Twelve_Labs_API_E_Learning_Demo.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oT_AjsAurpIR"
      },
      "source": [
        "Twelve Labs Video Understanding Platform, currently in beta, offers an API suite for integrating a state-of-the-art (“SOTA”) foundation model that understands contextual information from your videos, making it accessible to your applications. The API is organized around REST and is compatible with most programming languages. You can also use Postman or other REST clients to send requests and view responses.\n",
        "\n",
        "The following diagram illustrates the architecture of the Twelve Labs Video Understanding Platform and how different parts interact:\n",
        "\n",
        "![](https://files.readme.io/5fb7a80-image.png)\n",
        "\n",
        "## 1 - Setup and Requirements\n",
        "The Twelve Labs Video Understanding API is currently in open beta. Before you begin, [sign up](https://api.twelvelabs.io) for a free account, or if you already have one, [sign in](https://api.twelvelabs.io).\n",
        "\n",
        "You will receive a signup code that you can use to create an account. Once you have created an account, you can access the API Dashboard.\n",
        "\n",
        "This demo will use an existing account. To make calls to the API, you need your secret key and specify the URL of the API. You can use environment variables to pass configuration to your application."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ydgqdioXpkq1",
        "outputId": "17c5f438-065e-457a-c8a5-c73be43fabab"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: API_KEY=tlk_0BKG1ZQ08FCHV92X59YZG3NR7T1Q\n",
            "env: API_URL=https://api.twelvelabs.io/p/v1.2\n"
          ]
        }
      ],
      "source": [
        "# Specify the API key and the URL of the API\n",
        "%env API_KEY=tlk_0BKG1ZQ08FCHV92X59YZG3NR7T1Q\n",
        "%env API_URL=https://api.twelvelabs.io/p/v1.2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "31isfodVuYPx"
      },
      "source": [
        "The next step is to install the required package."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RpJCQ42RuxFF",
        "outputId": "b6132b03-2e0c-49a6-9e80-b9cc5e358f90"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (2.31.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests) (3.3.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests) (2.0.6)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests) (2023.7.22)\n"
          ]
        }
      ],
      "source": [
        "!pip install requests"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XgLXWW74u59S"
      },
      "source": [
        "You want to import the required Python packages and retrieve the API key as well as the API URL."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GW9vRq7NuycH"
      },
      "outputs": [],
      "source": [
        "# Import the required packages\n",
        "import requests\n",
        "import glob\n",
        "from pprint import pprint\n",
        "import os"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jpAEIBMavBZv"
      },
      "outputs": [],
      "source": [
        "# Retrieve the URL of the API and my API key\n",
        "API_URL = os.getenv(\"API_URL\")\n",
        "assert API_URL\n",
        "\n",
        "API_KEY = os.getenv(\"API_KEY\")\n",
        "assert API_KEY"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zUkH6-QZuZ6Y"
      },
      "source": [
        "## 2 - Index API\n",
        "The next step is to [create a video index](https://docs.twelvelabs.io/v1.2/docs/create-indexes). An index groups one or more video vectors and is the most granular level at which you can perform a search."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dHHc7mOEvaUS"
      },
      "source": [
        "### 2.1 - Create An Index\n",
        "An index is a basic unit to organize and store your video data (video embeddings and metadata) to facilitate information retrieval and processing.\n",
        "\n",
        "You can use indexes to group related videos. For example, if you want to upload multiple videos from a car race, Twelve Labs recommends you create a single index and upload all the videos to it. Then, to find a specific moment in that race, you call the /search endpoint once, passing it the unique identifier of the index.\n",
        "\n",
        "When creating a new index, you must specify the following information:\n",
        "\n",
        "*   **Name**: Use a brief and descriptive name to facilitate future reference and management.\n",
        "*   **Engine configuration**: Provide a list containing the [video understanding engines](https://docs.twelvelabs.io/v1.2/docs/video-understanding-engines) and the associated [engine options](https://docs.twelvelabs.io/v1.2/docs/indexing-options) you want to enable.\n",
        "\n",
        "#### Video Understanding Engines\n",
        "Twelve Labs' video understanding engines consist of a family of deep neural networks built on our multimodal foundation model for video understanding that you can use for the following downstream tasks:\n",
        "\n",
        "*   Search using natural language queries\n",
        "*   Zero-shot classification\n",
        "*   Generate concise textual representations\n",
        "\n",
        "Twelve Labs provides two distinct engine types - embedding and generative, each serving unique purposes in multimodal video understanding.\n",
        "*   **Embedding engines**: These engines are proficient at performing tasks such as search and classification, enabling enhanced video understanding. We recommend choosing Marengo2.5.\n",
        "*   **Generative engines**: These engines specialize in generating concise textual representations for video. We recommend choosing Pegasus1.0.\n",
        "\n",
        "#### Engine Options\n",
        "\n",
        "Engine options indicate the types of information a video understanding engine will process. When creating a new index, you must specify the engines and the associated engines options that you want to enable.\n",
        "\n",
        "The following engine options are available:\n",
        "\n",
        "*   **visual**: This option allows you to analyze video content as you would see and hear from it, including actions, objects, sounds, and events, and excluding human speech.\n",
        "*   **conversation**: This option allows you to analyze human speech within your videos.\n",
        "*   **text_in_video**: This option allows you to detect and extract text (OCR) shown within your videos.\n",
        "*   **logo**: This option allows you to identify the presence of brand logos within your videos."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZSmhDwX-wtUR",
        "outputId": "4a430634-648a-43b6-bb14-e179d7eb7f27"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 201\n",
            "{'_id': '6528dd338f9cd95a98cbd072'}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/indexes` endpoint\n",
        "INDEXES_URL = f\"{API_URL}/indexes\"\n",
        "\n",
        "# Specify the name of the index\n",
        "INDEX_NAME = \"E-Learning Videos\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named data\n",
        "data = {\n",
        "  \"engines\": [\n",
        "    {\n",
        "      \"engine_name\": \"marengo2.5\",  # Configure the video understanding engine\n",
        "      \"engine_options\": [\"visual\", \"conversation\", \"text_in_video\", \"logo\"]  # Specify the engine options\n",
        "    },\n",
        "    {\n",
        "      \"engine_name\": \"pegasus1\",  # Configure the video understanding engine\n",
        "      \"engine_options\": [\"visual\", \"conversation\"]  # Specify the engine options\n",
        "    }\n",
        "  ],\n",
        "  \"index_name\": INDEX_NAME,\n",
        "  \"addons\": [\"thumbnail\"]  # Enable the thumbnail generation feature\n",
        "}\n",
        "\n",
        "# Create an index\n",
        "response = requests.post(INDEXES_URL, headers=headers, json=data)\n",
        "\n",
        "# Store the unique identifier of your index\n",
        "INDEX_ID = response.json().get('_id')\n",
        "\n",
        "# Print the status code and response\n",
        "print(f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cgGpRwEMyeQ6"
      },
      "source": [
        "### 2.2 - Upload A Video\n",
        "Once you've created an index, you can upload a video. When the video has finished uploading, the API service will automatically create a rich set of vectors containing all the information it needs to perform fast, semantic, accurate, and scalable searches.\n",
        "\n",
        "For this demo, we will work with sports videos. The video resolution must be greater or equal than 360p and less or equal than 4K.\n",
        "\n",
        "Below, we show how to upload a video file from YouTube: [How to Fillet a Salmon Into 10 Equal Pieces | Gordon Ramsay](https://www.youtube.com/watch?v=T21phFISCmw)\n",
        "\n",
        "The API service will retrieve the file directly from the specified URL, so your application doesn't have to store the video locally and upload the bytes. Our platform currently supports only YouTube as an external provider, but we will add support for additional providers in the future."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D3ob1vEEbdGV",
        "outputId": "52238960-30dd-43c1-a554-e2502e8eadb8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 201\n",
            "{'_id': '6528dd3c8f9cd95a98cbd073'}\n"
          ]
        }
      ],
      "source": [
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare the /tasks/external-provider endpoint\n",
        "TASKS_URL = f\"{API_URL}/tasks/external-provider\"\n",
        "\n",
        "# Construct the body of the request\n",
        "data = {\n",
        "    \"index_id\": INDEX_ID,  # Specify the unique ID of the index\n",
        "    \"url\": \"https://www.youtube.com/watch?v=T21phFISCmw\",  # Specify the YouTube URL of the video\n",
        "}\n",
        "\n",
        "# Upload the video\n",
        "response = requests.post(TASKS_URL, headers=headers, json=data)\n",
        "\n",
        "# Store the ID of the task in a variable named TASK_ID\n",
        "TASK_ID = response.json().get(\"_id\")\n",
        "\n",
        "# Print the status code and response\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n7kjB-kq3d5C"
      },
      "source": [
        "The API service must have finished indexing the video before it becomes searchable. You can use the `GET` method of the `/tasks/{_id}` endpoint to monitor the indexing process. Construct the URL for monitoring the indexing process based on the `TASK_ID` variable you’ve declared in the previous step, and wait until the status shows as `ready`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cYuL6V3L3b-T",
        "outputId": "2d3ee412-4f26-4671-d8b2-e30764099a53"
      },
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Start uploading video\n"
          ]
        }
      ],
      "source": [
        "import time\n",
        "\n",
        "# Define starting time\n",
        "start = time.time()\n",
        "print(\"Start uploading video\")\n",
        "\n",
        "# Monitor the indexing process\n",
        "TASK_STATUS_URL = f\"{API_URL}/tasks/{TASK_ID}\"\n",
        "while True:\n",
        "    response = requests.get(TASK_STATUS_URL, headers=headers)\n",
        "    STATUS = response.json().get(\"status\")\n",
        "    if STATUS == \"ready\":\n",
        "        print(f\"Status code: {STATUS}\")\n",
        "        break\n",
        "    time.sleep(10)\n",
        "\n",
        "# Define ending time\n",
        "end = time.time()\n",
        "print(\"Finish uploading video\")\n",
        "print(\"Time elapsed (in seconds): \", end - start)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xdZsX_Fh5Fcq"
      },
      "outputs": [],
      "source": [
        "# Retrieve the unique identifier of the video\n",
        "VIDEO_ID = response.json().get('video_id')\n",
        "\n",
        "# Print the status code, the unique identifier of the video, and the response\n",
        "print(f\"VIDEO ID: {VIDEO_ID}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Note that the 1.2 version of the API is in beta, and videos can take longer to upload and process when using the Pegasus video understanding engine.\n",
        "\n",
        "For the purpose of this demo, let's use a sample account with sample indexes that has been preloaded with videos. These indexes have been processed with both the Marengo 2.5 and the Pegasus 1.0 engines."
      ],
      "metadata": {
        "id": "tZbewIGklP9N"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Specify the API key and the API URL of the sample account\n",
        "%env API_KEY=tlk_2K9E0BB2W5TJY227437G62VR1617\n",
        "%env API_URL=https://api.twelvelabs.io/v1.2"
      ],
      "metadata": {
        "id": "xieMT4vclTTH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Retrieve the new API URL and the new API key\n",
        "API_URL = os.getenv(\"API_URL\")\n",
        "assert API_URL\n",
        "\n",
        "API_KEY = os.getenv(\"API_KEY\")\n",
        "assert API_KEY"
      ],
      "metadata": {
        "id": "50OKjHralYFa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tm6cSWWruuc-"
      },
      "source": [
        "### 2.3 - List Indexes\n",
        "Let's return a list of the indexes in this account. The API returns indexes sorted by creation date, with the oldest indexes at the top of the list."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oqzlUiGTu6E1",
        "outputId": "89246a7b-6e1e-487b-ca19-b5f06f6d6d64"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'_id': '6528dc4b8f9cd95a98cbd06b',\n",
            "           'addons': ['thumbnail'],\n",
            "           'created_at': '2023-10-13T05:57:31.155Z',\n",
            "           'engines': [{'engine_name': 'marengo2.5',\n",
            "                        'engine_options': ['visual',\n",
            "                                           'conversation',\n",
            "                                           'text_in_video',\n",
            "                                           'logo']},\n",
            "                       {'engine_name': 'pegasus1',\n",
            "                        'engine_options': ['visual', 'conversation']}],\n",
            "           'expires_at': '2024-01-11T05:57:31.155Z',\n",
            "           'index_name': 'Security Videos',\n",
            "           'total_duration': 0,\n",
            "           'updated_at': '2023-10-13T05:57:54.766Z',\n",
            "           'video_count': 0},\n",
            "          {'_id': '6526d94f23c1347ffbe3a1fa',\n",
            "           'addons': ['thumbnail'],\n",
            "           'created_at': '2023-10-11T17:20:15.766Z',\n",
            "           'engines': [{'engine_name': 'marengo2.5',\n",
            "                        'engine_options': ['visual',\n",
            "                                           'conversation',\n",
            "                                           'text_in_video',\n",
            "                                           'logo']},\n",
            "                       {'engine_name': 'pegasus1',\n",
            "                        'engine_options': ['visual', 'conversation']}],\n",
            "           'expires_at': '2024-01-09T17:20:15.766Z',\n",
            "           'index_name': 'Sports Videos',\n",
            "           'total_duration': 74,\n",
            "           'updated_at': '2023-10-11T17:28:17.012Z',\n",
            "           'video_count': 1}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'page': 1,\n",
            "               'total_page': 1,\n",
            "               'total_results': 2}}\n"
          ]
        }
      ],
      "source": [
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY,\n",
        "    \"Content-Type\": \"application/json\"\n",
        "}\n",
        "\n",
        "# List indexes\n",
        "url = f\"{API_URL}/indexes?page=1&page_limit=10&sort_by=created_at&sort_option=desc\"\n",
        "\n",
        "response = requests.get(url, headers=headers)\n",
        "print(f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "For this demo, let's go with E-Learning videos."
      ],
      "metadata": {
        "id": "M9yjN8UqlcjU"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HSlZg-S_84cX",
        "outputId": "f1ae234b-6203-48f0-e1e3-15ffcaaed8e1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: INDEX_ID=6527e59e74b5a5ab84015cf5\n"
          ]
        }
      ],
      "source": [
        "# Specify the unique identifier of the \"E-Learning\" existing index\n",
        "%env INDEX_ID=6527e59e74b5a5ab84015cf5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SMR6AnEh8tob"
      },
      "source": [
        "### 2.4 - List Videos In An Index\n",
        "Let's list all the videos in this existing \"E-Learning\" index for verification."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jYGhUdm19FAM",
        "outputId": "f376e313-a65e-4b47-b9d2-813a4354483c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6527e59e74b5a5ab84015cf5\n",
            "Status code: 200\n",
            "{'data': [{'_id': '6528a8e643e8c47e4eb47e5c',\n",
            "           'created_at': '2023-10-13T02:18:09Z',\n",
            "           'metadata': {'duration': 711,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': '9 Riddles Only People with High IQ Can '\n",
            "                                    'Solve',\n",
            "                        'fps': 30,\n",
            "                        'height': 720,\n",
            "                        'size': 34850057,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-13T02:18:14Z'},\n",
            "          {'_id': '6528a8d043e8c47e4eb47e5b',\n",
            "           'created_at': '2023-10-13T02:17:48Z',\n",
            "           'metadata': {'duration': 521,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'How to take good pictures of people',\n",
            "                        'fps': 30,\n",
            "                        'height': 720,\n",
            "                        'size': 25698754,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-13T02:17:52Z'},\n",
            "          {'_id': '6528a82443e8c47e4eb47e59',\n",
            "           'created_at': '2023-10-13T02:14:55Z',\n",
            "           'metadata': {'duration': 577,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'Why Large Language Models Hallucinate',\n",
            "                        'fps': 30,\n",
            "                        'height': 720,\n",
            "                        'size': 26360388,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-13T02:15:00Z'},\n",
            "          {'_id': '65282bf243e8c47e4eb47e4d',\n",
            "           'created_at': '2023-10-12T17:25:02Z',\n",
            "           'metadata': {'duration': 267,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'The benefits of good posture - Murat '\n",
            "                                    'Dalkilinç',\n",
            "                        'fps': 24,\n",
            "                        'height': 720,\n",
            "                        'size': 6856457,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:25:06Z'},\n",
            "          {'_id': '65282bf143e8c47e4eb47e4b',\n",
            "           'created_at': '2023-10-12T17:25:01Z',\n",
            "           'metadata': {'duration': 235,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'STOP WASTING TIME - Best Motivational '\n",
            "                                    'Video',\n",
            "                        'fps': 25,\n",
            "                        'height': 720,\n",
            "                        'size': 27489841,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:25:05Z'},\n",
            "          {'_id': '65282bf243e8c47e4eb47e4c',\n",
            "           'created_at': '2023-10-12T17:25:00Z',\n",
            "           'metadata': {'duration': 795,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'Photosynthesis: Crash Course Biology #8',\n",
            "                        'fps': 24,\n",
            "                        'height': 720,\n",
            "                        'size': 64747344,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:25:06Z'},\n",
            "          {'_id': '65282bef43e8c47e4eb47e4a',\n",
            "           'created_at': '2023-10-12T17:24:59Z',\n",
            "           'metadata': {'duration': 800,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'Basic multiplication | Multiplication and '\n",
            "                                    'division | Arithmetic | Khan Academy',\n",
            "                        'fps': 15,\n",
            "                        'height': 360,\n",
            "                        'size': 12841881,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 640},\n",
            "           'updated_at': '2023-10-12T17:25:03Z'},\n",
            "          {'_id': '65282b9243e8c47e4eb47e48',\n",
            "           'created_at': '2023-10-12T17:23:23Z',\n",
            "           'metadata': {'duration': 615,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'Rotate to a Better Golf Swing - Golf with '\n",
            "                                    'Michele Low',\n",
            "                        'fps': 25,\n",
            "                        'height': 720,\n",
            "                        'size': 45039096,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:23:30Z'},\n",
            "          {'_id': '65282b9043e8c47e4eb47e47',\n",
            "           'created_at': '2023-10-12T17:23:22Z',\n",
            "           'metadata': {'duration': 252,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'How to Play Chess',\n",
            "                        'fps': 24,\n",
            "                        'height': 720,\n",
            "                        'size': 9519681,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:23:28Z'},\n",
            "          {'_id': '65282b8f43e8c47e4eb47e46',\n",
            "           'created_at': '2023-10-12T17:23:21Z',\n",
            "           'metadata': {'duration': 103,\n",
            "                        'engine_ids': ['marengo2.5', 'pegasus1'],\n",
            "                        'filename': 'Norm Duke - Learn To Bowl Competitively',\n",
            "                        'fps': 30,\n",
            "                        'height': 720,\n",
            "                        'size': 11660325,\n",
            "                        'vispresso_index_id': '6527e59e73878b24f9377743',\n",
            "                        'width': 1280},\n",
            "           'updated_at': '2023-10-12T17:23:27Z'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'page': 1,\n",
            "               'total_duration': 10102,\n",
            "               'total_page': 3,\n",
            "               'total_results': 26}}\n"
          ]
        }
      ],
      "source": [
        "# Retrieve the unique identifier of the existing index\n",
        "INDEX_ID = os.getenv(\"INDEX_ID\")\n",
        "print (INDEX_ID)\n",
        "assert INDEX_ID\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY,\n",
        "    \"Content-Type\": \"application/json\"\n",
        "}\n",
        "\n",
        "# List all the videos in an index\n",
        "INDEXES_VIDEOS_URL = f\"{API_URL}/indexes/{INDEX_ID}/videos\"\n",
        "\n",
        "response = requests.get(INDEXES_VIDEOS_URL, headers=headers)\n",
        "print(f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WIvyhd9qwCPR"
      },
      "source": [
        "## 3 - Search API\n",
        "Twelve Labs provides a holistic understanding of your videos, moving beyond the limitations of relying solely on individual types of data like keywords, metadata, or transcriptions. By simultaneously integrating all available forms of information, including images, sounds, spoken words, and on-screen text, the platform captures the complex relationships among these elements for a more human-like interpretation.\n",
        "\n",
        "Search options specify the source of information the engine uses when performing a search. The following values are supported:\n",
        "\n",
        "*   **visual**: This option allows you to analyze video content as you would see and hear from it, including actions, objects, sounds, and events, and excluding human speech. The following examples are valid search terms: \"birds flying near a castle\", \"sun shining on water\", \"chickens on the road\", \"an officer holding a child's hand.\", \"crowd cheering in the stadium.\"\n",
        "*   **conversation**: This option allows you to analyze human speech within your videos.\n",
        "*   **text_in_video**: This option allows you to detect and extract text (OCR) shown within your videos.\n",
        "*   **logo**: This option allows you to identify the presence of brand logos within your videos."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GbgqFjaZt7mu"
      },
      "source": [
        "### 3.1 - Visual\n",
        "The platform allows you to analyze video content as you would see and hear from it, including actions, objects, sounds, and events, excluding human speech. The following example sets the value of the `search_options` parameter to  `[\"visual\"]` to search for \"**Knit red stitches**\" using visual cues:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NNvNPU_n-Hqx",
        "outputId": "b13e303d-8c32-4fb8-c15f-36956b163020"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'confidence': 'high',\n",
            "           'end': 13.28125,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 83.58,\n",
            "           'start': 0,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/1.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=d817741ce85b4de096616a6e250efa3b8a7931c11de864bce1479bc6bb38c6f9',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 42.1875,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 83.49,\n",
            "           'start': 34.84375,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/35.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=1f627bd4b783674524f44f0c0ac09e9a32ea8948712132251f60d6c338e47803',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 457.296875,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 83.32,\n",
            "           'start': 427.21875,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/428.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6dd086ca9343ea327863e594b37607e74d5634585d9e281b7cf656bbd04036cb',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 427.21875,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 83.11,\n",
            "           'start': 42.1875,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/43.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=3151503508befef13b00c4107d83cca1da182c32f15d3ce5c5e09282d0cfdb4d',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 20.0625,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 72.08,\n",
            "           'start': 13.28125,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/14.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=8e1c9f5aac80189d5a4e1fc1299609841ee198919fa9e9f52c983781c2f95fa6',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 484,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 71.54,\n",
            "           'start': 461.296875,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/462.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=24f4290a48ebbd23ad85ded9d23879d210acc272a082917f6420c34a1a65c83e',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 461.296875,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 68.17,\n",
            "           'start': 457.296875,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/458.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=dc3b8d6d2aa716c8356942a6475df510f8df98adab594295a40aa6cbd1d9d84c',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 31.796875,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 67.8,\n",
            "           'start': 20.0625,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/21.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=69302a13bdbdf511311f9e460c086f0c617283efbc0752480f6f4c217790d9fd',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 34.84375,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 60.09,\n",
            "           'start': 31.796875,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/32.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=cbafabbe4a402aa35bbd45c278e193899d6c92e00b7e5f8ebbf1d17164c15c4a',\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'confidence': 'low',\n",
            "           'end': 604.15625,\n",
            "           'metadata': [{'type': 'visual'}],\n",
            "           'score': 46.61,\n",
            "           'start': 596.15625,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bef43e8c47e4eb47e4a/597.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4fc5086425ecef9f6cbe108ae37c943828b4c3e7d5a128c03fa6cc64028b15f9',\n",
            "           'video_id': '65282bef43e8c47e4eb47e4a'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'page_expired_at': '2023-10-13T03:32:44Z',\n",
            "               'total_results': 10},\n",
            " 'search_pool': {'index_id': '6527e59e74b5a5ab84015cf5',\n",
            "                 'total_count': 23,\n",
            "                 'total_duration': 8293}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/search` endpoint\n",
        "SEARCH_URL = f\"{API_URL}/search/\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "query = \"Knit red stitches\"\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "    \"query\": query,  # Specify your search query\n",
        "    \"index_id\": INDEX_ID,  # Indicate the unique identifier of your index\n",
        "    \"search_options\": [\"visual\"],  # Specify the search options\n",
        "}\n",
        "\n",
        "# Make a search request\n",
        "response = requests.post(SEARCH_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "HxjRwt6-tlBG",
        "outputId": "4191c050-04e9-4b3a-a06d-1eeb1b061c1a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Search Query:  Knit red stitches\n",
            "Option: Visual\n"
          ]
        },
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          "output_type": "display_data",
          "data": {
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.58\n"
          ]
        },
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          "output_type": "display_data",
          "data": {
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.49\n"
          ]
        },
        {
          "output_type": "display_data",
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/428.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6dd086ca9343ea327863e594b37607e74d5634585d9e281b7cf656bbd04036cb\"/>"
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            "Confidence Level: high\n",
            "Confidence Score: 83.32\n"
          ]
        },
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          "output_type": "display_data",
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.11\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/14.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=8e1c9f5aac80189d5a4e1fc1299609841ee198919fa9e9f52c983781c2f95fa6\"/>"
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          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 72.08\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/462.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=24f4290a48ebbd23ad85ded9d23879d210acc272a082917f6420c34a1a65c83e\"/>"
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              "<IPython.core.display.Image object>"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 71.54\n"
          ]
        },
        {
          "output_type": "display_data",
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              "<IPython.core.display.Image object>"
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 68.17\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/21.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=69302a13bdbdf511311f9e460c086f0c617283efbc0752480f6f4c217790d9fd\"/>"
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              "<IPython.core.display.Image object>"
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          "metadata": {}
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 67.8\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527ee5843e8c47e4eb47e2c/32.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=cbafabbe4a402aa35bbd45c278e193899d6c92e00b7e5f8ebbf1d17164c15c4a\"/>"
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              "<IPython.core.display.Image object>"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 60.09\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bef43e8c47e4eb47e4a/597.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033244Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4fc5086425ecef9f6cbe108ae37c943828b4c3e7d5a128c03fa6cc64028b15f9\"/>"
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              "<IPython.core.display.Image object>"
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          "metadata": {}
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: low\n",
            "Confidence Score: 46.61\n"
          ]
        }
      ],
      "source": [
        "# Import libraries to display visual in the notebook\n",
        "from IPython.display import display\n",
        "from IPython.display import Image\n",
        "\n",
        "# Display a list of thumbnail URLs of the returning videos\n",
        "res = response.json()\n",
        "print (\"Search Query: \", query)\n",
        "print (\"Option:\", \"Visual\")\n",
        "\n",
        "for item in res[\"data\"]:\n",
        "  display(Image(url=item[\"thumbnail_url\"]))\n",
        "  print(\"Confidence Level:\", item[\"confidence\"])\n",
        "  print(\"Confidence Score:\", item[\"score\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WxKmySMmAutH"
      },
      "source": [
        "### 3.2 - Conversation\n",
        "The platform allows you to analyze human speech within your videos.\n",
        "The following example sets the value of the `search_options` parameter to `[\"conversation\"]` to perform a semantic search and returns the matches for the specified search term - \"**Set up a tent**\":"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qLVIrR7tBPV0",
        "outputId": "2e3e00dd-0172-4aa7-8468-378f8846170c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'confidence': 'high',\n",
            "           'end': 108.75,\n",
            "           'metadata': [{'text': '  Now that your tent is up, you will want to '\n",
            "                                 'secure it to the ground. Most tents will '\n",
            "                                 'have nylon webbing straps that loop or have '\n",
            "                                 'grumme at their edges, place a peg through '\n",
            "                                 'each of the nylon straps along the edge of '\n",
            "                                 'the tent and pull them away from the tent so '\n",
            "                                 'that the floor is stretched tight. Now push '\n",
            "                                 'the peg into the ground at a 45 degree '\n",
            "                                 'angle. This will ensure your tent stays '\n",
            "                                 'secure in windy conditions.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 85.3,\n",
            "           'start': 81.3,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/82.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=89367d3496fba744fe909691c974827e0bacf9e5a20594554d75058e2b3671ea',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 45.47,\n",
            "           'metadata': [{'text': 'Next, roll out the tent and line up your '\n",
            "                                 'door in the desired position.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 84.84,\n",
            "           'start': 41.52,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/42.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=e2a0cd85340fd357e6bf1577b245605bbfb62006dc4461e3f7f70773de957f54',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 39.479,\n",
            "           'metadata': [{'text': ' Also be sure to keep a good distance from '\n",
            "                                 'your fire pit in your tent bag, you should '\n",
            "                                 'have the tent body. The tent fly some poles, '\n",
            "                                 'pegs and ideally a ground sheet and some '\n",
            "                                 'guidelines. If you have a ground sheet, '\n",
            "                                 'place it over your selected location.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 84.77,\n",
            "           'start': 19.62,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/20.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=ade0ae1449a585595fc385fda6d28067537aeebae840f4f5e1532f426a8d6bf7',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 13.27,\n",
            "           'metadata': [{'text': 'Once you arrive at the campsite, you want to '\n",
            "                                 'choose the best place to raise your tent. '\n",
            "                                 'Look for a nice flat spot without any roots '\n",
            "                                 'or rocks.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 83.66,\n",
            "           'start': 4.32,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/5.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=72c7f6b1de8f94747b7d236af1a33d512d9562a1b5b28d4433b7fe21d735f2d9',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 72.25,\n",
            "           'metadata': [{'text': 'This will raise the tent body and is easier '\n",
            "                                 'when performed by two people with the first '\n",
            "                                 'pole attached to the tent. Repeat the same '\n",
            "                                 'steps for the second pole.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 83.58,\n",
            "           'start': 63.27,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/64.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6b3b1b100b8c87a086f8e4dcf906e11df57573a8a5b838b4cfa5a32375b3144f',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 62.619,\n",
            "           'metadata': [{'text': ' After assembling the tent poles, insert one '\n",
            "                                 'end of a pole into the grommet on the corner '\n",
            "                                 'of the tent body, then work your way across '\n",
            "                                 'the tent by securing the poles using the '\n",
            "                                 'clips. Now attach the end of the pool on the '\n",
            "                                 'opposite side of the tent to the grommet.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 83.44,\n",
            "           'start': 47.84,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/48.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=a62f123364ea3404efca894b9d8039e757e8b1d82b8d8305750f1387c257e471',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 151.149,\n",
            "           'metadata': [{'text': 'Make sure to keep all your gear dry and '\n",
            "                                 'organized and pack it all back into your '\n",
            "                                 'tent bag.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 83.35,\n",
            "           'start': 146.02,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/147.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=c418a97423f493b4b0bf240e4f83df25f0fd9f8eff8eafb18f770d8c54ca8ae3',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'medium',\n",
            "           'end': 115.099,\n",
            "           'metadata': [{'text': 'You will now want to attach the tent fly. It '\n",
            "                                 'will keep you dry in case of rainy weather.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 82.7,\n",
            "           'start': 109.889,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/110.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=69868384f953e0448831314766359d88a645a836c895ad162f7060db69eb288a',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'medium',\n",
            "           'end': 129.169,\n",
            "           'metadata': [{'text': ' Toss the fly over the tent like a blanket, '\n",
            "                                 'make sure that the front of the tent fly '\n",
            "                                 'lines up with the entrance of the tent. Most '\n",
            "                                 'flies will attach to the poles of the tent '\n",
            "                                 'body or to the edges of the tent where the '\n",
            "                                 'poles are attached.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 82.6,\n",
            "           'start': 116.389,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/117.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=424cc51bd40f8189bf518d9e393ff981e20e1ae8e1ec95eff8bc9448f8a72fb9',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'},\n",
            "          {'confidence': 'medium',\n",
            "           'end': 18.629,\n",
            "           'metadata': [{'text': 'Avoid hilly sites where water could trickle '\n",
            "                                 'down and collect into a pool under your '\n",
            "                                 'tent.',\n",
            "                         'type': 'conversation'}],\n",
            "           'score': 81.78,\n",
            "           'start': 13.97,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282b8d43e8c47e4eb47e45/14.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033408Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=52df61960623696c4e244c23d2ba157f072329b8e883dfb607368a1acc8a6193',\n",
            "           'video_id': '65282b8d43e8c47e4eb47e45'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'next_page_token': '0f83bb17-dc39-4947-b3ce-e34bfcfbd8c5-1',\n",
            "               'page_expired_at': '2023-10-13T03:34:08Z',\n",
            "               'total_results': 18},\n",
            " 'search_pool': {'index_id': '6527e59e74b5a5ab84015cf5',\n",
            "                 'total_count': 23,\n",
            "                 'total_duration': 8293}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/search` endpoint\n",
        "SEARCH_URL = f\"{API_URL}/search/\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "query = \"Set up a tent\"\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "    \"query\": query,  # Specify your search query\n",
        "    \"index_id\": INDEX_ID,  # Indicate the unique identifier of your index\n",
        "    \"search_options\": [\"conversation\"],  # Specify the search options\n",
        "    \"conversation_option\": \"semantic\",  # Specifty the conversation option\n",
        "}\n",
        "\n",
        "# Make a search request\n",
        "response = requests.post(SEARCH_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "m5r56Sks45nd",
        "outputId": "8b3acb65-78c3-4785-868e-5358d474134f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Search Query:  Set up a tent\n",
            "Option: Conversation\n",
            "GT Text:    Now that your tent is up, you will want to secure it to the ground. Most tents will have nylon webbing straps that loop or have grumme at their edges, place a peg through each of the nylon straps along the edge of the tent and pull them away from the tent so that the floor is stretched tight. Now push the peg into the ground at a 45 degree angle. This will ensure your tent stays secure in windy conditions.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 85.3\n",
            "GT Text:  Next, roll out the tent and line up your door in the desired position.\n"
          ]
        },
        {
          "output_type": "display_data",
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        {
          "output_type": "stream",
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 84.84\n",
            "GT Text:   Also be sure to keep a good distance from your fire pit in your tent bag, you should have the tent body. The tent fly some poles, pegs and ideally a ground sheet and some guidelines. If you have a ground sheet, place it over your selected location.\n"
          ]
        },
        {
          "output_type": "display_data",
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 84.77\n",
            "GT Text:  Once you arrive at the campsite, you want to choose the best place to raise your tent. Look for a nice flat spot without any roots or rocks.\n"
          ]
        },
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.66\n",
            "GT Text:  This will raise the tent body and is easier when performed by two people with the first pole attached to the tent. Repeat the same steps for the second pole.\n"
          ]
        },
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          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.58\n",
            "GT Text:   After assembling the tent poles, insert one end of a pole into the grommet on the corner of the tent body, then work your way across the tent by securing the poles using the clips. Now attach the end of the pool on the opposite side of the tent to the grommet.\n"
          ]
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.44\n",
            "GT Text:  Make sure to keep all your gear dry and organized and pack it all back into your tent bag.\n"
          ]
        },
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 83.35\n",
            "GT Text:  You will now want to attach the tent fly. It will keep you dry in case of rainy weather.\n"
          ]
        },
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: medium\n",
            "Confidence Score: 82.7\n",
            "GT Text:   Toss the fly over the tent like a blanket, make sure that the front of the tent fly lines up with the entrance of the tent. Most flies will attach to the poles of the tent body or to the edges of the tent where the poles are attached.\n"
          ]
        },
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          "name": "stdout",
          "text": [
            "Confidence Level: medium\n",
            "Confidence Score: 82.6\n",
            "GT Text:  Avoid hilly sites where water could trickle down and collect into a pool under your tent.\n"
          ]
        },
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: medium\n",
            "Confidence Score: 81.78\n"
          ]
        }
      ],
      "source": [
        "# Display a list of thumbnail URLs of the returning videos\n",
        "res = response.json()\n",
        "print (\"Search Query: \", query)\n",
        "print (\"Option:\", \"Conversation\")\n",
        "\n",
        "for item in res[\"data\"]:\n",
        "  print (\"GT Text: \", item[\"metadata\"][0][\"text\"])\n",
        "  display(Image(url=item[\"thumbnail_url\"]))\n",
        "  print(\"Confidence Level:\", item[\"confidence\"])\n",
        "  print(\"Confidence Score:\", item[\"score\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qVl9drJYBfun"
      },
      "source": [
        "### 3.3 - Text In Video\n",
        "The platform allows you to detect and extract text (OCR) shown within your videos. The following example sets the value of the `search_options` parameter to `[\"text_in_video\"]` to search for text that matches \"**Time waits for no man**\":"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2c9zJvy9B37z",
        "outputId": "e6e86644-1c3b-4735-d999-6810365e7d2c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'confidence': 'high',\n",
            "           'end': 10,\n",
            "           'metadata': [{'text': 'And time waits for no man.',\n",
            "                         'type': 'text_in_video'}],\n",
            "           'score': 92.28,\n",
            "           'start': 8,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bf143e8c47e4eb47e4b/9.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033750Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=c8909f20b8f0dea7011dcf775f82fbc52685ad7fa5c0551cb010ecf7771f85e2',\n",
            "           'video_id': '65282bf143e8c47e4eb47e4b'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'page_expired_at': '2023-10-13T03:37:50Z',\n",
            "               'total_results': 1},\n",
            " 'search_pool': {'index_id': '6527e59e74b5a5ab84015cf5',\n",
            "                 'total_count': 23,\n",
            "                 'total_duration': 8293}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/search` endpoint\n",
        "SEARCH_URL = f\"{API_URL}/search/\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "query = \"Time waits for no man\"\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "    \"query\": query,  # Specify your search query\n",
        "    \"index_id\": INDEX_ID,  # Indicate the unique identifier of your index\n",
        "    \"search_options\": [\"text_in_video\"],  # Specify the search options\n",
        "}\n",
        "\n",
        "# Make a search request\n",
        "response = requests.post(SEARCH_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "SuzeF1Bc5EfR",
        "outputId": "4b3a9795-4a4f-4e50-9a95-c35eb4332857"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Search Query:  Time waits for no man\n",
            "Option: Text In Video\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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              "<IPython.core.display.Image object>"
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 92.28\n"
          ]
        }
      ],
      "source": [
        "# Display a list of thumbnail URLs of the returning videos\n",
        "res = response.json()\n",
        "print (\"Search Query: \", query)\n",
        "print (\"Option:\", \"Text In Video\")\n",
        "\n",
        "for item in res[\"data\"]:\n",
        "  display(Image(url=item[\"thumbnail_url\"]))\n",
        "  print(\"Confidence Level:\", item[\"confidence\"])\n",
        "  print(\"Confidence Score:\", item[\"score\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uNjYx--BuZFA"
      },
      "source": [
        "### 3.4 - Logo\n",
        "The platform allows you to detect and extract brand logos as shown within your videos. For this, call the [`POST`](/reference/make-search-request) method of the `/search` endpoint with the following parameters:\n",
        "\n",
        "- `query`:  The name of the company\n",
        "- `search_options`:  The source of information the platform uses (`logo`)\n",
        "- `index_id`: The unique identifier of the index you've previously created\n",
        "\n",
        "The example code below finds when the TED logo appears in your videos:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4Z86ZDk5urAS",
        "outputId": "88e360b2-59a9-401d-8131-ff0b2a8616eb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'confidence': 'high',\n",
            "           'end': 5,\n",
            "           'metadata': [{'text': 'Ted', 'type': 'logo'}],\n",
            "           'score': 92.28,\n",
            "           'start': 2,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bf243e8c47e4eb47e4d/3.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033907Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b971868bdf4da8a64a4e7bbb8e8fe148243d980ce866ab06bc75bafe28799ace',\n",
            "           'video_id': '65282bf243e8c47e4eb47e4d'},\n",
            "          {'confidence': 'high',\n",
            "           'end': 266,\n",
            "           'metadata': [{'text': 'Ted', 'type': 'logo'}],\n",
            "           'score': 92.28,\n",
            "           'start': 257,\n",
            "           'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bf243e8c47e4eb47e4d/258.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033907Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b41732b450f93fdff808e5717bea4a4a429a461a26a96b6bd66117640a2b1ea8',\n",
            "           'video_id': '65282bf243e8c47e4eb47e4d'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'page_expired_at': '2023-10-13T03:39:07Z',\n",
            "               'total_results': 2},\n",
            " 'search_pool': {'index_id': '6527e59e74b5a5ab84015cf5',\n",
            "                 'total_count': 23,\n",
            "                 'total_duration': 8293}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/search` endpoint\n",
        "SEARCH_URL = f\"{API_URL}/search/\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "query = \"TED\"\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "    \"query\": query,  # Specify your search query\n",
        "    \"index_id\": INDEX_ID,  # Indicate the unique identifier of your index\n",
        "    \"search_options\": [\"logo\"],  # Specify the search options\n",
        "}\n",
        "\n",
        "# Make a search request\n",
        "response = requests.post(SEARCH_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 850
        },
        "id": "dzld_8Ex0b6N",
        "outputId": "c250ff54-4eec-439f-b871-73ca78f71e49"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Search Query:  TED\n",
            "Option: Logo\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bf243e8c47e4eb47e4d/3.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033907Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b971868bdf4da8a64a4e7bbb8e8fe148243d980ce866ab06bc75bafe28799ace\"/>"
            ],
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 92.28\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<img src=\"https://project-one-thumbnail.s3.us-west-2.amazonaws.com/65282bf243e8c47e4eb47e4d/258.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T033907Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b41732b450f93fdff808e5717bea4a4a429a461a26a96b6bd66117640a2b1ea8\"/>"
            ],
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Confidence Level: high\n",
            "Confidence Score: 92.28\n"
          ]
        }
      ],
      "source": [
        "# Display a list of thumbnail URLs of the returning videos\n",
        "res = response.json()\n",
        "print (\"Search Query: \", query)\n",
        "print (\"Option:\", \"Logo\")\n",
        "\n",
        "for item in res[\"data\"]:\n",
        "  display(Image(url=item[\"thumbnail_url\"]))\n",
        "  print(\"Confidence Level:\", item[\"confidence\"])\n",
        "  print(\"Confidence Score:\", item[\"score\"])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TQ2Hsn0LwKT2"
      },
      "source": [
        "## 4 - Classify API\n",
        "Content classification is the process of organizing content into distinct categories based on specific criteria. This process helps you organize your videos into more manageable and useful categories, making them easier to find, access, and use.\n",
        "\n",
        "If you have an extensive library of videos you'd like to analyze to identify specific actions or entities, manually finding the segments that meet your criteria is time-consuming. With a single API call, the Twelve Labs platform automatically identifies the actions and entities you specify whenever they appear in your videos and assigns a likelihood score that indicates how likely those actions or entities are to occur in each of your videos.\n",
        "\n",
        "The platform allows you to define either a simple or a hierarchical taxonomy system to organize your videos.  A simple taxonomy system is composed of a single set of categories, similar to [YouTube video categories](https://developers.google.com/youtube/v3/docs/videoCategories/list). A hierarchical taxonomy system is composed of categories and subcategories, similar to [IAB Tech Lab Content Taxonomy](https://iabtechlab.com/standards/content-taxonomy/).\n",
        "\n",
        "The following parameters allow you to control how classification works:\n",
        "\n",
        "- `classes`: An array of objects containing the names and definitions of the entities or actions that the platform must identify. Each object is composed of the following fields:\n",
        "  - `name`: A string representing the name you want to give this class.\n",
        "  - `prompts`: An array of strings that specifies what the class contains. The platform uses the values you provide in this array to classify your videos.\n",
        "- `threshold`: A numerical value that indicates the confidence level of the video segment's match with a certain class.\n",
        "- `ratio`: A numerical value that displays the ratio of the sum of the lengths of the matching video segments divided by the total length of the video."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KYlCycWht90s"
      },
      "source": [
        "### Classifying videos based on one class\n",
        "The following example code classifies the content of your videos based on one classes - `Technology & Computing`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mBhALApwaLox",
        "outputId": "0ff338bb-9539-40d2-fa39-bd6688c7a202"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'classes': [{'duration_ratio': 0.82,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 96.88}],\n",
            "           'video_id': '6527e78943e8c47e4eb47e1b'},\n",
            "          {'classes': [{'duration_ratio': 0.86,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 95.79}],\n",
            "           'video_id': '6527e78c43e8c47e4eb47e1d'},\n",
            "          {'classes': [{'duration_ratio': 0.58,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 88.74}],\n",
            "           'video_id': '6527e94843e8c47e4eb47e1f'},\n",
            "          {'classes': [{'duration_ratio': 0.51,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 87.2}],\n",
            "           'video_id': '6527e94143e8c47e4eb47e1e'}],\n",
            " 'page_info': {'limit_per_page': 4,\n",
            "               'next_page_token': '',\n",
            "               'page_expired_at': '2023-10-13T03:59:40Z',\n",
            "               'prev_page_token': '',\n",
            "               'total_results': 4}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/classify/bulk` endpoint\n",
        "CLASSIFY_BULK_URL = f\"{API_URL}/classify/bulk\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data =  {\n",
        "  \"options\": [\n",
        "        \"visual\",\n",
        "        \"conversation\",\n",
        "        \"text_in_video\"\n",
        "  ],  # Specify how the platform will analyze your video\n",
        "  \"index_id\": INDEX_ID,  # Indicate the unique identifier of your index\n",
        "  \"classes\": [\n",
        "      {\n",
        "          \"name\": \"Technology & Computing\",\n",
        "          \"prompts\": [\n",
        "              \"Artificial Intelligence\",\n",
        "              \"Augmented Reality\",\n",
        "              \"Consumer Electronics\",\n",
        "              \"Robotics\",\n",
        "              \"AWS\",\n",
        "              \"Microsoft\",\n",
        "              \"GPUS\",\n",
        "              \"Data Mining\",\n",
        "              \"Big Data\",\n",
        "              \"Cloud Computing\"\n",
        "          ]\n",
        "      }\n",
        "  ],\n",
        "  \"threshold\": {\n",
        "        \"min_video_score\": 80,  # Minimum video score is 80\n",
        "        \"min_duration_ratio\": 0.5  # Minimum duration ratio is 50%\n",
        "  }\n",
        "}\n",
        "\n",
        "# Make a classification request\n",
        "response = requests.post(CLASSIFY_BULK_URL, headers=headers, json=data)\n",
        "print (f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CPMj836badap"
      },
      "source": [
        "In the example output above, note that the `data` array is composed of three objects. Each object contains the following:\n",
        "\n",
        "*   A field named `video_id` representing the unique identifier of the video that has been classified.\n",
        "*   An array named `labels` containing information about each video. Note that, when classifying a video, the API service finds all video fragments that match the label you've specified in the request. For each video fragment found, the API service determines the level of confidence that the fragment matches the label. The `max_score` field is determined by comparing the confidence scores of each fragment and selecting the highest one.\n",
        "\n",
        "### Retrieving detailed information about each matching video fragment\n",
        "\n",
        "The following example code sets the `include_clips` parameter to true to specify that the API service should retrieve detailed information about each matching video fragment:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hzta-Yy7D3Mv",
        "outputId": "24fa1165-6dca-4b1c-e4ac-74f56e67366d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'classes': [{'clips': [{'end': 311.44,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 89.1,\n",
            "                                   'start': 277.7,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/278.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6d487175e2f9710731b8fdc5089acfcbe1a0495aec96386fc172c24ce59102ff'},\n",
            "                                  {'end': 11.289,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 87.24,\n",
            "                                   'start': 0.87,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/1.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=755fa419920b95688f9f36ceee0cedb121f4ab03160a465e1d3c76d30715e742'},\n",
            "                                  {'end': 230.039,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 86.3,\n",
            "                                   'start': 220.199,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/221.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=9971f4b0ba7f47866d08f39c8497d778f892981eb7a8f97ec58c6983dc081b72'},\n",
            "                                  {'end': 75.55,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 85.87,\n",
            "                                   'start': 37.25,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/38.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=da7e50b71414c3032ab673e11d21314fd92db790bc0f0875a706510903803c8a'},\n",
            "                                  {'end': 203.919,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 85.3,\n",
            "                                   'start': 126.73,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/127.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=ea0672bab2a0ea41c2012af71c52129709139c566065bc3dca535cb750a29ab2'},\n",
            "                                  {'end': 277.029,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 85.06,\n",
            "                                   'start': 240.169,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/241.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4c607aeaab0390a1e9c14d4f53b451b83f85d79d302d735cdee9f6e9fb7568f9'},\n",
            "                                  {'end': 311.44,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 84.84,\n",
            "                                   'start': 277.7,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/278.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6d487175e2f9710731b8fdc5089acfcbe1a0495aec96386fc172c24ce59102ff'},\n",
            "                                  {'end': 120.58,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 84.54,\n",
            "                                   'start': 97.529,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/98.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4d0a6e0df9d7c0b68f58a8f01d2ff7897014317af03b7b09e9065b3df2869b52'},\n",
            "                                  {'end': 158.8,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 84.28,\n",
            "                                   'start': 126.73,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/127.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=ea0672bab2a0ea41c2012af71c52129709139c566065bc3dca535cb750a29ab2'},\n",
            "                                  {'end': 120.58,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 84.17,\n",
            "                                   'start': 97.529,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/98.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4d0a6e0df9d7c0b68f58a8f01d2ff7897014317af03b7b09e9065b3df2869b52'},\n",
            "                                  {'end': 158.8,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 84.06,\n",
            "                                   'start': 97.529,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/98.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4d0a6e0df9d7c0b68f58a8f01d2ff7897014317af03b7b09e9065b3df2869b52'},\n",
            "                                  {'end': 331.7,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 84.06,\n",
            "                                   'start': 318.75,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/319.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=5d18c5d7101b0be8e7db45cfd7626a353bd4c28109a03a413e33613f4b5d3c79'},\n",
            "                                  {'end': 253.96,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.97,\n",
            "                                   'start': 240.169,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/241.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4c607aeaab0390a1e9c14d4f53b451b83f85d79d302d735cdee9f6e9fb7568f9'},\n",
            "                                  {'end': 75.55,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 83.9,\n",
            "                                   'start': 46.549,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/47.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=13403d208156c5501edf90e4db8171761ad3d020ae0e5edc816c101f64c9c5d7'},\n",
            "                                  {'end': 75.55,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.8,\n",
            "                                   'start': 37.25,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/38.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=da7e50b71414c3032ab673e11d21314fd92db790bc0f0875a706510903803c8a'},\n",
            "                                  {'end': 214.979,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.79,\n",
            "                                   'start': 171.07,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/172.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=63820a9e0d17d54466284bdffe9aaccefbf28ef6c3cae0adcd47122c2cc29563'},\n",
            "                                  {'end': 96.739,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.77,\n",
            "                                   'start': 83.94,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/84.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4f4a1c8cefa2a2937e8efa335d0bb6e36627ce916c5a0ee168086b7a54be8b16'},\n",
            "                                  {'end': 302.97,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Augmented Reality',\n",
            "                                   'score': 83.65,\n",
            "                                   'start': 277.7,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/278.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6d487175e2f9710731b8fdc5089acfcbe1a0495aec96386fc172c24ce59102ff'},\n",
            "                                  {'end': 11.289,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.64,\n",
            "                                   'start': 0.87,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/1.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=755fa419920b95688f9f36ceee0cedb121f4ab03160a465e1d3c76d30715e742'},\n",
            "                                  {'end': 243.389,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 83.64,\n",
            "                                   'start': 240.169,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e78943e8c47e4eb47e1b/241.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=4c607aeaab0390a1e9c14d4f53b451b83f85d79d302d735cdee9f6e9fb7568f9'},\n",
            "                                  {'end': 96.739,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.63,\n",
            "                                   'start': 78.389,\n",
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            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/227.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=57a85b28c60b44911d41c9ada0766fb5f11f6254a0666a35b2796e0039b5581c'},\n",
            "                                  {'end': 248.8,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.85,\n",
            "                                   'start': 237.529,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/238.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=bc836257fd257df732fc21c4a70e0e0aaab71fe02fbd7195fd4cd64971b1b330'},\n",
            "                                  {'end': 22.37,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.82,\n",
            "                                   'start': 12.39,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/13.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=a679c4815e3c284adffb3b0fa9113325e24e11f6c533b706bed8b6c89bd3b1c5'},\n",
            "                                  {'end': 326.19,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.73,\n",
            "                                   'start': 322.97,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/323.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=5ed475f5d060398e5f391cf08bc5f591ba95c2e7a43fc36bf438c442391680b4'},\n",
            "                                  {'end': 275.45,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.69,\n",
            "                                   'start': 267.92,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/268.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=45c258414168835bf88a00000a83ffe536b5406da80d39edf8a098cc56fc157a'},\n",
            "                                  {'end': 54.68,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.56,\n",
            "                                   'start': 35.59,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/36.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=23a2e56abc6d634c959b15674626435b55b579e56d3eb84304b2c32bd1e7b24b'},\n",
            "                                  {'end': 225.529,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 83.54,\n",
            "                                   'start': 213.139,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/214.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=09447071c4fd0cdbfb20c3d4a805985da2ca049b1f2b7bb5617324b9a5f8789a'},\n",
            "                                  {'end': 236.88,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.45,\n",
            "                                   'start': 226.179,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/227.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=57a85b28c60b44911d41c9ada0766fb5f11f6254a0666a35b2796e0039b5581c'},\n",
            "                                  {'end': 174.6,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.41,\n",
            "                                   'start': 160.339,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/161.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=ba4d237014e4f501c807e17e0ec408dfc9fcd4d15869088b9d1d395fc8d393a1'},\n",
            "                                  {'end': 225.529,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 83.41,\n",
            "                                   'start': 213.139,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/214.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=09447071c4fd0cdbfb20c3d4a805985da2ca049b1f2b7bb5617324b9a5f8789a'},\n",
            "                                  {'end': 11.739,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.34,\n",
            "                                   'start': 1.44,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/2.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=5989868b063d679b376581f791a72c8978d415f90d7e93b39fec61394fa61416'},\n",
            "                                  {'end': 118.709,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.27,\n",
            "                                   'start': 108.43,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/109.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=9bf10951d8407d4b9f817b3fd18fb38bf45f8c550beb3fd026916d35ee1b6d32'},\n",
            "                                  {'end': 54.68,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 83.06,\n",
            "                                   'start': 35.59,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/36.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=23a2e56abc6d634c959b15674626435b55b579e56d3eb84304b2c32bd1e7b24b'},\n",
            "                                  {'end': 225.529,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 82.58,\n",
            "                                   'start': 213.139,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/214.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=09447071c4fd0cdbfb20c3d4a805985da2ca049b1f2b7bb5617324b9a5f8789a'},\n",
            "                                  {'end': 86.669,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 81.96,\n",
            "                                   'start': 67.87,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/68.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=3f404cae3e7b6707199f4dfd0e4a40831c13668e7bd477303625f9b9612f6018'},\n",
            "                                  {'end': 322.329,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Augmented Reality',\n",
            "                                   'score': 81.23,\n",
            "                                   'start': 311.75,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/312.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=b35cfb341e000e292d58eef6edd6e93ba0b94f867f1bb6b90d69187b0b6f1bed'},\n",
            "                                  {'end': 22.37,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Robotics',\n",
            "                                   'score': 79.84,\n",
            "                                   'start': 12.39,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/13.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=a679c4815e3c284adffb3b0fa9113325e24e11f6c533b706bed8b6c89bd3b1c5'},\n",
            "                                  {'end': 326.19,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Augmented Reality',\n",
            "                                   'score': 79.63,\n",
            "                                   'start': 322.97,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/323.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=5ed475f5d060398e5f391cf08bc5f591ba95c2e7a43fc36bf438c442391680b4'},\n",
            "                                  {'end': 326.19,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 78.15,\n",
            "                                   'start': 322.97,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/323.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=5ed475f5d060398e5f391cf08bc5f591ba95c2e7a43fc36bf438c442391680b4'},\n",
            "                                  {'end': 248.8,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 77.84,\n",
            "                                   'start': 237.529,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/238.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=bc836257fd257df732fc21c4a70e0e0aaab71fe02fbd7195fd4cd64971b1b330'},\n",
            "                                  {'end': 141.86,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Artificial Intelligence',\n",
            "                                   'score': 77.8,\n",
            "                                   'start': 136.52,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/137.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=39511b50d1cad1264e78af58e4b2e80f9f0b612f7d1d3fc79abe31f4d4df8aa4'},\n",
            "                                  {'end': 236.88,\n",
            "                                   'option': 'conversation',\n",
            "                                   'prompt': 'Data Mining',\n",
            "                                   'score': 75.48,\n",
            "                                   'start': 226.179,\n",
            "                                   'thumbnail_url': 'https://project-one-thumbnail.s3.us-west-2.amazonaws.com/6527e94143e8c47e4eb47e1e/227.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAYRWJPOVHXE5SJ77T%2F20231013%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20231013T035528Z&X-Amz-Expires=604799&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=57a85b28c60b44911d41c9ada0766fb5f11f6254a0666a35b2796e0039b5581c'}],\n",
            "                        'duration_ratio': 0.51,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 87.2}],\n",
            "           'video_id': '6527e94143e8c47e4eb47e1e'}],\n",
            " 'page_info': {'limit_per_page': 10,\n",
            "               'next_page_token': '',\n",
            "               'page_expired_at': '2023-10-13T04:00:28Z',\n",
            "               'prev_page_token': '',\n",
            "               'total_results': 4}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/classify/bulk` endpoint\n",
        "CLASSIFY_BULK_URL = f\"{API_URL}/classify/bulk\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data =  {\n",
        "  \"options\": [\n",
        "        \"visual\",\n",
        "        \"conversation\",\n",
        "        \"text_in_video\"\n",
        "  ],\n",
        "  \"index_id\": INDEX_ID,\n",
        "  \"include_clips\": True,\n",
        "  \"classes\": [\n",
        "      {\n",
        "          \"name\": \"Technology & Computing\",\n",
        "          \"prompts\": [\n",
        "              \"Artificial Intelligence\",\n",
        "              \"Augmented Reality\",\n",
        "              \"Consumer Electronics\",\n",
        "              \"Robotics\",\n",
        "              \"AWS\",\n",
        "              \"Microsoft\",\n",
        "              \"GPUS\",\n",
        "              \"Data Mining\",\n",
        "              \"Big Data\",\n",
        "              \"Cloud Computing\"\n",
        "          ]\n",
        "      }\n",
        "  ],\n",
        "  \"threshold\": {\n",
        "        \"min_video_score\": 80,\n",
        "        \"min_duration_ratio\": 0.5\n",
        "  }\n",
        "}\n",
        "\n",
        "# Make a classification request\n",
        "response = requests.post(CLASSIFY_BULK_URL, headers=headers, json=data)\n",
        "print (f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bF6hzOM_lmGZ"
      },
      "source": [
        "In the example output above, note that, for each video, the API service returns an array named `clips` containing detailed information about a single matching video fragment.\n",
        "\n",
        "### Classifying a video based on multiple classes\n",
        "\n",
        "The following example code classifies the content of your videos based on three classes - `Food & Drink`, `Style & Fashion`, and `Technology & Computing`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tGrp5ldymSxf",
        "outputId": "111ee7a4-2d89-4243-ebc5-c33f1b87b1cb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'classes': [{'duration_ratio': 0.73,\n",
            "                        'name': 'Food & Drink',\n",
            "                        'score': 98.07}],\n",
            "           'video_id': '6527e95143e8c47e4eb47e22'},\n",
            "          {'classes': [{'duration_ratio': 0.82,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 96.88}],\n",
            "           'video_id': '6527e78943e8c47e4eb47e1b'},\n",
            "          {'classes': [{'duration_ratio': 0.86,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 95.79}],\n",
            "           'video_id': '6527e78c43e8c47e4eb47e1d'},\n",
            "          {'classes': [{'duration_ratio': 0.69,\n",
            "                        'name': 'Style & Fashion',\n",
            "                        'score': 90.37}],\n",
            "           'video_id': '6527ee5843e8c47e4eb47e2c'},\n",
            "          {'classes': [{'duration_ratio': 0.58,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 88.74}],\n",
            "           'video_id': '6527e94843e8c47e4eb47e1f'},\n",
            "          {'classes': [{'duration_ratio': 0.51,\n",
            "                        'name': 'Technology & Computing',\n",
            "                        'score': 87.2}],\n",
            "           'video_id': '6527e94143e8c47e4eb47e1e'},\n",
            "          {'classes': [{'duration_ratio': 0.52,\n",
            "                        'name': 'Food & Drink',\n",
            "                        'score': 86.56}],\n",
            "           'video_id': '6527e94f43e8c47e4eb47e21'}],\n",
            " 'page_info': {'limit_per_page': 7,\n",
            "               'next_page_token': '',\n",
            "               'page_expired_at': '2023-10-13T04:02:47Z',\n",
            "               'prev_page_token': '',\n",
            "               'total_results': 7}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/classify/bulk` endpoint\n",
        "CLASSIFY_BULK_URL = f\"{API_URL}/classify/bulk\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data =  {\n",
        "  \"options\": [\n",
        "        \"visual\",\n",
        "        \"conversation\",\n",
        "        \"text_in_video\"\n",
        "  ],\n",
        "  \"index_id\": INDEX_ID,\n",
        "  \"classes\": [\n",
        "        {\n",
        "            \"name\": \"Food & Drink\",\n",
        "            \"prompts\": [\n",
        "                \"Alcoholic Beverages\",\n",
        "                \"Cooking\",\n",
        "                \"Healthy Cooking and Eating\",\n",
        "                \"Food\",\n",
        "                \"Beverages\",\n",
        "                \"Food Culture\",\n",
        "                \"Nutrition\",\n",
        "                \"Food Preparation\",\n",
        "                \"Recipes\",\n",
        "                \"Diet\"\n",
        "            ]\n",
        "        },\n",
        "        {\n",
        "            \"name\": \"Style & Fashion\",\n",
        "            \"prompts\": [\n",
        "                \"Beauty\",\n",
        "                \"Designer Clothing\",\n",
        "                \"Fashion Trends\",\n",
        "                \"Men's Fashion\",\n",
        "                \"Women's Fashion\",\n",
        "                \"Hairstyles\",\n",
        "                \"Makeup\",\n",
        "                \"Accessories\",\n",
        "                \"Footwear\",\n",
        "                \"Jewelry\",\n",
        "                \"Outfits\",\n",
        "                \"Clothing Care\",\n",
        "                \"Sewing\"\n",
        "            ]\n",
        "        },\n",
        "        {\n",
        "            \"name\": \"Technology & Computing\",\n",
        "            \"prompts\": [\n",
        "                \"Artificial Intelligence\",\n",
        "                \"Augmented Reality\",\n",
        "                \"Consumer Electronics\",\n",
        "                \"Robotics\",\n",
        "                \"AWS\",\n",
        "                \"Microsoft\",\n",
        "                \"GPUS\",\n",
        "                \"Data Mining\",\n",
        "                \"Big Data\",\n",
        "                \"Cloud Computing\"\n",
        "            ]\n",
        "        }\n",
        "  ],\n",
        "  \"threshold\": {\n",
        "        \"min_video_score\": 80,\n",
        "        \"min_duration_ratio\": 0.5\n",
        "  }\n",
        "}\n",
        "\n",
        "# Make a classification request\n",
        "response = requests.post(CLASSIFY_BULK_URL, headers=headers, json=data)\n",
        "print (f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QgY8gyXnnE1w"
      },
      "source": [
        "In the example output above, note that the `data` array contains three objects, each corresponding to a different video. For each video, the response contains information that helps you determine the likelihood that each of the labels you've specified in the request appears in that video.\n",
        "\n",
        "### Retrieving a detailed score for each class\n",
        "\n",
        "The following example code sets the `show_detailed_score` parameter to `true` to specify that the platform should retrieve the maximum score, average score, duration weighted score, and normalized score for each class:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bo2cXWD82cv7",
        "outputId": "d7236f85-58e8-46a0-f857-e6edfa1952de"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': [{'classes': [{'detailed_scores': {'avg_score': 80.53,\n",
            "                                            'max_score': 83.95,\n",
            "                                            'normalized_score': 100},\n",
            "                        'duration_ratio': 0.73,\n",
            "                        'name': 'Food & Drink',\n",
            "                        'score': 92.75}],\n",
            "           'video_id': '6527e95143e8c47e4eb47e22'},\n",
            "          {'classes': [{'detailed_scores': {'avg_score': 79.34,\n",
            "                                            'max_score': 83.91,\n",
            "                                            'normalized_score': 100},\n",
            "                        'duration_ratio': 0.52,\n",
            "                        'name': 'Food & Drink',\n",
            "                        'score': 86.56}],\n",
            "           'video_id': '6527e94f43e8c47e4eb47e21'}],\n",
            " 'page_info': {'limit_per_page': 2,\n",
            "               'next_page_token': '',\n",
            "               'page_expired_at': '2023-10-13T04:02:57Z',\n",
            "               'prev_page_token': '',\n",
            "               'total_results': 2}}\n"
          ]
        }
      ],
      "source": [
        "# Construct the URL of the `/classify/bulk` endpoint\n",
        "CLASSIFY_BULK_URL = f\"{API_URL}/classify/bulk\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data =  {\n",
        "  \"options\": [\"visual\"],\n",
        "  \"index_id\": INDEX_ID,\n",
        "  \"show_detailed_score\": True,\n",
        "  \"classes\": [\n",
        "        {\n",
        "            \"name\": \"Food & Drink\",\n",
        "            \"prompts\": [\n",
        "                \"Alcoholic Beverages\",\n",
        "                \"Cooking\",\n",
        "                \"Healthy Cooking and Eating\",\n",
        "                \"Food\",\n",
        "                \"Beverages\",\n",
        "                \"Food Culture\",\n",
        "                \"Nutrition\",\n",
        "                \"Food Preparation\",\n",
        "                \"Recipes\",\n",
        "                \"Diet\"\n",
        "            ]\n",
        "        },\n",
        "        {\n",
        "            \"name\": \"Style & Fashion\",\n",
        "            \"prompts\": [\n",
        "                \"Beauty\",\n",
        "                \"Designer Clothing\",\n",
        "                \"Fashion Trends\",\n",
        "                \"Men's Fashion\",\n",
        "                \"Women's Fashion\",\n",
        "                \"Hairstyles\",\n",
        "                \"Makeup\",\n",
        "                \"Accessories\",\n",
        "                \"Footwear\",\n",
        "                \"Jewelry\",\n",
        "                \"Outfits\",\n",
        "                \"Clothing Care\",\n",
        "                \"Sewing\"\n",
        "            ]\n",
        "        },\n",
        "        {\n",
        "            \"name\": \"Technology & Computing\",\n",
        "            \"prompts\": [\n",
        "                \"Artificial Intelligence\",\n",
        "                \"Augmented Reality\",\n",
        "                \"Consumer Electronics\",\n",
        "                \"Robotics\",\n",
        "                \"AWS\",\n",
        "                \"Microsoft\",\n",
        "                \"GPUS\",\n",
        "                \"Data Mining\",\n",
        "                \"Big Data\",\n",
        "                \"Cloud Computing\"\n",
        "            ]\n",
        "        }\n",
        "  ],\n",
        "  \"threshold\": {\n",
        "        \"min_video_score\": 80,\n",
        "        \"min_duration_ratio\": 0.5\n",
        "  }\n",
        "}\n",
        "\n",
        "# Make a classification request\n",
        "response = requests.post(CLASSIFY_BULK_URL, headers=headers, json=data)\n",
        "print (f'Status code: {response.status_code}')\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3E9b76L0wD1f"
      },
      "source": [
        "## 5 - Generate API\n",
        "The Generate API suite creates concise textual representations such as titles, summaries, chapters, and highlights for your videos, to name as a few. Unlike conventional models limited to unimodal interpretations (for example, summary videos relying solely on video transcription), the Generate API suite uses a multimodal approach that analyzes the whole context of a video, including visuals, sounds, spoken words, and texts and their relationship with one another. This ensures a holistic understanding of your videos, capturing nuances that an unimodal interpretation might miss. And then, using video-to-text generative capabilities, our model can turn that understanding into actual text format of your choice.\n",
        "\n",
        "The Generate API suite offers three distinct endpoints tailored to meet various requirements for creating concise textual representations from videos. Each endpoint has been designed with specific levels of flexibility and customization to accommodate different needs.\n",
        "\n",
        "**1 - The `/gist` endpoint**\n",
        "\n",
        "- **Function**: Generates topics, titles, and hashtags.\n",
        "- **Customization**: Uses predefined templates.\n",
        "- **Prompt **: No.\n",
        "- **Best use**: To generate an immediate and straightforward text representation without specific customization.\n",
        "\n",
        "**2 - The `/summarize` endpoint**\n",
        "\n",
        "- **Function**: Generates summaries, chapters, and highlights.\n",
        "- **Customization**: Operates primarily on predefined templates, similar to `/gist`. However, you can provide a custom prompt that guides the model on how to generate the output.\n",
        "- **Prompt**: Optional. While you can invoke this endpoint without a prompt, providing one allows for tailored outputs.\n",
        "- **Best use:** To balance the efficiency of built-in templates and bespoke customization abilities.\n",
        "\n",
        "**3 - The `/generate` endpoint**\n",
        "\n",
        "- **Function**: Generates open-ended text representations from videos.\n",
        "- **Customization**: Relies solely on user-defined prompts, ensuring maximum flexibility.\n",
        "- **Prompt**: Required. You must provide clear instructions to guide the model.\n",
        "- **Best use**: Ideal for advanced users with specific output requirements beyond the built-in templates.\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Specify the unique identifier of an existing video ('How To Play Chess')\n",
        "%env VIDEO_ID=65282b9043e8c47e4eb47e47"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XwUHg4qDAd4D",
        "outputId": "1e3b91c4-d164-448e-a0a3-c99931c6bd99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: VIDEO_ID=65282b9043e8c47e4eb47e47\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Retrieve the unique identifier of the existing video\n",
        "VIDEO_ID = os.getenv(\"VIDEO_ID\")\n",
        "print (VIDEO_ID)\n",
        "assert VIDEO_ID"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hc1wY3A3Audj",
        "outputId": "412fba30-e91f-4e02-9356-1d8e9968bf77"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "65282b9043e8c47e4eb47e47\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "To demonstrate the Generate API, let's work with this video: [How To Play Chess](https://youtu.be/fKxG8KjH1Qg?si=KVrqveP85EoN3AsF)"
      ],
      "metadata": {
        "id": "po8GILtmlwy4"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8G_u7-emIseC"
      },
      "source": [
        "### 5.1 - Generate titles, topics, and hashtags\n",
        "Use the `/gist` endpoint if you require a swift breakdown of the essence of your videos. This endpoint operates exclusively on a set of predefined templates to generate the following concise and accurate textual representations:\n",
        "\n",
        "- **Title**: Distills the essence of a video into a brief, coherent phrase, facilitating quick understanding and categorization. For example, a title like \"From Consumerism to Minimalism: A Journey Toward Sustainable Living\" clearly indicates the video's narrative trajectory,  emphasizing themes related to consumption patterns and sustainable lifestyles.\n",
        "- **Topic**: Represents the central themes or subjects of a video and provides a high-level understanding based on the meaning conveyed by all modalities. Topics enable effective categorization and quick referencing. For example, \"Shopping Vlog Lifestyle\" denotes a video covering aspects related to shopping experiences, vlogging, and the associated lifestyle.\n",
        "- **Hashtag**: Concisely summarizes the themes, subjects, or sentiments expressed within a video. Hashtags improve categorization and searchability on social media platforms. For example, hashtags such as `#BlackFriday,` `#ShoppingMania,` and `#Consumerism` indicate key focal points in a video, potentially related to shopping events, consumer behaviors, or broader commentary on consumption patterns.\n",
        "\n",
        "Handling this set of predefined tasks offers a streamlined approach to obtaining concise textual representations, essential for rapid content understanding and categorization."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M0aONOTLM4O2"
      },
      "source": [
        "The following example generates a title, topic, and hashtag for the specified video:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2hXru2ujzFp5",
        "outputId": "a2e9dce3-0c9c-4173-8c2e-57fbb5f35f2f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'hashtags': ['checkmate',\n",
            "              'chess tutorial',\n",
            "              'chessboard setup',\n",
            "              'chess rules',\n",
            "              'chess basics',\n",
            "              'chess pieces',\n",
            "              'pawn promotion',\n",
            "              'knight movement',\n",
            "              'bishop movement',\n",
            "              'queen movement',\n",
            "              'king movement',\n",
            "              'check',\n",
            "              'checkmate',\n",
            "              'castle',\n",
            "              'en passant',\n",
            "              'strategic moves'],\n",
            " 'id': 'fc029370-c621-4bd2-9715-e56aeca21f34',\n",
            " 'title': 'Mastering Chess: Learn How to Play, Strategize, and Achieve '\n",
            "          'Checkmate',\n",
            " 'topics': ['Chess']}\n"
          ]
        }
      ],
      "source": [
        "# Define the /gist endpoint\n",
        "GIST_URL = f\"{API_URL}/gist\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"types\": [\"title\", \"topic\", \"hashtag\"]\n",
        "}\n",
        "\n",
        "# Make a gist request\n",
        "response = requests.post(GIST_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fJ201R6-DezM"
      },
      "source": [
        "### 5.2 - Generate summaries, chapters, and highlights\n",
        "Use the `/summarize` endpoint if you want to utilize pre-defined templates for general summarization tasks and, optionally, provide a prompt to customize the output. This endpoint generates the following textual representations:\n",
        "\n",
        "- **Summaries**:  The platform returns a brief that encapsulates the key points of a video, presenting the most important information clearly and concisely. Depending on your prompt, a summary can take various forms, such as a single paragraph, a series of paragraphs, an email, or a structured list of bullet points. For example, a summary highlighting Black Friday events might include a description of a crowded mall, key commentary by a news reporter on consumer behavior, and individual perspectives on societal values associated with consumption.\n",
        "- **Chapters**: The platform returns a chronological list of all the segments in a video, providing a granular breakdown of its content. For each chapter, the platform returns its starting and end times, measured in seconds from the beginning of the video segment, a descriptive headline that offers a brief of the events or activities within that segment, and an accompanying summary that elaborates on the headline. For example, the first chapter of a stand-up comedy might describe the comedian's entrance and the first joke. The accompanying summary could delve into the content, detailing the comedian's humorous take on a specific subject, such as the cultural nuances of Tai Chi exercises.\n",
        "- **Highlights**: The platform returns a chronologically ordered list of the most important events within a video. Unlike chapters, highlights only capture the key moments, providing a snapshot of the video's main topics. For each highlight, the platform returns its starting and end times, measured in seconds from the beginning of the video, and a brief description that captures the essence of the segment. For example, a highlight might capture a significant event like a bank heist in a video with multiple scenes."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AM1Qd39MPCAo"
      },
      "source": [
        "The following example code generates a summary for the specified video:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gn2RMdjuny_f",
        "outputId": "8c162a04-a523-4ca8-ca8c-f1081e10383a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'id': '6c6d35ee-3615-4ea9-ad17-9490585cad4b',\n",
            " 'summary': 'This instructional video provides a comprehensive guide on how to '\n",
            "            'play chess. The narrator explains the objective of the game, '\n",
            "            \"which is to achieve checkmate by placing the opponent's king in a \"\n",
            "            'position where it cannot escape capture. The video begins by '\n",
            "            'showing the setup of the chessboard, with each player sitting '\n",
            "            'facing each other and the white pieces starting on the bottom '\n",
            "            'right square. The narrator emphasizes the correct positioning of '\n",
            "            'the pieces, including the specific arrangement of the second row '\n",
            "            'with pawns. The video then delves into the rules of the game, '\n",
            "            'highlighting that players take turns moving one piece at a time '\n",
            "            'and that pieces cannot move through or over other pieces. The '\n",
            "            \"capturing of opponents' pieces is also explained, with the \"\n",
            "            \"importance of moving a piece to the square of the opponent's \"\n",
            "            'piece to eliminate it from the board. The distinct movement '\n",
            "            'patterns of each piece are discussed, such as pawns moving '\n",
            "            'forward and capturing diagonally, while rooks can move '\n",
            "            'horizontally or vertically. The narrator also explains the '\n",
            "            'concept of pawn and rook promotion, where pawns can be changed '\n",
            "            'into any other type of piece and rooks cannot jump over other '\n",
            "            'pieces. The video demonstrates the movement of knights in an '\n",
            "            'L-shape pattern and how bishops can move any number of squares '\n",
            "            'diagonally. The narrator goes on to discuss the movement of the '\n",
            "            'queen, which can move in any direction, and the king, which can '\n",
            "            'move one square at a time and must be protected from checkmate. '\n",
            "            'The video shows strategic moves being made to protect the king '\n",
            "            \"and capture opponents' pieces, as well as the declaration of \"\n",
            "            \"check and checkmate when a move threatens the opponent's king \"\n",
            "            'with no possible escape. Throughout the video, the narrator '\n",
            "            'provides clear explanations and visual demonstrations of the '\n",
            "            'rules and strategies of chess, making it a valuable resource for '\n",
            "            'beginners and those looking to improve their gameplay.'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"summary\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7CYf7KKBPWSi"
      },
      "source": [
        "Optionally, you can use the `prompt` field to provide context for the summarization task. The following example specifies the purpose and the desired length:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "r_go51_bPbLY",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "05dda7e5-46ea-44ca-8e05-35093634cf47"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'id': '2fbbb434-58be-49a4-aefe-c8613ee0b2e5',\n",
            " 'summary': 'An informative video tutorial on how to play chess is presented '\n",
            "            'in a clear and detailed manner. The narrator explains the '\n",
            "            'objective of the game, which is to achieve checkmate by capturing '\n",
            "            \"the opponent's king. The tutorial covers various aspects of the \"\n",
            "            'game, including setting up the chessboard, the movement and '\n",
            "            'capturing abilities of each piece, and important rules such as '\n",
            "            'turn-taking and pawn promotion.'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"summary\",\n",
        "  \"prompt\": \"Generate a summary of this video for a Netflix show, up to three sentences.\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NVvS8QrsPnPU"
      },
      "source": [
        "The following example generates a list of chapters for the specified video:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KS3KRyXDPpHK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "21a3a62e-dd1a-4aab-8cf0-ee041d695cf4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'chapters': [{'chapter_number': 0,\n",
            "               'chapter_summary': 'The video provides a tutorial on how to '\n",
            "                                  'play chess, with a focus on the objective '\n",
            "                                  'of the game and the setup of the '\n",
            "                                  'chessboard.',\n",
            "               'chapter_title': 'Chess Objective and Setup',\n",
            "               'end': 30,\n",
            "               'start': 0},\n",
            "              {'chapter_number': 1,\n",
            "               'chapter_summary': 'The video explains the concept of turns and '\n",
            "                                  'the movement rules for each chess piece, '\n",
            "                                  'emphasizing that players take turns moving '\n",
            "                                  'one piece at a time and explaining the '\n",
            "                                  'unique movements of pawns, rooks, knights, '\n",
            "                                  'bishops, queens, and kings.',\n",
            "               'chapter_title': 'Turns and Piece Movements',\n",
            "               'end': 75,\n",
            "               'start': 30},\n",
            "              {'chapter_number': 2,\n",
            "               'chapter_summary': 'The video demonstrates how to capture '\n",
            "                                  \"opponent's pieces by moving one's own piece \"\n",
            "                                  \"to the square of the opponent's piece, and \"\n",
            "                                  'highlights the importance of checkmate as '\n",
            "                                  'the ultimate goal of the game.',\n",
            "               'chapter_title': 'Capturing and Checkmate',\n",
            "               'end': 150,\n",
            "               'start': 75},\n",
            "              {'chapter_number': 3,\n",
            "               'chapter_summary': 'The video explains how to protect the king '\n",
            "                                  'from threats and describes the conditions '\n",
            "                                  'for declaring check and checkmate, with a '\n",
            "                                  'demonstration of strategic moves and the '\n",
            "                                  'declaration of checkmate.',\n",
            "               'chapter_title': 'Protecting the King and Checkmate',\n",
            "               'end': 180,\n",
            "               'start': 150}],\n",
            " 'id': 'c22e697d-714e-4238-a03b-58bef6b6377d'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"chapter\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uJsEMtxQPxqS"
      },
      "source": [
        "Optionally, you can use the `prompt` parameter to indicate that the tone of voice should be instructional:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "IEpeMHGaPzUE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b6a17a7f-06b0-4eb8-95ef-e3717c6f5fc1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'chapters': [{'chapter_number': 0,\n",
            "               'chapter_summary': 'The video provides a tutorial on how to '\n",
            "                                  'play chess, with a focus on the setup of '\n",
            "                                  'the chessboard and the basic rules of the '\n",
            "                                  'game.',\n",
            "               'chapter_title': 'Chessboard setup and basic rules',\n",
            "               'end': 105,\n",
            "               'start': 0},\n",
            "              {'chapter_number': 1,\n",
            "               'chapter_summary': 'The video explains the movement patterns of '\n",
            "                                  'each chess piece and the concept of '\n",
            "                                  \"capturing opponent's pieces through correct \"\n",
            "                                  'moves.',\n",
            "               'chapter_title': 'Piece movement and capturing',\n",
            "               'end': 165,\n",
            "               'start': 105},\n",
            "              {'chapter_number': 2,\n",
            "               'chapter_summary': 'The video discusses the importance of '\n",
            "                                  'protecting the king and achieving checkmate '\n",
            "                                  'to win the game.',\n",
            "               'chapter_title': 'Check and checkmate',\n",
            "               'end': 210,\n",
            "               'start': 165},\n",
            "              {'chapter_number': 3,\n",
            "               'chapter_summary': 'The video highlights special moves in '\n",
            "                                  'chess, including pawn promotion and en '\n",
            "                                  'passant, providing players with additional '\n",
            "                                  'strategic options.',\n",
            "               'chapter_title': 'Special moves: Pawn promotion and en passant',\n",
            "               'end': 225,\n",
            "               'start': 210},\n",
            "              {'chapter_number': 4,\n",
            "               'chapter_summary': 'The video explores advanced strategies in '\n",
            "                                  'chess and explains the conditions for '\n",
            "                                  'winning the game, such as capturing the '\n",
            "                                  \"opponent's pieces and placing the \"\n",
            "                                  \"opponent's king in checkmate.\",\n",
            "               'chapter_title': 'Advanced strategies and winning the game',\n",
            "               'end': 240,\n",
            "               'start': 225}],\n",
            " 'id': 'f9684d89-89f6-43f5-971f-6ce260b452b8'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"chapter\",\n",
        "  \"prompt\": \"Generate chapters using instructional language.\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "flUhM8kSP7CQ"
      },
      "source": [
        "The following example generates a list of the important events or activities within a video:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3fRtWUmqP7db",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d600af57-0048-4c3c-bdb8-a4e886005ffd"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'highlights': [{'end': 120,\n",
            "                 'highlight': 'The video showcases a man in blue attire '\n",
            "                              'explaining chess fundamentals, focusing on '\n",
            "                              \"capturing opponent's pieces and their removal \"\n",
            "                              'from the board.',\n",
            "                 'highlight_summary': 'The video showcases a man in blue '\n",
            "                                      'attire explaining chess fundamentals, '\n",
            "                                      \"focusing on capturing opponent's pieces \"\n",
            "                                      'and their removal from the board.',\n",
            "                 'start': 75},\n",
            "                {'end': 180,\n",
            "                 'highlight': 'The man in the blue shirt and black suit '\n",
            "                              'explains the rules of checkmate in chess, '\n",
            "                              'highlighting how an attacking player can win by '\n",
            "                              'moving their king into its final diagonal '\n",
            "                              'position on the board without any moves from '\n",
            "                              'either player.',\n",
            "                 'highlight_summary': 'The man in the blue shirt and black '\n",
            "                                      'suit explains the rules of checkmate in '\n",
            "                                      'chess, highlighting how an attacking '\n",
            "                                      'player can win by moving their king '\n",
            "                                      'into its final diagonal position on the '\n",
            "                                      'board without any moves from either '\n",
            "                                      'player.',\n",
            "                 'start': 135},\n",
            "                {'end': 225,\n",
            "                 'highlight': 'In this video, a man wearing a blue shirt is '\n",
            "                              'seated at a table with a chessboard. He '\n",
            "                              'explains the rules of chess and provides '\n",
            "                              'strategies for efficient gameplay. The '\n",
            "                              'importance of first moves, en passant pawns, '\n",
            "                              'and king placement is emphasized. Textual '\n",
            "                              'information is displayed on the screen for '\n",
            "                              'further clarification.',\n",
            "                 'highlight_summary': 'In this video, a man wearing a blue '\n",
            "                                      'shirt is seated at a table with a '\n",
            "                                      'chessboard. He explains the rules of '\n",
            "                                      'chess and provides strategies for '\n",
            "                                      'efficient gameplay. The importance of '\n",
            "                                      'first moves, en passant pawns, and king '\n",
            "                                      'placement is emphasized. Textual '\n",
            "                                      'information is displayed on the screen '\n",
            "                                      'for further clarification.',\n",
            "                 'start': 210}],\n",
            " 'id': '9889873a-149a-4ee9-a49f-de2e95475826'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"highlight\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L9idbrj8QBwD"
      },
      "source": [
        "Optionally, you can use the `prompt` parameter to generate highlights for the same video, showcasing the most surprising parts:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "g4azaGnUQDr4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c928f7b8-ca3a-4fb7-edd3-850f642b951e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'highlights': [{'end': 60,\n",
            "                 'highlight': 'Basic Movement and Capturing',\n",
            "                 'highlight_summary': 'The video explains the basics of chess, '\n",
            "                                      'including how pieces move and capture '\n",
            "                                      \"opponent's pieces.\",\n",
            "                 'start': 45},\n",
            "                {'end': 105,\n",
            "                 'highlight': 'Promotion and Rook Movement',\n",
            "                 'highlight_summary': 'The tutorial covers the concept of pawn '\n",
            "                                      'promotion and the movement of rooks on '\n",
            "                                      'the chessboard.',\n",
            "                 'start': 90},\n",
            "                {'end': 210,\n",
            "                 'highlight': 'Importance of First Move and En Passant',\n",
            "                 'highlight_summary': 'The narrator explains the significance '\n",
            "                                      'of the first move and the en passant '\n",
            "                                      'rule in chess.',\n",
            "                 'start': 195}],\n",
            " 'id': 'd75e372c-6aee-4575-8bfa-a04cb0662293'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /summarize endpoint\n",
        "SUMMARIZE_URL = f\"{API_URL}/summarize\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"type\": \"highlight\",\n",
        "  \"prompt\": \"Generate highlights that showcase the most surprising parts of the video.\"\n",
        "}\n",
        "\n",
        "# Make a summarization request\n",
        "response = requests.post(SUMMARIZE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oUn2t1Oa4JI3"
      },
      "source": [
        "### 5.3 - Generate open-ended textual representations\n",
        "Use the `/generate` endpoint for open-ended textual representations that are more customizable and tailor-made than the templates offered by the `/gist` and `/summarize` endpoints. This endpoint can produce a diverse range of textual representations based on your prompt, including, but not limited to, tables of content, action items, memos, reports and comprehensive analyses.\n",
        "\n",
        "The following example generates a checklist of important takeaways for chess newbies:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YV4bfITL4Nke",
        "outputId": "cb11575a-663a-4e01-aa1e-87bbae2b6d81"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': 'Checklist of Important Takeaways for Chess Newbies:\\n'\n",
            "         '\\n'\n",
            "         \"1. The objective of chess is to checkmate the opponent's king.\\n\"\n",
            "         '2. Checkmate occurs when the king is in a position to be captured, '\n",
            "         'is in check, and cannot escape from capture.\\n'\n",
            "         '3. The chess board is laid out so that each player is sitting in a '\n",
            "         'position to play.\\n'\n",
            "         \"4. Pawns can only move one square forward towards the opponent's \"\n",
            "         'pieces and capture diagonally.\\n'\n",
            "         '5. Each type of chess piece has a unique movement pattern and '\n",
            "         \"captures opponent's pieces differently.\\n\"\n",
            "         '6. The queen can move any number of spaces vertically or '\n",
            "         'horizontally and can capture the first enemy piece it moves into.\\n'\n",
            "         '7. Rooks can move any number of squares horizontally or vertically '\n",
            "         'but cannot move diagonally.\\n'\n",
            "         '8. Understanding the correct setup of the chess pieces on the board '\n",
            "         'is essential.\\n'\n",
            "         '9. The player with the white pieces always moves first.\\n'\n",
            "         '10. It is important to not move the king into a position where it is '\n",
            "         'threatened.\\n'\n",
            "         \"11. Capturing an opponent's piece requires strategic positioning and \"\n",
            "         'planning.\\n'\n",
            "         '12. Hand gestures and visual cues can assist in understanding the '\n",
            "         'game.\\n'\n",
            "         '13. It is crucial to learn and understand basic chess rules and '\n",
            "         'gameplay strategies.\\n'\n",
            "         '14. Take note of specific game situations such as promotion of pawns '\n",
            "         'and movement of rooks.\\n'\n",
            "         '15. Chess is a game that requires patience, strategy, and critical '\n",
            "         'thinking.\\n'\n",
            "         '\\n'\n",
            "         'Remember to refer to the video for more detailed instructions and '\n",
            "         'explanations. Enjoy your journey into the world of chess!',\n",
            " 'id': '7ac30b7e-d246-49fa-9b7a-2e7162b9d0bb'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /generate endpoint\n",
        "GENERATE_URL = f\"{API_URL}/generate\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"prompt\": \"Write a checklist of important takeaways for chess newbies based on this video.\"\n",
        "}\n",
        "\n",
        "# Make a generation request\n",
        "response = requests.post(GENERATE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kuMxEBx1Q4_k"
      },
      "source": [
        "The following example generates a rap song based on the provided template:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2j9F1N6xQ7Ax",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1fd3c5ec-0d1a-49e1-dce8-e835524bd6b1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Status code: 200\n",
            "{'data': '(Verse 1)\\n'\n",
            "         'Yo, check it out, gather round, listen to my flow,\\n'\n",
            "         \"I'm about to drop some rhymes about chess and how it goes,\\n\"\n",
            "         \"In a blue shirt, he's seated at a table so neat,\\n\"\n",
            "         \"Explaining chess's objective, gotta bring the heat.\\n\"\n",
            "         '\\n'\n",
            "         '(Chorus)\\n'\n",
            "         \"Checkmate, that's the aim, to win the game,\\n\"\n",
            "         \"Capture the opponent's king, that's the name,\\n\"\n",
            "         'In chess, strategy is key, gotta plan your moves,\\n'\n",
            "         'Lay out the board, position yourself to groove.\\n'\n",
            "         '\\n'\n",
            "         '(Verse 2)\\n'\n",
            "         \"Start with pawns on the front, the battle's begun,\\n\"\n",
            "         \"Piece by piece, that's how the game is won,\\n\"\n",
            "         \"Animated chessboard, pieces movin' with flair,\\n\"\n",
            "         \"Black pants, blue shirt, he's the teacher who cares.\\n\"\n",
            "         '\\n'\n",
            "         '(Chorus)\\n'\n",
            "         \"Checkmate, that's the aim, to win the game,\\n\"\n",
            "         \"Capture the opponent's king, that's the name,\\n\"\n",
            "         'In chess, strategy is key, gotta plan your moves,\\n'\n",
            "         'Lay out the board, position yourself to groove.\\n'\n",
            "         '\\n'\n",
            "         '(Verse 3)\\n'\n",
            "         \"He gestures with his hands, explainin' it all,\\n\"\n",
            "         'Capture enemy pieces, stand proud and tall,\\n'\n",
            "         'Each piece has its own unique way to attack,\\n'\n",
            "         \"Pawns movin' forward, stayin' on the right track.\\n\"\n",
            "         '\\n'\n",
            "         '(Bridge)\\n'\n",
            "         'Chess, a game of intellect and skill,\\n'\n",
            "         'Think ahead, strategize, gotta bring the thrill,\\n'\n",
            "         'Seated on chairs, black pants, blue shirt,\\n'\n",
            "         \"Master the moves, show 'em what you're worth.\\n\"\n",
            "         '\\n'\n",
            "         '(Chorus)\\n'\n",
            "         \"Checkmate, that's the aim, to win the game,\\n\"\n",
            "         \"Capture the opponent's king, that's the name,\\n\"\n",
            "         'In chess, strategy is key, gotta plan your moves,\\n'\n",
            "         'Lay out the board, position yourself to groove.\\n'\n",
            "         '\\n'\n",
            "         '(Outro)\\n'\n",
            "         'So next time you see a chessboard, take a seat and play,\\n'\n",
            "         'Remember the lessons, enjoy the game, they say,\\n'\n",
            "         'Chess is a challenge, a battle of the mind,\\n'\n",
            "         'Master the moves, victory you will find.',\n",
            " 'id': '7beaeb9f-752c-4044-9637-ed843e56e709'}\n"
          ]
        }
      ],
      "source": [
        "# Define the /generate endpoint\n",
        "GENERATE_URL = f\"{API_URL}/generate\"\n",
        "\n",
        "# Set the header of the request\n",
        "headers = {\n",
        "    \"x-api-key\": API_KEY\n",
        "}\n",
        "\n",
        "# Declare a dictionary named `data`\n",
        "data = {\n",
        "  \"video_id\": VIDEO_ID,\n",
        "  \"prompt\": \"Write a rap song based on this video.\"\n",
        "}\n",
        "\n",
        "# Make a generation request\n",
        "response = requests.post(GENERATE_URL, headers=headers, json=data)\n",
        "print(f\"Status code: {response.status_code}\")\n",
        "pprint(response.json())"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Have fun playing around with the Twelve Labs API!🚀"
      ],
      "metadata": {
        "id": "d6RJboDRm71F"
      }
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}