "colab_type": "text"
      },
      "source": [
        "Now for each `tag` you need to create two data structures, which will serve as online search index:\n",
        "* `tag_post_ids` � a list of post_ids with shape `(counts_by_tag[tag],)`. It will be needed to show the title and link to the thread;\n",
        "* `tag_vectors` � a matrix with shape `(counts_by_tag[tag], embeddings_dim)` where embeddings for each answer are stored.\n",
        "\n",
        "Implement the code which will calculate the mentioned structures and dump it to files. It should take several minutes to compute it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fvs5vQSkRBNk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "os.makedirs(RESOURCE_PATH['THREAD_EMBEDDINGS_FOLDER'], exist_ok=True)\n",
        "\n",
        "for tag, count in counts_by_tag.items():\n",
        "    tag_posts = posts_df[posts_df['tag'] == tag]\n",
        "    \n",
        "    tag_post_ids = tag_posts['post_id'].values\n",
        "    \n",
        "    tag_vectors = np.zeros((count, embeddings_dim), dtype=np.float32)\n",
        "    for i, title in enumerate(tag_posts['title']):\n",
        "        tag_vectors[i, :] = question_to_vec(title, starspace_embeddings, embeddings_dim)\n",
        "\n",
        "    # Dump post ids and vectors to a file.\n",
        "    filename = os.path.join(RESOURCE_PATH['THREAD_EMBEDDINGS_FOLDER'], os.path.normpath('%s.pkl' % tag))\n",
        "    pickle.dump((tag_post_ids, tag_vectors), open(filename, 'wb'))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SI0Fd-3pBh6s",
        "colab_type": "code",
        "outputId": "1d77a5de-8d99-447d-dfe3-ba60fb5cf384",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 155
        }
      },
      "source": [
        "!ls"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "adc.json\t\t\t  __pycache__\n",
            "boost_1_63_0.zip\t\t  sample_data\n",
            "common\t\t\t\t  setup_google_colab.py\n",
            "data\t\t\t\t  Starspace\n",
            "dialogue_manager.py\t\t  tag_classifier.pkl\n",
            "intent_recognizer.pkl\t\t  tfidf_vectorizer.pkl\n",
            "main_bot.py\t\t\t  thread_embeddings_by_tags\n",
            "my_starspace_embeddings_0612.tsv  utils.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0SoUG1sUCJR_",
        "colab_type": "code",
        "outputId": "927ce92e-54ef-4b41-ad80-c41b6d4bed10",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "!ls thread_embeddings_by_tags/"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c_cpp.pkl  java.pkl\t   php.pkl     r.pkl\t swift.pkl\n",
            "c#.pkl\t   javascript.pkl  python.pkl  ruby.pkl  vb.pkl\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}