IR_JelenaKitanovic.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "IR_JelenaKitanovic.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "machine_shape": "hm",
      "mount_file_id": "1GFOStUH6t0_56KSHRCTO1bFq8A6k7buI",
      "authorship_tag": "ABX9TyNOyZGB+JVpKhaWRDEdyz+B",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "b40e01ad41284bc4adb4afeca9229f4e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_b35d70c85ea4444681e78ba223e9ed25",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_99bd5333ddb5420a905cda576a50fefd",
              "IPY_MODEL_1717453c9e0f482f92b313d10ef4322d",
              "IPY_MODEL_87f6f38292ff42fd9964b1ae41d49a68"
            ]
          }
        },
        "b35d70c85ea4444681e78ba223e9ed25": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "99bd5333ddb5420a905cda576a50fefd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_821855a5645f4c9a92723e6a55e5be3e",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_10e698174dbe4f60b08e0748b56b65f4"
          }
        },
        "1717453c9e0f482f92b313d10ef4322d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_1d51716ad6e240788d25e97f8433335b",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 571,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 571,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_ee896dea0f04408e96ebbb81e23f15cb"
          }
        },
        "87f6f38292ff42fd9964b1ae41d49a68": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_c0cc39772a1847499a503ba90e8f1f89",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 571/571 [00:00&lt;00:00, 14.5kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_df9465ba95a341e7b27c36f22de98cdd"
          }
        },
        "821855a5645f4c9a92723e6a55e5be3e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "10e698174dbe4f60b08e0748b56b65f4": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1d51716ad6e240788d25e97f8433335b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "ee896dea0f04408e96ebbb81e23f15cb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c0cc39772a1847499a503ba90e8f1f89": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "df9465ba95a341e7b27c36f22de98cdd": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "dcbd5b4d34ee40018fb7d7979068902e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_d7a8df5acc0c46d4a00bd542b3b5d5dc",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_fd62cbf562844e51a561c480216c6c13",
              "IPY_MODEL_bee37ef46bf14fbb808cbc650e6701f0",
              "IPY_MODEL_e48500c6637b4bcc8230cbda8b3636cc"
            ]
          }
        },
        "d7a8df5acc0c46d4a00bd542b3b5d5dc": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "fd62cbf562844e51a561c480216c6c13": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_5d62fd39ae124c91906671e1d961ec4c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_a2e3cef8ee8c449fb31be1ac2e4afc93"
          }
        },
        "bee37ef46bf14fbb808cbc650e6701f0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_cb9254b5264e4351b93722fe7fa31182",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 496313727,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 496313727,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_2a25df3aa8d24e1cb402994d8758d37c"
          }
        },
        "e48500c6637b4bcc8230cbda8b3636cc": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_07fafd02e60745828f8cac7e7ce1f533",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 496M/496M [00:09&lt;00:00, 59.5MB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_f339374abb944c0189f767d958ad2212"
          }
        },
        "5d62fd39ae124c91906671e1d961ec4c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "a2e3cef8ee8c449fb31be1ac2e4afc93": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "cb9254b5264e4351b93722fe7fa31182": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "2a25df3aa8d24e1cb402994d8758d37c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "07fafd02e60745828f8cac7e7ce1f533": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "f339374abb944c0189f767d958ad2212": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1834c13b96974cb29b65569bcebd83ad": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_5159a34c6d9847dba52947b0478bc259",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_76bc9f53fdd34be88c09e0d8e019d705",
              "IPY_MODEL_a2206e0ed8704565887aa61bc610ba5c",
              "IPY_MODEL_a13ac052c4f4478b9d6a10342f95a1aa"
            ]
          }
        },
        "5159a34c6d9847dba52947b0478bc259": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "76bc9f53fdd34be88c09e0d8e019d705": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_5844489aae7f42f58e9a6021e905356a",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_f36d0ddd05634552b65e3abd7ada720e"
          }
        },
        "a2206e0ed8704565887aa61bc610ba5c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_3aec95bad86f43888923d78c79b5e6fd",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 898822,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 898822,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_1195d3854ae84a279f1bc4e0f0cf90c5"
          }
        },
        "a13ac052c4f4478b9d6a10342f95a1aa": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_4f2128ba50cd4012a61f8b20b60c940a",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 899k/899k [00:00&lt;00:00, 1.13MB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_80ba8d091f5349b2a9284cb7bf8115c5"
          }
        },
        "5844489aae7f42f58e9a6021e905356a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "f36d0ddd05634552b65e3abd7ada720e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3aec95bad86f43888923d78c79b5e6fd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "1195d3854ae84a279f1bc4e0f0cf90c5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "4f2128ba50cd4012a61f8b20b60c940a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "80ba8d091f5349b2a9284cb7bf8115c5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "f8c26840fbad4a69a9e4b8f91f93a929": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_e551fa61c1b945ac8ae7ff06184e776a",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_5e5d99f6a9c343b68ee1d7b19e136209",
              "IPY_MODEL_b0927b2579de4ee88991124b2ae2aafd",
              "IPY_MODEL_0a9592ddd28a4bcdb2e9aa2b57ef5f2e"
            ]
          }
        },
        "e551fa61c1b945ac8ae7ff06184e776a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "5e5d99f6a9c343b68ee1d7b19e136209": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_76e196c19c614de2aaf8d9228ee6f7cf",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_6720bcc1aee443129623197230273ca6"
          }
        },
        "b0927b2579de4ee88991124b2ae2aafd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_bc2eb0c00f774bfe87526c8eeec4d302",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 456318,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 456318,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_3f8252a22ede45989993841f30e4a448"
          }
        },
        "0a9592ddd28a4bcdb2e9aa2b57ef5f2e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_a13a54247ea64cfabed770632c197123",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 456k/456k [00:00&lt;00:00, 1.43MB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5fee111c22334a7b880c7a19ca72fc15"
          }
        },
        "76e196c19c614de2aaf8d9228ee6f7cf": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "6720bcc1aee443129623197230273ca6": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "bc2eb0c00f774bfe87526c8eeec4d302": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "3f8252a22ede45989993841f30e4a448": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a13a54247ea64cfabed770632c197123": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5fee111c22334a7b880c7a19ca72fc15": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "cd6f01ca2e63416bbf9665bb93655fa0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_071048a888b24e948fde51c07de15b27",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_01da91d9f06447b68c4daf96ac8e5d45",
              "IPY_MODEL_d50015ee5d8c44f69b2351ec503e3bdb",
              "IPY_MODEL_456256c9e3ef428492b007ef6ed88db6"
            ]
          }
        },
        "071048a888b24e948fde51c07de15b27": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "01da91d9f06447b68c4daf96ac8e5d45": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_7a364b48d78f4495adc741bd2235e23f",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_95a91e57210443e6b1c80e6f0824b330"
          }
        },
        "d50015ee5d8c44f69b2351ec503e3bdb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_e952a7a796d348bea04a27dad3da00fe",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 772,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 772,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_7317022cfc054395a740d85de264358a"
          }
        },
        "456256c9e3ef428492b007ef6ed88db6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_bd2e75bec30e4d739ee9ca4b39d1baf4",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 772/772 [00:00&lt;00:00, 31.7kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_ad8bbd7df61a46d88cdc1f38be9461df"
          }
        },
        "7a364b48d78f4495adc741bd2235e23f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "95a91e57210443e6b1c80e6f0824b330": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "e952a7a796d348bea04a27dad3da00fe": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "7317022cfc054395a740d85de264358a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "bd2e75bec30e4d739ee9ca4b39d1baf4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "ad8bbd7df61a46d88cdc1f38be9461df": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "8ff13c15fa864ec6b42a81eaf9b84ff2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_f22314dc852e498588cd87943d1ff76b",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_ecbb16450b5f46d797127eec8c649007",
              "IPY_MODEL_0a2dbdaac42d40df95945b665c3ba674",
              "IPY_MODEL_36a83cc5510a4bf2bb1b3dfaded91e94"
            ]
          }
        },
        "f22314dc852e498588cd87943d1ff76b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "ecbb16450b5f46d797127eec8c649007": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_9a272ca8463c43e2af1e1eaa3e147cf4",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_af2a3caaa4a642a9a2f46cce0a6123e0"
          }
        },
        "0a2dbdaac42d40df95945b665c3ba674": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_0b4d91c15737408d9076463def287e9b",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 79,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 79,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_2e175dcc152c458fb76ae0d169c1bde2"
          }
        },
        "36a83cc5510a4bf2bb1b3dfaded91e94": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_40dd7bde18674ec6a40308e12b283445",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 79.0/79.0 [00:00&lt;00:00, 3.03kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_a871373b01f9423992086f89d511f671"
          }
        },
        "9a272ca8463c43e2af1e1eaa3e147cf4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "af2a3caaa4a642a9a2f46cce0a6123e0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "0b4d91c15737408d9076463def287e9b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "2e175dcc152c458fb76ae0d169c1bde2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "40dd7bde18674ec6a40308e12b283445": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "a871373b01f9423992086f89d511f671": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "f1e088360f8745659ce983099b8312df": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_36f7d7d6780542698b81d49164e63ae5",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_d3120cbb2e154adaa11b43783af720e3",
              "IPY_MODEL_333ade597d23455eb2a2bbabd4eca067",
              "IPY_MODEL_17f506f3edb341fea6c667380ac5796c"
            ]
          }
        },
        "36f7d7d6780542698b81d49164e63ae5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "d3120cbb2e154adaa11b43783af720e3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_ef18f9e9ddf5471d8447cbc58aa92a5f",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_83276da6c98144de912889df0623c6c9"
          }
        },
        "333ade597d23455eb2a2bbabd4eca067": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_c4e03f3703924215913680832d97b727",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 715,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 715,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_4def692d561449d3afc6da0fda6f275e"
          }
        },
        "17f506f3edb341fea6c667380ac5796c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_8c99e9fbfab64f30bf6a3d7d2c0eb96c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 715/715 [00:00&lt;00:00, 26.9kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_4bfe963c7cd54d5bb20996aa203900b0"
          }
        },
        "ef18f9e9ddf5471d8447cbc58aa92a5f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "83276da6c98144de912889df0623c6c9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c4e03f3703924215913680832d97b727": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "4def692d561449d3afc6da0fda6f275e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "8c99e9fbfab64f30bf6a3d7d2c0eb96c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "4bfe963c7cd54d5bb20996aa203900b0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a1cc9ecc90994711afd7e4438c9eaf10": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_63ca9b943cfb4f9888d3d8b3913e6d82",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_c23cf8c9c56e45c5a0e9bbc2d3b85ca5",
              "IPY_MODEL_2cd9cb2bcff94c67b256ca1f6ae7907a",
              "IPY_MODEL_ac745905836b4158b912726eb9764ae0"
            ]
          }
        },
        "63ca9b943cfb4f9888d3d8b3913e6d82": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c23cf8c9c56e45c5a0e9bbc2d3b85ca5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_f3316cc1140d4bf3ba874b3b51ce3a28",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_af22536b97c047608d79c37133a0b9c9"
          }
        },
        "2cd9cb2bcff94c67b256ca1f6ae7907a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_2bed8f7f5c9944619a2e17dfd057d904",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 890431403,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 890431403,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_d5fdafdb94414659ba5dfae755f90ea9"
          }
        },
        "ac745905836b4158b912726eb9764ae0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_247c3a8ca25a452aa949663adadcb7ad",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 890M/890M [00:17&lt;00:00, 54.2MB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5a7f7cf56dde41e48b0dd6dcf7bf10d3"
          }
        },
        "f3316cc1140d4bf3ba874b3b51ce3a28": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "af22536b97c047608d79c37133a0b9c9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "2bed8f7f5c9944619a2e17dfd057d904": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "d5fdafdb94414659ba5dfae755f90ea9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "247c3a8ca25a452aa949663adadcb7ad": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5a7f7cf56dde41e48b0dd6dcf7bf10d3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1dce9281130845369f67784be04272e5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_37410d19c80e4b48a190dc5e0b4da60e",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_a739cf63692947aea06a58ff62de9e20",
              "IPY_MODEL_931542c57d7a4965aeb201204d44db8c",
              "IPY_MODEL_1c08b5d25bed459592dfd36203935644"
            ]
          }
        },
        "37410d19c80e4b48a190dc5e0b4da60e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a739cf63692947aea06a58ff62de9e20": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_fcb0bc5e489745b98de96c4f9c1c4649",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_17961c1756844c1b9522c90e1717990c"
          }
        },
        "931542c57d7a4965aeb201204d44db8c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_7c1268666bbb455189ed046186b0aa20",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 760289,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 760289,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_4a814a194a434888b020c240bbd008cb"
          }
        },
        "1c08b5d25bed459592dfd36203935644": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_6b4ef0f9f5134325a631e0ba7a35b6de",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 760k/760k [00:00&lt;00:00, 868kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_1cb5da7f39e34ddf9623ac743739a9a9"
          }
        },
        "fcb0bc5e489745b98de96c4f9c1c4649": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "17961c1756844c1b9522c90e1717990c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "7c1268666bbb455189ed046186b0aa20": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "4a814a194a434888b020c240bbd008cb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "6b4ef0f9f5134325a631e0ba7a35b6de": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "1cb5da7f39e34ddf9623ac743739a9a9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3aaec7207aea4601b5c0af1b24f5ea99": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_e151d0e60b124c35a00bafebd9213d6d",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_912cd8ca46a44f4fa4f73112b8a1835d",
              "IPY_MODEL_2c3387902c6148019457887f5b0aafeb",
              "IPY_MODEL_2709cca70a5145dd954bdbabdb7022fe"
            ]
          }
        },
        "e151d0e60b124c35a00bafebd9213d6d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "912cd8ca46a44f4fa4f73112b8a1835d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_4de37d8033eb461e9f339061e5c1a41c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_217ae79f3afe4a5ba9d1edac3dc9fdcb"
          }
        },
        "2c3387902c6148019457887f5b0aafeb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_8a8518657fa6460b9101bfe8f7bf27bf",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 156,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 156,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_00ef4ed0a45c4252b0ff166784911ac0"
          }
        },
        "2709cca70a5145dd954bdbabdb7022fe": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_b9a17c6c44d94954904a3d1a822d517b",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 156/156 [00:00&lt;00:00, 6.28kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_f1478fba22aa49688fda821e355f74c7"
          }
        },
        "4de37d8033eb461e9f339061e5c1a41c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "217ae79f3afe4a5ba9d1edac3dc9fdcb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "8a8518657fa6460b9101bfe8f7bf27bf": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "00ef4ed0a45c4252b0ff166784911ac0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "b9a17c6c44d94954904a3d1a822d517b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "f1478fba22aa49688fda821e355f74c7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "ce5a55d24a5647f8bba7b0487693f2c1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_eb7c5ed2cef642168412533ed413dd9b",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_43345bb310b3487ebf08b7b69be85d38",
              "IPY_MODEL_0130d284bf3747f3b28d9e70141f56d4",
              "IPY_MODEL_1b6a7856d43443a9b895939900984e9f"
            ]
          }
        },
        "eb7c5ed2cef642168412533ed413dd9b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "43345bb310b3487ebf08b7b69be85d38": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_5b565047358a42e192346328d7c5b579",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Downloading: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_930a87689f6940cfbb554340c1dc8fc5"
          }
        },
        "0130d284bf3747f3b28d9e70141f56d4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_ae518e0bf69d4ac9bdab5a748894a962",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 48,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 48,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_fc13cf2967544b2f85f8183147ae3310"
          }
        },
        "1b6a7856d43443a9b895939900984e9f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_18d415707f1143348f79f20c36969f3b",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 48.0/48.0 [00:00&lt;00:00, 1.82kB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5b8efcc5e40e46c0a13f29edb216e01d"
          }
        },
        "5b565047358a42e192346328d7c5b579": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "930a87689f6940cfbb554340c1dc8fc5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "ae518e0bf69d4ac9bdab5a748894a962": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "fc13cf2967544b2f85f8183147ae3310": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "18d415707f1143348f79f20c36969f3b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5b8efcc5e40e46c0a13f29edb216e01d": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a0adf9c480e8411e9bd679c0c5a33b1d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ButtonModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ButtonView",
            "style": "IPY_MODEL_d13b4ca3700f4a58bff355b7fc1c699d",
            "_dom_classes": [],
            "description": "Pretrazi",
            "_model_name": "ButtonModel",
            "button_style": "",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "tooltip": "",
            "_view_count": null,
            "disabled": false,
            "_view_module_version": "1.5.0",
            "layout": "IPY_MODEL_1b48993419084cf3b949153bc95e67c7",
            "_model_module": "@jupyter-widgets/controls",
            "icon": ""
          }
        },
        "d13b4ca3700f4a58bff355b7fc1c699d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ButtonStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ButtonStyleModel",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "button_color": null,
            "font_weight": "",
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "1b48993419084cf3b949153bc95e67c7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "77ef60e63d2b45f8abd934b58ffd940a": {
          "model_module": "@jupyter-widgets/output",
          "model_name": "OutputModel",
          "model_module_version": "1.0.0",
          "state": {
            "_view_name": "OutputView",
            "msg_id": "",
            "_dom_classes": [],
            "_model_name": "OutputModel",
            "outputs": [],
            "_view_module": "@jupyter-widgets/output",
            "_model_module_version": "1.0.0",
            "_view_count": null,
            "_view_module_version": "1.0.0",
            "layout": "IPY_MODEL_c6642126350e439b94eb23a43ca3eaa9",
            "_model_module": "@jupyter-widgets/output"
          }
        },
        "c6642126350e439b94eb23a43ca3eaa9": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/JelenaKitanovic/qa_system_covid/blob/main/IR_JelenaKitanovic.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BQ6qQNvHN1RG"
      },
      "source": [
        "# Sistem za pretraživanje informacija o virusu COVID-19 implementiran korišćenjem Haystack framework-a"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ooa1wE-9J8eZ"
      },
      "source": [
        "Cilj projekta bio je implementacija sistem za odgovore na pitanja (tzv. QA system), koji bi na postavljeno pitanje pronašao odgovore među dostupnim dokumentima. Za realizaciju ovog projekta korišćen je [Haystack framework](https://haystack.deepset.ai/overview/intro) koji omogućava brzu i laku pretragu primenom najpopularnijih algoritama iz ove oblasti."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xyAOnPe6JCNM"
      },
      "source": [
        "U ovom projektu korišćen je podskup skupa podataka \n",
        "[COVID-19 Open Research Dataset Challenge (CORD-19)](https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge). Originalni skup se sastoji od preko 500,000 stručnih radova, od kojih je preko 200,000 o COVID-19, SARS-CoV-2, i sličnim virusima. \n",
        "\n",
        "Napomena: Radi lakšeg treniranja i reprodukcije programa, prilkom izrade ovog projekta korišćen je podskup od oko 12,000 radova. Folder sa tim radovima mozete pronaći na ovoj adresi: https://drive.google.com/drive/folders/1MrqXb0VXad0f0skhyhgGwypdEy3khzKg?usp=sharing, i kopirati na svoj Google Drive."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ajsx7DxJC3n_"
      },
      "source": [
        "###Uputstva za krajnjeg korisnika\n",
        "\n",
        "Ukoliko se program učita kroz Google Colab, sa gronje leve strane se nalazi Sadržaj (Table of contents) koji se može koristiti radi lakše navigacije kroz sam fajl.\n",
        "\n",
        "Na dnu ovog Colab fajla nalazi se forma za slobodan korisnički unos. Tu korisnik može postaviti pitanje i dobiće listu sa najrelevantnijim dokumentima i predloženim odgovorima. \n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ReiSMLamMzu3"
      },
      "source": [
        "## Učitavanje skupa podataka\n",
        "\n",
        "Kako su podaci u navedenom direktorijumu u JSON formatu, potrebno je da iz njih izvučemo informacije koje nam trebaju, kao i da prilagodimo format onome koji nama odgovara. \n",
        "\n",
        "Za dalju analizu biće nam dovoljan naziv rada (title), sažetak (abstract), sam tekst rada (full_text) i imena autora (authors)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ndo8NbPt_p5M",
        "outputId": "57da68ef-3576-4d5f-ace2-9385aeaac0ca"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import os\n",
        "import json\n",
        "import re\n",
        "from tqdm import tqdm\n",
        "\n",
        "directory_path = \"/content/drive/MyDrive/COVID\"\n",
        "docs = []\n",
        "\n",
        "for filename in tqdm(os.listdir(directory_path)):\n",
        "  file_path = directory_path + f\"/{filename}\"\n",
        "  json_content = json.load(open(file_path, \"rb\"))\n",
        "  \n",
        "  paper_id = json_content['paper_id']\n",
        "  title = json_content['metadata']['title']    \n",
        "  authors = ''\n",
        "  for author in json_content['metadata']['authors']:\n",
        "    authors += author['first'] + ' ' + author['last'] + ', '\n",
        "  authors = authors[:-2]\n",
        "  \n",
        "  #Ovde obradjujemo situaciju kada ne postoji abstract u dokumentu\n",
        "  try:\n",
        "    abstract = json_content['abstract'][0]['text']\n",
        "  except:\n",
        "    abstract = ''\n",
        "            \n",
        "  full_text = ''\n",
        "  for text in json_content['body_text']:\n",
        "    full_text += text['text']       \n",
        "  \n",
        "  #Dodajemo dokument u listu\n",
        "  docs.append([paper_id, title, abstract, full_text, authors])  \n",
        "\n",
        "#Od liste dokumenata napravicemo Pandas DataFrame objekat jer nam je lakse da baratamo sa njim :)\n",
        "df = pd.DataFrame(docs, columns = ['paper_id', 'title', 'abstract', 'full_text', 'authors'])"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 12336/12336 [00:18<00:00, 679.19it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "id": "_ew3OOzwTvEe",
        "outputId": "ea40b49e-53e1-4eac-c0a4-5ddde0970f4d"
      },
      "source": [
        "print('Dimenzije skupa podataka:', df.shape)\n",
        "print('Pregled prvih par redova:')\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dimenzije skupa podataka: (12336, 5)\n",
            "Pregled prvih par redova:\n"
          ]
        },
        {
          "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>paper_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "      <th>full_text</th>\n",
              "      <th>authors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>f4151bf1d61e7808033d59606f364c02d41234ed</td>\n",
              "      <td>Akute bilaterale Vestibulopathie nach SARS-CoV...</td>\n",
              "      <td>Wir berichten über eine 68-jährige Patientin, ...</td>\n",
              "      <td>Einschränkend bleibt natürlich festzustellen, ...</td>\n",
              "      <td>Florian Sachse</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>f42961a84c4587d2adac0afecd40abcfb0ce989d</td>\n",
              "      <td>Nursing Informatics: A Core Competency for the...</td>\n",
              "      <td>This chapter provides the reader with a summar...</td>\n",
              "      <td>Learning Objectives for the Chapter 1. Underst...</td>\n",
              "      <td>Pamela Hussey, Kathryn Hannah, P Hussey, P Hannah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>f40856d6d07cfe364cffb9b4d00b7a8bc40cf679</td>\n",
              "      <td>Epidemic Investigation</td>\n",
              "      <td></td>\n",
              "      <td>One of the key roles of public health is to ma...</td>\n",
              "      <td>Els Mathieu, Yao Sodahlon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>f42578b823280a3931165040e8a79b23470df0de</td>\n",
              "      <td>Structure, activity and inhibition of human TM...</td>\n",
              "      <td>9 Transmembrane protease, serine 2 (TMPRSS2) h...</td>\n",
              "      <td>. Engineered activation and structural charact...</td>\n",
              "      <td>Bryan Fraser#, Serap Beldar#, Almagul Seitova,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>f412033f08fe73d4affcfb381114f4ad306d7f07</td>\n",
              "      <td>HSV Forms an HCMV-like Viral Assembly Center i...</td>\n",
              "      <td>Herpes simplex virus (HSV) is a neuroinvasive ...</td>\n",
              "      <td>It is commonly observed that viruses concentra...</td>\n",
              "      <td>Shaowen White, Hiroyuki Kawano, N Charles Hara...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                   paper_id  ...                                            authors\n",
              "0  f4151bf1d61e7808033d59606f364c02d41234ed  ...                                     Florian Sachse\n",
              "1  f42961a84c4587d2adac0afecd40abcfb0ce989d  ...  Pamela Hussey, Kathryn Hannah, P Hussey, P Hannah\n",
              "2  f40856d6d07cfe364cffb9b4d00b7a8bc40cf679  ...                          Els Mathieu, Yao Sodahlon\n",
              "3  f42578b823280a3931165040e8a79b23470df0de  ...  Bryan Fraser#, Serap Beldar#, Almagul Seitova,...\n",
              "4  f412033f08fe73d4affcfb381114f4ad306d7f07  ...  Shaowen White, Hiroyuki Kawano, N Charles Hara...\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "PeVzBWe4q9aq",
        "outputId": "b0238895-39ca-473a-bc6c-00265eaf4650"
      },
      "source": [
        "#Brisemo duplikate\n",
        "df.drop_duplicates(inplace = True)\n",
        "df.describe()"
      ],
      "execution_count": 3,
      "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>paper_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "      <th>full_text</th>\n",
              "      <th>authors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>12332</td>\n",
              "      <td>12332</td>\n",
              "      <td>12332</td>\n",
              "      <td>12332</td>\n",
              "      <td>12332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>12332</td>\n",
              "      <td>10863</td>\n",
              "      <td>8621</td>\n",
              "      <td>12318</td>\n",
              "      <td>11135</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>89d6f4193a09f27569eb35990e1ad6e9b4697817</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>The nuclear receptor heterodimers of liver X r...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>1</td>\n",
              "      <td>1256</td>\n",
              "      <td>3635</td>\n",
              "      <td>4</td>\n",
              "      <td>1125</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                        paper_id  ... authors\n",
              "count                                      12332  ...   12332\n",
              "unique                                     12332  ...   11135\n",
              "top     89d6f4193a09f27569eb35990e1ad6e9b4697817  ...        \n",
              "freq                                           1  ...    1125\n",
              "\n",
              "[4 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-J7FbEcbostq"
      },
      "source": [
        "###Nedostajuće vrednosti\n",
        "\n",
        "Primećujemo da imamo nedostajuće vrednosti za atribut *authors*. Hajde da ih pregledamo da vidimo da li je u pitanju greška ili baš tako treba da bude."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "zKGf0JN_ThrJ",
        "outputId": "e2d95cee-2a07-410c-96fa-c26ffef9921e"
      },
      "source": [
        "df[df['authors'] == ''].head(10)"
      ],
      "execution_count": 6,
      "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>paper_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "      <th>full_text</th>\n",
              "      <th>authors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>f40631c38739955895a09a0796722e29f1bc5512</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>The pandemic of Corona Virus Disease 2019 (COV...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>f4597c208f01029c3ff3abbaf444a2d250c75e9e</td>\n",
              "      <td>PLOS ONE Impact of Covid-19 pandemic on obstet...</td>\n",
              "      <td>The advent of Covid-19 pandemic adversely affe...</td>\n",
              "      <td>Short title: Effects of Covid-19 pandemic on o...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>f45365ece4607c0d1f38f1d98697f7a32bfe58c2</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Background: Health care professionals (PS) are...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>f4607f104e185f6db161e94363a3315ae2f08f22</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Technological advances in the field of technic...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>f4319d7d36e11d6b29590ea57d9cc339d0cc9048</td>\n",
              "      <td>Supplementary information</td>\n",
              "      <td>1</td>\n",
              "      <td>(IBA). For further purification, the eluted sa...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>f485357fdddbbc022862d4512d19c78ded6f5b2a</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Submissions should be made via our electronic ...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>f4792a84bb430aa257cbae37abe16a59ab19f6ed</td>\n",
              "      <td>Acknowledgements 6 0</td>\n",
              "      <td></td>\n",
              "      <td>. 1 0 5 . CC-BY 4.0 International license It i...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>f4767a18070c219d7a4f705fc1b851d4814170a9</td>\n",
              "      <td>The Impact of COVID-19 on the Continuity of Ca...</td>\n",
              "      <td>The authors discuss the challenges and offer p...</td>\n",
              "      <td>Healthcare services globally are combating the...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>f49893a6de7ba4d7694ae4db2c81b35ae4bc71e0</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>The face-to-face consultations are a norm for ...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>103</th>\n",
              "      <td>f4668e1fe8dff3b9f4395316cd1caf946ed08e19</td>\n",
              "      <td>12A) A Symposium: Interventions to Prevent Chr...</td>\n",
              "      <td></td>\n",
              "      <td>E pisodes commonly described as bronchitic exa...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                     paper_id  ... authors\n",
              "7    f40631c38739955895a09a0796722e29f1bc5512  ...        \n",
              "40   f4597c208f01029c3ff3abbaf444a2d250c75e9e  ...        \n",
              "43   f45365ece4607c0d1f38f1d98697f7a32bfe58c2  ...        \n",
              "47   f4607f104e185f6db161e94363a3315ae2f08f22  ...        \n",
              "61   f4319d7d36e11d6b29590ea57d9cc339d0cc9048  ...        \n",
              "85   f485357fdddbbc022862d4512d19c78ded6f5b2a  ...        \n",
              "94   f4792a84bb430aa257cbae37abe16a59ab19f6ed  ...        \n",
              "96   f4767a18070c219d7a4f705fc1b851d4814170a9  ...        \n",
              "99   f49893a6de7ba4d7694ae4db2c81b35ae4bc71e0  ...        \n",
              "103  f4668e1fe8dff3b9f4395316cd1caf946ed08e19  ...        \n",
              "\n",
              "[10 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ucH7VtQOUtbZ"
      },
      "source": [
        "### Tretiranje nedostajućih vrednosti\n",
        "\n",
        "Možemo primetiti da redovi koji nemaju podatak ni za polje *authors*, ni za polje *title*, su uglavnom ili loši dokumenti ili je došlo do neke greške prilikom parsiranja ulaza. Kako imamo dovoljno podataka i bez njih, takve redove ćemo ovoga puta samo ukloniti, da nam ne bi kvarili dalju analizu."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 563
        },
        "id": "szsQ38hwU6xx",
        "outputId": "5995da92-81a4-49f8-c6f9-1e8e983eaad2"
      },
      "source": [
        "clean_dataframe = df[(df['authors'] != '') | (df['title'] != '')]\n",
        "\n",
        "print(\"Dimenzije ociscenog skupa podataka: \", clean_dataframe.shape)\n",
        "print(\"Pregled prvih nekoliko redova osiscenog skupa podataka: \")\n",
        "clean_dataframe.head(10)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dimenzije ociscenog skupa podataka:  (11652, 5)\n",
            "Pregled prvih nekoliko redova osiscenog skupa podataka: \n"
          ]
        },
        {
          "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>paper_id</th>\n",
              "      <th>title</th>\n",
              "      <th>abstract</th>\n",
              "      <th>full_text</th>\n",
              "      <th>authors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>f4151bf1d61e7808033d59606f364c02d41234ed</td>\n",
              "      <td>Akute bilaterale Vestibulopathie nach SARS-CoV...</td>\n",
              "      <td>Wir berichten über eine 68-jährige Patientin, ...</td>\n",
              "      <td>Einschränkend bleibt natürlich festzustellen, ...</td>\n",
              "      <td>Florian Sachse</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>f42961a84c4587d2adac0afecd40abcfb0ce989d</td>\n",
              "      <td>Nursing Informatics: A Core Competency for the...</td>\n",
              "      <td>This chapter provides the reader with a summar...</td>\n",
              "      <td>Learning Objectives for the Chapter 1. Underst...</td>\n",
              "      <td>Pamela Hussey, Kathryn Hannah, P Hussey, P Hannah</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>f40856d6d07cfe364cffb9b4d00b7a8bc40cf679</td>\n",
              "      <td>Epidemic Investigation</td>\n",
              "      <td></td>\n",
              "      <td>One of the key roles of public health is to ma...</td>\n",
              "      <td>Els Mathieu, Yao Sodahlon</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>f42578b823280a3931165040e8a79b23470df0de</td>\n",
              "      <td>Structure, activity and inhibition of human TM...</td>\n",
              "      <td>9 Transmembrane protease, serine 2 (TMPRSS2) h...</td>\n",
              "      <td>. Engineered activation and structural charact...</td>\n",
              "      <td>Bryan Fraser#, Serap Beldar#, Almagul Seitova,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>f412033f08fe73d4affcfb381114f4ad306d7f07</td>\n",
              "      <td>HSV Forms an HCMV-like Viral Assembly Center i...</td>\n",
              "      <td>Herpes simplex virus (HSV) is a neuroinvasive ...</td>\n",
              "      <td>It is commonly observed that viruses concentra...</td>\n",
              "      <td>Shaowen White, Hiroyuki Kawano, N Charles Hara...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>f40717f7d6802d0df1135e8225b5c3f69e1b726f</td>\n",
              "      <td>How the COVID-19 pandemic will change the futu...</td>\n",
              "      <td>has posed unprecedented healthcare system chal...</td>\n",
              "      <td>Since December 2019, the Coronavirus disease-1...</td>\n",
              "      <td>Yaseen Arabi, Elie Azoulay, Hasan Al-Dorzi, Ja...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>f4202aa37835ea8e52e0230e2c056a99d06d96f9</td>\n",
              "      <td>The misunderstanding of vaccine efficacy</td>\n",
              "      <td>Although the efficacies of vaccines against SA...</td>\n",
              "      <td>The protective effect of a vaccine is typicall...</td>\n",
              "      <td>K Passerini, A Timberlake, B Pighin, S</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>f4185f72f8808fa0c927ce358267368866cfa2eb</td>\n",
              "      <td>Characterizing 56 complete SARS-CoV S-gene seq...</td>\n",
              "      <td>Background: The spike glycoprotein (S) gene of...</td>\n",
              "      <td>Since the severe acute respiratory syndrome (S...</td>\n",
              "      <td>Julian Tang, Jo Cheung, Ida Chu, Margaret Ip, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>f42669f3577a3f410cff85a4b1ad9ae5a5065c0e</td>\n",
              "      <td>0123456789) 1 3 Journal of Science in Sport an...</td>\n",
              "      <td>It is known that COVID-19 spread mainly from p...</td>\n",
              "      <td>It is known that COVID-19 spread mainly from p...</td>\n",
              "      <td>Francisco Arias</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>f4242f1af7a17ad76cb437f827ef8d1ff291a731</td>\n",
              "      <td>Disease-Suppressive Soils-Beyond Food Producti...</td>\n",
              "      <td>In the pursuit of higher food production and e...</td>\n",
              "      <td>The COVID-19 pandemic is testing the capabilit...</td>\n",
              "      <td>Somasundaram Jayaraman, &amp;amp; Naorem, Rattan L...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                    paper_id  ...                                            authors\n",
              "0   f4151bf1d61e7808033d59606f364c02d41234ed  ...                                     Florian Sachse\n",
              "1   f42961a84c4587d2adac0afecd40abcfb0ce989d  ...  Pamela Hussey, Kathryn Hannah, P Hussey, P Hannah\n",
              "2   f40856d6d07cfe364cffb9b4d00b7a8bc40cf679  ...                          Els Mathieu, Yao Sodahlon\n",
              "3   f42578b823280a3931165040e8a79b23470df0de  ...  Bryan Fraser#, Serap Beldar#, Almagul Seitova,...\n",
              "4   f412033f08fe73d4affcfb381114f4ad306d7f07  ...  Shaowen White, Hiroyuki Kawano, N Charles Hara...\n",
              "5   f40717f7d6802d0df1135e8225b5c3f69e1b726f  ...  Yaseen Arabi, Elie Azoulay, Hasan Al-Dorzi, Ja...\n",
              "6   f4202aa37835ea8e52e0230e2c056a99d06d96f9  ...            K Passerini, A Timberlake, B Pighin, S \n",
              "8   f4185f72f8808fa0c927ce358267368866cfa2eb  ...  Julian Tang, Jo Cheung, Ida Chu, Margaret Ip, ...\n",
              "9   f42669f3577a3f410cff85a4b1ad9ae5a5065c0e  ...                                    Francisco Arias\n",
              "10  f4242f1af7a17ad76cb437f827ef8d1ff291a731  ...  Somasundaram Jayaraman, &amp; Naorem, Rattan L...\n",
              "\n",
              "[10 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eQs8qmu8pTk9"
      },
      "source": [
        "### Oblak reči (word cloud)\n",
        "\n",
        "Primenićemo tehniku *oblak reči* (*word cloud*), kako bismo vizuelno prikazali najčešće pojmove koji se nalaze u sažecima (*abstract*) ovih radova."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "id": "cHO38vzNpTB7",
        "outputId": "84142474-ec89-4b5f-8066-c0e50788c052"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from PIL import Image\n",
        "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n",
        "\n",
        "abstracts_merged = \" \".join(title for title in clean_dataframe.abstract)\n",
        "print(\"Ukupno, u svim sazecima ima {} reci.\".format(len(abstracts_merged)))\n",
        "\n",
        "# Izbacujemo tzv. STOPWORDS, to su reci koje se cesto ponavljaju u tekstu a ne donose dodatno znacenje, na primer veznici: and i or\n",
        "stopwords = set(STOPWORDS)\n",
        "# Izbacujemo jos neke cesto koriscenje reci koje nisu usko vezane za temu istrazivanja\n",
        "stopwords.update([\"et al\", \"one\", \"use\", \"group\", \"two\", \"may\", \"using\", \"used\", \"new\", \"time\"])\n",
        "\n",
        "wordcloud = WordCloud(stopwords=stopwords, background_color = \"white\").generate(abstracts_merged)\n",
        "\n",
        "# Prikaz generisane slike:\n",
        "plt.figure(figsize = (15, 10))\n",
        "plt.imshow(wordcloud, interpolation = 'bilinear', aspect = 'auto')\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Ukupno, u svim sazecima ima 8555950 reci.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y8kGB2IPq7Vk"
      },
      "source": [
        "## Implementacija programa za pretragu informacija\n",
        "\n",
        "Sada, kada smo odradili osnovni pregled i analizu skupa podataka, znamo sa čime radimo, pa možemo da pređemo na primenu algoritama za pretraživanje informacija.\n",
        "\n",
        "Za izgradnju QA sistema korišćen je [Haystack framework](https://haystack.deepset.ai/overview/get-started). To je open-source sistem koji nam omogućava inteligentnu pretragu nad velikim skupom dokumenata.   \n",
        "\n",
        "Osnovni pipeline jedne aplikacije izgleda kao na slici:\n",
        "![Screenshot 2021-09-07 at 21.20.43.png](data:image/png;base64,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)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D04tHHTBaOV3"
      },
      "source": [
        "### Instalacija najnovije verzije Heystack framework-a"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "dQQlfGDjLJfn",
        "outputId": "d553351d-6054-410c-8922-a5f2f8914127"
      },
      "source": [
        "!pip install grpcio-tools==1.34.1\n",
        "!pip install git+https://github.com/deepset-ai/haystack.git"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting grpcio-tools==1.34.1\n",
            "  Downloading grpcio_tools-1.34.1-cp37-cp37m-manylinux2014_x86_64.whl (2.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.5 MB 7.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from grpcio-tools==1.34.1) (57.4.0)\n",
            "Requirement already satisfied: grpcio>=1.34.1 in /usr/local/lib/python3.7/dist-packages (from grpcio-tools==1.34.1) (1.39.0)\n",
            "Requirement already satisfied: protobuf<4.0dev,>=3.5.0.post1 in /usr/local/lib/python3.7/dist-packages (from grpcio-tools==1.34.1) (3.17.3)\n",
            "Requirement already satisfied: six>=1.5.2 in /usr/local/lib/python3.7/dist-packages (from grpcio>=1.34.1->grpcio-tools==1.34.1) (1.15.0)\n",
            "Installing collected packages: grpcio-tools\n",
            "Successfully installed grpcio-tools-1.34.1\n",
            "Collecting git+https://github.com/deepset-ai/haystack.git\n",
            "  Cloning https://github.com/deepset-ai/haystack.git to /tmp/pip-req-build-t3wxogg0\n",
            "  Running command git clone -q https://github.com/deepset-ai/haystack.git /tmp/pip-req-build-t3wxogg0\n",
            "Collecting farm==0.8.0\n",
            "  Downloading farm-0.8.0-py3-none-any.whl (204 kB)\n",
            "\u001b[K     |████████████████████████████████| 204 kB 8.2 MB/s \n",
            "\u001b[?25hCollecting fastapi\n",
            "  Downloading fastapi-0.68.1-py3-none-any.whl (52 kB)\n",
            "\u001b[K     |████████████████████████████████| 52 kB 1.0 MB/s \n",
            "\u001b[?25hCollecting uvicorn\n",
            "  Downloading uvicorn-0.15.0-py3-none-any.whl (54 kB)\n",
            "\u001b[K     |████████████████████████████████| 54 kB 3.4 MB/s \n",
            "\u001b[?25hCollecting gunicorn\n",
            "  Downloading gunicorn-20.1.0-py3-none-any.whl (79 kB)\n",
            "\u001b[K     |████████████████████████████████| 79 kB 9.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (1.1.5)\n",
            "Requirement already satisfied: sklearn in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (0.0)\n",
            "Collecting elasticsearch<=7.10,>=7.7\n",
            "  Downloading elasticsearch-7.10.0-py2.py3-none-any.whl (321 kB)\n",
            "\u001b[K     |████████████████████████████████| 321 kB 74.9 MB/s \n",
            "\u001b[?25hCollecting elastic-apm\n",
            "  Downloading elastic_apm-6.4.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (332 kB)\n",
            "\u001b[K     |████████████████████████████████| 332 kB 58.4 MB/s \n",
            "\u001b[?25hCollecting tox\n",
            "  Downloading tox-3.24.3-py2.py3-none-any.whl (85 kB)\n",
            "\u001b[K     |████████████████████████████████| 85 kB 5.9 MB/s \n",
            "\u001b[?25hRequirement already satisfied: coverage in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (3.7.1)\n",
            "Collecting langdetect\n",
            "  Downloading langdetect-1.0.9.tar.gz (981 kB)\n",
            "\u001b[K     |████████████████████████████████| 981 kB 78.3 MB/s \n",
            "\u001b[?25hCollecting pytesseract==0.3.7\n",
            "  Downloading pytesseract-0.3.7.tar.gz (13 kB)\n",
            "Collecting pillow==8.2.0\n",
            "  Downloading Pillow-8.2.0-cp37-cp37m-manylinux1_x86_64.whl (3.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0 MB 43.3 MB/s \n",
            "\u001b[?25hCollecting pdf2image==1.14.0\n",
            "  Downloading pdf2image-1.14.0-py3-none-any.whl (10 kB)\n",
            "Collecting sentence-transformers>=0.4.0\n",
            "  Downloading sentence-transformers-2.0.0.tar.gz (85 kB)\n",
            "\u001b[K     |████████████████████████████████| 85 kB 5.9 MB/s \n",
            "\u001b[?25hCollecting python-multipart\n",
            "  Downloading python-multipart-0.0.5.tar.gz (32 kB)\n",
            "Collecting python-docx\n",
            "  Downloading python-docx-0.8.11.tar.gz (5.6 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.6 MB 25.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: sqlalchemy>=1.4.2 in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (1.4.22)\n",
            "Collecting sqlalchemy_utils\n",
            "  Downloading SQLAlchemy_Utils-0.37.8-py3-none-any.whl (100 kB)\n",
            "\u001b[K     |████████████████████████████████| 100 kB 13.3 MB/s \n",
            "\u001b[?25hCollecting faiss-cpu>=1.6.3\n",
            "  Downloading faiss_cpu-1.7.1.post2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (8.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 8.4 MB 97.2 MB/s \n",
            "\u001b[?25hCollecting tika\n",
            "  Downloading tika-1.24.tar.gz (28 kB)\n",
            "Collecting httptools\n",
            "  Downloading httptools-0.3.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (402 kB)\n",
            "\u001b[K     |████████████████████████████████| 402 kB 64.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: nltk in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (3.2.5)\n",
            "Requirement already satisfied: more_itertools in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (8.8.0)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.7/dist-packages (from farm-haystack==0.9.0) (2.6.2)\n",
            "Collecting pymilvus\n",
            "  Downloading pymilvus-1.1.2-py3-none-any.whl (56 kB)\n",
            "\u001b[K     |████████████████████████████████| 56 kB 5.6 MB/s \n",
            "\u001b[?25hCollecting SPARQLWrapper\n",
            "  Downloading SPARQLWrapper-1.8.5-py3-none-any.whl (26 kB)\n",
            "Collecting mmh3\n",
            "  Downloading mmh3-3.0.0-cp37-cp37m-manylinux2010_x86_64.whl (50 kB)\n",
            "\u001b[K     |████████████████████████████████| 50 kB 8.7 MB/s \n",
            "\u001b[?25hCollecting weaviate-client==2.5.0\n",
            "  Downloading weaviate_client-2.5.0-py3-none-any.whl (56 kB)\n",
            "\u001b[K     |████████████████████████████████| 56 kB 5.5 MB/s \n",
            "\u001b[?25hCollecting ray==1.5.0\n",
            "  Downloading ray-1.5.0-cp37-cp37m-manylinux2014_x86_64.whl (51.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 51.5 MB 40 kB/s \n",
            "\u001b[?25hCollecting psycopg2-binary\n",
            "  Downloading psycopg2_binary-2.9.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.4 MB 52.3 MB/s \n",
            "\u001b[?25hCollecting uvloop==0.14\n",
            "  Downloading uvloop-0.14.0-cp37-cp37m-manylinux2010_x86_64.whl (3.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.8 MB 48.3 MB/s \n",
            "\u001b[?25hCollecting dotmap\n",
            "  Downloading dotmap-1.3.24-py3-none-any.whl (11 kB)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (2.23.0)\n",
            "Collecting mlflow<=1.13.1\n",
            "  Downloading mlflow-1.13.1-py3-none-any.whl (14.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 14.1 MB 39.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: flask in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (1.1.4)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (57.4.0)\n",
            "Collecting boto3\n",
            "  Downloading boto3-1.18.36-py3-none-any.whl (131 kB)\n",
            "\u001b[K     |████████████████████████████████| 131 kB 83.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: dill in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (0.3.4)\n",
            "Collecting transformers==4.6.1\n",
            "  Downloading transformers-4.6.1-py3-none-any.whl (2.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.2 MB 85.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (1.4.1)\n",
            "Collecting flask-restplus\n",
            "  Downloading flask_restplus-0.13.0-py2.py3-none-any.whl (2.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 2.5 MB 86.7 MB/s \n",
            "\u001b[?25hCollecting flask-cors\n",
            "  Downloading Flask_Cors-3.0.10-py2.py3-none-any.whl (14 kB)\n",
            "Collecting sentencepiece\n",
            "  Downloading sentencepiece-0.1.96-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.2 MB 63.3 MB/s \n",
            "\u001b[?25hCollecting torch<1.9,>1.5\n",
            "  Downloading torch-1.8.1-cp37-cp37m-manylinux1_x86_64.whl (804.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 804.1 MB 1.8 kB/s \n",
            "\u001b[?25hRequirement already satisfied: wheel in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (0.37.0)\n",
            "Collecting seqeval\n",
            "  Downloading seqeval-1.2.2.tar.gz (43 kB)\n",
            "\u001b[K     |████████████████████████████████| 43 kB 2.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (4.62.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.7/dist-packages (from farm==0.8.0->farm-haystack==0.9.0) (5.4.8)\n",
            "Collecting Werkzeug==0.16.1\n",
            "  Downloading Werkzeug-0.16.1-py2.py3-none-any.whl (327 kB)\n",
            "\u001b[K     |████████████████████████████████| 327 kB 81.9 MB/s \n",
            "\u001b[?25hCollecting aiohttp\n",
            "  Downloading aiohttp-3.7.4.post0-cp37-cp37m-manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.3 MB 69.3 MB/s \n",
            "\u001b[?25hCollecting aiohttp-cors\n",
            "  Downloading aiohttp_cors-0.7.0-py3-none-any.whl (27 kB)\n",
            "Collecting pydantic>=1.8\n",
            "  Downloading pydantic-1.8.2-cp37-cp37m-manylinux2014_x86_64.whl (10.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 10.1 MB 89.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: jsonschema in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (2.6.0)\n",
            "Collecting opencensus\n",
            "  Downloading opencensus-0.7.13-py2.py3-none-any.whl (127 kB)\n",
            "\u001b[K     |████████████████████████████████| 127 kB 71.9 MB/s \n",
            "\u001b[?25hCollecting colorama\n",
            "  Downloading colorama-0.4.4-py2.py3-none-any.whl (16 kB)\n",
            "Collecting gpustat\n",
            "  Downloading gpustat-0.6.0.tar.gz (78 kB)\n",
            "\u001b[K     |████████████████████████████████| 78 kB 9.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: grpcio>=1.28.1 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (1.39.0)\n",
            "Requirement already satisfied: prometheus-client>=0.7.1 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (0.11.0)\n",
            "Requirement already satisfied: msgpack<2.0.0,>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (1.0.2)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (3.13)\n",
            "Requirement already satisfied: click>=7.0 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (7.1.2)\n",
            "Collecting aioredis\n",
            "  Downloading aioredis-2.0.0-py3-none-any.whl (69 kB)\n",
            "\u001b[K     |████████████████████████████████| 69 kB 9.5 MB/s \n",
            "\u001b[?25hCollecting redis>=3.5.0\n",
            "  Downloading redis-3.5.3-py2.py3-none-any.whl (72 kB)\n",
            "\u001b[K     |████████████████████████████████| 72 kB 777 kB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (1.19.5)\n",
            "Collecting py-spy>=0.2.0\n",
            "  Downloading py_spy-0.3.8-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (3.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.1 MB 43.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: protobuf>=3.15.3 in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (3.17.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from ray==1.5.0->farm-haystack==0.9.0) (3.0.12)\n",
            "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (4.6.4)\n",
            "Collecting sacremoses\n",
            "  Downloading sacremoses-0.0.45-py3-none-any.whl (895 kB)\n",
            "\u001b[K     |████████████████████████████████| 895 kB 74.4 MB/s \n",
            "\u001b[?25hCollecting huggingface-hub==0.0.8\n",
            "  Downloading huggingface_hub-0.0.8-py3-none-any.whl (34 kB)\n",
            "Collecting tokenizers<0.11,>=0.10.1\n",
            "  Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.3 MB 69.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (2019.12.20)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (21.0)\n",
            "Collecting validators>=0.18.2\n",
            "  Downloading validators-0.18.2-py3-none-any.whl (19 kB)\n",
            "Requirement already satisfied: urllib3<2,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from elasticsearch<=7.10,>=7.7->farm-haystack==0.9.0) (1.24.3)\n",
            "Requirement already satisfied: certifi in /usr/local/lib/python3.7/dist-packages (from elasticsearch<=7.10,>=7.7->farm-haystack==0.9.0) (2021.5.30)\n",
            "Requirement already satisfied: six>=1.5.2 in /usr/local/lib/python3.7/dist-packages (from grpcio>=1.28.1->ray==1.5.0->farm-haystack==0.9.0) (1.15.0)\n",
            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.7/dist-packages (from mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (2.8.2)\n",
            "Collecting databricks-cli>=0.8.7\n",
            "  Downloading databricks-cli-0.15.0.tar.gz (56 kB)\n",
            "\u001b[K     |████████████████████████████████| 56 kB 6.0 MB/s \n",
            "\u001b[?25hCollecting docker>=4.0.0\n",
            "  Downloading docker-5.0.2-py2.py3-none-any.whl (145 kB)\n",
            "\u001b[K     |████████████████████████████████| 145 kB 80.9 MB/s \n",
            "\u001b[?25hRequirement already satisfied: sqlparse>=0.3.1 in /usr/local/lib/python3.7/dist-packages (from mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (0.4.1)\n",
            "Collecting alembic<=1.4.1\n",
            "  Downloading alembic-1.4.1.tar.gz (1.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.1 MB 40.5 MB/s \n",
            "\u001b[?25hCollecting prometheus-flask-exporter\n",
            "  Downloading prometheus_flask_exporter-0.18.2.tar.gz (22 kB)\n",
            "Collecting gitpython>=2.1.0\n",
            "  Downloading GitPython-3.1.18-py3-none-any.whl (170 kB)\n",
            "\u001b[K     |████████████████████████████████| 170 kB 54.0 MB/s \n",
            "\u001b[?25hCollecting azure-storage-blob>=12.0.0\n",
            "  Downloading azure_storage_blob-12.8.1-py2.py3-none-any.whl (345 kB)\n",
            "\u001b[K     |████████████████████████████████| 345 kB 80.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: cloudpickle in /usr/local/lib/python3.7/dist-packages (from mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (1.3.0)\n",
            "Requirement already satisfied: entrypoints in /usr/local/lib/python3.7/dist-packages (from mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (0.3)\n",
            "Collecting querystring-parser\n",
            "  Downloading querystring_parser-1.2.4-py2.py3-none-any.whl (7.9 kB)\n",
            "Collecting Mako\n",
            "  Downloading Mako-1.1.5-py2.py3-none-any.whl (75 kB)\n",
            "\u001b[K     |████████████████████████████████| 75 kB 5.4 MB/s \n",
            "\u001b[?25hCollecting python-editor>=0.3\n",
            "  Downloading python_editor-1.0.4-py3-none-any.whl (4.9 kB)\n",
            "Collecting azure-core<2.0.0,>=1.10.0\n",
            "  Downloading azure_core-1.18.0-py2.py3-none-any.whl (166 kB)\n",
            "\u001b[K     |████████████████████████████████| 166 kB 85.7 MB/s \n",
            "\u001b[?25hCollecting msrest>=0.6.18\n",
            "  Downloading msrest-0.6.21-py2.py3-none-any.whl (85 kB)\n",
            "\u001b[K     |████████████████████████████████| 85 kB 5.2 MB/s \n",
            "\u001b[?25hCollecting cryptography>=2.1.4\n",
            "  Downloading cryptography-3.4.8-cp36-abi3-manylinux_2_24_x86_64.whl (3.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0 MB 51.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.7/dist-packages (from cryptography>=2.1.4->azure-storage-blob>=12.0.0->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (1.14.6)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.7/dist-packages (from cffi>=1.12->cryptography>=2.1.4->azure-storage-blob>=12.0.0->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (2.20)\n",
            "Requirement already satisfied: tabulate>=0.7.7 in /usr/local/lib/python3.7/dist-packages (from databricks-cli>=0.8.7->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (0.8.9)\n",
            "Collecting websocket-client>=0.32.0\n",
            "  Downloading websocket_client-1.2.1-py2.py3-none-any.whl (52 kB)\n",
            "\u001b[K     |████████████████████████████████| 52 kB 1.8 MB/s \n",
            "\u001b[?25hCollecting gitdb<5,>=4.0.1\n",
            "  Downloading gitdb-4.0.7-py3-none-any.whl (63 kB)\n",
            "\u001b[K     |████████████████████████████████| 63 kB 2.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: typing-extensions>=3.7.4.0 in /usr/local/lib/python3.7/dist-packages (from gitpython>=2.1.0->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (3.7.4.3)\n",
            "Collecting smmap<5,>=3.0.1\n",
            "  Downloading smmap-4.0.0-py2.py3-none-any.whl (24 kB)\n",
            "Requirement already satisfied: requests-oauthlib>=0.5.0 in /usr/local/lib/python3.7/dist-packages (from msrest>=0.6.18->azure-storage-blob>=12.0.0->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (1.3.0)\n",
            "Collecting isodate>=0.6.0\n",
            "  Downloading isodate-0.6.0-py2.py3-none-any.whl (45 kB)\n",
            "\u001b[K     |████████████████████████████████| 45 kB 4.7 MB/s \n",
            "\u001b[?25hRequirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->farm==0.8.0->farm-haystack==0.9.0) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->farm==0.8.0->farm-haystack==0.9.0) (3.0.4)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.5.0->msrest>=0.6.18->azure-storage-blob>=12.0.0->mlflow<=1.13.1->farm==0.8.0->farm-haystack==0.9.0) (3.1.1)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.7/dist-packages (from sentence-transformers>=0.4.0->farm-haystack==0.9.0) (0.10.0+cu102)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.7/dist-packages (from sentence-transformers>=0.4.0->farm-haystack==0.9.0) (0.22.2.post1)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.7/dist-packages (from sqlalchemy>=1.4.2->farm-haystack==0.9.0) (1.1.1)\n",
            "Requirement already satisfied: decorator>=3.4.0 in /usr/local/lib/python3.7/dist-packages (from validators>=0.18.2->weaviate-client==2.5.0->farm-haystack==0.9.0) (4.4.2)\n",
            "Collecting async-timeout<4.0,>=3.0\n",
            "  Downloading async_timeout-3.0.1-py3-none-any.whl (8.2 kB)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->ray==1.5.0->farm-haystack==0.9.0) (21.2.0)\n",
            "Collecting multidict<7.0,>=4.5\n",
            "  Downloading multidict-5.1.0-cp37-cp37m-manylinux2014_x86_64.whl (142 kB)\n",
            "\u001b[K     |████████████████████████████████| 142 kB 94.3 MB/s \n",
            "\u001b[?25hCollecting yarl<2.0,>=1.0\n",
            "  Downloading yarl-1.6.3-cp37-cp37m-manylinux2014_x86_64.whl (294 kB)\n",
            "\u001b[K     |████████████████████████████████| 294 kB 96.8 MB/s \n",
            "\u001b[?25hCollecting botocore<1.22.0,>=1.21.36\n",
            "  Downloading botocore-1.21.36-py3-none-any.whl (7.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 7.9 MB 65.5 MB/s \n",
            "\u001b[?25hCollecting jmespath<1.0.0,>=0.7.1\n",
            "  Downloading jmespath-0.10.0-py2.py3-none-any.whl (24 kB)\n",
            "Collecting s3transfer<0.6.0,>=0.5.0\n",
            "  Downloading s3transfer-0.5.0-py3-none-any.whl (79 kB)\n",
            "\u001b[K     |████████████████████████████████| 79 kB 11.1 MB/s \n",
            "\u001b[?25hCollecting urllib3<2,>=1.21.1\n",
            "  Downloading urllib3-1.25.11-py2.py3-none-any.whl (127 kB)\n",
            "\u001b[K     |████████████████████████████████| 127 kB 83.0 MB/s \n",
            "\u001b[?25hCollecting starlette==0.14.2\n",
            "  Downloading starlette-0.14.2-py3-none-any.whl (60 kB)\n",
            "\u001b[K     |████████████████████████████████| 60 kB 9.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: Jinja2<3.0,>=2.10.1 in /usr/local/lib/python3.7/dist-packages (from flask->farm==0.8.0->farm-haystack==0.9.0) (2.11.3)\n",
            "Requirement already satisfied: itsdangerous<2.0,>=0.24 in /usr/local/lib/python3.7/dist-packages (from flask->farm==0.8.0->farm-haystack==0.9.0) (1.1.0)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from Jinja2<3.0,>=2.10.1->flask->farm==0.8.0->farm-haystack==0.9.0) (2.0.1)\n",
            "Collecting aniso8601>=0.82\n",
            "  Downloading aniso8601-9.0.1-py2.py3-none-any.whl (52 kB)\n",
            "\u001b[K     |████████████████████████████████| 52 kB 1.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pytz in /usr/local/lib/python3.7/dist-packages (from flask-restplus->farm==0.8.0->farm-haystack==0.9.0) (2018.9)\n",
            "Requirement already satisfied: nvidia-ml-py3>=7.352.0 in /usr/local/lib/python3.7/dist-packages (from gpustat->ray==1.5.0->farm-haystack==0.9.0) (7.352.0)\n",
            "Collecting blessings>=1.6\n",
            "  Downloading blessings-1.7-py3-none-any.whl (18 kB)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (3.5.0)\n",
            "Requirement already satisfied: google-api-core<2.0.0,>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from opencensus->ray==1.5.0->farm-haystack==0.9.0) (1.26.3)\n",
            "Collecting opencensus-context==0.1.2\n",
            "  Downloading opencensus_context-0.1.2-py2.py3-none-any.whl (4.4 kB)\n",
            "Requirement already satisfied: google-auth<2.0dev,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (1.34.0)\n",
            "Requirement already satisfied: googleapis-common-protos<2.0dev,>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (1.53.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth<2.0dev,>=1.21.1->google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (4.7.2)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<2.0dev,>=1.21.1->google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (4.2.2)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<2.0dev,>=1.21.1->google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (0.2.8)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (2.4.7)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2.0dev,>=1.21.1->google-api-core<2.0.0,>=1.0.0->opencensus->ray==1.5.0->farm-haystack==0.9.0) (0.4.8)\n",
            "Requirement already satisfied: grpcio-tools<1.38.0,>=1.22.0 in /usr/local/lib/python3.7/dist-packages (from pymilvus->farm-haystack==0.9.0) (1.34.1)\n",
            "Collecting ujson>=2.0.0\n",
            "  Downloading ujson-4.1.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (178 kB)\n",
            "\u001b[K     |████████████████████████████████| 178 kB 75.1 MB/s \n",
            "\u001b[?25hCollecting grpcio>=1.28.1\n",
            "  Downloading grpcio-1.37.1-cp37-cp37m-manylinux2014_x86_64.whl (4.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 4.2 MB 67.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: lxml>=2.3.2 in /usr/local/lib/python3.7/dist-packages (from python-docx->farm-haystack==0.9.0) (4.2.6)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers==4.6.1->farm==0.8.0->farm-haystack==0.9.0) (1.0.1)\n",
            "Collecting rdflib>=4.0\n",
            "  Downloading rdflib-6.0.0-py3-none-any.whl (376 kB)\n",
            "\u001b[K     |████████████████████████████████| 376 kB 77.7 MB/s \n",
            "\u001b[?25hCollecting torchvision\n",
            "  Downloading torchvision-0.10.0-cp37-cp37m-manylinux1_x86_64.whl (22.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 22.1 MB 1.1 MB/s \n",
            "\u001b[?25h  Downloading torchvision-0.9.1-cp37-cp37m-manylinux1_x86_64.whl (17.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 17.4 MB 208 kB/s \n",
            "\u001b[?25hRequirement already satisfied: py>=1.4.17 in /usr/local/lib/python3.7/dist-packages (from tox->farm-haystack==0.9.0) (1.10.0)\n",
            "Collecting pluggy>=0.12.0\n",
            "  Downloading pluggy-1.0.0-py2.py3-none-any.whl (13 kB)\n",
            "Requirement already satisfied: toml>=0.9.4 in /usr/local/lib/python3.7/dist-packages (from tox->farm-haystack==0.9.0) (0.10.2)\n",
            "Collecting virtualenv!=20.0.0,!=20.0.1,!=20.0.2,!=20.0.3,!=20.0.4,!=20.0.5,!=20.0.6,!=20.0.7,>=16.0.0\n",
            "  Downloading virtualenv-20.7.2-py2.py3-none-any.whl (5.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 5.3 MB 63.8 MB/s \n",
            "\u001b[?25hCollecting backports.entry-points-selectable>=1.0.4\n",
            "  Downloading backports.entry_points_selectable-1.1.0-py2.py3-none-any.whl (6.2 kB)\n",
            "Collecting distlib<1,>=0.3.1\n",
            "  Downloading distlib-0.3.2-py2.py3-none-any.whl (338 kB)\n",
            "\u001b[K     |████████████████████████████████| 338 kB 90.0 MB/s \n",
            "\u001b[?25hCollecting platformdirs<3,>=2\n",
            "  Downloading platformdirs-2.3.0-py3-none-any.whl (13 kB)\n",
            "Collecting h11>=0.8\n",
            "  Downloading h11-0.12.0-py3-none-any.whl (54 kB)\n",
            "\u001b[K     |████████████████████████████████| 54 kB 3.6 MB/s \n",
            "\u001b[?25hCollecting asgiref>=3.4.0\n",
            "  Downloading asgiref-3.4.1-py3-none-any.whl (25 kB)\n",
            "Building wheels for collected packages: farm-haystack, pytesseract, alembic, databricks-cli, sentence-transformers, gpustat, langdetect, prometheus-flask-exporter, python-docx, python-multipart, seqeval, tika\n",
            "  Building wheel for farm-haystack (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for farm-haystack: filename=farm_haystack-0.9.0-py3-none-any.whl size=196873 sha256=178899cfec989d32a6c16f0ef3be0a9f1f9cb704f5ae23e620ae83cfab0686ed\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-03qzmv3q/wheels/a7/05/3b/9b33368d9af06a39f8e6af2e97fa2af876e893ade323cfc2c9\n",
            "  Building wheel for pytesseract (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pytesseract: filename=pytesseract-0.3.7-py2.py3-none-any.whl size=13954 sha256=3e1d8dafbedcdfc104a729a8cbfb71ac4b0ef684e48d216e35675e559fa35ab3\n",
            "  Stored in directory: /root/.cache/pip/wheels/67/71/6c/7a8c5ca2e699752506999ae7baeb692e2b4fc6488c2cddcb22\n",
            "  Building wheel for alembic (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for alembic: filename=alembic-1.4.1-py2.py3-none-any.whl size=158172 sha256=d8904ce92319773588024b3c2ae4e78d2925c80bf6abb97dd4a6b0182fa402fc\n",
            "  Stored in directory: /root/.cache/pip/wheels/be/5d/0a/9e13f53f4f5dfb67cd8d245bb7cdffe12f135846f491a283e3\n",
            "  Building wheel for databricks-cli (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for databricks-cli: filename=databricks_cli-0.15.0-py3-none-any.whl size=105260 sha256=ef1219df345843a07e9aa555fd4c8765b9e1176281994204eb982d6fbbe8e80e\n",
            "  Stored in directory: /root/.cache/pip/wheels/e7/ba/75/284f9a90ff7a010bb23b9798f2e9a19dd9fe619379c917bff4\n",
            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence-transformers: filename=sentence_transformers-2.0.0-py3-none-any.whl size=126710 sha256=11f3ecae1e4e67d1f900692178e0d63c5ac873789a592c6196148a9ad2c45fef\n",
            "  Stored in directory: /root/.cache/pip/wheels/d1/c1/0f/faafd427f705c4b012274ba60d9a91d75830306811e1355293\n",
            "  Building wheel for gpustat (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for gpustat: filename=gpustat-0.6.0-py3-none-any.whl size=12617 sha256=db271ac1b6713bbf0ccfdf494884f36fcd3fa9abfb785e09aa67c845fa8b9073\n",
            "  Stored in directory: /root/.cache/pip/wheels/e6/67/af/f1ad15974b8fd95f59a63dbf854483ebe5c7a46a93930798b8\n",
            "  Building wheel for langdetect (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for langdetect: filename=langdetect-1.0.9-py3-none-any.whl size=993242 sha256=57895a7e770947cc8e5d061c56ea395f126c6aab8116bd2e4cc9cc00ce3deedc\n",
            "  Stored in directory: /root/.cache/pip/wheels/c5/96/8a/f90c59ed25d75e50a8c10a1b1c2d4c402e4dacfa87f3aff36a\n",
            "  Building wheel for prometheus-flask-exporter (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for prometheus-flask-exporter: filename=prometheus_flask_exporter-0.18.2-py3-none-any.whl size=17415 sha256=c1d652de99dc7df9304b3a4950324779489fd0b121f47ca9713891becbc61c23\n",
            "  Stored in directory: /root/.cache/pip/wheels/6a/1e/1c/c765920cb92b2f0343d2dd8b481a407cee2823f9b4bbd2e52a\n",
            "  Building wheel for python-docx (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-docx: filename=python_docx-0.8.11-py3-none-any.whl size=184508 sha256=a4e0b2721bc5cdf02b4a3e6078ce824b3ec2e5e21dc63515b22f1c1f69d5cc56\n",
            "  Stored in directory: /root/.cache/pip/wheels/f6/6f/b9/d798122a8b55b74ad30b5f52b01482169b445fbb84a11797a6\n",
            "  Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-multipart: filename=python_multipart-0.0.5-py3-none-any.whl size=31678 sha256=55d3a81fdfd9fe63a50bf0e0a83c8df52b96933b8891a5507148f81e0490cbf6\n",
            "  Stored in directory: /root/.cache/pip/wheels/2c/41/7c/bfd1c180534ffdcc0972f78c5758f89881602175d48a8bcd2c\n",
            "  Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for seqeval: filename=seqeval-1.2.2-py3-none-any.whl size=16181 sha256=dbbf3ea3ac2e7a5e84a53c8181d88f4bf7e6a58553c1563c3e2c93c3a1d043de\n",
            "  Stored in directory: /root/.cache/pip/wheels/05/96/ee/7cac4e74f3b19e3158dce26a20a1c86b3533c43ec72a549fd7\n",
            "  Building wheel for tika (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for tika: filename=tika-1.24-py3-none-any.whl size=32891 sha256=24daf09ddf7314168654d205c64e6ba188b5dc30e8685a80702deb7726527d71\n",
            "  Stored in directory: /root/.cache/pip/wheels/ec/2b/38/58ff05467a742e32f67f5d0de048fa046e764e2fbb25ac93f3\n",
            "Successfully built farm-haystack pytesseract alembic databricks-cli sentence-transformers gpustat langdetect prometheus-flask-exporter python-docx python-multipart seqeval tika\n",
            "Installing collected packages: urllib3, Werkzeug, smmap, multidict, jmespath, isodate, yarl, websocket-client, python-editor, msrest, Mako, gitdb, cryptography, botocore, azure-core, async-timeout, torch, tokenizers, sacremoses, s3transfer, querystring-parser, prometheus-flask-exporter, platformdirs, pillow, opencensus-context, huggingface-hub, gunicorn, grpcio, gitpython, docker, distlib, databricks-cli, blessings, backports.entry-points-selectable, azure-storage-blob, aniso8601, alembic, aiohttp, virtualenv, validators, ujson, transformers, torchvision, starlette, seqeval, sentencepiece, redis, rdflib, pydantic, py-spy, pluggy, opencensus, mlflow, h11, gpustat, flask-restplus, flask-cors, dotmap, colorama, boto3, asgiref, aioredis, aiohttp-cors, weaviate-client, uvloop, uvicorn, tox, tika, sqlalchemy-utils, SPARQLWrapper, sentence-transformers, ray, python-multipart, python-docx, pytesseract, pymilvus, psycopg2-binary, pdf2image, mmh3, langdetect, httptools, fastapi, farm, faiss-cpu, elasticsearch, elastic-apm, farm-haystack\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 1.24.3\n",
            "    Uninstalling urllib3-1.24.3:\n",
            "      Successfully uninstalled urllib3-1.24.3\n",
            "  Attempting uninstall: Werkzeug\n",
            "    Found existing installation: Werkzeug 1.0.1\n",
            "    Uninstalling Werkzeug-1.0.1:\n",
            "      Successfully uninstalled Werkzeug-1.0.1\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 1.9.0+cu102\n",
            "    Uninstalling torch-1.9.0+cu102:\n",
            "      Successfully uninstalled torch-1.9.0+cu102\n",
            "  Attempting uninstall: pillow\n",
            "    Found existing installation: Pillow 7.1.2\n",
            "    Uninstalling Pillow-7.1.2:\n",
            "      Successfully uninstalled Pillow-7.1.2\n",
            "  Attempting uninstall: grpcio\n",
            "    Found existing installation: grpcio 1.39.0\n",
            "    Uninstalling grpcio-1.39.0:\n",
            "      Successfully uninstalled grpcio-1.39.0\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.10.0+cu102\n",
            "    Uninstalling torchvision-0.10.0+cu102:\n",
            "      Successfully uninstalled torchvision-0.10.0+cu102\n",
            "  Attempting uninstall: pluggy\n",
            "    Found existing installation: pluggy 0.7.1\n",
            "    Uninstalling pluggy-0.7.1:\n",
            "      Successfully uninstalled pluggy-0.7.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchtext 0.10.0 requires torch==1.9.0, but you have torch 1.8.1 which is incompatible.\n",
            "pytest 3.6.4 requires pluggy<0.8,>=0.5, but you have pluggy 1.0.0 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed Mako-1.1.5 SPARQLWrapper-1.8.5 Werkzeug-0.16.1 aiohttp-3.7.4.post0 aiohttp-cors-0.7.0 aioredis-2.0.0 alembic-1.4.1 aniso8601-9.0.1 asgiref-3.4.1 async-timeout-3.0.1 azure-core-1.18.0 azure-storage-blob-12.8.1 backports.entry-points-selectable-1.1.0 blessings-1.7 boto3-1.18.36 botocore-1.21.36 colorama-0.4.4 cryptography-3.4.8 databricks-cli-0.15.0 distlib-0.3.2 docker-5.0.2 dotmap-1.3.24 elastic-apm-6.4.0 elasticsearch-7.10.0 faiss-cpu-1.7.1.post2 farm-0.8.0 farm-haystack-0.9.0 fastapi-0.68.1 flask-cors-3.0.10 flask-restplus-0.13.0 gitdb-4.0.7 gitpython-3.1.18 gpustat-0.6.0 grpcio-1.37.1 gunicorn-20.1.0 h11-0.12.0 httptools-0.3.0 huggingface-hub-0.0.8 isodate-0.6.0 jmespath-0.10.0 langdetect-1.0.9 mlflow-1.13.1 mmh3-3.0.0 msrest-0.6.21 multidict-5.1.0 opencensus-0.7.13 opencensus-context-0.1.2 pdf2image-1.14.0 pillow-8.2.0 platformdirs-2.3.0 pluggy-1.0.0 prometheus-flask-exporter-0.18.2 psycopg2-binary-2.9.1 py-spy-0.3.8 pydantic-1.8.2 pymilvus-1.1.2 pytesseract-0.3.7 python-docx-0.8.11 python-editor-1.0.4 python-multipart-0.0.5 querystring-parser-1.2.4 ray-1.5.0 rdflib-6.0.0 redis-3.5.3 s3transfer-0.5.0 sacremoses-0.0.45 sentence-transformers-2.0.0 sentencepiece-0.1.96 seqeval-1.2.2 smmap-4.0.0 sqlalchemy-utils-0.37.8 starlette-0.14.2 tika-1.24 tokenizers-0.10.3 torch-1.8.1 torchvision-0.9.1 tox-3.24.3 transformers-4.6.1 ujson-4.1.0 urllib3-1.25.11 uvicorn-0.15.0 uvloop-0.14.0 validators-0.18.2 virtualenv-20.7.2 weaviate-client-2.5.0 websocket-client-1.2.1 yarl-1.6.3\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "PIL"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gODioZqkI9ks"
      },
      "source": [
        "### Učitavanje potrebnih funkcija i biblioteka (za konvertovanje i pripremu dokumenata za skladištenje)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RdpILeojK1q5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9c5a231e-cf83-40f1-f534-794794f318a1"
      },
      "source": [
        "from haystack.preprocessor.cleaning import clean_wiki_text\n",
        "from haystack.preprocessor.utils import convert_files_to_dicts, fetch_archive_from_http"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ray/autoscaler/_private/cli_logger.py:61: FutureWarning: Not all Ray CLI dependencies were found. In Ray 1.4+, the Ray CLI, autoscaler, and dashboard will only be usable via `pip install 'ray[default]'`. Please update your install command.\n",
            "  \"update your install command.\", FutureWarning)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AmPRFwxoL59s"
      },
      "source": [
        "### Učitavanje dokumenata u DocumentStore\n",
        "\n",
        "Haystack traži odgovore na pitanja u dokumentima koji se nalaze u [DocumentStore](https://haystack.deepset.ai/usage/document-store)-u. Postoji više podržanih implementacija DocumentStore-a (ElasticsearchDocumentStore, SQLDocumentStore, MilvusDocumentStore, InMemoryDocumentStore, etc.)\n",
        "\n",
        "U ovom projektu je korišćen ElasticSearchDocumentStore, zato što dolazi sa implementiranim algoritmima kao što su BM25 i full-text queries."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yaaVppMjylOB"
      },
      "source": [
        "#### Instalacija i pokretanje ElasticSearch-a"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BMdcqfaqPC8O",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7016ca20-13d8-4325-eb96-c378fd9baeac"
      },
      "source": [
        "! wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.9.2-linux-x86_64.tar.gz -q\n",
        "! tar -xzf elasticsearch-7.9.2-linux-x86_64.tar.gz\n",
        "! chown -R daemon:daemon elasticsearch-7.9.2\n",
        "\n",
        "from subprocess import Popen, PIPE, STDOUT\n",
        "es_server = Popen(['elasticsearch-7.9.2/bin/elasticsearch'],\n",
        "                   stdout=PIPE, stderr=STDOUT,\n",
        "                   preexec_fn=lambda: os.setuid(1)  # as daemon\n",
        "                  )\n",
        "\n",
        "# Cekamo malo dok ES startuje\n",
        "! sleep 30\n",
        "\n",
        "# Inicijalizacija ES-a\n",
        "from haystack.document_store.elasticsearch import ElasticsearchDocumentStore\n",
        "document_store = ElasticsearchDocumentStore(host=\"localhost\", username=\"\", password=\"\", index=\"document\")"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 19:46:38 - INFO - elasticsearch -   HEAD http://localhost:9200/ [status:200 request:0.066s]\n",
            "09/07/2021 19:46:38 - INFO - elasticsearch -   PUT http://localhost:9200/document [status:200 request:0.272s]\n",
            "09/07/2021 19:46:38 - INFO - elasticsearch -   PUT http://localhost:9200/label [status:200 request:0.159s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-EfHoqvbPT9k"
      },
      "source": [
        "#### Transformacija i upisivanje podataka u DocumentStore\n",
        "\n",
        "Da bismo upisali dokumente u ElasticsearchDocumentStore potrebno je da oni budu u sledećem formatu (dictionary):\n",
        "<br>\n",
        "[\n",
        "*    {\"name\": \"ime dokumenta 1\", \"text\": \"sadrzaj dokumenta 1\"}\n",
        "*    {\"name\": \"ime dokumenta 2\", \"text\": \"sadrzaj dokumenta 2\"}\n",
        "*    {\"name\": \"ime dokumenta 3\", \"text\": \"sadrzaj dokumenta 3\"}\n",
        "\n",
        "],\n",
        "\n",
        "pa ćemo morati da dodatno transformišemo naš dataframe.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hIFcRFNHPTrL"
      },
      "source": [
        "dictionary = clean_dataframe[['title', 'full_text']].rename(columns = {'title': 'name', 'full_text': 'text'}).to_dict(orient = 'records')"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W7sH-vFncsIm",
        "outputId": "654d9ee4-51e5-477e-fa9c-81ef22a495cc"
      },
      "source": [
        "document_store.write_documents(dictionary)"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 19:52:16 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.164s]\n",
            "09/07/2021 19:52:18 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.285s]\n",
            "09/07/2021 19:52:21 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.380s]\n",
            "09/07/2021 19:52:23 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.259s]\n",
            "09/07/2021 19:52:26 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.163s]\n",
            "09/07/2021 19:52:28 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.190s]\n",
            "09/07/2021 19:52:30 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.135s]\n",
            "09/07/2021 19:52:32 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.153s]\n",
            "09/07/2021 19:52:34 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.145s]\n",
            "09/07/2021 19:52:36 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.174s]\n",
            "09/07/2021 19:52:38 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.139s]\n",
            "09/07/2021 19:52:40 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.155s]\n",
            "09/07/2021 19:52:42 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.140s]\n",
            "09/07/2021 19:52:45 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.724s]\n",
            "09/07/2021 19:52:47 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.111s]\n",
            "09/07/2021 19:52:49 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.122s]\n",
            "09/07/2021 19:52:51 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.132s]\n",
            "09/07/2021 19:52:52 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.142s]\n",
            "09/07/2021 19:52:54 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.154s]\n",
            "09/07/2021 19:52:56 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:2.148s]\n",
            "09/07/2021 19:52:58 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.123s]\n",
            "09/07/2021 19:52:59 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.161s]\n",
            "09/07/2021 19:53:00 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.141s]\n",
            "09/07/2021 19:53:01 - INFO - elasticsearch -   POST http://localhost:9200/_bulk?refresh=wait_for [status:200 request:1.047s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FQceKF5u0Zch"
      },
      "source": [
        "### Inicijalizacija Retriever-a\n",
        "\n",
        "Retriever se ponaša kao Kerber koji ne dozvoljava da svašta dođe do Reader-a :). \n",
        "\n",
        "On prvi pregleda sve dokumente koja se nalaze u DocumentStore-u, brzo primeti koji dokumenti su relevantni, a koji ne, i na kraju prosledi filtrirani skup dokumenata Reader-u. \n",
        "\n",
        "Haystack podržava više modela za indeksiranje dokumenata, a mi ćemo ovde uporediti 2 Retriever-a: \n",
        "\n",
        "1.   TF-IDF\n",
        "2.   B25 (ElasticSearchRetriever) koji je unapredjena verzija 1.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-FUFdUiQcvhn",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6754bf9f-8f8c-4b41-a602-1250a8966403"
      },
      "source": [
        "from haystack.retriever.sparse import TfidfRetriever\n",
        "from haystack.retriever.sparse import ElasticsearchRetriever\n",
        "\n",
        "retriever_tfidf = TfidfRetriever(document_store)\n",
        "retriever_b25 = ElasticsearchRetriever(document_store)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:07:49 - INFO - elasticsearch -   POST http://localhost:9200/document/_search?scroll=1d&size=10000 [status:200 request:2.025s]\n",
            "09/07/2021 20:07:50 - INFO - elasticsearch -   POST http://localhost:9200/_search/scroll [status:200 request:0.300s]\n",
            "09/07/2021 20:07:50 - INFO - elasticsearch -   POST http://localhost:9200/_search/scroll [status:200 request:0.004s]\n",
            "09/07/2021 20:07:50 - INFO - elasticsearch -   DELETE http://localhost:9200/_search/scroll [status:200 request:0.003s]\n",
            "09/07/2021 20:07:50 - INFO - haystack.retriever.sparse -   Found 11638 candidate paragraphs from 11638 docs in DB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qzd2a5113lgm"
      },
      "source": [
        "### Inicijalizacija Reader-a\n",
        "\n",
        "Reader je onaj koji na kraju vrši ključnu pretragu, i iz dokumenata koje mu je prosledio Retriever bira one u kojima smatra da se nalazi odgovor na pitanje.\n",
        "\n",
        "Kao i za Retriever, Haystack podržava više implementacija Readera, a mi ćemo uporediti sledeća dva: \n",
        "\n",
        "1.   RoBERTa\n",
        "2.   ALBERT"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "b40e01ad41284bc4adb4afeca9229f4e",
            "b35d70c85ea4444681e78ba223e9ed25",
            "99bd5333ddb5420a905cda576a50fefd",
            "1717453c9e0f482f92b313d10ef4322d",
            "87f6f38292ff42fd9964b1ae41d49a68",
            "821855a5645f4c9a92723e6a55e5be3e",
            "10e698174dbe4f60b08e0748b56b65f4",
            "1d51716ad6e240788d25e97f8433335b",
            "ee896dea0f04408e96ebbb81e23f15cb",
            "c0cc39772a1847499a503ba90e8f1f89",
            "df9465ba95a341e7b27c36f22de98cdd",
            "dcbd5b4d34ee40018fb7d7979068902e",
            "d7a8df5acc0c46d4a00bd542b3b5d5dc",
            "fd62cbf562844e51a561c480216c6c13",
            "bee37ef46bf14fbb808cbc650e6701f0",
            "e48500c6637b4bcc8230cbda8b3636cc",
            "5d62fd39ae124c91906671e1d961ec4c",
            "a2e3cef8ee8c449fb31be1ac2e4afc93",
            "cb9254b5264e4351b93722fe7fa31182",
            "2a25df3aa8d24e1cb402994d8758d37c",
            "07fafd02e60745828f8cac7e7ce1f533",
            "f339374abb944c0189f767d958ad2212",
            "1834c13b96974cb29b65569bcebd83ad",
            "5159a34c6d9847dba52947b0478bc259",
            "76bc9f53fdd34be88c09e0d8e019d705",
            "a2206e0ed8704565887aa61bc610ba5c",
            "a13ac052c4f4478b9d6a10342f95a1aa",
            "5844489aae7f42f58e9a6021e905356a",
            "f36d0ddd05634552b65e3abd7ada720e",
            "3aec95bad86f43888923d78c79b5e6fd",
            "1195d3854ae84a279f1bc4e0f0cf90c5",
            "4f2128ba50cd4012a61f8b20b60c940a",
            "80ba8d091f5349b2a9284cb7bf8115c5",
            "f8c26840fbad4a69a9e4b8f91f93a929",
            "e551fa61c1b945ac8ae7ff06184e776a",
            "5e5d99f6a9c343b68ee1d7b19e136209",
            "b0927b2579de4ee88991124b2ae2aafd",
            "0a9592ddd28a4bcdb2e9aa2b57ef5f2e",
            "76e196c19c614de2aaf8d9228ee6f7cf",
            "6720bcc1aee443129623197230273ca6",
            "bc2eb0c00f774bfe87526c8eeec4d302",
            "3f8252a22ede45989993841f30e4a448",
            "a13a54247ea64cfabed770632c197123",
            "5fee111c22334a7b880c7a19ca72fc15",
            "cd6f01ca2e63416bbf9665bb93655fa0",
            "071048a888b24e948fde51c07de15b27",
            "01da91d9f06447b68c4daf96ac8e5d45",
            "d50015ee5d8c44f69b2351ec503e3bdb",
            "456256c9e3ef428492b007ef6ed88db6",
            "7a364b48d78f4495adc741bd2235e23f",
            "95a91e57210443e6b1c80e6f0824b330",
            "e952a7a796d348bea04a27dad3da00fe",
            "7317022cfc054395a740d85de264358a",
            "bd2e75bec30e4d739ee9ca4b39d1baf4",
            "ad8bbd7df61a46d88cdc1f38be9461df",
            "8ff13c15fa864ec6b42a81eaf9b84ff2",
            "f22314dc852e498588cd87943d1ff76b",
            "ecbb16450b5f46d797127eec8c649007",
            "0a2dbdaac42d40df95945b665c3ba674",
            "36a83cc5510a4bf2bb1b3dfaded91e94",
            "9a272ca8463c43e2af1e1eaa3e147cf4",
            "af2a3caaa4a642a9a2f46cce0a6123e0",
            "0b4d91c15737408d9076463def287e9b",
            "2e175dcc152c458fb76ae0d169c1bde2",
            "40dd7bde18674ec6a40308e12b283445",
            "a871373b01f9423992086f89d511f671",
            "f1e088360f8745659ce983099b8312df",
            "36f7d7d6780542698b81d49164e63ae5",
            "d3120cbb2e154adaa11b43783af720e3",
            "333ade597d23455eb2a2bbabd4eca067",
            "17f506f3edb341fea6c667380ac5796c",
            "ef18f9e9ddf5471d8447cbc58aa92a5f",
            "83276da6c98144de912889df0623c6c9",
            "c4e03f3703924215913680832d97b727",
            "4def692d561449d3afc6da0fda6f275e",
            "8c99e9fbfab64f30bf6a3d7d2c0eb96c",
            "4bfe963c7cd54d5bb20996aa203900b0",
            "a1cc9ecc90994711afd7e4438c9eaf10",
            "63ca9b943cfb4f9888d3d8b3913e6d82",
            "c23cf8c9c56e45c5a0e9bbc2d3b85ca5",
            "2cd9cb2bcff94c67b256ca1f6ae7907a",
            "ac745905836b4158b912726eb9764ae0",
            "f3316cc1140d4bf3ba874b3b51ce3a28",
            "af22536b97c047608d79c37133a0b9c9",
            "2bed8f7f5c9944619a2e17dfd057d904",
            "d5fdafdb94414659ba5dfae755f90ea9",
            "247c3a8ca25a452aa949663adadcb7ad",
            "5a7f7cf56dde41e48b0dd6dcf7bf10d3",
            "1dce9281130845369f67784be04272e5",
            "37410d19c80e4b48a190dc5e0b4da60e",
            "a739cf63692947aea06a58ff62de9e20",
            "931542c57d7a4965aeb201204d44db8c",
            "1c08b5d25bed459592dfd36203935644",
            "fcb0bc5e489745b98de96c4f9c1c4649",
            "17961c1756844c1b9522c90e1717990c",
            "7c1268666bbb455189ed046186b0aa20",
            "4a814a194a434888b020c240bbd008cb",
            "6b4ef0f9f5134325a631e0ba7a35b6de",
            "1cb5da7f39e34ddf9623ac743739a9a9",
            "3aaec7207aea4601b5c0af1b24f5ea99",
            "e151d0e60b124c35a00bafebd9213d6d",
            "912cd8ca46a44f4fa4f73112b8a1835d",
            "2c3387902c6148019457887f5b0aafeb",
            "2709cca70a5145dd954bdbabdb7022fe",
            "4de37d8033eb461e9f339061e5c1a41c",
            "217ae79f3afe4a5ba9d1edac3dc9fdcb",
            "8a8518657fa6460b9101bfe8f7bf27bf",
            "00ef4ed0a45c4252b0ff166784911ac0",
            "b9a17c6c44d94954904a3d1a822d517b",
            "f1478fba22aa49688fda821e355f74c7",
            "ce5a55d24a5647f8bba7b0487693f2c1",
            "eb7c5ed2cef642168412533ed413dd9b",
            "43345bb310b3487ebf08b7b69be85d38",
            "0130d284bf3747f3b28d9e70141f56d4",
            "1b6a7856d43443a9b895939900984e9f",
            "5b565047358a42e192346328d7c5b579",
            "930a87689f6940cfbb554340c1dc8fc5",
            "ae518e0bf69d4ac9bdab5a748894a962",
            "fc13cf2967544b2f85f8183147ae3310",
            "18d415707f1143348f79f20c36969f3b",
            "5b8efcc5e40e46c0a13f29edb216e01d"
          ]
        },
        "id": "kiKFZ-mbc1Je",
        "outputId": "28654ba3-41f1-4f84-84e4-11614ed92289"
      },
      "source": [
        "from haystack.reader.farm import FARMReader\n",
        "\n",
        "reader_roberta = FARMReader(model_name_or_path = \"deepset/roberta-base-squad2\", use_gpu = True, context_window_size = 1000)\n",
        "reader_albert = FARMReader(model_name_or_path = \"ahotrod/albert_xxlargev1_squad2_512\", use_gpu = True, context_window_size = 1000)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:12 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:10:12 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:10:12 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:10:12 - INFO - farm.utils -   Automatic Mixed Precision: None\n",
            "09/07/2021 20:10:12 - INFO - filelock -   Lock 140574045561296 acquired on /root/.cache/huggingface/transformers/c40d0abb589629c48763f271020d0b1f602f5208c432c0874d420491ed37e28b.122ed338b3591c07dba452777c59ff52330edb340d3d56d67aa9117ad9905673.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b40e01ad41284bc4adb4afeca9229f4e",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/571 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:13 - INFO - filelock -   Lock 140574045561296 released on /root/.cache/huggingface/transformers/c40d0abb589629c48763f271020d0b1f602f5208c432c0874d420491ed37e28b.122ed338b3591c07dba452777c59ff52330edb340d3d56d67aa9117ad9905673.lock\n",
            "09/07/2021 20:10:13 - INFO - filelock -   Lock 140574044559952 acquired on /root/.cache/huggingface/transformers/eac3273a8097dda671e3bea1db32c616e74f36a306c65b4858171c98d6db83e9.084aa7284f3a51fa1c8f0641aa04c47d366fbd18711f29d0a995693cfdbc9c9e.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dcbd5b4d34ee40018fb7d7979068902e",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/496M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:23 - INFO - filelock -   Lock 140574044559952 released on /root/.cache/huggingface/transformers/eac3273a8097dda671e3bea1db32c616e74f36a306c65b4858171c98d6db83e9.084aa7284f3a51fa1c8f0641aa04c47d366fbd18711f29d0a995693cfdbc9c9e.lock\n",
            "Some weights of the model checkpoint at deepset/roberta-base-squad2 were not used when initializing RobertaModel: ['qa_outputs.weight', 'qa_outputs.bias']\n",
            "- This IS expected if you are initializing RobertaModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing RobertaModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some weights of RobertaModel were not initialized from the model checkpoint at deepset/roberta-base-squad2 and are newly initialized: ['roberta.pooler.dense.weight', 'roberta.pooler.dense.bias']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
            "09/07/2021 20:10:30 - INFO - filelock -   Lock 140574047234960 acquired on /root/.cache/huggingface/transformers/81c80edb4c6cefa5cae64ccfdb34b3b309ecaf60da99da7cd1c17e24a5d36eb5.647b4548b6d9ea817e82e7a9231a320231a1c9ea24053cc9e758f3fe68216f05.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1834c13b96974cb29b65569bcebd83ad",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/899k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:31 - INFO - filelock -   Lock 140574047234960 released on /root/.cache/huggingface/transformers/81c80edb4c6cefa5cae64ccfdb34b3b309ecaf60da99da7cd1c17e24a5d36eb5.647b4548b6d9ea817e82e7a9231a320231a1c9ea24053cc9e758f3fe68216f05.lock\n",
            "09/07/2021 20:10:31 - INFO - filelock -   Lock 140574049158480 acquired on /root/.cache/huggingface/transformers/b87d46371731376b11768b7839b1a5938a4f77d6bd2d9b683f167df0026af432.5d12962c5ee615a4c803841266e9c3be9a691a924f72d395d3a6c6c81157788b.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f8c26840fbad4a69a9e4b8f91f93a929",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/456k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:32 - INFO - filelock -   Lock 140574049158480 released on /root/.cache/huggingface/transformers/b87d46371731376b11768b7839b1a5938a4f77d6bd2d9b683f167df0026af432.5d12962c5ee615a4c803841266e9c3be9a691a924f72d395d3a6c6c81157788b.lock\n",
            "09/07/2021 20:10:32 - INFO - filelock -   Lock 140574047234960 acquired on /root/.cache/huggingface/transformers/c9d2c178fac8d40234baa1833a3b1903d393729bf93ea34da247c07db24900d0.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "cd6f01ca2e63416bbf9665bb93655fa0",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/772 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:33 - INFO - filelock -   Lock 140574047234960 released on /root/.cache/huggingface/transformers/c9d2c178fac8d40234baa1833a3b1903d393729bf93ea34da247c07db24900d0.cb2244924ab24d706b02fd7fcedaea4531566537687a539ebb94db511fd122a0.lock\n",
            "09/07/2021 20:10:33 - INFO - filelock -   Lock 140574049209488 acquired on /root/.cache/huggingface/transformers/e8a600814b69e3ee74bb4a7398cc6fef9812475010f16a6c9f151b2c2772b089.451739a2f3b82c3375da0dfc6af295bedc4567373b171f514dd09a4cc4b31513.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8ff13c15fa864ec6b42a81eaf9b84ff2",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/79.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:33 - INFO - filelock -   Lock 140574049209488 released on /root/.cache/huggingface/transformers/e8a600814b69e3ee74bb4a7398cc6fef9812475010f16a6c9f151b2c2772b089.451739a2f3b82c3375da0dfc6af295bedc4567373b171f514dd09a4cc4b31513.lock\n",
            "09/07/2021 20:10:33 - WARNING - farm.utils -   ML Logging is turned off. No parameters, metrics or artifacts will be logged to MLFlow.\n",
            "09/07/2021 20:10:33 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:10:33 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:10:33 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:10:33 - INFO - farm.utils -   Automatic Mixed Precision: None\n",
            "09/07/2021 20:10:34 - INFO - farm.infer -   Got ya 3 parallel workers to do inference ...\n",
            "09/07/2021 20:10:34 - INFO - farm.infer -    0    0    0 \n",
            "09/07/2021 20:10:34 - INFO - farm.infer -   /w\\  /w\\  /w\\\n",
            "09/07/2021 20:10:34 - INFO - farm.infer -   /'\\  / \\  /'\\\n",
            "09/07/2021 20:10:34 - INFO - farm.infer -       \n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Automatic Mixed Precision: None\n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:10:34 - INFO - farm.utils -   Automatic Mixed Precision: None\n",
            "09/07/2021 20:10:34 - INFO - filelock -   Lock 140573998039696 acquired on /root/.cache/huggingface/transformers/4c0f9feb4f27d0baac7cada8552ee966286be516b2e925d322f8d275915e2cdb.9d6c2c65959d735e45573bd3230b64f1fe4ffbdabafba97dbb5822d2673312a7.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f1e088360f8745659ce983099b8312df",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/715 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:34 - INFO - filelock -   Lock 140573998039696 released on /root/.cache/huggingface/transformers/4c0f9feb4f27d0baac7cada8552ee966286be516b2e925d322f8d275915e2cdb.9d6c2c65959d735e45573bd3230b64f1fe4ffbdabafba97dbb5822d2673312a7.lock\n",
            "09/07/2021 20:10:35 - INFO - filelock -   Lock 140574044997968 acquired on /root/.cache/huggingface/transformers/f91c5efe33bd9eae2353aa0711152f4ca23d5dc0ad8f1cbc8b5c2f36dba0233c.0b363692abe6210ed650f4122e4fda3502a6eef3b9b51f7ef7d9f378d0054425.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a1cc9ecc90994711afd7e4438c9eaf10",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/890M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:10:52 - INFO - filelock -   Lock 140574044997968 released on /root/.cache/huggingface/transformers/f91c5efe33bd9eae2353aa0711152f4ca23d5dc0ad8f1cbc8b5c2f36dba0233c.0b363692abe6210ed650f4122e4fda3502a6eef3b9b51f7ef7d9f378d0054425.lock\n",
            "Some weights of the model checkpoint at ahotrod/albert_xxlargev1_squad2_512 were not used when initializing AlbertModel: ['qa_outputs.weight', 'qa_outputs.bias']\n",
            "- This IS expected if you are initializing AlbertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing AlbertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "09/07/2021 20:10:59 - INFO - filelock -   Lock 140573998040208 acquired on /root/.cache/huggingface/transformers/9b9eacfd4d9df8961ff8d516fdabc682a1a8619bb62ef49e0a7aff725a6f1e14.d6110e25022b713452eb83d5bfa8ae64530995a93d8e694fe52e05aa85dd3a7d.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1dce9281130845369f67784be04272e5",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/760k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:11:00 - INFO - filelock -   Lock 140573998040208 released on /root/.cache/huggingface/transformers/9b9eacfd4d9df8961ff8d516fdabc682a1a8619bb62ef49e0a7aff725a6f1e14.d6110e25022b713452eb83d5bfa8ae64530995a93d8e694fe52e05aa85dd3a7d.lock\n",
            "09/07/2021 20:11:00 - INFO - filelock -   Lock 140573998041488 acquired on /root/.cache/huggingface/transformers/823683742b9faf73a10ec0c4f2166c3c551444da7583c0690b546d2c53439117.623993453f3f6b9f6ad831899812f482e5cde100e664124feb3a6446d69a26bf.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3aaec7207aea4601b5c0af1b24f5ea99",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/156 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:11:01 - INFO - filelock -   Lock 140573998041488 released on /root/.cache/huggingface/transformers/823683742b9faf73a10ec0c4f2166c3c551444da7583c0690b546d2c53439117.623993453f3f6b9f6ad831899812f482e5cde100e664124feb3a6446d69a26bf.lock\n",
            "09/07/2021 20:11:01 - INFO - filelock -   Lock 140573998014672 acquired on /root/.cache/huggingface/transformers/bf060af73f5ebd53064c22f19e52d2b6855f936cb9549a1bc48c0c0e150dca23.76ea01b4b85ac16e2cec55c398cba7a943d89ab21dfdd973f6630a152e4b9aed.lock\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ce5a55d24a5647f8bba7b0487693f2c1",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "09/07/2021 20:11:01 - INFO - filelock -   Lock 140573998014672 released on /root/.cache/huggingface/transformers/bf060af73f5ebd53064c22f19e52d2b6855f936cb9549a1bc48c0c0e150dca23.76ea01b4b85ac16e2cec55c398cba7a943d89ab21dfdd973f6630a152e4b9aed.lock\n",
            "09/07/2021 20:11:01 - WARNING - farm.utils -   ML Logging is turned off. No parameters, metrics or artifacts will be logged to MLFlow.\n",
            "09/07/2021 20:11:01 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:11:01 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:11:01 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:11:01 - INFO - farm.utils -   Automatic Mixed Precision: None\n",
            "09/07/2021 20:11:02 - INFO - farm.infer -   Got ya 3 parallel workers to do inference ...\n",
            "09/07/2021 20:11:02 - INFO - farm.infer -    0    0    0 \n",
            "09/07/2021 20:11:02 - INFO - farm.infer -   /w\\  /w\\  /w\\\n",
            "09/07/2021 20:11:02 - INFO - farm.infer -   /'\\  / \\  /'\\\n",
            "09/07/2021 20:11:02 - INFO - farm.infer -       \n",
            "09/07/2021 20:11:02 - INFO - farm.utils -   Using device: CUDA \n",
            "09/07/2021 20:11:02 - INFO - farm.utils -   Number of GPUs: 1\n",
            "09/07/2021 20:11:02 - INFO - farm.utils -   Distributed Training: False\n",
            "09/07/2021 20:11:02 - INFO - farm.utils -   Automatic Mixed Precision: None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "COn01kBjNgNj"
      },
      "source": [
        "### Kreiranje Pipeline-a i postavljanje pitanja\n",
        "\n",
        "Testiracemo 4 kombinacije Reader-a i Retriever-a:\n",
        "1.   TF-IDF i RoBERTa\n",
        "2.   TF-IDF i ALBERT\n",
        "3.   B25 i RoBERTa\n",
        "4.   B25 i ALBERT\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WHWm4a2pc-GN"
      },
      "source": [
        "from haystack.pipeline import ExtractiveQAPipeline\n",
        "\n",
        "pipe_tfidf_roberta = ExtractiveQAPipeline(reader_roberta, retriever_tfidf)\n",
        "pipe_tfidf_albert = ExtractiveQAPipeline(reader_albert, retriever_tfidf)\n",
        "pipe_b25_roberta = ExtractiveQAPipeline(reader_roberta, retriever_b25)\n",
        "pipe_b25_albert = ExtractiveQAPipeline(reader_albert, retriever_b25)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qSz7wuW9dDqN",
        "outputId": "b274d3d9-60fa-4c01-fe7e-63ef5dea0cb0"
      },
      "source": [
        "# query = 'What is the impact of coronavirus on pregnant women?'\n",
        "query = 'What is the impact of coronavirus on babies?'\n",
        "#query = 'Which country has the best survival rate?'\n",
        "\n",
        "prediction_tfidf_roberta = pipe_tfidf_roberta.run(query = query, top_k_retriever = 10, top_k_reader = 2)\n",
        "prediction_tfidf_albert = pipe_tfidf_albert.run(query = query, top_k_retriever = 10, top_k_reader = 2)\n",
        "prediction_b25_roberta = pipe_b25_roberta.run(query = query, top_k_retriever = 10, top_k_reader = 2)\n",
        "prediction_b25_albert = pipe_b25_albert.run(query = query, top_k_retriever = 10, top_k_reader = 2)"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  4.06 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.48 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.52 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:00<00:00,  2.05 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:00<00:00,  2.32 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  4.27 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.52 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  3.54 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:01<00:00,  1.81 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.94 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:03<00:00,  3.98s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:17<00:00, 17.66s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:15<00:00, 15.71s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:24<00:00, 12.30s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:22<00:00, 11.15s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:06<00:00,  6.09s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:17<00:00, 17.90s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:07<00:00,  7.63s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:29<00:00, 14.96s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:15<00:00, 15.63s/ Batches]\n",
            "09/07/2021 20:41:48 - INFO - elasticsearch -   POST http://localhost:9200/document/_search [status:200 request:0.020s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.37 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:00<00:00,  2.08 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:01<00:00,  1.15 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  3.31 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  2.25 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.40 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:01<00:00,  1.65 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.33 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.46 Batches/s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:00<00:00,  1.43 Batches/s]\n",
            "09/07/2021 20:41:56 - INFO - elasticsearch -   POST http://localhost:9200/document/_search [status:200 request:0.013s]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:16<00:00, 16.86s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:22<00:00, 11.40s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 3/3 [00:40<00:00, 13.62s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:07<00:00,  7.92s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:11<00:00, 11.09s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:19<00:00, 19.02s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:29<00:00, 14.84s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:17<00:00, 17.41s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:16<00:00, 16.59s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:18<00:00, 18.61s/ Batches]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w4axQQtndI2j",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "96ec7801-6cd5-4b92-cbb0-2760961b8565"
      },
      "source": [
        "from haystack.utils import print_answers\n",
        "\n",
        "for prediction in [prediction_tfidf_roberta, prediction_tfidf_albert, prediction_b25_roberta, prediction_b25_albert]:\n",
        "  print(f\"Postavljeno pitanje: {prediction['query']}\")\n",
        "  print('\\n')\n",
        "  for i in range(2):\n",
        "      print(f\"#{i+1}\")\n",
        "      print(f\"Odgovor: {prediction['answers'][i]['answer']}\")\n",
        "      print(f\"Naziv rada: {prediction['answers'][i]['meta']['name']}\")\n",
        "      print(f\"Dodatni kontekst: {prediction['answers'][i]['context']}\")\n",
        "      print(f\"Ocena sigurnosti (od 0 do 1): {prediction['answers'][i]['score']}\")\n",
        "  print('\\n===================================================\\n')"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Postavljeno pitanje: What is the impact of coronavirus on babies?\n",
            "\n",
            "\n",
            "#1\n",
            "Odgovor: very contagious\n",
            "Naziv rada: Clinical overview Promoting attachment between parents and neonates despite the COVID-19 pandemic\n",
            "Dodatni kontekst: es (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) .National quarantine measures have included prohibited or restricted visits to infants or limited them to one parent or caregiver, even if none of the parties have COVID-19. We analyse how the primary needs of neonates can be balanced with infection control measures and the advice and support healthcare professionals can provide for parents.Coronaviruses are usually spread by respiratory droplets and COVID-19 is very contagious. Early data showed that infants only accounted for 1-5% of infections, were often asymptomatic and had milder cases than adults (20) . This may also mean they were less likely to be tested.This article is protected by copyright. All rights reservedThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 binds to the human angiotensin-converting enzyme-2 receptor and its expression in neonates, and on the placenta, are not well known (21) . COVID-19 has\n",
            "Ocena sigurnosti (od 0 do 1): 0.5956169366836548\n",
            "#2\n",
            "Odgovor: the epidemic recedes for R 0 < 1\n",
            "Naziv rada: Optimal control of epidemics with purely non-pharmaceutical interventions\n",
            "Dodatni kontekst: that is estimated from reported data (see Fig. 2 (b)) as Γ ≈ 0.26d -1 (doubling time of infections within Γ -1 log (2) ≈ 2.67d). Substituting Eq. (20) in Eqs. (1b)-(1c) yieldsand the relation between the growth rate and R 0 :Note that Eq. (21) is equivalent to the equation for the leading eigenvalue η (1) + if the whole population is susceptible, i.e. Γ = η (1) + |¯S =N(0) (see Appendix A). Hence, Eq. (21) implies that the exponential growth rate Γ changes sign at R 0 = 1, i.e., the epidemic recedes for R 0 < 1. The mean incubation period was reported to be 5.1d, but there are indications that the latency time may be shorter [66] . Assuming the onset of infectiousness 2.5d before the onset of symptoms, this implies an average latency period of γ -1 l = 2.6d, i.e., the latency period is assumed to equal roughly half of the incubation period. The reported values of the basic reproduction number R 0 are heavily scattered. According to the Robert Koch Institute, serious estimates range bet\n",
            "Ocena sigurnosti (od 0 do 1): 0.3176107406616211\n",
            "\n",
            "===================================================\n",
            "\n",
            "Postavljeno pitanje: What is the impact of coronavirus on babies?\n",
            "\n",
            "\n",
            "#1\n",
            "Odgovor: babies were milder and prognosis was less severe\n",
            "Naziv rada: The clinical characteristics of pediatric inpatients with SARS-CoV-2 infection：a meta-analysis and systematic review\n",
            "Dodatni kontekst: hers of them were infected with SARS-CoV-2, 3 displayed symptoms before delivery and 1 after delivery, but none of the babies had any severe complications 34 . In addition, the study on 9 pregnant women with SARS-CoV-2 infection suggested that there is no obvious evidence of intrauterine infection caused by vertical transmission from mother to child 35 . In a word, newborn babies are easy to be infected by SARS-CoV-2. compared with adults, the clinical features in newborn babies were milder and prognosis was less severe. Intrauterine vertical transmission is possible but obvious evidence is still lacking.As for the diagnosis of pediatric patients, all of them were confirmed SARS-CoV-2 infection by RT-PCR of samples that were taken from upper nasopharyngeal swabs. In addition, rectal swabs were used to identify viral This article is protected by copyright. All rights reserved.shedding through gastrointestinal tract in parts of studies 22 . At present, the therapeutic methods for pediatr\n",
            "Ocena sigurnosti (od 0 do 1): 0.8848477602005005\n",
            "#2\n",
            "Odgovor: neurodevelopmental disabilities remain an issue\n",
            "Naziv rada: Clinical overview Promoting attachment between parents and neonates despite the COVID-19 pandemic\n",
            "Dodatni kontekst: wedish recommendations can allow couplet care with strict conditions, such as no need for NICU admission, single family rooms and enough nursing staff (14) .A closed incubator in a pressure-negative room, or at least with no pressure, is recommended if the baby is at risk of COVID-19.Infant-parent attachment is fragile and can be interrupted by early separation, the infant's illness and NICU admission (3, 25) . Although medical advances mean more vulnerable babies survive, neurodevelopmental disabilities remain an issue. Bonding to the primary caregiver is fundamental to children's growth and development (26) and the neurobiological processes involved in the maturation of the brain and activation of neuroendocrine systems are driven by attachment-related behavioursThis article is protected by copyright. All rights reserved (27) . This attachment is facilitated by couplet care or no separation from birth. The initial hours and days after birth are vital for establishing breastfeeding, d\n",
            "Ocena sigurnosti (od 0 do 1): 0.8311677575111389\n",
            "\n",
            "===================================================\n",
            "\n",
            "Postavljeno pitanje: What is the impact of coronavirus on babies?\n",
            "\n",
            "\n",
            "#1\n",
            "Odgovor: rare\n",
            "Naziv rada: Value Frameworks for Vaccines: Which Dimensions Are Most Relevant?\n",
            "Dodatni kontekst: he disease (against which VACCINEX protects) is more common in disadvantaged groups.The disease (against which VACCINEX protects) is rare in disadvantaged groups.Target group: affects migrantsThe disease (against which VACCINEX protects) is more common in migrants.The disease (against which VACCINEX protects) is rare in migrants.Target group: affects babiesThe disease (against which VACCINEX protects) is more common in babies and young children.The disease (against which VACCINEX protects) is rare in babies and young children.Target group: affects elderlyThe disease (against which VACCINEX protects) is more common in elderly people.The disease (against which VACCINEX protects) is rare in elderly people.Target group: affects LGBTThe disease (against which VACCINEX protects) is more common in people from the LGBT (lesbian-gay-bisexual-transgender) community.The disease (against which VACCINEX protects) is rare in people from the LGBT (lesbian-gay-bisexual-transgender) community.Target gr\n",
            "Ocena sigurnosti (od 0 do 1): 0.688169538974762\n",
            "#2\n",
            "Odgovor: very contagious\n",
            "Naziv rada: Clinical overview Promoting attachment between parents and neonates despite the COVID-19 pandemic\n",
            "Dodatni kontekst: es (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) .National quarantine measures have included prohibited or restricted visits to infants or limited them to one parent or caregiver, even if none of the parties have COVID-19. We analyse how the primary needs of neonates can be balanced with infection control measures and the advice and support healthcare professionals can provide for parents.Coronaviruses are usually spread by respiratory droplets and COVID-19 is very contagious. Early data showed that infants only accounted for 1-5% of infections, were often asymptomatic and had milder cases than adults (20) . This may also mean they were less likely to be tested.This article is protected by copyright. All rights reservedThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 binds to the human angiotensin-converting enzyme-2 receptor and its expression in neonates, and on the placenta, are not well known (21) . COVID-19 has\n",
            "Ocena sigurnosti (od 0 do 1): 0.5956169366836548\n",
            "\n",
            "===================================================\n",
            "\n",
            "Postavljeno pitanje: What is the impact of coronavirus on babies?\n",
            "\n",
            "\n",
            "#1\n",
            "Odgovor: not clear\n",
            "Naziv rada: Journal Pre-proof COVID-19 infection among asymptomatic and symptomatic pregnant women: Two weeks of confirmed presentations to an affiliated pair of New York City hospitals COVID-19 infection among asymptomatic and symptomatic pregnant women: Two weeks of confirmed presentations to an affiliated pair of New York City hospitals\n",
            "Dodatni kontekst: r, or postoperative shortness of breath) arise in untested women, COVID-19 infection should be part of the differential diagnosis and testing is indicated.The implications of asymptomatic COVID-19 infection in pregnant women are just now being understood. This report may have important implications for obstetric practice during the pandemic, but our understanding will continue to evolve as we follow these and other similar patients. Ramifications for their infants and family members are also not clear, particularly if the patients never become symptomatic. Importantly, this manuscript does not provide the important denominator of total number of women tested for COVID-19 during the study period. This was an intentional decision given changing testing strategies over the study time period that we believe would limit conclusions. An evaluation of the COVID-19 detection rate with our current hospital testing strategy that includes universal testing of admitted patients is the focus of a p\n",
            "Ocena sigurnosti (od 0 do 1): 0.9260127544403076\n",
            "#2\n",
            "Odgovor: unable to complete fetal-neonatal transition and breathe independently\n",
            "Naziv rada: Antenatal N-acetylcysteine to improve outcomes of premature infants with intra-amniotic infection and inflammation (Triple I): randomized clinical trial\n",
            "Dodatni kontekst: g incidence. 38 In premature babies born at ≤28 weeks, the prevalence of BPD is~40%, which concurs with the 38% rate observed in our placebo group. 39 Risk factors for BPD unanimously point to exposure to invasive mechanical ventilation and supplemental oxygen after birth, which lead to volutrauma, barotrauma, and oxidative stress-induced lung injury. 40 These therapies are, however, required to ensure an adequate gas exchange of premature infants who are often unable to complete fetal-neonatal transition and breathe independently.NAC is a well-established mucolytic agent via the supply of CYS, which induces molecular disaggregation of the mucoprotein constituents. 41 This mucolytic effect of NAC would facilitate lung fluid clearance in the immediate postnatal period. NAC may have other favorable effects on respiratory outcomes. For example, in vitro, NAC disrupts biofilm formation and affects adherence to respiratory epithelial cells of relevant pathogens. 42, 43 For these reasons, se\n",
            "Ocena sigurnosti (od 0 do 1): 0.8947485089302063\n",
            "\n",
            "===================================================\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uQ1pvByk7RyH"
      },
      "source": [
        "### Korisnička pretraga\n",
        "\n",
        "Nakon eksperimenta sa različitim kombinacijama algoritama, za pretragu informacija na osnovu korisničkog unosa odabraćemo B25 Retriever i ALBERT Reader. Ovo jeste najsporija kombinacija, ali daje rezultate sa najvecom sigurnošću (što potvrđuje i zvanična dokumentacija)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 511,
          "referenced_widgets": [
            "a0adf9c480e8411e9bd679c0c5a33b1d",
            "d13b4ca3700f4a58bff355b7fc1c699d",
            "1b48993419084cf3b949153bc95e67c7",
            "77ef60e63d2b45f8abd934b58ffd940a",
            "c6642126350e439b94eb23a43ca3eaa9"
          ]
        },
        "id": "ddg6KvLjsyVR",
        "cellView": "form",
        "outputId": "947583f1-5460-43f5-a9be-e9299472c434"
      },
      "source": [
        "#@title Unesite pitanje ili skup reci za koji zelite da se izvrsi pretraga:\n",
        "\n",
        "query = 'What is the impact of coronavirus on pregnant women?' #@param {type:\"string\"}\n",
        "\n",
        "\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display\n",
        "button = widgets.Button(description=\"Pretrazi\")\n",
        "output = widgets.Output()\n",
        "\n",
        "def on_button_clicked(b):\n",
        "  prediction = pipe_b25_albert.run(query = query, top_k_retriever = 10, top_k_reader = 2)\n",
        "  print(f\"Postavljeno pitanje: {prediction['query']}\")\n",
        "  print('\\n')\n",
        "  for i in range(2):\n",
        "      print(f\"#{i+1}\")\n",
        "      print(f\"Odgovor: {prediction['answers'][i]['answer']}\")\n",
        "      print(f\"Naziv rada: {prediction['answers'][i]['meta']['name']}\")\n",
        "      print(f\"Dodatni kontekst: {prediction['answers'][i]['context']}\")\n",
        "      print(f\"Ocena sigurnosti (od 0 do 1): {prediction['answers'][i]['score']}\")\n",
        "  print('\\n===================================================\\n')\n",
        "\n",
        "\n",
        "button.on_click(on_button_clicked)\n",
        "display(button, output)\n"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Inferencing Samples: 100%|██████████| 1/1 [00:16<00:00, 16.59s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:14<00:00, 14.01s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:16<00:00, 16.85s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:03<00:00,  3.27s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:14<00:00, 14.56s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:16<00:00, 16.22s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 2/2 [00:29<00:00, 14.64s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:05<00:00,  5.02s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:10<00:00, 10.75s/ Batches]\n",
            "Inferencing Samples: 100%|██████████| 1/1 [00:18<00:00, 18.02s/ Batches]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Postavljeno pitanje: What is the impact of coronavirus on pregnant women?\n",
            "\n",
            "\n",
            "#1\n",
            "Odgovor: lower weeks gestation\n",
            "Naziv rada: Chinese Maternal and Child Health Association\n",
            "Dodatni kontekst: 38 pregnant women participated in the study, with 2012 in Group 1 and 1326 in Group 2 ( Figure 1 ). Table 1 shows the comparisons of the baseline characteristics between the two groups before and after propensity-score matching. The majority of women overall were between 30 and 39 years old (n =1832, 54.9%), nondrinkers (n =2834, 97.7%), and nonsmokers (n =2885, 99.5%). Compared with Group 1, Group 2 was more likely to be older (31 vs 30 years old, P<0.001), earlier in pregnancy (i.e., lower weeks gestation) (12.1 vs 12.7 weeks, P<0.001) and less likely to be a current drinker (1.4% vs. 2.7%, P=0.03). With propensity score matching, 727 women exposed to the COVID-19 outbreak (Group 2) were matched with 727 women in Group 1. After matching, the P values of all variables were greater than 0.05, indicating that no significant differences existed between the two groups ( Table 1) .Women in Group 2 who were exposed to the COVID-19 outbreak had significantly higher FT3 (5.7 vs. 5.2 pmol/L, P\n",
            "Ocena sigurnosti (od 0 do 1): 0.9623708128929138\n",
            "#2\n",
            "Odgovor: severe life and psychological impacts\n",
            "Naziv rada: Highlights Sleep Conditions Associate with Anxiety and Depression Symptoms among Pregnant Women during the Epidemic of Coronavirus Disease 2019 (COVID-19) in Shenzhen\n",
            "Dodatni kontekst: irmed or suspected coronavirus infections among their acquaintances (1.6%), or even none report among their family members (0.0%).Nearly all women (99.6%) reported having taken precautions against the coronavirus infection. Only 2.0% of them thought they were at high risk of being infected by the coronavirus, while 15.3% and 82.7% of the respondents considered moderate or low risk, respectively. More than thirty percent (31.6%) and ten percent (10.9%) of pregnant women reported severe life and psychological impacts by this novel virus, respectively.During the epidemic of COVID-19, one fifth of pregnant women did not have physical exercise, 57.5% of them took exercise for less than 30 minutes, and the remaining one fifth spent over 30 minutes in exercise. About half of the participants (49.4%) spent over five hours per day in the internet or social media, whereas 10.8% of pregnant women followed news related to the coronavirus for more than three hours per day. Sleep conditions of pregn\n",
            "Ocena sigurnosti (od 0 do 1): 0.9621395468711853\n",
            "\n",
            "===================================================\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a0adf9c480e8411e9bd679c0c5a33b1d",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Button(description='Pretrazi', style=ButtonStyle())"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "77ef60e63d2b45f8abd934b58ffd940a",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Output()"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}