230-Deep_Learning_Vector_Similarity.ipynb

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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/JSJeong-me/KOSA_Generate_AI_for_Image/blob/main/230-Deep_Learning_Vector_Similarity.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j-3d7uwzjJ4O"
      },
      "source": [
        "# Embedding Images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1QAsifr8PoqR"
      },
      "source": [
        "import tensorflow as tf\n",
        "import tensorflow_hub as hub\n",
        "from PIL import Image\n",
        "import numpy as np"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RTmI4n3mLZMs"
      },
      "source": [
        "model_url = \"https://tfhub.dev/tensorflow/efficientnet/lite0/feature-vector/2\"\n",
        "\n",
        "IMAGE_SHAPE = (224, 224)\n",
        "\n",
        "layer = hub.KerasLayer(model_url)\n",
        "model = tf.keras.Sequential([layer])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4rJJf1MeNT3w"
      },
      "source": [
        "def extract(file):\n",
        "  file = Image.open(file).convert('L').resize(IMAGE_SHAPE)\n",
        "  display(file)\n",
        "\n",
        "  file = np.stack((file,)*3, axis=-1)\n",
        "\n",
        "  file = np.array(file)/255.0\n",
        "\n",
        "  embedding = model.predict(file[np.newaxis, ...])\n",
        "  #print(embedding)\n",
        "  vgg16_feature_np = np.array(embedding)\n",
        "  flattended_feature = vgg16_feature_np.flatten()\n",
        "\n",
        "  #print(len(flattended_feature))\n",
        "  #print(flattended_feature)\n",
        "  #print('-----------')\n",
        "  return flattended_feature"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d4Thl2aDPsrl",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 744
        },
        "outputId": "5c374061-20e4-473a-9430-34fbb1310d07"
      },
      "source": [
        "cat1 = extract('./cat1.png')\n",
        "cat2 = extract('./cat2.jpg')\n",
        "rocket = extract('./rocket.jpg')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 2s 2s/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224>"
            ],
            "image/png": 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iC/H9gf7NJ8GS5nnKk1fE6WxRkeVBiY3Jlkz3paVpyffRCLaTST0Te5w4uJhIHahciuCZ4gA+cRvLj6NcTD5omifFNEOaBUJVZ/gHoEHAFURZJXQGT1m+4gcZn6WQL83DBNUyGTpHI/mc5ZTAUasnGrqAZBFLKGbjt9T387B8Pk/TXWGa6TPWgu/cYO25xcnpEJxSH5DC24VvSXiHIAnXJCQwcX5x1eyrMDycQhzAD41/JnLpVKYJeuLlIY5gMhmLGYLJHwIS9Mf725D4MTtHmK09ZgJokU3KYgxAiaFpRkDPpBjnb6O8Ohze3w7J6SyUcFaJzLkntjxFK9G3Zc7pFOotLOiCUbYkz8zFQisRNEm0IqLimaOc7pc1VTVi0dlaPpljwIxek28KA4Y9rgrOzjQfOxsiWAjkJKOzdMx6epaJ06VZiRJi2benB9lD1Q+Gkmme8iUZFy/B4fJ6AIuAN02xLizEE98VJ0qVYFuSFR8MKy4utvAXMXPyj6UBnlp/zN5OdQH8AACMPd0NDx9WzpnLeoWSuB+p0Cd3TTg0m2adZkEN5FxSZuHS/aaxTGKqfMGBwIvxykvXh/BUVHA+NxueZFBwqb8puMWUa4A4HEVkOr37iEe+H0ytznMeXcyjTLFEZHv2p5DCBU02AiMHz1IpT6cc8gwAACBB21qSojBDWdDiDk9Q/3RfnNkEc3icjC1Gxp0Hssk4+PHDb/ugsCs1dJ23CABAkcfT4cubLs2sQk43R7D9Q26fvckuSlWkPfVdWBXYuDpq4qwa03RkQT8nOWtFcp4KE9xIgpVZCIpKfdv+uh8+VlU/Bot1X1JW5Hm25lxQTh/oNEWaGWMme7JwnjMbMnOza9O+bTt3LMx203arjZ0kceLkfG5KqOd4fk6eRA+2MM6L6UAFBKSxG74duzs2B09VxaduwzDNZrKlOHlE1KwCihnnJrATUxZzgDHfKw91mhoFVdThFNwIQ/Mgl4dOtybp/CxnM6qcNPsMaGJOQSvmHMHTF+Fw0sN9f9g2VWi99qdwfJaJh4WVzn/EEDmanhRRTgcvUxaTJM1vnwxAnI698S5460Ljbt1lQZk7mANFna+zyAROlmqexzzG6a/4mzAcZf+bB7gsxwONe1WDdy+KKZcywy3F7LwX0CP71iQyZrKaczj51NJkr6WqfgwerDk8mJd7JXeSi4LpjxgmXCI4PbsQpBAxfzA7ZkBVQDSu9x9/5y+OCpvTo5rx2D4v+2Q3dbrMDDQWedd8wyzDKek0TXDWjDltlC+UZNTfP3R2W629O4nawt35urGGIGEKhKxvi4Rj0ndFkMUU6OyyszaqKiDS2O7/foD6UN9s+RH2hMGJcULTXOkMXmG2WbP70ZmPCCb598kdTYQ94UsMvdxp5+oeNzflYehOzQt/8q6qrVlQk8HPPEOz283KsXQX8biUREACOZ6+PRjvj9uTX9uLUvbF/uDa5Chmlk2vP2az0zcKYJKdnKcTdcKRS/cU522UYrOpynBbsjDuV6y2a+tVY/lsRs8gWLzVU8h4PpBkFBjBtcPuFNRg5TvXYQe2FvB9H7I7k0nQYWmOJxeTksDZJ5hZC9JhggAxDj4fMqiCeuf55Dy5gzG0DWHARsLY+7pinshZutzpZ071zSF+1r38w6z+4dY9Hrnu9uOmGsmsXCBTiWFJmeqYS4SsdIpn4GwO2vOgp9T9InDJjn+Jv+IsqY4DG2OEVo2VkQpqfw/XVUfeVyUvhORpMgxBUXPQukxQRP2I0IsYXN92R7Pu3x3M5bZ4VXtx7WHU5tRLkodYnZt86OT8Z7s1G2xUzan7ic0LE5od62KO1ayO9lmtBNpU/njXXupDqNfOgR9XtfmhaMMTvYaz/BpE04KqoIiGYfQde1sa/LSy1pui2cCHE9ftgUY5G/3CZyyzPYvZTU4xIhn9wbczuswioQCqoe3AKGxrFdeOUD4cN58VrNa52gWoDGXPtNDAH1x8Jg3yNAMiGlbnur49HeXzz/p24MvSkK9u9EDtg2edyJqR8Xz5yWhmuzbdaVkfjPJM57zOjABQBbRq6vp6XXgXoO6rKxeCKY5ikE1HWlk6u9oCpmtCb1N+RqdhIAAiEwc/+M4PBeAwtECbSzbQ7rAAsqVVrzlkThKebfVSGgBjpSkDAIg5mcSpqMVJTc8dRZ4PAjfypqrUY4X9yEV/PB2umtNQ94XtUNUynoFSBIh12DNvsKhKA6giEjFqcEMIj369fzytnq9OD7vC1gU7JDAQ3JiAks4QMFu0MxmBFCqhoiqiLvRmURXCxQkZiAEAgEBVcmmhBD/0F+Js4R+BS0EY2Q+iWvB5Wn2eKs0dBDCh3hQIEhsJGJxz4TSuPh5fvbpxv70n8lKvy5VF2lx2QbPSzAycnEY2MZG/MyRDmLJqy/LTGcdnShVBaYWuXHGwEFQNuABFtR5OFvyKgsioIqWZYN+scQi5sUOjz5ujC0RkiyFACBjeHovv5Z80u9+EQzn26h8t2M+3xwDllLROMG22fxEU5WrDIokRZTLHg9PELJi4xFugMctYHQ873CjC0AXvRoJxReNofb/uDUgfVEpDeDYxACkdJYAgUTc0gztCIoQgIiP6x4cNbszxYbyw1NuiH5sT+F//+FkIA/HZjE3ebmljFokumTyyWZyxhE2YqVy8EJAv2tFZHdygZAOC3XShLB+O1puqLyhgBxiMyYmPVHyOGT1RwUSuSjIyaAhVJIgEMe27dtvzsJcvXg5FU4/7R1/ddutxX1/chsy82YtmSZneLJgxl3wMzjqPMOeqFqcsbC6WF/3Fi6o9UF2gC3UdCEbbM+4uAtXdyvrRsBdFJkLNjlkpJQYEQBAolrlECYAIQ/DBq2DZf/+22O1eVs/o6njE1lP1wll891De9MVFYeg8qMTs3XWBYCZfOx8arSjmauuTjrXlK17HlT+57mVlrQydIJJzwd91On7TlVsfjLIcsVLWgkGihRMBVSAUAVEVisAFkRVRwIfggwgCwe7bk9y9vjnp+FVbGhXvy6ui2WpQ8mVVYGp2WgB4jUXQrFkTZNGMDRUXjUB/zL4s411UBaAC5ePQyab0YLDzK1uMD6bqDYTBXX20VaGDd1BYQ6oIEJAABQAQ/CBiAZCAQJEQIHgnbgAIlhR19zt3Ub/YumJ4/F7rwgGU+l14u7+svAoR4VMVnAwZzjlHmrsdkvCd1ybmszPbFgALENDY3a9HoXBZ1I2hFVl0/bo4ITlu3SerriIpkLmwKCEwgCKQAiChG/oRgUCQKFYMRLrOSY+l2KDl/be3V7xaHT9uLazo1K+GCt5/kP3QIHnigmDK82dOpSpiBgtxmDoZbJiyajNN530xc9yVFZu4bD2JPr+opGn8OHhpO3DabDaHR4OfQRAoV2AtjBQ8ARASIAGIBiAWQQRIKU6V4FpvShZ3wPL+H4atbB6+udk88IvavToafnjntMVtY1QGS2eFkgT9YaZvthgw9R2CLgg8Zxgk+7BgX6TS1FVnCLrDdm0clTy0WHHfo2jVP+zXL06u4BLEu2BUmLL2qwSFshgJmVERRVVDH4IbKibfBth+565/e3+JzbB66fETsLV5COX7U19crWHsh7qkxXxn9JLHtSy0owDMPWy6bMZLnJ7zDXMAlclEKu1JqKyqt+Uz17Itr7APDcjxrqOXx+NL2K8vyYxuLAcBNKA2IIKCBCKDEBQQAhCqhLbDToOIZx1utLWnb+7ePMdqW7nT7cs6hNWP3t2NgWsKXlYXDadZn4qLycDgElxqAuALT2LOWJdKwrNP1Exq9FsKhkNjyvrhgz2+sLY0Mlbg+yGglarbdxtVo0zDaPwIbEQYKOInAg9eCJRAAoA6790J2CP4oV/dj8MfTg3dvr35yQ1cX5hvdoUW14X7rkQBEFNbQlHIeUZZsDESknL6k3TmsOwHBdAM+/9I8QQVEE1T8Yp2Y9N+893q9RVDAcN+H0bXuXE4Hq/FIHjiChEICbyAAoIABHUyYqkKqioKjovWIXjXBXOt339907Edrt5s+++uX1f806/v214quypZAgqXZpanOHI9Qy8JhM+RXZbHSQeXOWmdGQ7nLwVu6MQUwNE19N8dmmt7P0p5IB7Hsai9Ey9GgVC0IBMlCRWdQW8ZyBYhgIJzBpwaZtvCALp+Pux2zzYfwstPXprD8OLu4fn2F4f3f/hwoisotadQoso0UEwucP4g0r3wIpMjBDDnBYwU3kzanLNdUyaMmrrbFTJ2zM1zxm05VGU3PLvdA8NqO7R11AFfEKlKYFECtQjKgRDYBeOAZVTsDJkr9hKoKQrfr5870P4f/nr9yx/dDeZxuPjJ5xff+vG2NcF5LY3Xs1xkJklp5qtOPNEM4RCmlMWZmJ5TvPwGzXrz0RfAG+61uK5wLPnQOyAQ5brGdsWEgFTaUZScsAQgC6BiXEnkg6qHEHAM0o5awOXo/dYO+7ZGfPX9o68/ffN7f1GH7vSbumuPPlgZNNC6zOKIcG78dP5vtvtLvcpWdBk0LmibgrrMcSrXCKBYYo9FI1Tv96Nt7verES/rIPfbNYCiJefhVBekLB5NUOMEwBtQRRVV03roQgVUm2JoeHdg/PjZza67/U/e/Os37nflRot25K4gL31vzeaaJdfAz3u96MmgcUkKZj+4oOQs3zF12efYFAGAt8/vH0W5WV01jy4o2iLcP/Tt81NDxwtyhI48lu2xJKsIolwolBYlOAhKAw3MCkJaDmGksSyIBqq27nJ9e/H45U/+ldgbfLczoat/cvUIq8dR0ayLvkBcDmeRuzqL6SiXzqZM97mILiOO+SNFjZkhBQCqLt56ckM3rA/VZrgri6Onm771n6yd79faVdrf41W/X22ws4yAFg07q0HZI5AfuBJVDlSZjpw5so6l37i67b//7H/3b9tu7D+7Pu4O3z6+/xfld45MYdc3x/02Ya+ZwukHFZVAgWBKdy3k0SzC2myN8rwkxzIZ4mibiovGqfQevt/W3XiJbmX7vVdTb++37ahe4BjoVJcaOhyhRqNGB9QggGoCC0PoZMDSmTHA4O+2VzYUm+8O5ftP//z/Rc3nm6ZSW7388i58f1MesLKmtr+f4lPNrjplkHQa/hQgzBH9wtED5DBwFmCcJfYMya9e7XxpQoAblK2OpHf3Q5DisSofqk1lvOhKlTbC4J2yAQkyVj0OrIfKgBoana32DEfcdL3/w5uL470W47gLf/b/uLq5uCzWjIXZH80LHCq73gx+/Oa3f2YydTjxJ9ubWFTInNPJnkbJMzrTtaxDQzKzy9x2zPl1rfSrywsdr7Wy/el0Un/vDez74lMfjKXA6ioXbPA9moIqZBmDB0UM1gsok3I5Voge7cEOx430w+WhtP0v/7s928sSunV1quvV2797vvHFs+3uw8N73vLZ2HTWxyVTZoCaERuAmXN6s+XNvfspcp4gHioghT/03gcnn5dS79rjSbrTQ2VDGNpxc+gN+0JZSi+9PVw3bNRoGL0x3oPaMQTHKCo9GF3pCOSvL7rhouirw3/4Vw+wN73zh5v7/Vi9Wf3mYPhyVe0+vOv+oiFcJMyABFLCX1MMjAv8nDQqvp05eJ7gXki14jIFgKb9evNiewIdyzsH4mElfvO8VXKnavXQXxpf0+C1K+y2rMmLBKUSRusZHAAfEJC17IYV+6NvzeV4PF48hOblb//eG+t+840p3teF69228l1jCB9+629e2amvbOLSJKGwjDN0JiN26ywLoJOLyOZlFtfMdQAsn3/1ePHCWsR3j9Q3mxNToXfj1UXwY3l5GIOtve3Er8ya7DhWAoGD6y+IqEMVi2GQsMZWXT9a1fXoetv7Fx//LVRFHWgc6fD+y9fucOoCjWrLA3z26QXlMC+RkYk6qw1EtdMp/aoIsbq0IGdZ1lviAZjdDt+8+q6zG4Xfv1/d/uH5q3Xl9seyPFU1yLD1fQMA2rQVF4a6Xq1KW4m4Byt8IlOYVgfrHVad6sUA+mLvpe/Wzb978+lp/cHYbm3C+r1+yX0QPB1a3vz05ZVdBjV50vEMt+giCp7BdqpNzGzLVE4RxyKmT7+petbdlGF/++043qLB4/hMfn8aePXCmuFU7C/QG4CCAHynwiBhqAJf3ZkAVnkwoWgq19c4VFvvtGq7nbr9P/kKb25//EFef/dZtfqJfHj7W3PAdenM6F6vAkFqic1ERPoy/kadQOjEnUiRIppcr4lobsoR5zOjscr/xwjLXr3S7776OJhb0wDJ3WPzT3fvx7tXlchhU54uUIG2LDD2dU2ibq2+d6zgRqwOJTdWYGhBgPVt+BzD4/rudXtv3l8Pt//s8NN/1r773embhwv5iK9Xx279yRu6c1qYibyc8kyswkzwXOrF+TBFkz/BHAJOVniB65Y0E8DF6sM/3O36DfoCwVge/M+f/WH8UBjg7vJoyBlp1wimHrgajJYn3xnuSCR4Dg4erVQPzTUAMKxCOYxXP/ufTqtP+O3PPltXh493LXzstmLVrNBcbuW0f1ZUlib+5IGpTgg5tzjMCdzJLJol9QszehbvLpIzCEiVwXddWWooT1LJptqL7i7rwXmLjFz6euD9YG3oTVWCcjkONKJUbqjZUS0h3MKL8cb1V/Byu2qrbfEXv9oz890vXvU4rFbVm193ax3t5pLN9mc30vUjGKZliwYuctqJas1mMw8/FcpNjiCzdZn5NddAz2SWzCbouho3xQ438j1fv6jeiqELHErPvtZN76thKEPAUBk8uWI8GSlH7kcL9UPpa+IQek9d0D4Ugy9vftafXtbH419U76sGj+6qG2+uvd+8Kge+fNO4How1jMs8w5NwCackzGQppsje5MBwGdIndZtg6Ox2EBC4Br++vLPOHC9fP5768kXNDbJcGN8HslT11bCqymNA1w5k/QkdYl/puHGPVPbQmlq4wssdNp5bwDfrb4JdbbZ3dzerIdxTJT96Le/Ns20H69cXFI5c1+aHdRKJdEkSrMmiZlOZVG3GomcJCl1SvAywAIitQmXX96ECoC/omdWSmFypUFKFo66LwSo66J7hAIDa6KgAoTwNzWNNshkPvYEtQNVh7cfi8MXdylx+Yf4Wbuh4cq0x/Gr8Pd2sTmH7yY2Bdri+sAlYTcsLJnbpxDClzB2dcTWCOadsibDPamcLlWTjis3FiS/rvT7gs5o9OSioOI6XRfDiQuGw7EZbDIb999tnzhsOolKyVuogbFiLGtCdduvP3tH4/DgWr/7UfVddq3s39H5lN9uP76Rp6eriZWmaXi5KnRrbzyLzMx1cdLXOsAzPG2KmCOvJNc6zT6ZwUrx+3Thhf7+7v3e2aizY0pArrRsw8Gmw44M1e1Val8Gb4TSKD9ifZDwZFSx40KP5OPBOt4V/UPfLD3/TrlalnoaaqCz064/B++3Vq+sCju+gDsARMv9w7co0yFSYy1zIUqtmMScLS4PnZjSTrwiKaJyvwuVIe1qXthsGwwAhhNqTlNCt97rd7QIHrLmVtaXC+JYqdSpNN6xKDdo/K3beKOj3rz7U/ap+8W++G3/x5uhtsxoMuHD3HTUWePWsCrbTNxuyHLG1nqlOSpPKogdttiDJqIJZeMAMep7OkU7gBgFQiRrFgT8t3t43jblc1bYrRXGkqj7B+mCHxyvucbW/NEN5D2VjoOr0sAmGS5QyhKEdAQs52bH6/v3hT9r6za9/S3/6ReiKvr8wjdx587M2IJzqph3Wmz+tLFe8GD/mXoTJU0xrXrNLxxgiACoQTor5JPOUym/zvOQ/0a4qLqrq+Vpu2/qzl2ybwHUJYzix5edSyiG4WtUUpaAdXGdGUwXrbVkWod8B+mv74Tu+/+rl3WX/2W9ffLL/9tlfvrG/o+II9eqzV5/U9ee/vAHv0PWFhHWJzAh5OfJcp15q4IIVmkFZfJNq9GkHgpxWnIX0h9k2ALQaCqD189Ot/fSqkNaQMTDIaLuLXoqxcJf33IyAyFixob2Ew0DX983om1JuNdj+oRzhpv4w1h1ub4fq1bV5qFds/8w00jfjptz3LRD4Fezvhur6AiACl6d+eQ5adWFbMGf2EaZGoDMzmQV1UbBYeElV9b2QMlbUiYLTQ1HBftOU4MPYe1gZlU1rQ7BDzcP+pcWTPmzVtXyv4Ey/acag4kLz4fKbn338j79bjTcW+qG460/Vxt0W7LfHbigtjuFZ9btf75/zOkqfKk7NLgtnDovmiadFUjyrLp3ROEOGRV9XmiJ/a6+CqIZnn60xKK3ZYVe4UJgPK+R2FbqLkcQSB7nrNnWgboW7Tf96lOL9Sx7ovmiM/War1WfNp77dPDQH/ehqPl293MOL41GpuPq0q8LhRsT3IShleUOIJf7JX2T3npUy5WymQ6ZVhfADcUzIVuF8+aoCAJimbir0R/35Ly8IQ8OFRXE83o8yokFptG/aoede7PWmOx2JX7balQOvq8uRSzIruxn19sK/PjUfmp3a9W71uf/be3jcN+O9f3VZ16/WUttw6srL589WllA1hjQaw6C4LgkAdF6Pqgqo+XNAUNHcbZhPPBPSRfA/szyysLg2xrv70/VnjQ69rCxWwR05hJ5WbqS+ag5bD+pYUEX6RkJT+pb666LrwvF6T9Dd7K8+ljtH7/TCPy/uf/1id/gEDnJJoaR+V1+v8FePF6e6uPzJ4fqqMnmacy/xHPj9sHdmEsjIjCcSecbEyWWekanIjfUawuvn60DSGzEYCqVhMCfeb6mHrqR3zZr61TD0ZVcfysqsj5fy+JzD+CA/un3Zlv3+cLX/oi9Xq9Xj74rf2ueHcnxV2tO967v15Vb85s3H062tVl90WJdMklRqWiP4Q7Of6NDUHJdGnVafze7gHIJqWvG0dK4IxOyluq7X6gkvLB2dC836cbXeH77jzcZ1w8b1xl2gKfq39LzmdXB3N3pV+aH+rhIadPv9UL5t/GDN6vavr+qfNpfNx4uL77XfnxpDD6EOxZ9/+9H6riwpZJeH00qohV+YR5eXbE3iiIoxJ4MTiUt3twzul0VwACBSKcwKwRvfVVSG1bHrry4HaezmWLXlxelj82HTbvu2OOHncmdeHD6Y1tS+a+GTw8Mr+yvpm3D9+pvqanXL/6z/w2X9cPv+5jt6Nd58VlL3/sNzS5vniOSPMY6Y0k2T7ctePiPvmUe4NK141vGbJwCnuZktD+ZvEIDJoxWjA6or+uDRmXI4mfqIvjj94ZnZC+yqFgNZbjz3/nrXrcQNV16rd8zuaFer+7Ye3r6sqgd7+nj4/PQ/v+zlam2Gumq9rp+fYNOPz7b9h8BohGg2EbNjyFmm3DYyZUiXqpndxNOm39xUmijLvadZXwkBwEBA60JhFEeoqFx1PRoTXvaDDbz54GrZ1UGQtK46BRhWr2SEm68uCz2Jvjte9NV6qN/XHx/Wnxzlk535HN7dDj9qToquFtRSfbEKBx25yIttsxTpNErA7P0zQYs+7jTY32MyvJnPc2siTH+d43hkHAOqdwxelII9aIkSBmcHVF8JUPtYGjXFCofhty9Anrl+sKEuuK2GP5Sm6Vfdt/RQ9T/+yeXe23dvL2wJn2+639Zh111e6/geXt7U2oUaT7twUdnaoIjGVbSKoDKt51UAjYvuIt+m2oWmudBFtmpSVshNgtMsLHBAUgDGESwNo2Wh0Zge2axCux/C0ZZ4U63fdZ+Jq+G+uOwvd/e6ffFuL0094h2jPRRDt/Z/+PJPX24RubIvmp2u5X1/uRqr0Q2P/fq6KZypHEKle1fORc/MjDN5y6KakomZnHTWIqKfaF8o3VkMmXiMiErqlWgMio+6Di64tcgH4BpPeLXD3cFA//616U4df/pwGOjwYtjd1Dz6ET7p3xXtriy7mzqU/njcmU3xiD3ehaI+vofPYc3hCo6P3acbGzzWOopoqpUlyVyQmzDnwiLqtF1ObkJIo56T4DmamqfoKakI7JVwEGIvY7XqxtIHKQ53u6u67hz21UVFNept8azfHcW9vBlXDcHjqw/YfjcU6+Mn//DjfX083t2O5fPyV/vKyqCr693Ni8MHf/cM7gdlCi4EQin8aDSJX2SXLqhLVSbMW3VMsUKK8DSufFmsyoLUxjYD7eW2I5rsqIAacQ48+Wbru6EM3kJ7OjTHt76vXxi3X+/e/0d8snLwV0O7uQ+v6Pp0PEK43vcF0P2z94wvP6PN0bZf3V754hUdjruqP+7Lm+F0LeOlJVQSkAClD/pDpzAPduHAcGFPMqb7R5oQdA7+F+xLxWNUFUERDSORF8ccZDW8243+Nx8HuHjzTXVzfHZ9d0v3xzc+rA7VI9fHejhdD9WditAt9GHLe7n41arq3rpfvYeq/vkXe+aj2PAIm1D72+KZLezQBQyAzplz+xdNxBRFUG5/WYCu5OowFl+mom96s4BvCJN0ZMyQLJk79SMhFDD2x2fN8d239PavaUMn+N34RV/uPnm+H4u1Kbl7Y+X62/bmYE310J02AnuUt8fnr5792xcfv/v2K6rENP5f/+aXp6qy+j1/6u/WZYF+JFNpiyDgWjNtfrTwzIupJ4itoksUlqR25uBcnFquWJ3DwRkpKACwD35oKyuue7y+0uPdv//k9//Dy5+Gh1dvu/bfffVp+KzfNyfPh9fd9oT3I427mj8Ge+G6OwVPj5f6Eb9+/68Aa7HGX9z8r+7nb6uqNPqwsrY7fHbRhc6yGyzD0FrDMIvUHKBO1iaXixZilqn8ffxiaT8XbIPJBU7ulAg1BG1PnZO+42rN/aE6/Ubl//lPf3R0F3b4H+1j++nnn/7l78aLu9o8h6tD2DyUm19/cUv83cXboOU+PF6Z583//K8/Vf1T+7U7hM0L/rvtm7vLl1enYq2XF5WRje3K8tAygvPVRbVQFJglbgoxZuVKZd80ZDUT45c9FucV0GiBFokBUQyuH03dPTZ23Hfl/btV/X//4nP56X/mH//wKf3Vd5v74/PLndmeLu7+pD9cf/umu/t51foT3tPel8fLi/UV/8v/4SX8+JN//rf/2V/9nvr953/x312tYb+6tJ/vK65pHFxRiIIiFCzO8pKyWdTOy7TJRCwWoCwSvzpTpQtEFEnPpyMCEqhgwGIkcFXtd/1V8/3rVes/veEv+//P+//r8//2Sgap/vV/4+v1tli9ry9CoRXDR+LV4USuwaL91NZ/+/8uLi9r81f/l//zYaswmhefvP2vv77HH9V18VgfnNWSjnXhBy4AI6GTB0x4ZWEDl/yIdFJi2dSMl1MAWdSnuiHmDFySVARQ0NB3hwbkKhzpDd2F+urd9U//+R/43/9+e+r+5sf18Y37V3//y4dye1e7zf3F5lSX+7HEh/2RSgpUCLT/U/fl1auHP9lV/73+891Fwesfvd2+xDV2t/bgO1f0zar2NZ7gCpXsAoVgNhNZ3eb4draj545+0tjz0C8LRU7+48xsCA4axQaqF34ImyowXd98kGPHw+u/v/tFDxf45q//03Cxf9lJX2MoyoL7jusirHVswrX1335zdfXF5191m+ffVDupj1Le7KpXr3YvGv7eHoarT7jzYIwh11bEBpf2c+omXAQZMEcVy4AezTlrcb7GfNDTlwgoUevJFiVgYTvWa2hI+41ctnalf9E+VC/g87/aPzaMpZpdQZYd0uoUumcdrlltYb4uq8s3F88vPisvV7urva3Ib7F/fiNYfBG+Xr34prru8KBaW/GlmVEZ5Bgiy90UBeNyvNP2HakJQWFCNDNHp1mbC/SoAOA9qTvhNhShMAEChpf8sB53Zb/6LGyqv7gxt19cuxf3b1+HojkNFXDTi/JQtLurowO8sUonfjE0z37mr67/7Osvf/EOYavf/6n8GAKMFeOnH/+taKub9++fhY4NyJl0TbqYgVX8S88TuWnMsx/ME5DFcFEcnPVZEREUeeyluVRSoycxZvBmLE+4Nv6u+w3/n9p283Ld3V7ufjoi1oagcld8kqpjex94K2JH67ef/H34WA7vP/7Z3ci77Wc3J3/NL/1Aw03hhvqLDwfk8vLOsO/BFhNj4jCzop1vN7qUzJxJjHs6LRk77ZEyhVuq54IqAqBcWWG03kMx9p4qPm5+zVX3dx/Nv2jvDher8PHd5+vBjIOvD2uq+9pgXe1co5urN4a31fHyR/1v+sPGDebPftRff/IpPtTPN6YoLj7Vj/3+7fujbD7Bj40GuqiCiGaEtVhMrZNJPKsqpcAj9ZcuOkqnqGFi1/SVLvOjQRkRyLXei3EDVE3jx6b67O++hxe/uDT7h339Rc3f3/242TtDVWgK4RWUBjTg8KKoh3ARqq76aXVDXF6Z2+/v2mdfXrk/vKo+R9m4wax49fMvXr9Bvym9joMWMvhFwDaNCaZd1TKsXHq3xMZpI/EfvM4QwaLnEkRB1SoAWwULVgbr4aK/bv7qv3zzXFbgnn96New6/E+67sYQOt+NG+Gted+vLRhTh+2p00Nz85ff/nr8chOeWdOtblYfzJ9dGUePpJuxa+pH543lq0A0jFXFQc/dQO4VSUOa2arZbWR+U2LxjPTOdpY7Z2XMKAMRmgLGHlnVFCEYNGPXvPjFd//rh3H96Sdf/vza2G/+xz+/Dms5KUBhtnriIvAjQaGrUI5q9q1r/7f77waB4sVPfvT6Bf/9v3rz7ALKwm7M/tG6/+Whor/7unckWBkBytsy4dkil/gLF4Oc9xAAjKUoM7vLcyR0htymuUn2VUfPyMh4ChC8jn5lN69+/PBv4M+rcPFycL8//cvn/+J72ROhRbS+8xqw9IHBbFju7diaw7c//q//+z/c/kn1Jb0j/9Xv3vzktUEV25/G9TpciKt/5u+Kyh3AKIJMRg+y3VuK61m+ZTKOOsWDeX7OqvXneHT5MYJAVQQPAQrxYl1RFXIHr3/J/+77f3oj7iTv/mb/Xzy61++3RQkFSXt8XWD/jRZudWn8yvZH9+nq3fe/+P5f/sg8v+xh9+3Dz//8U3vqS48Dbivnbr4fcDueHHth2wao4IlcncloCtEnHi59eE4bLv+bI6WFlMbGEiBQVWJmIhHRDtUGx8MA6pof8cVf/99eXL/p3v7q5v9Y0xc3K1cYS6ynSx4Zrt3pojH+8tD4ujleBP/9f9D+zUP1K1+dfvR/+KIanCekqgm9O2jVfH98XoaPz1Y0FLWCiNHFoGAuZM5jVYDFtp5Z1gzAEx4tXgtoBwnfIikQyGjDgSuSctTWQ29lBAzh85sX79+++x3CP/+Pr5qmRO+1HCt0o0Hmm/Adc2274pnKx96E9baX/81/pKfdxebNJ5duOK6JgAbXBguN6V+9Z1x3jx5OvtkUNOeLpmGd7bl45uMXzALzpC9jwtr4VAHjaRHjCoDWpaEhMJMfFGlo3bPNrf0nP0H1MHJtbNf/vrIbSzgMlbEFUMHWtVXRVsz7we5uvtj30IttqqY53btyXSm0j81heHGv7VHWV1+vLxyMpH05lJw2ADsLWzUlGSb4CTDtEpX4l3vVFmRPOW+dQcxkp2LPlBBqjxWD+MDwQNqglHL1/ccbeyy3bqjAFgIfCj9auC0LZ2xdgFD5jIf+VBXH1fHbZ+VrKF8fbdWHQv0wlhUY53r1snlOb+hDGbriR74YsFFBHcYwI8YJsuVYJ5mLqS1higwhY9Gz14xqFgH++R8qajoy7ALhUFqHra8bi5/0azKFYF2jNWNY3azf7la2HPfVM4KgKBeepdgLf+Bn7YtfPvQNW7Ma0DMXtTlogzK8xMP9Vg1ZCu+evT6WwFqiCy4RpNlH5JwSpOUfuhh69pdxgaH5gZ1cFnKybV74QwUQZA8FqRhDzm92Yst1bz76Y29NdclNOK0ITT26y+74SdltCm6tL3FlOzL/UOw2b40q3LljWRRIJQ3kC6d16Ib7QUe3PjjEce911/WILTAWcI5QZmiCC+Jw+iJLH6Q+maccw4nBOE3VRKWCCiIMY8ViGPHkuB6Y+ofuePHMWqGPW99f+HZVtFqasW60qlAKUe0bZoA/OXXh5u+rly/3tl4zeqee1ahzY4Cw2VTFeP/Nz2gn2t6E20O/fl6OFaMRmTrRnojb1Gg49SXMKBoUpu03F5sFnB27rEUl/yLAqgawgKBQcy9gCcxNDYEPjLqv7H3hnAmbih5LcOoIKNBBjamUdQi6CnytRYPDxQCm90zAjtwwDs+pPSi+6Vf1wV+EstkxQ4njumlKmou7cxZpQSNMnTSafaLmDXOihqbw6SyB8TQ5F/lvBIA7X1BAB0waVqi4ZiwH2XT8tg6n5gjNfrVVudmOY7AeRIxTYxBM84KG/kVZQiC1o6r0QexxXZ/0+XEEU3b1pTvt36+3G7ztjtXa9ARo435Kk3NfrG7Jv6YBKyjmfa00V5emKOqJDOhSQSPYRQR1AKqiCAEDoA0QOja0It8SHhu83/+J6/dXayDeOupL75WdeByKUkPgy25VHjfNiKGrurqDjbsdh9JeeqoZwwYeD3oomvC4blYFIONJ6yAQY3ldDmXOXCxoSKqXwee0p5POErgQ6ETlwtCQKqpXhoolCFgcsbTclWiORXuyu1Mpq822L+12axjsqGPogWAECLVhUjWhrgc4jlfluOXe97rBnl4X94fh5SE01FDrBz1y78PIq89bY1vBcYQ5HlrYmsmYgM7f5bguL3w1yZcsQYueX+ecqcIIokojlCQMQawfHsvaHyq/s+WFgOH6lgsXuKTW2QCD8avRHMmtAIFGdqaC90MXtlZXhFbEXr83Vxe335XF94XotryR8ujNhen3dHX05bEiswjLcRGZatoTQLOPXoABzbnFb7J3n+mbTGwKMxY4AciasRVQN2waBFGFrufWeAqnHnSLd9Y3Etg3ytvG+qMZALY4ulOJxasi+F5IEHsq7terMRDgh4bv2jCsBWoN1nuo9ETjMPJo92Mreq1ldXXd2GmxLiiAZL8ugFOrYRw2SjY7kYvzE0NmIZ1d4cy4qQCDiEg6uAYdMyCMQygu/LBy+kxcN1jaPn68oQ3gRko6SVcI2RFLvi9ZqA8hsFBVobxCKJTuH7fdYbA0wAbUFTRq+3G1KgsIRh667b1/ZhWIMD81IvEqBz65jDuNVqfdUwURztYunYl2WvCZK6FpryRISRvr+7EsJSg6L96uUcNGtXGieKhKgGelKmzGpu497q5ATgQhUFFI7/sRA9UFkoTCjWqrNaNt4H0wBsqHYEqqL4vG3blwqgl0hS83447rgucCbQrX41aQuWYy8+Mck+Qui6WxXEgnJHyk0+o1UCG2UBqRQAiqUFn1jozQ2HvvqsrxVUvboWb7rGy14wGvR1+40ThfUie91g2LBTZEBruy7o+r1fccbveb37mXBVeFiNt3H4eSqPBuU9YVWmPyBsyTpUSUM5eNMxCPEDyXQc1SQtMZ8zq9s8THpIYmkHhlZgHxMpogPHadK4IUWB0LWLv7F8aX7jTSuGqvRWk4qhbSUzeO1Whd5RmFiKQaYV272xL6+jBej5Yf3zcb2d8OVrD2AMS9A9uYH4TemI0hLhUpMWQ+FvPOeDqlESdmL+zOfFEAREQRUkKjoOKPTYl22A0nLfxhVYIM7MlqqDdmtX8sTN9zOyA8+Mptjx9LcL6uwRsGRBQADg82mFX//ivYNDUGVfeRf1uVsrYKd9t1Mfo1coEwG8kol0kwz5bDLDc41Jw0NRMonx1NNrU6+w7IKEAVQEU57r2gPUpPYJrOhS0Ra+gKLTVcOVDtulWr5mLovwEEtadHf+wuL2U46oUVAlUEIrrq2wPYZwzs+q5c33zYA7tDzS9GZSmkH1flvG9vJgTP5SrTtQCYWWwxVzWSb0gcx9nVYPIoGHEQEhIBsQ9iFAClV/C14qV0pdn6w7bpHvX5WtTjKFVod92Xdw8NWe0tOIEPa/g4bg0jqhAghqDYVOrKl909bW6q9ncfx1E1PH5Bx7aqir4HLUuROZkySSYgROAx14aWdOZ2k7kRKH03Rx1z70VexwsIiETMIQSFoaDOCWAfxnIlogAPgvAuFCujHjcY1j3V/t8HV4mAtwJ6gvI4+DclJvEABSQI/ft3dUPH0FfgDu8I15f84FtTrM1ut61VmARj4+7SOkx6OWdmsglalGTSPtsLPdW8Pi9PCC6/IzZMbL0TGxwroBc9Fv37alOtOWC7PWxsWPlAm0I5nEif//nffbz9w/9+K4faHP7dx396fPOnJXGuEhGBNgUWa3p/tZH+/fEj34Btb9f1he3J0L7dXpUoAXBO3ebRz4ngs0pYRDpp0DRz8En6RTPR56YL2RomZXBsoDbsexJcHY7SWltaV6xQoFG9gq4o4eRXjvryP/hbOf6b/2q4f+X/v3/751dffLldW1GwyQ+Teth8enW/4s6fvjnyeFuvr9wd7mG91fuxurgsxQeL+YE1mnZ4n729znZf5xnIsSyaM/rOq5947h4BiJgNAbFtUNUW2vBuxwiqbfW8AiAauVJdKRiCPZAxwa31L/9J/79Y149j/5f/+euXVYFICKOzjEiAwLprtaDOrPf7/XZzaqvxunyLxS7YU/P8zUoPuEIC1qmcd9YYmICNTtxL+pQ8Z1wB+oPXgqVnSI6ZEYHYgu/QumEIYMCLp3VFaIlCaAI62X38gpyrqo5X5mjfPJT/onXiwqdvvqybGogBTOiBpDM1+oBAuOvbsu5ha5uG1mHAT8Do/YEbourUgiFKXiBjTlzKFiogyLmsLaKJp4VPXUzOfHiUUGJCAEBCQXXaDUwIm/oFeyUMvR0HPzysN8frFRQv0DcoYJD4OPZMssU31bYhRCUAe8kk3jIAm5tWq9tH04c3RTlwQG79penuPDU3lWGVuIMZxmdETbIW1XjSqIygU39FRj1gplAjEzeTeqaY8QMiBAAiDeIYoYLBlKHtSR63eiVjN2rxci2v1wWWqASCUIjU8tCa0jT1p9s1I0pAE6hAxBXGx8jWYutrdHZ/f3C+0vL5aA+H02ptyucNQqHeRRmkXEWZcxD65AfOnOTUq3ZmRQFgenzIwpYiQiQPCJhh8IzeQuGHgVf4QQ7VyrItGHpvC2YGDQiBGEnt+rk7XdbbV88NMYN3/coOoTQQEy0K4vcHsfTy+Rcd+XsYu1KHsG2eFVdFoYoS+hBNy7Tr/OzOFDKe0Ql94VxsOc+LZjc/G5ccTQAAALNJ25giEVGorqB9OGysKjzrB3JFaWHYy7b9YFcXFasSIzKw4KWrvq7fXFsyiGBDicOpFFYsGBUgKK9O3f7uuL5w4eLVUDTtyZyY1+WFxXEIzlNM/BpEUFKapDTiTl2MOklo9NuKqmcELtvZcrCbAI6iAnAy1UDEBZQrOjksPTek3bgyaozsW9q/X18ZEEQiZFAFDQHXerGqUYAQ1RtjnC9tOFrQ0KPR0ePK4sthfyrle6W35aVpXlYgQVECBAfoRAUQkTBlzXJqQgGmZssJcs00oJ61kcwwISvqJJ+qy6cOERFbqw7L/bhZ+/sT31yuqJBuMKbZrAjLxuZJEzfiMdhtZUZjOmYDVpFXjHQphpWCCJYy7O+obi5DX+2+Ko77tfHlT57VVvoYNzgFQIqNr5j2vI2dFRBT9xqTFGc9lQqqOFeXzgvVM37FLKlIeW9bRGLD3kNovWmMbK9wPJzwqllVpxMqQLkxCf6LD25QOvF4CqStWQehgQ0QKSmDqLHqnMKqfnZ6/O29vX725Wd/w4REZmjHsmpK9g9ORVWAIgPT8GKBc07cJ5KyrwcUUM3NeAspnSOpM8uDSERTxwKSlUFEAz3bFH3X9x/4+dXF1vZ7WbtAxqIIBSRRdU4D0npXGC3AGi9I3lfsCRmQIDgCKEHaW1m9vLy7vX+/evln2t4N4aohI30v9Pry9j54r0TEJMtigi6VLg87UZHwrubN/CfClxK8zAIQGzvtlAzEjGQsobjbtnp+9/nFqgqt7YtqPOEAx1velsoURELgSp2H3dhBxaBtLY8SypNYY4QZRzSKEkKzf8dm9Uze7x67/pNftu1YGCVE6ffj+ub4/uiJDRPhlOBOgV4iKzfUJdsRdQpk3m7lKQvj5KReBVAUJZrgIBBzzXp4DMZWl7C/vAndR9oWlfTOnIIWXAugIgYmcghjcLrbNw5Ks0aptUKjgCNS7xl6YRweO3uFrv+Az1+4Xfv33Ztn0MaJJTy+54tPYdd2RBy3K51MxCyhU9ImrSyPCvJ0f9GFhs6ZtUgVJSefoha2NPadkKkakevq2EpF3lXj/jAE4JtLqBgQxZIXwWPwB8+nY12GkYQbYDKqjJ5q70jakZwpwdlVVbUHzy9e3PvHrrmSU0AIfnCh33/b3Ly2IqMKGELM3Uk5gpgqE5h+BBIYMLhIYWh2e8tIPjoPmnxgxrsBuLJYWiyIel4HBGZQgGszXm7GtQGAIBjcIBraXVcX9+bGaGAmAA1i2LFVoQJl644nXRv1fXFR7m33sXxRntrhbn05ts71/SgKYbcrL28uKkJUnZDMMnjF7OVwYpTq+Tr6rLJz5D9xEJE5b4ylAAjErBaDKQm9YAkqQEBQXq/s6fVut0JR9l7VB/Ey7m/Hdcsnwyvxtqci+NoD+rhVrCGsufNaNN6NTdjVDvfFZtsOh3590fZ954FFRMeHU7Pdrio2iKqgkhe7pOgyeuype1tBFWTeKX2qyp9r5GxVTPbyUZnZQGAiEWUCRGVEBaEKoN6HCjqyMgrqCF7bt62prFayHzarFagj8L0dEIAHtnpAG3CrY/CGh8fm8mSCgaPdrk/jwVQ348cAoCLqAVTFD0VhmRCRcmQbF7xOpjLGEpIQgJmpmDsQlqzMsktpVQkmGUBWRu8BDSGSAiCIEmJ1cPsL3PevJCBSz6N8v3uob9p60xOM96dnWyyUSjNiUCiC60u+5UsDXEsIwYbe3hwUg4W93fijO431579qjUIQAhBAIuKM1fLGPnMid86dxQPmJoSzJrYp3Qsp6wsUTejclYKkVgIyEFGKQAUYBfCidebh3RcUlMg5vQ+Pw/pytSlCQXwXuneuqk1ALgWpk/oRDs3V/e6C1LASu4I63oyBNODom8vj8f62+tm3dwSoQQFdx8ZYoXlDQpgfsxhzwYiLbmcF/GZpOZMfibxSyNsEExlbWFxKr6qKqE4PnEQVJVARwlHcO30jTKT9cHjHflXWK0Vkccd+GKjeNIbKyo9FP670dvTbq3ZclcFirzx4owKjiCIhUtX9+u2p/Fn42vtRqLCGm+12U1hDUxQfdU9BAST2pyEpgAQNsmgEmuvB6U0MoGXSQD7TTgUEyoW4VNFiBQAizzY8K4IHknHwUkO50k0xlsGgUdO0Y3iAkoHFDAy71fbWDo9X9Ukb0coNlpSltz4AIur4OL7oju3ffPmLX+/BI7Gg78vKiKRA6wwxL3Fm3Eg4uol5jcHylUORhGSJFuXfqZackqapxwtBkTyw58a2hQiqQgNqCyl4i6qIUvYcvHNolMlLkO748npvYL+5Op0qdlgOanXkYL0QqYbhXfuJ+Y3/6uXP/+FDXCHv+qK0lIaTx55T1HjWzgsx4J1t6OTUJyCKKZ8xP85iPgryLksKqBj3l0ZUIBFgtSooNjCQWKtUmiCuKIU9QRhBgkdzLLuawv1L7Rnbct2fipV31Tha24MrRpUQumP3+P7TX/xG7rov9DuUwKS+7wvCtGwgN87olLFJTXWah5p63BJNs8FZeEdETIZrruSkczQZJEKAuI++IgZAUgRCICvAQGSMVQyuosKgkjVhVBlERwolwv5SBdGFtT2d6sJb7KnyHVs/hvF06IL85tWfftO3f/dj/prIgAbXFwbxfOUyLEYLoFFAY5oDYG5Yxql8mDQ36hgxJ4yLue4R6QZEVBVNbjVuxyBpvSIBorFclKjECgE4qI6iqMaAoqqRUq1l7bYEQNjRFjpvCAvXm1UITOJ9CCLw7tc/uRb3q6ufOOdcENe1Qwhh2uIBErai5MXyvg+RIspOcAI+eag5+CVEZsIUPJ/1+GGeAtW4clhidp9BYmWFKQJHARUwAugAFYMioDABGbCMzq0JAbX1DQydFGTHPa4lMDOzIVQ+/cPra9F/WP3YOy/qh753EqbCUspHTd3AKR0lUUFpFtlFP3saf/yZA90oATjPCCEAEWjKNksUzrj9JxEhIiEQgqKo+ACqBCohGGZismqULZGnWlUBh1Nlxv3OYgUnWRMWttqsCkIs5dc318Bfr3/ifVAN49D7IJp36sCUE8sea+43obi0MAPvxMWlx4eYXp8sE2bhzH8BAki6V0BMOQSNbNW4aoEBRACDDIqk3gVFQ4xkgEGZCEdrRYKq23HR7T9y2eg4VOCQ0DZVgWjkq1fXyF+VP3ZBQMZ+HMWHCPozYIseMG1TMi+FIACQXDmc7enEflACn8vXC0Zm/SbMKqwSF/SrAghShviAiBLLJxoCkEUFVGIGQUKKO2X3NQT13vcf/aX0d7BeSdijEQiDj9A+/PbTrSm/MT/yQcT3/eiCC3PdfrbrediggCAw6WA2LfrEMClBmKk63+Rpam8EURGdAhdSRJlyJ0Cg4oMCAogCcbR/hIAEiEAh6DjaU9d3w+ju+hckD/2qEX+gFei4P3piBeh//VlF5vflJ6MPrjt1g5Mg894xaTODbCA1mXSNMHkOr85yFgCArIm+qSK6EGBMa7QVJKQNbeLlo1ZAVFEEVAkSFFREwFiiqNeCwCCkwetO/b4dvYTwcHxu4XCsCqKBLtCPTohQVY9/+MJa83X90vng+rYbQwiSik66kClIkVQKGyl6gxR15KFPng5FEhWTdzifgCiDKhqSAItiNDqxxk0ECogIEhQURBQQgFMKSwkDwHjw7YfGjy6IKByP1wzuUK8Ze3lZG2YQCSHo48OnQPDVdutF+rbrRx/CgiE6EZC1UEVj8QVm4z9XplABSQNkeD5dZ0lhLpdHowKoKpLb+wUozqQoqiJ6ABRkRWVVYkVSUFGP/alfhbFs9mwIgKjlm0fBwwXs4TR8ckJjSENQoI/NzQf0X/10HEA7IiYSoTnIi/3WOu3LAQA6PdVRZ0eYCFVAkJAnfUHi0sEmI4IIiKIgIgLRvsQQNWgI4lWiH0aIzxciZoq9N+LH4+nYjb3izsZcFhH344V6eCgaDR9+/2YLxCoKEOTbTRW0+8MbFHF9ZGFIiCTtBjHZT83Clh/YPe8MkHlJOV4WPH/S7pknSSQSqqKGOBkCCBqSlAQPIjErDYCacAMpBHFj27rjYfTqlaRfETMzEXMrK6/hVDTi73736hIjzFCV715wCPf3bwRR+mFwWUaTHsLZyGKvHk0xbTpyMriLbMX5Uw8UdMlRxGhNUENMk6iCileJHSchpHlEUoj54/g8t74f29NRwEPQoMb0FYMAESHozjTBBmfXthy/fXYNTApICP3uJYh+1BtA8F0/uBD3gZixV2YoQGxXg1zhzQI6/8rBIbOcKSEsrW1UONLoYQFAVQhAFCQggGpQEASJqUpEAlIGAJBhVHSO1YgCM6mIr0bM0cxhOyrhuL4Z+/D+Dd2rRjC2K9krvP+8FxA3GGaKJiJ76lSqiJs6xjhgmR0GSCZvUlQFZiE+dx+LDr+8pQAixedFIYKARBs9bxQd2UlAlHokxt55CUgoCMjGkggOFREgMyJgaLdYqGmfX11szMdy5VEViQ2dkEH9/UsECOM4Dl6CpHg+QeWskIqImhdI6jTm3GqYH5vGGOgHe5BOYWWGEZjlFAAAJCYcgLKxisYVAaIso/hhAFBViwpIljEIYgCjSIgqotpJhUw8vrS20NtyG0ABkG3JhIBHtxENYz+MLoS4XmmCaBlYJVnNogVTHDG1/wAoGAiAsHwyXhLhXBCHlLXAvBozyUPENVONIEZSCICoEsYhIBtEjiJGTCJEOlpAhCAKotjWSFCpXjkv4dbUzrsgCmSIIMDdCiW4YRhH572X2QtOhIlEcJU3zIGUAUgeJaVkSANGVJWPinqHE6U6N/3F8uuUt0NM25uTIkACqoAi4r0ya+kAACRw7MklAVdAwlyAIGPplO2j5XsMbnc59hjrZ6Sq4g7be6PB+TEJRkr9TvEsQOyf0aetXGdNhhQBe7Ix01H6A28f6VBSganCA+Az3E/GLdp6DXGRHlgADwDAqD6ACgWIM0EKADhsPQiH9/bkCd37i34QJqvx+WL48MoGUteJQgnKnCKfFEigQH5ausn9X/MTJdIkzIiZkmk9i6MgQ4d4qiKkikdEdrlNQ5TSo5JJSVQxaiMKKmIAQoNCIiG2WrMAEJEGAVDHYwjdrrr6npDHh+1BvEgEgCr0eHWP6qMRUcjRy6yJmSEGp/7nRN+UhcJYAaOpMj+/dEknpAATgTTCeFJNW4FJUAVUQdAAKAIgghgACASBANmKt8EHEmRSjkUsUUGkvgzBe79/OYTg0bVFQBUIQqIi7KVpFcFFsZU0xETgFKulBw1rRm5ZmBAikAQEoidOcEnm0trEiVQBVpEUW6V8o0T0JiIYA7RAnE4JoDB6J6gGUSk+D5VUREAdDK6yrnt5KyEwaMHEyupUAhPvLo9K5BEAmWN4FP1T7k2IYmVSLSX1LUydNpiOo/OMxVJSlx22qWqjCAQqFI2aAMbpJQRBiQGgoAaQ2DiMHJ+jmeyuKocY4RCJJ/bcn2TTDdfrPnhgIkOILMQKEkhP1dEgqQhy7Ms/G1i26AbT1iWJvgw0o7lFjWP8oXQ+kdmpKS4axKh3SJpIRmUFVNKYJiGmuHDcyAjI5EMOSTVgjBPRew3cP3SEJly+DQBMmiJm9R4Dwv5SPXpQYGOsQNzIOfEllQsB0zNf5nJujtPze5WnMXAOj/7I51ONBxVUok6muBiEIT+BjgwAoWoAJBIkD8jMhKgqmPodGMX7IZxaBjNc0eBLo+LBABKKCDJiOBSdEQE/GmspypMIxKfHxt23Yep0miowqclt0TuzaK6YyI4J1EWvSfYDeQYwugLJCYNco0QMikro48N4lQgIlEqleB9KngwJfQhjJQE8+b5UYCugCkaBIAhLQD1tUUAFRraWSQhQAKPTV1QlUFQ0sbQHFCstOmW10zON6KwoccbFPxIFzxAgGhyMGcRctlPkFLipekAFZAaCQkCViABBc8MdspK6atWBEOxZDROTABFgQCAQUZWRY7aOR2cJUrSrecJj4d7M99cFG2dCKJeunzTU/LEEzsypueMo7iaRwxeKuUTUIEAEwBZBmAAUKXYyTZUPIhxCUQIVcLIEqGQAEAnZitegCOBq7wlIB1sYykFh5B/Gh4Nq2iF2auFWhRjczO47+wA8I+RcZOcoOHpUQZ0MskTLmpL+0XAqCQkReGEVBkWKvUYsohqQIVKsBwiGrQx91YnXoErGArLR6IdcJYIg4MeBqQBCFZWsMGmseRNjnS3ETEBkxVN6fiCw+IPPolQoxczalOghSXEIGUBBpKBgvCAqMAggoQmaHkQuAqpdRch+7MJFDyGoD2BLiyZ4UBBQcCQIqNoTkVrDojHnFT07gqat/6Z4PgE1XC4JmbpjfsA3XFiV6Y/ciiKoCIRKUWoRAFUQCUUIgZAl5HKbpt0lI8sZNT5GSvzQ1RRA3NCvDSigQQUJho1EII+uDKSqpMQx5zOh0ZRkyA/7TmOLv3RucJoK3k+pg1kQNJuWOXCeEDuicMQLqiCAjEiKiKQMBOCB0hIyiDGlCoACYXyaonRtI84ghnbAwIYgBAVVMCICqAG08IgKQYmQFCXCZ11onaaVL7NUYh5xAtI/pC11KCzk8ckxOnudVLwAQBVAAKJUDVFSDogqlIIVUkBU0vgkZFQANKXvzdGIRzNWIxMTSEhGKvpaHzCAKDAyEZFyIpAwFrV0XmYOOapIcRTMI/zHmXcunpAh7YQcJt1TiHtXx081rYpXJIaYtIAglAI78SFx1TTVWFn2jitAj2wNsRNQJCpcUBXBsRowKIIfjXeMkFYVxmFodBOThKZByZNoL0d0f8TtpSNmGJTpi8qYiIy4UACyQKKKGIhgFCU2bpNmXSBS1Rgd2K0HCTI4RgQRtBTGEQgg5sFI1ZUxwALxIxMqxUcaCKlEbZO8M15cahPtZvJmGIuYKeA6F+MzBsYIcgptcVLOTDum6yWkqsRR14IigZBAQEQlEEUBJhBIQevq1IkPQVEhqCAzqwoAmRhsBXVtfLQ9SPB+RGWTyi4xt4cqadMqTKxIXRWpz2mRPkuOctEJBNPYs205k9jJOUZ9j5cGVUZU5MhfFQQB41RVGQKhCmpAIBFAlRH5yARsvYr3YoSMqvpAHAIJKqGIMqMSqgRHoMEKRVCWlsNEAnO8O3Nosoxnw9bJHi2KbH8EdMfPBWIBZjFHKElJCIQgqIJHBbYigoGnVEIMJokk9F2lTA0NY+9URICI1XByc2Q0JlRUATSMqqLCFiQuP0BVievo51Hm/D7Owe9TK/PEK/4j5C1YDPOiaY0mlARZgATEQ2BVAiQQBUAMEnvOSRS4cM6PgUqG0I0+hu5GETR4CYI4r7BWVAmIBCqlCIIgoMS5nBaGRPZM452Cx9nE/FHL+ZRvOeKa7Wmy0OlNTIOAkiASD4QKYkBjFAikDmLPHahXJFuwtaXxSJ4BVcAYohBEJQgTEwYJDAQiQORVQ4m86OlROuv4ndrXJh+xqCpls69L7pxr32JepumZLpQWhUssHCogSghoxKiIIEXvDoAosasQJGhwClSVBiAosUHnSsKAoBp8EGQEUjUEHoFAAwRRRIq1AVVFVBQwS57pbBsiIIdzIDMf+wN8eiaqOXWcmsmSBYt6r4QyBZjGA6lKXPCAqIAMqkhBCNS749ADgQ794BFBJDcbRYkIBIgU+zwVBBHEkxFnoqeIsFenDVQn066YEWVMGKriD+n5wV9nFGLW5txeGsNjTP16oBTUC7IIKDJCblqKYXJ2hUPvutYUQfvdCQwSYeyHEwBNYCbaGgYPAhiLOp4k9msn+5535UopmCnoBUhA9Fwm0/izb/hHbU266FQtgmS54tY+IhhAgJgkVh9xahFAUiE1EEDc8TT4wOi6oUc0xJbIqGhMZIphQ0Ew4VZVICISbwKkFaKKQEBpT6d5iWhaLhOdl0pMv08xVR73/3/jOU1KEg2BqUeKQAkpAKGIAFD0y0hx21lURAEFZAgQTjspTYG+H5ygtVVhSIMTJgEXS8RIIsoAsYeFIARlEEJQIhQgmbehzgWoDGmSSc+uaRr2H2fYmXRO7J7yVfniCUyjsgLYUYIA+bgcCZBE0nPKlIAAq7EIrlwXZlA3qlU0hhTAqKoIogaPhEgh3pWYiMCBOEp+DlSJAM1y59jIuggjNS4a1dymlaHmD2TxHKrq4mcxHRITrVOJBEHQhLgBFohBkJSCk2hIEcmub/Y7sY1aw6wIAKJkbNF1bhy61hki4NjhQbEirUFAxCOCcMSPimiyZ1iQGenMoG4a7kzC3NqVCX/C0mSLs/kEjbUnZVEF1RDz5iQkSooxDwykGV9FJTBVPTpm4WoVxKIoEhsziHfeDc4DUWwl4th+j5CUKlDEmwCkBEZR520iMjieHLWKTrWkZDj0h1m2JMUzgFv2SylgDpiCgMOYOdRYSooJGlBEJZIENlBDisONMRicIBIDAJG14gKCeOc0hMAaBBgByacZFA9EALGBHBQX+6rhzJmUP8BFjJCZlOqYE7cX8jkLZoqT57wAqAoQKAREiVGuRhiZI8OACAhBETHyl1RVbBmMSBg8xmxwWRWiKKO4oBJlUACYWGOm2ftAgGAilo+pPTNb9AWA0TQ8jJAg+0lVUPjjedIFzyZMPpsu8WmqBCkQqgdiEQkY94hCEWBAEY3ryRFUKPih8+jDOGoBYuvCmLIogQZiUwYSKiwGDWqQGSD25YyBkRiAUx0bE1TD2YhOSZUMqmNJHxN9U7kXEosRFuo2ScNCoBVgytmDKpE6ZgmO1GkAChqMIqlIrK4pCCSk4XonyjT0YBBMYY1lYhHBAhC6wJY1eDSGmYVRMEgQ9RQLOpqzKmYa0wSuIEcTiqAqgec2jURfTqBm6XzCy3QZBQAQR6QQAZmm+XJsyAfQgD52YghRTNkkC5YSY84TuPE0KsQOIWMtutMQQgixEKHKoIEUTEAQVBGvwAEUJzSSkk6QoEbWqKSPCiooEo10Uq0pMpyN6lkafzJTCqCio5iU8gUVpZhSAk8UIUQgIkD1QCqx+qSoiKICyIVXpVOrxBxreOqGw64LEtAUsScsBEFFikkARSIBFZlagSDrYBbA6WkUgJA6BklEOJuQqVg/w/KJpkzfIkUTvDiDsZcEVUEDoSIHUicgGggACcSDatqrIvdiAAAg82mEcdDaMhAxoTjXDw6ZULwhJvCS+5sQQBQNCoqEQJqq6zmrBsmgTNI520SJu5RHtuAZJU8kdAq0kgSAOCe5fEoCyeMIoEdxwhjREogXwhC7NgMIcjKxbCz1ow8WgQhQRUWUayMaBBnRUCBKy+KQKCAicgAGCRN4AjVZpOZx4pICQVXJD4lNAT9MTkXz4YvtTqYSuQYfYuMSKCiIlxi1KQQQDcogmEt1qmIUUROqRIxVHwljUBq4NLHHzdqibEcHIOiVCGP7YvR8osQMsVd9Sp2d76umuT1Gl3Yxp6EWOoY6uX9NGp2nYJo6UHEeJvpEg0fVICBKAUBBFJRAFdBgwuJIqKghNcMoqENQDD0XxhpTWDY8coE4hggdkDj2oZOKIJCxGisDApjrdCa686nbKw1wUaSI7djLF078Te/OSsTTwSEAMxNCUASRECyqgqgKBQUCif3qjFgIeFFWJALAIBxvUK7aEOK2EmzZWkIh05AfBzeG1K0ddyhBBVYkwrh2XSA2USoqmlnkZjEEmPeJUAmBl0uXIBUxJg7nHO90jRRyBWXKjX0oSOgZE6qOEyGgSCIUyAL5gERqvCJJxDUi5do7FQAgw0VRl0VhsHfdMAYIXsmySiBLzAQcCIgQYi9SbNRW1LjdSlSt7M1xMo/xvYQQeElgZBRFxi/Doxh9ZLH2gZAo+rSYeQqAFNeeogCIAgohAaowgQZBYMCQLosQhKtVPyhwURhjq7KuLA6n0+iDd4OnQjV4QUjJGSGMRUYgIohNHjQtcZ1wTOJJYkQ09kFk6gdO6A0QNS2HThRPHgPjAp/gIDUCQ2wXVUExqghh2nIRIxw0qooUUt8YaVAlhOCdVzaIVBaExKYsGIbjcQwQxsEpqDovKMEgqiAwxQA2rtuSoAAagM63W9GJQpxdtoQQKCVpJvpokXzLVZsJnSmKOqFplSYAABCEWFgSQBYPpHnBUdRpistHgARBFKQ/7tvusO+prApCsqVlHfphDIjMqIJeFQSAUWPdMwDFWhoogYCCKKb6YIzBNPnAzKwJeUvIK7qjYcq5lonb0SxNMaWAaAiABBq3BaIUOpjIYdBcN5t2Moot8UGRUUkAw9Ae2rY/3bfBINuiKEtrCCA4KAghWPVEpCFGRxADLyQEFclANIrJVD7TTNNCpSYfmYUxcywTqBDjMMjX05iokCDCFG15LBWAAhtEBQLwAgAqDClNRqyKqEEhoJCIgm/3x1Pn9rsOqrIui6KqysIY9WQlgAQbhJApshwUEIkROTZfKHAamiplsJ1rI+eUzcZfk9zOiC0fitEtatp4CFUUQUSIEBAlr8tDEUNBEAAMOkE0KWmEooEIAEwk3IP4cTh83KtzXohtU1dFWZbWGgQuvBcqJPgxzo6JjlzJKAAEBREfM60aY/WwaASaXUXiZlqlTjDRMh8RSY251YRblABBgnCCFVGWY6kBcnUOFbDQkRhViBlJMahnQmREp/FZ3mHUQgcmoKKs67Ioi8JYZgKEoOwDqLdpJQayQVBCJVWPqF5FYdp3BmBRv5isQbJwiWyIcOo8N5woRNC8glRFQQjUC4KKapI+RVASQBUgUQBCURQiJYzrexRURT0RKBAHQAUVN2jdjAHZUF1X9WpV2sKQioqaitgHMlYVkTGACiATgmoAANWgcZkHSgyGppbmjCuzbRTKqRSIbeJLj5erYqmBXQAASRRAJC3hi9sHBACVBHSIPAAiBQFBIoi9BghqgqgkFREGlQAM0BwHBUNIXDZNZQtGCKpIRBwAuSTnBWIxiogQAqZGIiXCvOgPVP5/Nn8iqCIEi60AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 100ms/step\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=L size=224x224>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 88ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "QYS0GuQXjzQ6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1DkebP4bjMaF"
      },
      "source": [
        "# Distances Images"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PWAKffjBVz6J"
      },
      "source": [
        "from scipy.spatial import distance"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZY1_OkMjjIWD"
      },
      "source": [
        "metric = 'cosine'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vfUBzmFOkVFu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7de0e9ef-94f0-4925-c94d-223cdfe490ab"
      },
      "source": [
        "dc = distance.cdist([cat1], [cat1], metric)[0]\n",
        "print(dc)\n",
        "print(\"the distance between cat1 and the cat1 is {}\".format(dc))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.]\n",
            "the distance between cat1 and the cat1 is [0.]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JwsFe0tzkMA_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2f5fdc28-5329-415f-ae65-5c7425f9ab8e"
      },
      "source": [
        "dc = distance.cdist([cat1], [cat2], metric)[0]\n",
        "print(dc)\n",
        "print(\"the distance between cat1 and the cat2 is {}\".format(dc))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.37517998]\n",
            "the distance between cat1 and the cat2 is [0.37517998]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AfK4FBeEkOvz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "47ddc409-cee6-4b0f-969e-b9d6c24d6dba"
      },
      "source": [
        "dc = distance.cdist([cat1], [rocket], metric)[0]\n",
        "print(dc)\n",
        "print(\"the distance between cat1 and the rocket is {}\".format(dc))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.84023548]\n",
            "the distance between cat1 and the rocket is [0.84023548]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9A2EpWI0kRCL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3f1a5b29-a158-473d-e9a3-601d1ccd3bed"
      },
      "source": [
        "dc = distance.cdist([cat2], [rocket], metric)[0]\n",
        "print(dc)\n",
        "print(\"the distance cat2 original and the rocket is {}\".format(dc))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.81781548]\n",
            "the distance cat2 original and the rocket is [0.81781548]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9biyCatQkwVk"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Embedding Text"
      ],
      "metadata": {
        "id": "QUCUPzj7jz_6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install sentence-transformers"
      ],
      "metadata": {
        "id": "CTRF3BaLkXdO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "08614a2b-1a99-441c-d71c-70e2f1115fc0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting sentence-transformers\n",
            "  Downloading sentence-transformers-2.2.2.tar.gz (85 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/86.0 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━\u001b[0m \u001b[32m71.7/86.0 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.0/86.0 kB\u001b[0m \u001b[31m1.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting transformers<5.0.0,>=4.6.0 (from sentence-transformers)\n",
            "  Downloading transformers-4.34.0-py3-none-any.whl (7.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.7/7.7 MB\u001b[0m \u001b[31m19.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (from sentence-transformers) (3.8.1)\n",
            "Collecting sentencepiece (from sentence-transformers)\n",
            "  Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m42.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting huggingface-hub>=0.4.0 (from sentence-transformers)\n",
            "  Downloading huggingface_hub-0.17.3-py3-none-any.whl (295 kB)\n",
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            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers<5.0.0,>=4.6.0->sentence-transformers) (2023.6.3)\n",
            "Collecting tokenizers<0.15,>=0.14 (from transformers<5.0.0,>=4.6.0->sentence-transformers)\n",
            "  Downloading tokenizers-0.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.8 MB)\n",
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            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers<5.0.0,>=4.6.0->sentence-transformers)\n",
            "  Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
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            "\u001b[?25hRequirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk->sentence-transformers) (8.1.7)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk->sentence-transformers) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->sentence-transformers) (3.2.0)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision->sentence-transformers) (9.4.0)\n",
            "Collecting huggingface-hub>=0.4.0 (from sentence-transformers)\n",
            "  Downloading huggingface_hub-0.16.4-py3-none-any.whl (268 kB)\n",
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            "\u001b[?25hRequirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.6.0->sentence-transformers) (2.1.3)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.4.0->sentence-transformers) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.4.0->sentence-transformers) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.4.0->sentence-transformers) (2.0.5)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.4.0->sentence-transformers) (2023.7.22)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.6.0->sentence-transformers) (1.3.0)\n",
            "Building wheels for collected packages: sentence-transformers\n",
            "  Building wheel for sentence-transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sentence-transformers: filename=sentence_transformers-2.2.2-py3-none-any.whl size=125923 sha256=f628031bb9c29031c7ad8c44f79bec39cabe86026e3b58cb3ec840f58e444ca7\n",
            "  Stored in directory: /root/.cache/pip/wheels/62/f2/10/1e606fd5f02395388f74e7462910fe851042f97238cbbd902f\n",
            "Successfully built sentence-transformers\n",
            "Installing collected packages: sentencepiece, safetensors, huggingface-hub, tokenizers, transformers, sentence-transformers\n",
            "Successfully installed huggingface-hub-0.16.4 safetensors-0.3.3 sentence-transformers-2.2.2 sentencepiece-0.1.99 tokenizers-0.14.0 transformers-4.34.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# https://huggingface.co/blog/sentence-transformers-in-the-hub\n",
        "from sentence_transformers import SentenceTransformer\n",
        "model = SentenceTransformer('sentence-t5-base')"
      ],
      "metadata": {
        "id": "xLdFXnLSlVHZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 561,
          "referenced_widgets": [
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sentence = ['DoiT is a great company to work for']\n",
        "embedding = model.encode(sentence)\n",
        "print(len(embedding[0]))\n",
        "print(embedding[0])"
      ],
      "metadata": {
        "id": "ntrTODvRlZL8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sentences = ['I spent the day at the medical facility.', #0\n",
        "            'That a cultured medical genius found her inspiring was beyond flattering.',\n",
        "            'She drew nearer, eyes sweeping over the medical equipment in the room.',\n",
        "            'I did not ask the American Medical Association their opinion of this arrangement.',\n",
        "            'I think the cat wants dessert!', #4\n",
        "            'Im in no mood to watch a cat fight tonight.', #5\n",
        "            'The cat would like to eat the mouse.', #6\n",
        "            'A large grey cat was asleep on a rocking chair.', # 7\n",
        "            'The pilot was able to land the airplane'] #8"
      ],
      "metadata": {
        "id": "UPaDMEjOsyIs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with open(\"data.json\", \"w\") as f:\n",
        "    embedding = model.encode(sentences) # do smaller batches if you do it on large data\n",
        "    for i in range(len(sentences)):\n",
        "        f.write('{\"id\":\"' + str(i) + '\",')\n",
        "        f.write('\"embedding\":[' + \",\".join(str(x) for x in embedding[i]) + \"]}\")\n",
        "        f.write(\"\\n\")"
      ],
      "metadata": {
        "id": "vC-kyREppGCA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "sAr1zyzosnTm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Google Vertex AI Matching Engine\n",
        "\n",
        "* February 8th: Updated the code to use the latest version of the SDK and not the beta version anymore. This simplified things a lot as we don't need to work with protobufs anymore."
      ],
      "metadata": {
        "id": "bM5Mfc4aucgw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import auth\n",
        "auth.authenticate_user()"
      ],
      "metadata": {
        "id": "0ZSaFr94vXyY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud config set project \"sascha-playground-doit\""
      ],
      "metadata": {
        "id": "FEV4WNJMO42J",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ebc4df91-d099-4ae7-cc59-7d86043323a2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1;33mWARNING:\u001b[0m You do not appear to have access to project [sascha-playground-doit] or it does not exist.\n",
            "Are you sure you wish to set property [core/project] to sascha-playground-doit?\n",
            "\n",
            "Do you want to continue (Y/n)?  n\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install google-cloud-aiplatform==1.21.0"
      ],
      "metadata": {
        "id": "AEHBPjyXud64",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 964
        },
        "outputId": "0697e3d3-d208-4f57-8440-25871cf1c209"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "  Downloading google_cloud_aiplatform-1.21.0-py2.py3-none-any.whl (2.3 MB)\n",
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            "\u001b[?25hCollecting shapely<2.0.0 (from google-cloud-aiplatform==1.21.0)\n",
            "  Downloading Shapely-1.8.5.post1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.0 MB)\n",
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            "Requirement already satisfied: google-crc32c<2.0dev,>=1.0 in /usr/local/lib/python3.10/dist-packages (from google-resumable-media<3.0dev,>=0.6.0->google-cloud-bigquery<4.0.0dev,>=1.15.0->google-cloud-aiplatform==1.21.0) (1.5.0)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform==1.21.0) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform==1.21.0) (2023.5.7)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform==1.21.0) (2.0.12)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0.dev0,>=2.18.0->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform==1.21.0) (3.4)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform==1.21.0) (0.5.0)\n",
            "Installing collected packages: shapely, packaging, google-cloud-resource-manager, google-cloud-aiplatform\n",
            "  Attempting uninstall: shapely\n",
            "    Found existing installation: shapely 2.0.1\n",
            "    Uninstalling shapely-2.0.1:\n",
            "      Successfully uninstalled shapely-2.0.1\n",
            "  Attempting uninstall: packaging\n",
            "    Found existing installation: packaging 23.1\n",
            "    Uninstalling packaging-23.1:\n",
            "      Successfully uninstalled packaging-23.1\n",
            "Successfully installed google-cloud-aiplatform-1.21.0 google-cloud-resource-manager-1.10.2 packaging-21.3 shapely-1.8.5.post1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google",
                  "packaging"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.cloud import aiplatform\n",
        "from google.protobuf import struct_pb2\n",
        "import time"
      ],
      "metadata": {
        "id": "JjOZ_mIDxPRf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "aiplatform.init(project=\"sascha-playground-doit\", location=\"us-central1\")"
      ],
      "metadata": {
        "id": "3lkn94-1G-vX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "REGION = \"us-central1\"\n",
        "ENDPOINT = \"{}-aiplatform.googleapis.com\".format(REGION)\n",
        "\n",
        "PROJECT_ID = \"sascha-playground-doit\"\n",
        "PARENT = \"projects/{}/locations/{}\".format(PROJECT_ID, REGION)\n",
        "\n",
        "PROJECT_NUMBER = !gcloud projects list --filter=\"PROJECT_ID:'{PROJECT_ID}'\" --format='value(PROJECT_NUMBER)'\n",
        "PROJECT_NUMBER = PROJECT_NUMBER[0]"
      ],
      "metadata": {
        "id": "lpM4vUMFxYYD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PROJECT_NUMBER"
      ],
      "metadata": {
        "id": "i9prNAbpX84Q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Copy Embeddings\n",
        "Copy the embeddings to the Google Cloud Storage bucket"
      ],
      "metadata": {
        "id": "Bom1oRYEwYrN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! gsutil cp data.json gs://doit-vertex-demo/matching-engine/data/text/data.json"
      ],
      "metadata": {
        "id": "mZtyN_msvHkF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yOguoWcIxAyb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create VPC Network"
      ],
      "metadata": {
        "id": "-S3Al5D3Oqja"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "NETWORK_NAME = \"matching-engine-vpc-network\"\n",
        "PEERING_RANGE_NAME = \"matching-engine-range\""
      ],
      "metadata": {
        "id": "71OVDYB6OxG1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! gcloud compute networks create {NETWORK_NAME} --bgp-routing-mode=regional"
      ],
      "metadata": {
        "id": "Ia9OXNwhOs6c"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! gcloud compute firewall-rules create {NETWORK_NAME}-allow-icmp --network {NETWORK_NAME} --priority 65534 --project {PROJECT_ID} --allow icmp\n",
        "! gcloud compute firewall-rules create {NETWORK_NAME}-allow-internal --network {NETWORK_NAME} --priority 65534 --project {PROJECT_ID} --allow all --source-ranges 10.128.0.0/9\n",
        "! gcloud compute firewall-rules create {NETWORK_NAME}-allow-rdp --network {NETWORK_NAME} --priority 65534 --project {PROJECT_ID} --allow tcp:3389\n",
        "! gcloud compute firewall-rules create {NETWORK_NAME}-allow-ssh --network {NETWORK_NAME} --priority 65534 --project {PROJECT_ID} --allow tcp:22\n"
      ],
      "metadata": {
        "id": "tsCsu81HPMcL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! gcloud compute addresses create {PEERING_RANGE_NAME} --global --prefix-length=16 --network={NETWORK_NAME} --purpose=VPC_PEERING --project={PROJECT_ID} --description=\"peering range for uCAIP Haystack.\""
      ],
      "metadata": {
        "id": "zDQGUXynP4jc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud services enable servicenetworking.googleapis.com --project=\"sascha-playground-doit\""
      ],
      "metadata": {
        "id": "Fatgj4HNQyAB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "hiA-fEoAS1nc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! gcloud services vpc-peerings connect --service=servicenetworking.googleapis.com --network={NETWORK_NAME} --ranges={PEERING_RANGE_NAME}"
      ],
      "metadata": {
        "id": "XNmAooRtQNdo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create Index"
      ],
      "metadata": {
        "id": "7htUWQmbxH5f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "index = aiplatform.MatchingEngineIndex.create_tree_ah_index(\n",
        "    display_name=\"similar_text\",\n",
        "    contents_delta_uri=\"gs://doit-vertex-demo/matching-engine/data/text/\",\n",
        "    dimensions=768,\n",
        "    approximate_neighbors_count=150,\n",
        "    distance_measure_type=\"DOT_PRODUCT_DISTANCE\",\n",
        "    leaf_node_embedding_count=500,\n",
        "    leaf_nodes_to_search_percent=7,\n",
        "    description=\"Glove 100 ANN index\",\n",
        "    labels={\"label_name\": \"label_value\"},\n",
        ")"
      ],
      "metadata": {
        "id": "iLrkeUytGQLH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# manually reference the index if it is already existing\n",
        "INDEX_RESOURCE_NAME = \"projects/234439745674/locations/us-central1/indexes/5968580124126216192\"\n",
        "index = aiplatform.MatchingEngineIndex(index_name=INDEX_RESOURCE_NAME)"
      ],
      "metadata": {
        "id": "Ht_TRCpsGpeB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## List Index"
      ],
      "metadata": {
        "id": "ePr43o9FJMJR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai indexes list \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "Eun3J7yY5B4M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create Index Endpoint"
      ],
      "metadata": {
        "id": "zaI1hX9lTVPZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "VPC_NETWORK_NAME = \"projects/{}/global/networks/{}\".format(PROJECT_NUMBER, NETWORK_NAME)\n",
        "VPC_NETWORK_NAME"
      ],
      "metadata": {
        "id": "C0DdH2o_T2NT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "index_endpoint = aiplatform.MatchingEngineIndexEndpoint.create(\n",
        "    display_name=\"index_endpoint_for_demo\",\n",
        "    description=\"index endpoint description\",\n",
        "    network=VPC_NETWORK_NAME,\n",
        ")"
      ],
      "metadata": {
        "id": "3Xjgt-ekIVm2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#gcloud\n",
        "\n",
        "!gcloud ai index-endpoints create \\\n",
        "  --display-name=\"index_endpoint_for_demo\" \\\n",
        "  --network=\"projects/234439745674/global/networks/matching-engine-vpc-network\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "DgTq8SotJTIC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## List Endpoints"
      ],
      "metadata": {
        "id": "IQsX7opTJ0iL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints list --project=\"sascha-playground-doit\" --region=\"us-central1\""
      ],
      "metadata": {
        "id": "ly4CUiTKJ3QQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Deploy Index\n",
        "\n",
        "takes at least 40 min even for the smallest index"
      ],
      "metadata": {
        "id": "MjKcOoFAN9kT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "deployed_index = index_endpoint.deploy_index(\n",
        "    index=index, deployed_index_id=\"similar_text_index_deployed\"\n",
        ")"
      ],
      "metadata": {
        "id": "6EBmyiflJrBg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "deployed_index.deployed_indexes"
      ],
      "metadata": {
        "id": "UMnyNMP9J3G_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints deploy-index \"4732315638133948416\" \\\n",
        "  --deployed-index-id=\"deployed-index-text\" \\\n",
        "  --display-name=\"display name\" \\\n",
        "  --index=\"8291848193616904192\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "FqS4nZNUNDom"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai operations describe \"5345555672861769728\" \\\n",
        "  --index-endpoint=\"4732315638133948416\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "jcQVwhNONwTM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints describe 8204054389162246144 \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "19RSzjaUPd7Y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints list --project=\"sascha-playground-doit\" --region=\"us-central1\""
      ],
      "metadata": {
        "id": "L8F-0PqDPPg_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Query using the SDK (recommended approach)\n",
        "\n",
        "(IMPORTANT: only works withing the same VPC network. Will not work on your local environment or notebooks outside of the network)"
      ],
      "metadata": {
        "id": "2Uk5DNkR2Nxn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sentence = ['The cat likes to sleep in the sun']\n",
        "embedding = model.encode(sentence)\n",
        "print(embedding[0])"
      ],
      "metadata": {
        "id": "zbJBMZ4_DpTN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "response = index_endpoint.match(\n",
        "    deployed_index_id=\"similar_text_index_deployed\",\n",
        "    queries=[embedding[0]],\n",
        "    num_neighbors=5\n",
        ")\n",
        "\n",
        "response"
      ],
      "metadata": {
        "id": "WIGoMs4x2QH-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Query with gRPC and proto files (deprecated don't use this anymore rather use the SDK)\n",
        "\n",
        "(IMPORTANT: only works withing the same VPC network. Will not work on your local environment or notebooks outside of the network)"
      ],
      "metadata": {
        "id": "tZlFRHNhT-0l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install grpcio-tools"
      ],
      "metadata": {
        "id": "xGv5x92JUAfX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Create the vector used to query against the matching engine"
      ],
      "metadata": {
        "id": "zNUqrRDzWdgq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sentence = ['The cat likes to sleep in the sun']\n",
        "embedding = model.encode(sentence)\n",
        "print(embedding[0])"
      ],
      "metadata": {
        "id": "OmsWceh3WcmU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/googleapis/googleapis.git"
      ],
      "metadata": {
        "id": "UgXBfFbcYj_P"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile match_service.proto\n",
        "\n",
        "syntax = \"proto3\";\n",
        "\n",
        "package google.cloud.aiplatform.container.v1beta1;\n",
        "\n",
        "import \"google/rpc/status.proto\";\n",
        "\n",
        "// MatchService is a Google managed service for efficient vector similarity\n",
        "// search at scale.\n",
        "service MatchService {\n",
        "  // Returns the nearest neighbors for the query. If it is a sharded\n",
        "  // deployment, calls the other shards and aggregates the responses.\n",
        "  rpc Match(MatchRequest) returns (MatchResponse) {}\n",
        "\n",
        "  // Returns the nearest neighbors for batch queries. If it is a sharded\n",
        "  // deployment, calls the other shards and aggregates the responses.\n",
        "  rpc BatchMatch(BatchMatchRequest) returns (BatchMatchResponse) {}\n",
        "}\n",
        "\n",
        "// Parameters for a match query.\n",
        "message MatchRequest {\n",
        "  // The ID of the DeploydIndex that will serve the request.\n",
        "  // This MatchRequest is sent to a specific IndexEndpoint of the Control API,\n",
        "  // as per the IndexEndpoint.network. That IndexEndpoint also has\n",
        "  // IndexEndpoint.deployed_indexes, and each such index has an\n",
        "  // DeployedIndex.id field.\n",
        "  // The value of the field below must equal one of the DeployedIndex.id\n",
        "  // fields of the IndexEndpoint that is being called for this request.\n",
        "  string deployed_index_id = 1;\n",
        "\n",
        "  // The embedding values.\n",
        "  repeated float float_val = 2;\n",
        "\n",
        "  // The number of nearest neighbors to be retrieved from database for\n",
        "  // each query. If not set, will use the default from\n",
        "  // the service configuration.\n",
        "  int32 num_neighbors = 3;\n",
        "\n",
        "  // The list of restricts.\n",
        "  repeated Namespace restricts = 4;\n",
        "\n",
        "  // Crowding is a constraint on a neighbor list produced by nearest neighbor\n",
        "  // search requiring that no more than some value k' of the k neighbors\n",
        "  // returned have the same value of crowding_attribute.\n",
        "  // It's used for improving result diversity.\n",
        "  // This field is the maximum number of matches with the same crowding tag.\n",
        "  int32 per_crowding_attribute_num_neighbors = 5;\n",
        "\n",
        "  // The number of neighbors to find via approximate search before\n",
        "  // exact reordering is performed. If not set, the default value from scam\n",
        "  // config is used; if set, this value must be > 0.\n",
        "  int32 approx_num_neighbors = 6;\n",
        "\n",
        "  // The fraction of the number of leaves to search, set at query time allows\n",
        "  // user to tune search performance. This value increase result in both search\n",
        "  // accuracy and latency increase. The value should be between 0.0 and 1.0. If\n",
        "  // not set or set to 0.0, query uses the default value specified in\n",
        "  // NearestNeighborSearchConfig.TreeAHConfig.leaf_nodes_to_search_percent.\n",
        "  int32 leaf_nodes_to_search_percent_override = 7;\n",
        "}\n",
        "\n",
        "// Response of a match query.\n",
        "message MatchResponse {\n",
        "  message Neighbor {\n",
        "    // The ids of the matches.\n",
        "    string id = 1;\n",
        "\n",
        "    // The distances of the matches.\n",
        "    double distance = 2;\n",
        "  }\n",
        "  // All its neighbors.\n",
        "  repeated Neighbor neighbor = 1;\n",
        "}\n",
        "\n",
        "// Parameters for a batch match query.\n",
        "message BatchMatchRequest {\n",
        "  // Batched requests against one index.\n",
        "  message BatchMatchRequestPerIndex {\n",
        "    // The ID of the DeploydIndex that will serve the request.\n",
        "    string deployed_index_id = 1;\n",
        "\n",
        "    // The requests against the index identified by the above deployed_index_id.\n",
        "    repeated MatchRequest requests = 2;\n",
        "\n",
        "    // Selects the optimal batch size to use for low-level batching. Queries\n",
        "    // within each low level batch are executed sequentially while low level\n",
        "    // batches are executed in parallel.\n",
        "    // This field is optional, defaults to 0 if not set. A non-positive number\n",
        "    // disables low level batching, i.e. all queries are executed sequentially.\n",
        "    int32 low_level_batch_size = 3;\n",
        "  }\n",
        "\n",
        "  // The batch requests grouped by indexes.\n",
        "  repeated BatchMatchRequestPerIndex requests = 1;\n",
        "}\n",
        "\n",
        "// Response of a batch match query.\n",
        "message BatchMatchResponse {\n",
        "  // Batched responses for one index.\n",
        "  message BatchMatchResponsePerIndex {\n",
        "    // The ID of the DeployedIndex that produced the responses.\n",
        "    string deployed_index_id = 1;\n",
        "\n",
        "    // The match responses produced by the index identified by the above\n",
        "    // deployed_index_id. This field is set only when the query against that\n",
        "    // index succeed.\n",
        "    repeated MatchResponse responses = 2;\n",
        "\n",
        "    // The status of response for the batch query identified by the above\n",
        "    // deployed_index_id.\n",
        "    google.rpc.Status status = 3;\n",
        "  }\n",
        "\n",
        "  // The batched responses grouped by indexes.\n",
        "  repeated BatchMatchResponsePerIndex responses = 1;\n",
        "}\n",
        "\n",
        "// Namespace specifies the rules for determining the datapoints that are\n",
        "// eligible for each matching query, overall query is an AND across namespaces.\n",
        "message Namespace {\n",
        "  // The string name of the namespace that this proto is specifying,\n",
        "  // such as \"color\", \"shape\", \"geo\", or \"tags\".\n",
        "  string name = 1;\n",
        "\n",
        "  // The allowed tokens in the namespace.\n",
        "  repeated string allow_tokens = 2;\n",
        "\n",
        "  // The denied tokens in the namespace.\n",
        "  // The denied tokens have exactly the same format as the token fields, but\n",
        "  // represents a negation. When a token is denied, then matches will be\n",
        "  // excluded whenever the other datapoint has that token.\n",
        "  //\n",
        "  // For example, if a query specifies {color: red, blue, !purple}, then that\n",
        "  // query will match datapoints that are red or blue, but if those points are\n",
        "  // also purple, then they will be excluded even if they are red/blue.\n",
        "  repeated string deny_tokens = 3;\n",
        "}"
      ],
      "metadata": {
        "id": "X5ivygnkXDvv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "! python -m grpc_tools.protoc -I=. --proto_path=googleapis --python_out=. --grpc_python_out=. match_service.proto"
      ],
      "metadata": {
        "id": "mPxxNM8SYc3_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "DEPLOYED_INDEX_SERVER_IP = \"10.78.0.5\"\n",
        "\n",
        "import grpc\n",
        "import match_service_pb2\n",
        "import match_service_pb2_grpc\n",
        "\n",
        "channel = grpc.insecure_channel(\"{}:10000\".format(DEPLOYED_INDEX_SERVER_IP))\n",
        "stub = match_service_pb2_grpc.MatchServiceStub(channel)"
      ],
      "metadata": {
        "id": "1urwW_CcZ-vc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "request = match_service_pb2.MatchRequest()\n",
        "request.deployed_index_id = DEPLOYED_INDEX_ID\n",
        "for val in embedding[0]:\n",
        "    request.float_val.append(val)\n",
        "\n",
        "response = stub.Match(request)\n",
        "response"
      ],
      "metadata": {
        "id": "42XBgT-GaSdA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Update Index"
      ],
      "metadata": {
        "id": "kfR4alKjesKt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile metadata.json\n",
        "{\n",
        "  \"contentsDeltaUri\": \"gs://doit-vertex-demo/matching-engine/data/text/\",\n",
        "  \"isCompleteOverwrite\": True,\n",
        "  \"config\": {\n",
        "    \"dimensions\": 100,\n",
        "    \"approximateNeighborsCount\": 150,\n",
        "    \"distanceMeasureType\": \"DOT_PRODUCT_DISTANCE\",\n",
        "    \"algorithm_config\": {\n",
        "      \"treeAhConfig\": {\n",
        "      }\n",
        "    }\n",
        "  }\n",
        "}"
      ],
      "metadata": {
        "id": "TiZMARDzfLKw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai indexes update 8291848193616904192 \\\n",
        "  --metadata-file=\"./metadata.json\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "1Qz7KyKLeuAx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai operations describe 3500135356802531328 \\\n",
        "  --index=8291848193616904192 \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "uX0BiSE6gQpL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Change scaling / mutate"
      ],
      "metadata": {
        "id": "flds2Mij_DPV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints mutate-deployed-index 4732315638133948416 \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\" \\\n",
        "  --deployed-index-id=\"deployed-index-text\" \\\n",
        "  --min-replica-count=1 \\\n",
        "  --max-replica-count=1"
      ],
      "metadata": {
        "id": "ehb7FjKv_FnD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Undeploy Index\n",
        "\n",
        "* projects/234439745674/locations/us-central1/indexEndpoints/7097409129945235456\n",
        "\n",
        "* projects/234439745674/locations/us-central1/indexes/2682051907773530112\""
      ],
      "metadata": {
        "id": "MIRFGH94V9K7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints list --project=\"sascha-playground-doit\" --region=\"us-central1\""
      ],
      "metadata": {
        "id": "qj9WQKrUYD-F",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ea66ff5e-d604-437e-c27b-9034bb14c339"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Using endpoint [https://us-central1-aiplatform.googleapis.com/]\n",
            "---\n",
            "createTime: '2023-06-22T12:43:54.003997Z'\n",
            "description: palm-langchain-document-answering\n",
            "displayName: palm-langchain-document-answering\n",
            "etag: AMEw9yM50xjY-r2CTyRpe4DP_v-Daj3Nf4ZZYC8X5_WPko1iPMUajg_wmUUSEu6ZmG9r\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/4797978472544731136\n",
            "network: projects/234439745674/global/networks/matching-engine-vpc-network\n",
            "updateTime: '2023-06-22T12:43:54.681063Z'\n",
            "---\n",
            "createTime: '2023-06-09T15:11:55.283483Z'\n",
            "description: catawiki-langchain-document-answering\n",
            "displayName: catawiki-langchain-document-answering\n",
            "etag: AMEw9yMYmaByHeD7RKtKk_1PkM7Bfpvq83GSFCVbIfMxzKZk3VNwCGkqTRas1ewn0qQ=\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/4187459248059318272\n",
            "network: projects/234439745674/global/networks/matching-engine-vpc-network\n",
            "updateTime: '2023-06-09T15:11:56.042078Z'\n",
            "---\n",
            "createTime: '2023-06-08T18:12:58.604542Z'\n",
            "description: image-similarity-vpc\n",
            "displayName: image-similarity-vpc\n",
            "etag: AMEw9yMfVmQudG9-PcMo7nBzQ5_aSFoWE5Mg6SCB9iTKwlp8iNuIftOLK_9oT2pd5lz9\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/2199120012575244288\n",
            "network: projects/234439745674/global/networks/matching-engine-vpc-network\n",
            "updateTime: '2023-06-08T18:12:59.356654Z'\n",
            "---\n",
            "createTime: '2023-06-07T14:07:12.256941Z'\n",
            "description: image-similarity\n",
            "displayName: image-similarity\n",
            "etag: AMEw9yM6qFGFyxm1Ot1rB5gDmGtHnjO8BTFjFopkfk0VLksp5tSbxS63b8Bp4Geo3D-p\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/7203322886025641984\n",
            "publicEndpointDomainName: 1746094999.us-central1-234439745674.vdb.vertexai.goog\n",
            "updateTime: '2023-06-07T14:07:12.935544Z'\n",
            "---\n",
            "createTime: '2023-06-06T07:06:05.190362Z'\n",
            "description: palm-langchain-document-answering\n",
            "displayName: palm-langchain-document-answering\n",
            "etag: AMEw9yOX-316HVVaeGiumGXQ_O7hsYQXq6s1Tm2BTmBWt0tsFx958U0IqMK7jxaplwcB\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/1017628797832265728\n",
            "publicEndpointDomainName: 2034921986.us-central1-234439745674.vdb.vertexai.goog\n",
            "updateTime: '2023-06-06T07:06:06.923706Z'\n",
            "---\n",
            "createTime: '2023-02-17T16:32:12.159089Z'\n",
            "deployedIndexes:\n",
            "- automaticResources:\n",
            "    maxReplicaCount: 2\n",
            "    minReplicaCount: 2\n",
            "  createTime: '2023-02-18T12:15:51.103412Z'\n",
            "  deploymentGroup: default\n",
            "  displayName: ticket_similarity_deployed_v2\n",
            "  id: ticket_similarity_deployed_v2\n",
            "  index: projects/234439745674/locations/us-central1/indexes/8673273175338909696\n",
            "  indexSyncTime: '2023-07-14T10:15:15.330613Z'\n",
            "  privateEndpoints:\n",
            "    matchGrpcAddress: 10.78.0.5\n",
            "displayName: ticket_similarity_endpoint\n",
            "etag: AMEw9yN6oQSc3abAq1_B1TsuUpfP08cpJFqJP7qPGskIpPH-zUa2uqktOHl57P_KCUug\n",
            "name: projects/234439745674/locations/us-central1/indexEndpoints/4299714987208736768\n",
            "network: projects/234439745674/global/networks/matching-engine-vpc-network\n",
            "updateTime: '2023-02-17T16:32:12.701044Z'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints undeploy-index \"4299714987208736768\" \\\n",
        "  --deployed-index-id=\"ticket_similarity_deployed_v2\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "iziloyP_UMxe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b7c96abb-a70f-4ec8-cf37-fb94da5e9050"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Using endpoint [https://us-central1-aiplatform.googleapis.com/]\n",
            "'@type': type.googleapis.com/google.cloud.aiplatform.v1.UndeployIndexResponse\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai indexes list \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "gUzEv95xZ-cJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud -q ai indexes delete \"projects/234439745674/locations/us-central1/indexes/3621826486266232832\" \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "IpLzoMmPXK-t"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai indexes list \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\""
      ],
      "metadata": {
        "id": "1HyyM_0Ned8z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!gcloud ai index-endpoints delete 2514503927886512128 \\\n",
        "  --project=\"sascha-playground-doit\" \\\n",
        "  --region=\"us-central1\" \\\n",
        "  --quiet"
      ],
      "metadata": {
        "id": "L9uc4AvafCQU"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}