hw-01.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LG90jYcETE37"
      },
      "source": [
        "# 一些前置條件"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "96j49XECvTtp"
      },
      "source": [
        "## install & import"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "TgKOQ3ajTOmO"
      },
      "outputs": [],
      "source": [
        "import time, json\n",
        "import multiprocessing\n",
        "import functools\n",
        "import requests\n",
        "from tqdm.auto import tqdm\n",
        "from elasticsearch import Elasticsearch\n",
        "import tiktoken"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6t9EE3H7ZDk_"
      },
      "source": [
        "# Question 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4qIbFW_RayRa",
        "outputId": "e416526d-aad8-47c4-92ae-bce4ef47057a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "ObjectApiResponse({'name': 'c2b4fa8bc5dd', 'cluster_name': 'docker-cluster', 'cluster_uuid': 'o45Uoe5wTJuJsG2VFmAJKg', 'version': {'number': '8.4.3', 'build_flavor': 'default', 'build_type': 'docker', 'build_hash': '42f05b9372a9a4a470db3b52817899b99a76ee73', 'build_date': '2022-10-04T07:17:24.662462378Z', 'build_snapshot': False, 'lucene_version': '9.3.0', 'minimum_wire_compatibility_version': '7.17.0', 'minimum_index_compatibility_version': '7.0.0'}, 'tagline': 'You Know, for Search'})"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "es_client = Elasticsearch('http://localhost:9200')\n",
        "es_client.info()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3gokx-Sjau5e"
      },
      "source": [
        "# Question 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wNie7zVkbPD_"
      },
      "source": [
        "## prepare documents"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lP6weTcnTX4a",
        "outputId": "b25b3e7d-2bf2-41f7-af21-781910ff51e0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'text': \"The purpose of this document is to capture frequently asked technical questions\\nThe exact day and hour of the course will be 15th Jan 2024 at 17h00. The course will start with the first  “Office Hours'' live.1\\nSubscribe to course public Google Calendar (it works from Desktop only).\\nRegister before the course starts using this link.\\nJoin the course Telegram channel with announcements.\\nDon’t forget to register in DataTalks.Club's Slack and join the channel.\",\n",
              " 'section': 'General course-related questions',\n",
              " 'question': 'Course - When will the course start?',\n",
              " 'course': 'data-engineering-zoomcamp'}"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "docs_url = 'https://github.com/DataTalksClub/llm-zoomcamp/blob/main/01-intro/documents.json?raw=1'\n",
        "docs_response = requests.get(docs_url)\n",
        "documents_raw = docs_response.json()\n",
        "\n",
        "documents = []\n",
        "\n",
        "for course in documents_raw:\n",
        "    course_name = course['course']\n",
        "\n",
        "    for doc in course['documents']:\n",
        "        doc['course'] = course_name\n",
        "        documents.append(doc)\n",
        "\n",
        "# data 結構\n",
        "documents[0]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SD__84BQlBVR"
      },
      "source": [
        "# 共用的變數"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "id": "qz-KLCuMlGpB"
      },
      "outputs": [],
      "source": [
        "index_name = \"questions\"\n",
        "\n",
        "index_settings = {\n",
        "    \"settings\": {\n",
        "        \"number_of_shards\": 1,\n",
        "        \"number_of_replicas\": 0\n",
        "    },\n",
        "    \"mappings\": {\n",
        "        \"properties\": {\n",
        "            \"text\": {\"type\": \"text\"},\n",
        "            \"section\": {\"type\": \"text\"},\n",
        "            \"question\": {\"type\": \"text\"},\n",
        "            \"course\": {\"type\": \"keyword\"}\n",
        "        }\n",
        "    }\n",
        "}\n",
        "\n",
        "query = \"How do I execute a command in a running docker container?\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EfszuplOcseV"
      },
      "source": [
        "## index data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0zuLwhyYaD30",
        "outputId": "325fe7d8-4085-4f22-95b0-2f88f060d24d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "ObjectApiResponse({'acknowledged': True, 'shards_acknowledged': True, 'index': 'questions'})"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "es_client.indices.create(index=index_name, body=index_settings)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "dd3f12e287614d0da92d121646dab4c8",
            "b2331af9f6264af88568c4107b4185a5",
            "30c6777987d14526aec9dea8c8792299",
            "bd8723acaf4b42d08c049f4742dd0c5e",
            "32a51113ca8e427986e6d54a1a464fb8",
            "df22832f7659460481119206a9d4f57f",
            "f4205c12391f4b81a581a8ff31a71626",
            "bdbcb84e1e934e618fb1b72f5af29b77",
            "811360e383c045c0bfbac20947d0b9af",
            "865f495f2d1f4317910fda0e570d9c85",
            "0467b0efb8da456e89636468afaf8745"
          ]
        },
        "id": "-gU3pbanbyHO",
        "outputId": "de89a3fe-3812-47b9-996f-a7a0967b1a9e"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dd3f12e287614d0da92d121646dab4c8",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "  0%|          | 0/948 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "for doc in tqdm(documents):\n",
        "    es_client.index(index=index_name, document=doc)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qaRlDag2ch0F"
      },
      "source": [
        "# Question 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "id": "J_W6e3fQcj9F"
      },
      "outputs": [],
      "source": [
        "def search_q3(query):\n",
        "    search_query = {\n",
        "        \"size\": 1,\n",
        "        \"query\": {\n",
        "            \"bool\": {\n",
        "                \"must\": {\n",
        "                    \"multi_match\": {\n",
        "                        \"query\": query,\n",
        "                        \"fields\": [\"question^4\", \"text\"],\n",
        "                        \"type\": \"best_fields\"\n",
        "                    }\n",
        "                }\n",
        "            }\n",
        "        }\n",
        "    }\n",
        "\n",
        "    response = es_client.search(index=index_name, body=search_query)\n",
        "\n",
        "    return response['hits']['hits']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TULG8iRrewbV",
        "outputId": "06049173-0560-49b8-a35e-73fcaf50a178"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "84.050095"
            ]
          },
          "execution_count": 39,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "search_q3(query)[0]['_score']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Soji_dK8fhYI"
      },
      "source": [
        "# Questino 4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "EgD3ezBIfk07"
      },
      "outputs": [],
      "source": [
        "def search_q4(query):\n",
        "    search_query = {\n",
        "        \"size\": 3,\n",
        "        \"query\": {\n",
        "            \"bool\": {\n",
        "                \"must\": {\n",
        "                    \"multi_match\": {\n",
        "                        \"query\": query,\n",
        "                        \"fields\": [\"question^4\", \"text\"],\n",
        "                        \"type\": \"best_fields\"\n",
        "                    }\n",
        "                },\n",
        "                \"filter\": {\n",
        "                    \"term\": {\n",
        "                        \"course\": \"machine-learning-zoomcamp\"\n",
        "                    }\n",
        "                }\n",
        "            }\n",
        "        }\n",
        "    }\n",
        "\n",
        "    response = es_client.search(index=index_name, body=search_query)\n",
        "\n",
        "    return response['hits']['hits']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 40,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "bGdHC9qJfxE2",
        "outputId": "313945eb-661f-4705-943d-f7cdf67f8474"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'How do I copy files from a different folder into docker container’s working directory?'"
            ]
          },
          "execution_count": 40,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "q4_list = search_q4(query)\n",
        "q4_list[2]['_source']['question']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P84AGb7wh17m"
      },
      "source": [
        "# Question 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "id": "6gRbpeohh5ub"
      },
      "outputs": [],
      "source": [
        "context_template = \"\"\"\n",
        "Q: {question}\n",
        "A: {text}\n",
        "\"\"\".strip()\n",
        "\n",
        "prompt_template = \"\"\"\n",
        "You're a course teaching assistant. Answer the QUESTION based on the CONTEXT from the FAQ database.\n",
        "Use only the facts from the CONTEXT when answering the QUESTION.\n",
        "\n",
        "QUESTION: {question}\n",
        "\n",
        "CONTEXT:\n",
        "{context}\n",
        "\"\"\".strip()\n",
        "\n",
        "def get_prompt(query, answer):\n",
        "  context = \"\"\n",
        "\n",
        "  for q in q4_list:\n",
        "    context = context + context_template.format(question=q['_source']['question'], text=q['_source']['text']) + \"\\n\\n\"\n",
        "\n",
        "  return prompt_template.format(question=query, context=context).strip()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TIcTWCARlnaD",
        "outputId": "d3f93e34-9d63-49aa-be0b-60bfc7a86f3c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1462"
            ]
          },
          "execution_count": 51,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# q4_list[0]['_source']\n",
        "final_prompt = get_prompt(query, q4_list)\n",
        "len(final_prompt)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XaR6mwUMn8a4"
      },
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gpE9ioaen9-b"
      },
      "source": [
        "# Question 6"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0d-mgdhjn_zo",
        "outputId": "9c596e30-e385-40bf-ec48-3c1f5ef2ae48"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "322"
            ]
          },
          "execution_count": 54,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "encoding = tiktoken.encoding_for_model(\"gpt-4o\")\n",
        "tokens = encoding.encode(final_prompt)\n",
        "len(tokens)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EcJaEg41oT1v"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "0467b0efb8da456e89636468afaf8745": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "30c6777987d14526aec9dea8c8792299": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "FloatProgressModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_bdbcb84e1e934e618fb1b72f5af29b77",
            "max": 948,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_811360e383c045c0bfbac20947d0b9af",
            "value": 948
          }
        },
        "32a51113ca8e427986e6d54a1a464fb8": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "811360e383c045c0bfbac20947d0b9af": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "ProgressStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "865f495f2d1f4317910fda0e570d9c85": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b2331af9f6264af88568c4107b4185a5": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_df22832f7659460481119206a9d4f57f",
            "placeholder": "​",
            "style": "IPY_MODEL_f4205c12391f4b81a581a8ff31a71626",
            "value": "100%"
          }
        },
        "bd8723acaf4b42d08c049f4742dd0c5e": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HTMLModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_865f495f2d1f4317910fda0e570d9c85",
            "placeholder": "​",
            "style": "IPY_MODEL_0467b0efb8da456e89636468afaf8745",
            "value": " 948/948 [00:15&lt;00:00, 74.21it/s]"
          }
        },
        "bdbcb84e1e934e618fb1b72f5af29b77": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "dd3f12e287614d0da92d121646dab4c8": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "HBoxModel",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_b2331af9f6264af88568c4107b4185a5",
              "IPY_MODEL_30c6777987d14526aec9dea8c8792299",
              "IPY_MODEL_bd8723acaf4b42d08c049f4742dd0c5e"
            ],
            "layout": "IPY_MODEL_32a51113ca8e427986e6d54a1a464fb8"
          }
        },
        "df22832f7659460481119206a9d4f57f": {
          "model_module": "@jupyter-widgets/base",
          "model_module_version": "1.2.0",
          "model_name": "LayoutModel",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "f4205c12391f4b81a581a8ff31a71626": {
          "model_module": "@jupyter-widgets/controls",
          "model_module_version": "1.5.0",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}