04-vector-filtering.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0389c6d4-047f-4d7f-ba2b-8dcf95aef4be",
   "metadata": {},
   "source": [
    "# Filtering vectors with Vertex Matching Engine"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f341ebd-b1f4-48c9-adc3-d345acccadfd",
   "metadata": {},
   "source": [
    "> In Vertex AI Matching Engine, you can restrict vector matching searches to a subset of the index by using Boolean rules\n",
    "\n",
    "> Boolean predicates tell Matching Engine which vectors in the index to ignore. \n",
    "\n",
    "See the [filter vector docs](https://cloud.google.com/vertex-ai/docs/matching-engine/filtering)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abd882e9-d06a-4194-8989-c1ba6b4d7128",
   "metadata": {},
   "source": [
    "### this notebook...\n",
    "\n",
    "**major tasks**\n",
    "\n",
    "* Use pre-trained TFHub model to convert images to embedding vectors\n",
    "\n",
    "* Use Python SDK to query deployed ANN & BF indexes - from **(Notebook Link)** \n",
    "\n",
    "* TODO\n",
    "\n",
    "**vector attributes**\n",
    "\n",
    "* in this example, vectors are tagged with a `category` and a `tag_1`\n",
    "* `category` and `tag_1` are *namespaces*\n",
    "* `Beauty` , `Toys & Games`, and `Sports & Outdoors` are *tokens* from the `category` namespace (see all tokens below)\n",
    "* `even` and `odd` are *tokens* from the `tag_1` namespace\n",
    "\n",
    "```\n",
    "\n",
    "{\n",
    "    \"id\":\"B00C19IQ40\",\n",
    "    \"embedding\":[0.15452695, ..., 0.0047538234],\n",
    "    \"restricts\":[\n",
    "        {\"namespace\" : \"category\", \"allow\" : [\"All Beauty\"]},\n",
    "        {\"namespace\" : \"tag_1\", \"allow\" : [\"even\"]}\n",
    "    ]\n",
    "}\n",
    "\n",
    "```\n",
    "\n",
    "**queries**\n",
    "\n",
    "* Queries express an `AND` logical operator *across* namespaces\n",
    "* Queries express an `OR` logical operator *within* namespaces\n",
    "* A query that specifies `{color: red, blue}, {shape: square, circle}`, matches all database points that satisfy `(red || blue) && (square || circle)`\n",
    "* A query that specifies `{color: red}`, matches all `red` objects of any kind, with no restriction on `shape`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "70f91fce-5593-4ce8-ab1f-d78f93fe762e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Updated property [core/project].\n"
     ]
    }
   ],
   "source": [
    "PROJECT_ID = 'hybrid-vertex'  # <--- TODO: CHANGE THIS\n",
    "LOCATION = 'us-central1' \n",
    "!gcloud config set project {PROJECT_ID}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9118b9c9-3b9b-44e6-966d-ac6d8b4b3703",
   "metadata": {},
   "source": [
    "## pip & package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "a3049dd3-03a5-458b-a261-2aef50549ec7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import time\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "import tensorflow as tf\n",
    "import tensorflow_hub as hub\n",
    "\n",
    "from IPython.display import clear_output, Image\n",
    "from IPython.core.display import HTML\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a6e0e361-c6c7-48af-a95b-b49e80e56f62",
   "metadata": {},
   "outputs": [],
   "source": [
    "from google.cloud import aiplatform as vertex_ai\n",
    "from google.cloud import storage\n",
    "\n",
    "from pprint import pprint\n",
    "\n",
    "storage_client = storage.Client(project=PROJECT_ID)\n",
    "\n",
    "vertex_ai.init(project=PROJECT_ID,location=LOCATION)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d84d5e4c-e721-4066-999c-b644605cc615",
   "metadata": {},
   "source": [
    "# Prepare test queries\n",
    "\n",
    "* original image size - `100x100`\n",
    "* `42,000` train product images, with title, description, and each assigned a single product category\n",
    "* `6,368` test product images, with title, description, but no `category`\n",
    "\n",
    "```\n",
    "Product Category          value_counts\n",
    "Arts, Crafts & Sewing        2225\n",
    "Beauty                       2202\n",
    "Grocery & Gourmet Food       2201\n",
    "Sports & Outdoors            2201\n",
    "Automotive                   2200\n",
    "Industrial & Scientific      2200\n",
    "Musical Instruments          2200\n",
    "Appliances                   2200\n",
    "Office Products              2200\n",
    "All Beauty                   2200\n",
    "Toys & Games                 2200\n",
    "Electronics                  2200\n",
    "All Electronics              2200\n",
    "Cell Phones & Accessories    2200\n",
    "Patio, Lawn & Garden         2200\n",
    "Baby                         2200\n",
    "Baby Products                2200\n",
    "Health & Personal Care       2200\n",
    "Tools & Home Improvement     2200\n",
    "Clothing, Shoes & Jewelry    2200\n",
    "Pet Supplies                 2200\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0474f249-53cf-433e-943c-c92b9fa042c5",
   "metadata": {},
   "source": [
    "## read and decode query images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "be118538-e3d8-4039-aa5c-58c71ad65786",
   "metadata": {},
   "outputs": [],
   "source": [
    "IMG_HEIGHT = 224\n",
    "IMG_WIDTH = 224\n",
    "IMG_CHANNELS = 3\n",
    "\n",
    "def read_and_decode(filename, reshape_dims=[IMG_HEIGHT, IMG_WIDTH]):\n",
    "    # Read the file\n",
    "    img = tf.io.read_file(filename)\n",
    "  \n",
    "    # Convert the compressed string to a 3D uint8 tensor.\n",
    "    img = tf.image.decode_jpeg(img, channels=IMG_CHANNELS)\n",
    "\n",
    "    # Use `convert_image_dtype` to convert to floats in the [0,1] range.\n",
    "    # This makes the img 1 x 224 x 224 x 3 tensor with the data type of float32\n",
    "    img = tf.image.convert_image_dtype(img, tf.float32)[tf.newaxis, ...]\n",
    "\n",
    "    # Resize the image to the desired size.\n",
    "    return tf.image.resize(img, reshape_dims)\n",
    "\n",
    "\n",
    "def create_test_queries(embedder, img_uris):\n",
    "\n",
    "    dataset_embeddings = []\n",
    "    ids_list = []\n",
    "    \n",
    "    start = time.time()\n",
    "        \n",
    "    for uri in img_uris:\n",
    "        img_tensor = read_and_decode(uri, [IMG_WIDTH, IMG_HEIGHT])\n",
    "        embeddings = embedder(img_tensor)\n",
    "        dataset_embeddings.extend(embeddings)\n",
    "        \n",
    "        x = uri.split(\"/\")[-1]\n",
    "        x = x.split(\".\")[0]\n",
    "        ids_list.append(x)\n",
    "        \n",
    "    dataset_embeddings = tf.convert_to_tensor(dataset_embeddings)\n",
    "    \n",
    "    end = time.time()\n",
    "    elapsed_time = round((end - start), 2)\n",
    "    print(f'Elapsed time writting embeddings: {elapsed_time} seconds\\n')\n",
    "  \n",
    "    # return dataset_embeddings, ids_list, id_cat_list\n",
    "    return dataset_embeddings, ids_list\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f760c556-1ef2-4a23-84b3-9ab2e447d38b",
   "metadata": {},
   "source": [
    "connect to Cloud Storage..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "db7dc91c-264d-4bca-bc0e-96e7c5e43f79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gs://retail-products-kaggle/retail-products-classification.zip\n",
      "gs://retail-products-kaggle/data-full/\n",
      "gs://retail-products-kaggle/dataset/\n",
      "gs://retail-products-kaggle/indexes/\n",
      "gs://retail-products-kaggle/pipeline_root/\n",
      "gs://retail-products-kaggle/pipelines_root/\n",
      "gs://retail-products-kaggle/saved-models/\n"
     ]
    }
   ],
   "source": [
    "BUCKET = 'retail-products-kaggle'\n",
    "IMAGE_DIR = f'gs://{BUCKET}'\n",
    "!gsutil ls $IMAGE_DIR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0f874519-d04f-4fbf-877b-a5509cb1ca6a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of train_csv: (46229, 4)\n",
      "Shape of test_csv: (10596, 3)\n",
      "Number of test image files: 6367\n"
     ]
    }
   ],
   "source": [
    "# train and test images \n",
    "DATA_FOLDER = 'data-full' \n",
    "TRAIN_CSV_URI = f'gs://{BUCKET}/{DATA_FOLDER}/train.csv'\n",
    "TEST_CSV_URI = f'gs://{BUCKET}/{DATA_FOLDER}/test.csv'\n",
    "\n",
    "train_csv = pd.read_csv(TRAIN_CSV_URI)\n",
    "test_csv = pd.read_csv(TEST_CSV_URI)\n",
    "\n",
    "TEST_IMG_DIR = f'gs://{BUCKET}/{DATA_FOLDER}/test/test'\n",
    "TEST_LIST_DIR = tf.io.gfile.listdir(TEST_IMG_DIR)\n",
    "\n",
    "print(f\"Shape of train_csv: {train_csv.shape}\")\n",
    "print(f\"Shape of test_csv: {test_csv.shape}\")\n",
    "print(f\"Number of test image files: {len(TEST_LIST_DIR)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "369dd28b-9b0d-4f22-b2f6-13776bf74cdf",
   "metadata": {},
   "source": [
    "### Inspect `train` and `test` images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b8a02733-016f-42b9-900a-3f616b704fb4",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['gs://retail-products-kaggle/data-full/test/test/098415096X.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1134872615.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403710066.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403737010.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403742618.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403765049.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403766355.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403778809.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1403794677.jpg',\n",
       " 'gs://retail-products-kaggle/data-full/test/test/1427616566.jpg']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing Image class from PIL package\n",
    "from PIL import Image\n",
    "\n",
    "file_uri_list = []\n",
    "\n",
    "for file in TEST_LIST_DIR[:10]:\n",
    "    file_uri = f\"{TEST_IMG_DIR}/{file}\"\n",
    "    file_uri_list.append(file_uri)\n",
    "\n",
    "# file_uri_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "60d52fa8-dc20-4550-b379-1a50dd8a010f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 51,
     "metadata": {
      "image/jpeg": {
       "height": 300,
       "width": 300
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/098415096X.jpg' # rule book for game -  allow: 'Toys & Games'  | restrict: 'Arts, Crafts & Sewing'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1134872615.jpg' # educational computer game, scenic cover photo - allow: 'Toys & Games' | restrict: 'Patio, Lawn & Garden'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403710066.jpg' # Tom Sawyer - allow: 'Sports & Outdoors' | restrict: 'Toys & Games'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403737010.jpg' # \"Little Women\" book - allow: 'Toys & Games' | restrict: 'Baby', 'Baby Products'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403742618.jpg' # kids book(?) - allow: 'Toys & Games' | restrict: 'Pet Supplies' 'Clothing, Shoes & Jewelry'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403765049.jpg' # NO IMAGE AVAILABLE\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403766355.jpg' # My 2nd Grade (computer game?) - allow: 'Toys & Games', 'Electronics', 'All Electronics' | restrict: 'Baby Products'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403778809.jpg' # charlie brown image - allow: 'Toys & Games' | restrict: 'Baby', 'Baby Products'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1403794677.jpg' # Astronaut - allow: 'Arts, Crafts & Sewing', 'Industrial & Scientific' | restrict: 'Pet Supplies', 'Baby Products'\n",
    "# FILE_NAME = f'{DATA_FOLDER}/test/test/1427616566.jpg' # Habitat - allow: 'Toys & Games', 'Electronics', 'All Electronics' | restrict: 'Pet Supplies', 'Patio, Lawn & Garden'\n",
    "\n",
    "bucket = storage_client.get_bucket(BUCKET)\n",
    "blob = bucket.get_blob(FILE_NAME)\n",
    "Image(blob.download_as_bytes(), width=300, height=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "3c4741d7-0e42-4290-9954-f26aec5f4d93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Title: Little Women\n",
      "\n",
      "Description: \n",
      "Introduce your child to Louisa May Alcott's Little Women in this delightful 182-page condensation of the classic novel. This timeless story has been adapted by Bethany Snyder and retains the phrasing and flavor of the original. Illustrated with black and white drawings by artist Martin Hargreaves, the hardcover book will be a wonderful addition to your child's bookshelf. This beautiful book is part of The Great Classics for Children series published by Dalmatian Press and brought to you by Bendon Publishing. Bendon Publishing International provides entertaining, high quality books and activities for children.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ImgId</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9324</th>\n",
       "      <td>1403737010</td>\n",
       "      <td>Little Women</td>\n",
       "      <td>Introduce your child to Louisa May Alcott's Li...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ImgId         title  \\\n",
       "9324  1403737010  Little Women   \n",
       "\n",
       "                                            description  \n",
       "9324  Introduce your child to Louisa May Alcott's Li...  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# search title, description, category\n",
    "# category = train_csv.loc[train_csv['ImgId'] == IMAGE_ID, 'categories'].item()\n",
    "\n",
    "IMAGE_ID = '1403737010'\n",
    "\n",
    "sample = test_csv.loc[test_csv['ImgId'] == IMAGE_ID]\n",
    "\n",
    "print(f\"Title: {sample['title'].item()}\\n\")\n",
    "print(f\"Description: \\n{sample['description'].item()}\\n\")\n",
    "\n",
    "sample"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87919ae5-15cd-4d2f-a068-dfd389aa098c",
   "metadata": {},
   "source": [
    "### download pre-trained encoder from TF Hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5b24c3be-1e61-4e6d-89db-a50ee9e1a792",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ['TFHUB_MODEL_LOAD_FORMAT'] = 'COMPRESSED'\n",
    "TF_HUB_MODEL_DIR = \"https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4\"\n",
    "\n",
    "IMG_HEIGHT = 224\n",
    "IMG_WIDTH = 224\n",
    "IMG_CHANNELS = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "74a2fcd3-b56e-4e16-b7a9-4cc5f17fbd1a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-11-04 06:30:22.367455: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"visual_embedding\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " mobilenet_embedding (KerasL  (None, 1280)             2257984   \n",
      " ayer)                                                           \n",
      "                                                                 \n",
      " flatten (Flatten)           (None, 1280)              0         \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 2,257,984\n",
      "Trainable params: 0\n",
      "Non-trainable params: 2,257,984\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "layers = [\n",
    "      hub.KerasLayer(\n",
    "          f\"{TF_HUB_MODEL_DIR}\",\n",
    "          input_shape=(IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS),\n",
    "          trainable=False,\n",
    "          name='mobilenet_embedding'),\n",
    "      tf.keras.layers.Flatten()\n",
    "]\n",
    "model = tf.keras.Sequential(\n",
    "    layers, name='visual_embedding'\n",
    ")\n",
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4906cc31-ebfc-4a89-b68f-752dd7081c13",
   "metadata": {},
   "source": [
    "### convert images to vector embeddings using `model.predict()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "c596d71c-a5c7-45e9-933f-8ac760e72d0d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time writting embeddings: 1.91 seconds\n",
      "\n",
      "Shape of test_embeddings   : 10\n",
      "Shape of cleaned_test_embs : 10\n",
      "\n",
      "Shape of test_ids          : 10\n",
      "Shape of cleaned_test_ids  : 10\n",
      "cleaned_test_ids           : ['098415096X', '1134872615', '1403710066']\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0.08451159, 0.        , 0.00108564, ..., 0.3638365 , 0.11259918,\n",
       "       0.        ], dtype=float32)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# IMG_PATH = f'gs://{BUCKET}/{DEST_FOLDER}/test/test'\n",
    "# IMG_PATH = f'gs://{BUCKET}/{DEST_FOLDER}/train/train'\n",
    "\n",
    "# create_test_queries(embedder, img_uris)\n",
    "\n",
    "test_embeddings, test_ids = create_test_queries(\n",
    "    lambda x: model.predict(x),\n",
    "    file_uri_list,\n",
    ")\n",
    "\n",
    "# clean output\n",
    "cleaned_test_embs = [x.numpy() for x in test_embeddings]\n",
    "cleaned_test_ids = [x for x in test_ids]\n",
    "\n",
    "print(f\"Shape of test_embeddings   : {len(test_embeddings)}\")\n",
    "print(f\"Shape of cleaned_test_embs : {len(cleaned_test_embs)}\\n\")\n",
    "\n",
    "print(f\"Shape of test_ids          : {len(test_ids)}\")\n",
    "print(f\"Shape of cleaned_test_ids  : {len(cleaned_test_ids)}\")\n",
    "print(f\"cleaned_test_ids           : {cleaned_test_ids[:3]}\\n\")\n",
    "cleaned_test_embs[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8368020-0ace-4442-b690-84a41df37cd9",
   "metadata": {},
   "source": [
    "## Deployed index endpoints"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff938bc6-cc36-4fdf-8d1c-6fc8413326fb",
   "metadata": {},
   "source": [
    "> `index` + `index_endpoint`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "17c9c13d-d780-468d-a24c-9a7507125d26",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Matching Engine's VPC Network\n",
    "PROJECT_NUMBER = 934903580331\n",
    "VPC_NETWORK_NAME = 'ucaip-haystack-vpc-network'\n",
    "vpc_network_resource_uri = f'projects/{PROJECT_NUMBER}/global/networks/{VPC_NETWORK_NAME}'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56c9e382-4004-4667-8c6d-7627246a2ec2",
   "metadata": {},
   "source": [
    "> Retrieve an existing index endpoint given a name or ID\n",
    "\n",
    "```\n",
    "my_index_endpoint = aiplatform.MatchingEngineIndexEndpoint(\n",
    "                index_endpoint_name='projects/123/locations/us-central1/indexEndpoints/my_index_endpoint_id'\n",
    ")\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "882000b4-2ccc-4a55-aefe-5cfb76f6fe10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "my_ann_IndexEndpoint: <google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint.MatchingEngineIndexEndpoint object at 0x7f7888094a90> \n",
      "resource name: projects/934903580331/locations/us-central1/indexEndpoints/8693644926778343424\n",
      "\n",
      "my_bf_IndexEndpoint: <google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint.MatchingEngineIndexEndpoint object at 0x7f78880ffe50> \n",
      "resource name: projects/934903580331/locations/us-central1/indexEndpoints/4594243365964349440\n"
     ]
    }
   ],
   "source": [
    "# tree-ah index -> ann_1280_deployed_index_v5 \n",
    "ann_IndexEndpoint_ResourceName = \"projects/934903580331/locations/us-central1/indexEndpoints/8693644926778343424\"\n",
    "my_ann_IndexEndpoint = vertex_ai.MatchingEngineIndexEndpoint(index_endpoint_name=ann_IndexEndpoint_ResourceName)\n",
    "\n",
    "# brute force index -> brute_force_1280_deployed_index_v5\n",
    "bf_IndexEndpoint_ResourceName = \"projects/934903580331/locations/us-central1/indexEndpoints/4594243365964349440\"\n",
    "my_bf_IndexEndpoint = vertex_ai.MatchingEngineIndexEndpoint(index_endpoint_name=bf_IndexEndpoint_ResourceName)\n",
    "\n",
    "print(f\"my_ann_IndexEndpoint: {my_ann_IndexEndpoint}\\n\")\n",
    "print(f\"my_bf_IndexEndpoint: {my_bf_IndexEndpoint}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d34926e8-4569-42fb-a068-7058f3640ac7",
   "metadata": {},
   "source": [
    "## Query indexes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acdc1331-81c7-426f-8df0-655f812679ff",
   "metadata": {},
   "source": [
    "**Query deployed indexes**\n",
    "> * `Match` vs `BatchMatch` ? \n",
    "> * single vs ~many query items ?\n",
    "\n",
    "**queries**\n",
    "\n",
    "* Queries express an `AND` logical operator *across* namespaces\n",
    "* Queries express an `OR` logical operator *within* namespaces\n",
    "* A query that specifies `{color: red, blue}, {shape: square, circle}`, matches all database points that satisfy `(red || blue) && (square || circle)`\n",
    "* A query that specifies `{color: red}`, matches all `red` objects of any kind, with no restriction on `shape`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af9cd442-616d-4927-bfca-67a774fba523",
   "metadata": {},
   "source": [
    "**create class for** `namespace`\n",
    "* specifies the rules for determining the datapoints that are eligible for each matching query,\n",
    "* overall query is an AND across `namespaces`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "3074ec34-e5d2-4e59-810e-7fc66b711d57",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dataclasses import dataclass, field\n",
    "\n",
    "@dataclass\n",
    "class Namespace:\n",
    "    name: str\n",
    "    allow_tokens: list = field(default_factory=list)\n",
    "    deny_tokens: list = field(default_factory=list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b34bb82-6335-4c42-83e3-946d3bdb3fa7",
   "metadata": {},
   "source": [
    "### helper function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "95daae29-b362-41c9-909b-56e9d0e2d750",
   "metadata": {},
   "outputs": [],
   "source": [
    "import time \n",
    "\n",
    "def single_query_retrieval( \n",
    "    index_endpoint_resource, \n",
    "    deployed_index_id, \n",
    "    num_neighbs, \n",
    "    test_query,\n",
    "    query_id,\n",
    "    cat_allows, \n",
    "    cat_denies, \n",
    "    tag_1_allows,\n",
    "    tag_1_denies,\n",
    "):\n",
    "    '''\n",
    "    index_endpoint_resource (MatchingEngineIndexEndpoint): \n",
    "        Matching Engine index endpoint resource for Vertex AI\n",
    "    \n",
    "    deployed_index_id (str): \n",
    "        The ID of the DeployedIndex to match the queries against\n",
    "    \n",
    "    num_neighbs (int):\n",
    "        number of nearest neighbors to retrieve with each query\n",
    "    \n",
    "    test_query List[List[float]]): \n",
    "        A list of queries. Each query a list of floats, \n",
    "        representing a single embedding\n",
    "        e.g., `array([0.2, ..., 0.4], dtype=float32)`\n",
    "        \n",
    "    query_id (str):\n",
    "        id of query product\n",
    "    \n",
    "    cat_allows List[str]):\n",
    "        allow tokens for the \"category\" namespace\n",
    "    \n",
    "    cat_denies List[str]):\n",
    "        deny tokens for the \"category\" namespace\n",
    "    \n",
    "    tag_1_allows List[str]):\n",
    "        allow tokens for the \"tag_1\" namespace\n",
    "    \n",
    "    tag_1_denies List[str]):\n",
    "        deny tokens for the \"tag_1\" namespace\n",
    "    \n",
    "    '''\n",
    "    print(f'Restricts...\\n cat_allows: {cat_allows}, cat_denies: {cat_denies},\\ntag_1_allows: {tag_1_allows}, tag_1_denies: {tag_1_denies}\\n')\n",
    "    bucket = storage_client.get_bucket(BUCKET)\n",
    "    \n",
    "    # call match on tree-ah index endpoint\n",
    "    start = time.time()\n",
    "    \n",
    "    response = my_ann_IndexEndpoint.match(\n",
    "        deployed_index_id=deployed_index_id, \n",
    "        queries=test_query, \n",
    "        num_neighbors=num_neighbs,\n",
    "        filter=[         \n",
    "            Namespace(name=\"category\", allow_tokens=cat_allows, deny_tokens=cat_denies), \n",
    "            Namespace(name=\"tag_1\", allow_tokens=tag_1_allows, deny_tokens=tag_1_denies)\n",
    "        ]\n",
    "    )\n",
    "    \n",
    "    end = time.time()\n",
    "    elapsed_time = round((end - start), 2)\n",
    "    print(f'Elapsed time querying index-endpoint: {elapsed_time} seconds\\n')\n",
    "    \n",
    "    # ===============================================================\n",
    "    # gather metadata for query item...\n",
    "    # ===============================================================\n",
    "    \n",
    "    print(\"--> query item...\\n\")\n",
    "    q_title = test_csv.loc[test_csv['ImgId'] == query_id, 'title'].item()\n",
    "    q_desc = test_csv.loc[test_csv['ImgId'] == query_id, 'description'].item()\n",
    "    print(f\"id: {query_id} | title: {q_title} | description:\\n{q_desc}\\n\")\n",
    "    \n",
    "    query_id_filename = f'data-full/test/test/{query_id}.jpg'\n",
    "    blob = bucket.blob(query_id_filename)\n",
    "    z = Image(blob.download_as_bytes(), width=200, height=200)\n",
    "    display(z)\n",
    "    \n",
    "    # ===============================================================\n",
    "    # gather metadata for NNs...\n",
    "    # ===============================================================\n",
    "    \n",
    "    print(f\"\\n--> {num_neighbs} nearest neighbors...\\n\")\n",
    "    nn_ids_list = []\n",
    "    nn_distance_list = []\n",
    "    # NN ids n distances\n",
    "    for neighbor in response[0]:\n",
    "        nn_ids_list.append(neighbor.id)\n",
    "        nn_distance_list.append(round(neighbor.distance,2))\n",
    "\n",
    "    # for img_id in nn_ids_list:\n",
    "    for img_id, nn_dist in zip(nn_ids_list, nn_distance_list):\n",
    "        nn_cat = train_csv.loc[train_csv['ImgId'] == img_id, 'categories'].item()\n",
    "        nn_title = train_csv.loc[train_csv['ImgId'] == img_id, 'title'].item()\n",
    "        nn_desc = train_csv.loc[train_csv['ImgId'] == img_id, 'description'].item()\n",
    "        \n",
    "        print(f\"title: '{nn_title}'\\nid: {img_id} | dist: {nn_dist} | category: '{nn_cat}' | description:\\n'{nn_desc}'\")\n",
    "        # print(f\"id: {img_id} | title: '{nn_title}' | dist: {nn_dist} | category: '{nn_cat}' | description:\\n'{nn_desc}'\")\n",
    "        \n",
    "        filename = f'data-full/train/train/{img_id}.jpg'\n",
    "        blob = bucket.blob(filename)\n",
    "        y = Image(blob.download_as_bytes(), width=200, height=200)\n",
    "        display(y)\n",
    "        print('\\n')\n",
    "        \n",
    "        \n",
    "    return response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04518bed-84f2-47e9-b267-6d22ac27bc9b",
   "metadata": {},
   "source": [
    "### no restricts specified"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "b0707ba7-64a8-4b9a-ad91-ee6501684f93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restricts...\n",
      " cat_allows: [], cat_denies: [],\n",
      "tag_1_allows: [], tag_1_denies: []\n",
      "\n",
      "Elapsed time querying index-endpoint: 0.03 seconds\n",
      "\n",
      "--> query item...\n",
      "\n",
      "id: 098415096X | title: Malifaux: 2nd Edition Rulebook | description:\n",
      "The next level of hurt is here. They've bringing back Malifaux with bigger guns, sharper teeth, and more chest-pounding action than you can believe. They've added new characters to the game and a new way to build each character using their brand new upgrade system. It doesn't stop there, new stories will keep you on your toes, while reliving past events from your favorite characters!\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> 5 nearest neighbors...\n",
      "\n",
      "title: 'Warhammer Fantasy Roleplay: The Gathering Storm'\n",
      "id: 1589946987 | dist: 682.58 | category: 'Toys & Games' | description:\n",
      "'FFGWHF04 The Gathering Storm Warhammer Fantasy Roleplay Game by Fantasy Flight GamesDeath. Misery. Peril. Suffering. Disaster. And that is just the weather! The Gathering Storm is a complete campaign for Warhammer Fantasy Roleplay that centers around a series of bizarre events that bring the heroes face-to-face with dangerous enemies, moral dilemmas, and the raw fury of nature. In addition to introducing many sessions of exciting adventure, this campaign guide provides detailed information on the town of Stromdorf and a number of its odd citizens, as well as colorful maps that bring Stromdorf and the surrounding region to life.'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Once Upon a Time: Dark Tales'\n",
      "id: 1589780604 | dist: 661.28 | category: 'Toys & Games' | description:\n",
      "'Explore the grim side of your stories with the addition of the Dark Tales expansion to your Once Upon a Time storytelling card game. The 56 cards included in the set are designed to be mixed in with the original Once Upon a Time game, to provide new story elements and endings. In these stories, trolls lurk under every footbridge, inconsolable wraiths search for their lost loves, fiends tempt the innocent, and evil stepmothers serve up children in tasty stews.Not every fairy tale has a happy ending...'\n"
     ]
    },
    {
     "data": {
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4F4VcylVmWGWUAE9doTaSAMEAbf1l/wCDhHwBdfC3wd8HrXXFEU17e66sTSPjaEjsgVBbJAO8cDuB6V+WI8TJpuov4gsdRvGurTWbi4nla9uVSHMzON+wOEVQ+SqxkE89WxX6Nkt4ZRSTVrX/ADf/AAD5+pTTxtSXV2/BGpfW/jyfwj/wiI+G3gDS7rWXlisf7K8CWTXMQRBJIIp5Z/lOxWDFgX2nAyTX0B8I/Ev7Uk3hmT9m39nj9pYaRaanbWZ1Oy0zwF4U8MzK8gCgRyxTLcSSBE3mWAltxUMwYlq+a7L4s6Ba68If7N+2zwapb2sEVhqrTTFnkEglEquFYNg8GTcXAR9qnKz61+0Z4y8M6HrfhDStOsLOzMTrDZ+ZdM1vcSyySvdRhpBJBIssh3Ki+X32nB3dtSrSjI6YUpuKS0R9R+JYvjNrfjG/8M+IP2vvHOqX8F9dW9td3/jcwSzXFukwnhS2ttcjzIsio+VGFCNvL8EngD4XeGNb+O/g3Urf4rXviyXSvEVre2J1/WL6I2hjuUkkmeNtZuHkZHDYMLMsjrjaxOV8B8P/ABn+PvgTXtM8R3VvpXiLWb+0eW403x/p8GsWc1s8as9uIdTaSBsrhhKuyYmSTY6Idte6/Cv9sr9nT4w+F7Pwx+0R+xh4I8P69pd5Jv1DwbpR8Jy3bhDlopNLWB98bFSIpTLGCm4qwOweNOcZy91t9f61Po8PllT2Sc0o32unZvTrayfqdLrfjH/gonH430jwv4c1uefWv7Sik1iZtRgisDpzTsVkWaT5WSWJfMfZGz5llj8pNoQcSPC9hoHwZRfH2v3Gnx6TKH1G8uvG+qm31aycHfbfZUvRIWKMtv8AuXzs3ARqTuTH1vwx488WfEzTPA3wh/azRrazS6k0iTx3fzwahZwlEJhM1vE8M5cLEyuPK3shXy02gtofEz9oz9i/9nOxtdP1/wAe/Ff49eJZbGRNW0mbxXN4c8OoWGF+SwY3a7O7rdMkhB+XApRqe9yLUcssmqfPNKMVpdtflu/uNDVbDxtb2L3M/wC1f4s0/wAR3HixLa18DNY6c8N5JEwudwvrm+ELKqxktBIf3u7y9zI5NcR+1P8AC74ueNfDejeHPjH8RtC0ea3s59Vv9J0XwHouk29vG88gV5msLpLe7JYbxlGIZioOMFvD/iN8atJm1i3g0/8AZV8PeFdPubMS2ekDX/Es4hjZWjWWD7XqMgBCjCllbnnG07Qnwn+NviP4ZTSvpmuXKy63DN9kWa/be87EhPMWIoZgpZSDtAdi/Uk49OlNclpK/mePiMNUpT9zpurf5o2PCHwbn+A2uJrsH2q/1xJmXSL+dmsEtHZiqvHNZX6MxlDbdrH5QpHTketeA/id4t8R6Hqfjv4iaaml61qWqeZfS6XqU+1/JjRYmYmR0UBcfulJQ4G5cg58w1rx1BrIu7yCWSCOOOS4u5rzUFle8Hz7g8Y/1YwVfO7jKAb8nbneBPF50LRodP8AETww3+oaj5zQPLlm3bQAylQA20BShAYheRkHHrYWtCCai7RafXTa33ng43CSxFpzV5aK/W1729Otj97Wurm8keWeKbcGIyUJz7/db+dFd54ttvij4d8RXWneHvCxW18zdGrxBcZ7AKxAHHTNFfhVWlJVGrv7j6yDtBI+BP8Ag7G+ON9rOmfBDUNItY47ltS8TKDeMZGh3R6aFdVJVc4yMMCOehr8XdU8V3Wt3Umo+KbmKWUzA3VvCscay8MocKiBSQQCSCSdxPdiP1U/4Om/Gkvi23+D882ix2TDU/EDssdqI8/Jp+OnWvx+e4kmIL4JzyfWv1DLKsqmBi277/mc7pxUnZG1F4xurOWQeH/NtWk3JvibaTGQRtIX6/TgdSM17L8JP2YL74gw2viP4vePbrTtKmkEtxY2eDcSIcn5TJ8iNywAw2DnjkgeUfDDw6bnXYdXv4yLaKQeWO8r+i8duue2K+hbbxNdabYxSBXBcbFXYcdB6nLdiSu7HHUYA7LLmTsdeHoU53bR9AftF+C/gDJ8AJNE0H4oapb+KNM8Jab4jsdMvNNDxyaW2I2H2ocvMoKs6mONQzhQXOSLXwb+Dnin40fswyfEXwN8J9c8RaNovhtP7d1XRdHn1e806JiztEscbJtWMLlycgBMsCh3n4++K/i241rxHoqTXJM8ET6YHSdykFsRIzQphtoQtK7AY/iJHWvqP9in9rDw/wCH/hhrnwo8UXkVl4p8I6ZqOoeCbW8JELXRUeTcQgOoEiMqMxjKyr5EMqHMReP5XO8vnDDRnTvpJN2dtP8AJbn2PD+ct4udCSiuaFldXTttptd7Gdrdt4P8D/BPwp8VPHX7Lmt+HvAXiTUntND8Z3eirbTapfRRK+8XC3qebuWQMHZ4o1AlWMFopMYWi+Cv2eNd+CGs/GXStBub7XPDOkS6rZ32oRTLI7o7NBIyM7QBvuqRgqViUlZGJLeg+Pfjp+0Z+0pq8fxt1j4XQ6LcPH9lis9G8V6s1pZK22NrxxfC5hYFADK5nPnHf5gZ5mD+eeLfidD4F1nw/wCGdA8RpqepQ3xfUNQSWOeCNJQwNnuTMZIifbIifKNxQgYIrzIwqTxEaeGcleV5WnzaLe+9r7b3PdrNYPDfWMbGDajaKdPls3tZu1+XfRNaHlX7K3wg8WftS+N72/jtpbzUbbSJrjbcbPs1naQlMSs8m5pGZyyCMBSSzOX2qRXmn7T9pHofjdPB6wwq+nBwWhKnIYjbkgksdqA5J6MOBW78QfG3xJ/Zl+JOqWfwm12TRdO8QWZmt1htkIezlZj5Q3qQQj+ZGHXn5TyDkDx2+1O+1O6e+1C5eeeRy8s0zlndj1LMTkn619vTpJTUltbQ/M6tfng4y1lfV9y9pnjbxPo4SPT9ZnSOJi0cBkJjUnqdhO3P4frW/pnxUvr/AFGI6pp6Sy7THBIjkCJjjEgBz8w5HUDDcYPNcVVrSV/4mcB9J1/9CFdDk4o43Tg3do/sKm+I+qandz3V0mjs5lIJguLkL0HrbH+dFeML8Stds5ZYbDULtovMJUreuB0HYNiivzOWKble7OzlZ+Vn/ByJ4xuvF/g74L3N4DuivNf5DAg5TT+mPpX5TwoZJVQdyBX6P/8ABePx7o/jTQvhZY6QoCWd3rROGB+8tlwfT7tfm9X3uWQ9ngoxvtc55LllY9A8M+ILSzlWdp8RoFjiSJRwAeg9z1J7nPfr6loXjLwze6cE1fSLJkhYCJ5v3kgJIA2gsAz5b5SQejE5GA3zeZpDjJ6Hg+laVjc6pbWbT2+pxxMz7drO3mehxxxwecdjjviu+fvqzHCcqatE+kNH8K/DPUdXje60iG4nZhOtnbAq6HcRuITbgcYPzjnOMjCjrdR8Gfs+a3LFqeueGbEGwZl+0w6zc84br8siqmOTgyc5HHUj5OtPiR4s0tEistQQCNyykpuDPwA5DcEgDAJHSs+68T+INSlEl7q9xM4+60szMV9gSeB9KydJdDpp4rk1cU36L/I+wpfG3wD8CGIyaOt4hh2SRa3eTTacjAEgeVcTSA7hnhSBkfSvV/2Jfj3+zt8S/wBqfwP8I/Efwf8ACOo+G9e8Rw2h+z+Fksntr5+bcpOJIkR3mCxkOWLKxVFDlXH5uSXV1uPmtli2W3ckkeuetem+AviGNe0CfwbqTxxCW2EUkRHyTKpGw45ClSeMDjgjGCKxeEpuLS0vc6oZxioVIyaTSez/ACP3E+NHgn9i34o6A1p45+Hfw7/s19SktLn4pa4x/s22mHmt9gfVjFdRRTxI0iNFq0OnBZJomVNwjZ/y8/bj/Zk+B/hcyeKfht+z14x8L6Hpdgtm2uaZq9v4g0bU9SWd0Ij1WC4NsiOihlKJlmbAt4RXFeDf+CnP7U3wwXVPC/i7WbXxRJc2ttZSalq9xdG6aO1aT7P9oeOWNNWSNZGjii1SO9gjiAjWIR5Q5Unifw/+0vfat4l1HxFYeFNV1e8ae68KeGvDC2uneWvygwrEURWO48lnOWOd2445MLg6mEleUm16v5af1c9TNc5wWYUYqnBRfXRfnu/lbv5Hz9eaXcWjHI3IH2+aAdpP1I/Sk0v/AJCEH/XdP/QhXpWseFdI8MWU+ni5kuVkzlbhApI+hPJ/EV5+2njTdWhVXynmowLHp83Q/lXqRk5RPlVJSdkf0qXep+HdLvJrS98WrBIJCWQLFg57jcM4orwnxD8SPCOraxPfR3gfc/LfaS2T9WyaK+A+oxvsehySPym/b68e3HjLT/CsctwZFtZ74gsTkbhBn+VfNFep/G251TxRbaZBYadcXJgaUt5ETPtzs64HHT9K8+/4Q7xX/wBCtqf/AIAyf4V9zhYqFCKRxT+JmbT5pmncuwAyScCtFfCPi1M7fC+pjIwf9Bk/wpv/AAh3iv8A6FbU/wDwBk/wre6JM2itL/hDvFf/AEK2p/8AgDJ/hR/wh3iv/oVtT/8AAGT/AAougKM07Thd6/MowW9R2q/4T1KfTNWWWB0UONrl2wNuQfz44pP+EO8V/wDQran/AOAMn+FKvhDxYpz/AMIrqX/gDJ/hTUkgNeFbHxd4njjv0lKMqozW7Bd2Af4iCB1HUY47Vj674ev/AA3drHNIjLIC0E8MgZXUHGQRx/UV3HgHQo9F0n+0tY0WRrp3YIku+N4MfxAAA/8A66reLHk1iB0Hha/d1J8lkt5SUOMdSvTpx04q5ctr33MrzU7JHFw+INXiVo3v5ZEYYKSuWGPofw/KooZ/Nu4nYkkMASfrVv8A4Q7xX/0K2p/+AMn+FCeD/FYcH/hFtS4P/PjJ/hWd0an6Av8AHF/Mbc6n5v7iD+lFfOs/jd/MPP8A4+f8aK+c+qo9T2kTjDcSnq1Hny/3qKK7DnDz5f71KLmXu2fxNFFACG4kPf8AU0efL/eoooAPPl/vUefL/eoooAUXMvds/iaT7TN/fNFFAAbiU9Wo8+X+9RRQAfaZv75ooooA/9k=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'A Woman's View... Through Child Eyes'\n",
      "id: B000CA2JQ6 | dist: 658.17 | category: 'Baby Products' | description:\n",
      "'JACKIE RICHARDSON has been involved in Canada s blues, jazz and theatre scenes for more than 35 years.  A Woman s View...  features her diverse talent-extraordinary vocal prowess singing jazz, blues and gospel, along with sensitive readings of poems by Colina Philips and Salome Bey.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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79z+c6zjRbSNUJ+4OT2OKegYnc4wemM0y1BNpE0ZHzRqfm+lSEDcD+H0r9bVj+bxRjHzdc9vpSONyENwMc4/+tTlVnbC9MUvkv7UwGYJYsWJJJJJ96d5ReMlevI/SkrX8C+H7HxT4ottG1bV30+wy8+pX0aqzW9rGjSTuqu6LI4iSQrHuBkYKg5YVMpKMbslRdSooLqaGpX/9s+JJb6XRk083VjazfZ4pkdRm2jYMNvADAhgmWKg4JYgk918KvjPf6f4E13wTf3zoZtKuYrRo38uRXaJhlZP4Dzyeg+91yTwnxI8Vy+Lvirrnjw6p9sm1jXbi9lvEWRRMzyM28CUmTB/2yWOcsSSSc7UrQSS/2lbBgSpY7T3x1/WsPZQr0kp+R24bFVcFipVab11Xk0ffP7OvxG0vRPhR4a02wVQdP8O2EZCts8ySK2VHUlhkEENkZ4wMZyBXtEPxWsmsGuo4winYyCUqFUbSMDkggEjtgY444H52/Bj4w6j4b0yPSJdQNvZ23nCFGf7iqWKrkEZGW+hCjuOfWbH41eLfHV3D4V8H6aZJppSipK+1IgQArHnA4B5PACjAJJz8bj8krfWHNbb3P17I+MMM8FClJ++kla3bQ+gNe8Y+J/H0OsXXheB7w6RpszWNozBTPdiMusYOCTuPy5Y4+cZPWvF2/wCCoOg6Nq9vf6L4Q1qCeNQt750SBI36MAAxbcCTkEDr7ZPq/wALNc0b4aw6b4W8+GQPKsl9eoCxkbK73LHpkkYBxjdycc163pngnwV432C78GWVzcbv9If7N5m5c7s4xyMYAHAwn1A8dSwOGk6eIpOUelnb1ue9N5njkp4PEezn1TjzenVWt1PEU/4K7eDr2ztpT4mv4GWAK0LSSqVOT12kZ/HJ9SetFei+Of2UP2bLnxFK178K9Ltpgq+Yn9nAbiRu3H1JBBz+WRgkrup4jJ+RWjNfM8avT4l9q+edNvq+V/5n5PW6hIEUf3AfzGf60+o7Un7LED/zzGPp1qSv0RNM/ESaFUBJU8d/U1NBHuk2sccZqCD7h+tWLdxuLHPAzgUwIGtx5jKSeD61o6Zd3FjY3mn28qi2vgi3MUkasGKEsjDcDtYHI3DDbWZc7WYNX1FCGS6jG5ZVzjP3SOCP6/jUKyMw4X8xSaT3MueRa1HRJYdKttaACwTzywhFbJWSIIWyOwIlTHqQ/pUmi6ottKvnQ+YucFTjlepHPrz+ffkGD+2b+DR30YTM1vNcRzSRnH30V1U5xnpI4/EegqnJJIjhlJGOcGhX6k3s7o9L+D/gWy1fwqNRSJGMN6TMucbl4OCo6Dbjv1b14r6b+GfhvQPDXh1ItHhXiPEc0ag5BGfXuMdPavlD4Q/EiLQNQlsr2UNBOkKsTGiGNlRRkKnX7uNxyT1PzNke2+APFWsQX4s7PWma2D5jhMpA2nntnOc85xjA9OfBzWlXmtHovxPvuGMThKMVePvPRvrfudj4l+F/i3ToZviF4b+Muu6RrN25e4umEc1rboBlY2t2GPLHTeDuT5idw4St4Xg/a117WLTSYf2ofNvLspFbRXjXWnx+YxG1RLaZyCTwcEcZ46jt9O1XVruKK12hmwCAhByD6ceoGcdMDpzjlfEnwh+K8N0bz4TXccLyS+Y2mXtis1q8nXcinBhPXmMqCWJOTivIpYmMpctbl8m0vu2PrZ4SFKXPSU2u0ZNfO17M0PEcP/BS7RdRGnaZ+0L4cuYI4U2GXWfPMXHMW+4ty52nKnnGQcUVht+zp/wUq8TSNqei+AvDNzESFaRWERzgHBDsDnBHPPXrnNFdSnQSsvZ/h/keXVnN1G063zbX4XPiqzCLaIFJ6DAPpipUCk/OcCtHQvBHi/X/AA1qXiPQPDd5fWXh+zguNbns4DL9hgmnWCOaVVyUiaaSKLzCNokmiQkNKgbrrf8AZf8AjDe2J1mw0fT5rB9UtNOttWTW7ZrG9uLk6gIRa3AfZdK50rUlEkTOm+yeLPmtHG/0rxFGmryl/Wn+Z+ZQp1anwxb+X9djhYvK6Bv/AB0fzxUihlbcCQR3FdjJ+zV8aNP1u78OeIvB/wDZN7puuRaNqcGr30NobbUHtZ7sW7+a67CkMDtLIf3dvuj85ohIhbJ8O/DHXfE9zokXh/X/AA9MPEGtw6TZSPrsUaQ3E0VvLH9oMuwWsZFyqiWbYhaC5wxFvMYxYmjLaQ3RqxesX9xmG+imtXt7qLBDK8Zx9QR+OR+VCWEbx+YkeR3FdBbfCTxfqRhh8Py2mrz3qg6dDokdzem4DXs1jG6eTCxdJLmAwq4G3fPACw8xcwePfhV4++E3iafwt490u50zF3cwtqLQTNZTJb3bWdxLHKExcRRXKSQtJDvVpI2VC/GXCvSlomS6NSmtUzmboRmQBW3MOM4xTBuH7lweeR7GvUvG/wCyX8Wvh14jvfBOsWdjd61Y+KP+Eck0zS7uSeSTVvtOoWv2NNsWGdrjS7uJGB2OwXazDJEFv+yz8U77w/Y+MBpUY03UpdISwntTNefav7Rv72wgMf2aGTzFFzYXUZdchzEDF5odC0rF4d7SQSwlZL4X9x5kGPmbhwVOVI7cda3fD3xB8R+H5EFtqMwRPugSHGMfdIyMjpwfQegI6TxR+zb468CXPgu08ZW5sZ/HTTrpdubK7e5haHV7rSZElthB58b/AGmznURbDKeBsLZWuk0T9hj42eKPBOn/ABA0GXRzpmpahe2dvLc3FxFIWtdc0fQ5GMLwLIo+2a3ZsFK7/L8wlVdQjEq+HkrOS10/r7hU6WLhO8E00b/wp/am86+g0zXdQEEoYeTJN9xu+CePcdR1r63+FPxl8P6xo0aNcRCRQFLg7OMcZJx2J/XrXwZ8N/2Uvi/8UPFemeCdFsbLT9S1VPEPlWviC7FjNbyaLp5v9QiuIJP31uUhBRXdPLeRZFV8wzCPW+GPwk/aDfwVf/EL4ffEnRDpul3XhS1leXVZIY1l19ZzapLLPEsFqsJglS4nuJIYEZMLK4ZS3g5jlWDxaXJLlf4dj7XIeK8wy6XLXpua/E/QTWPiRYX1wkp1SNcR4w849SeM9RzRX5h63+0X8Urm981tejkUoPLk8hcsvbIHT0weeOcdKK5YcO11Be+j358a4OtNzVN6+n+Zxur3c2k3Edtb4YIpZWkGSDll7e1U21CVrfzjFFnzCPucdKKK+kPyqyuIur3bMDhBgEcLjvmnf2pcA5VUGRg4XqKKKBNIRtVuBkhE5PPy9acurXKYASPA7bcUUVUNxC/2zcbBH9ngwPWIHtigaxcqfkjiXknASiirW4AmtXiPvCxnIwVMYweMU6PXr+NTHiNkJyyPGCD/AIfUYNFFNARNqdwzFgka56hUo/tG4P3gpHYYx/KiigDT0TSLXWrZ7u6Z1YSFQExjAA9QfWiiik27m8EuVH//2Q==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Chipper Jones Atlanta Braves All-Star 12x18 Lithograph'\n",
      "id: B0000AX6EE | dist: 655.84 | category: 'Sports & Outdoors' | description:\n",
      "'Get the Big Picture! A great collector's item for MLB fans. Large 12 x 18 lithograph.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Baby Carrier - Black'\n",
      "id: B000813EQ8 | dist: 650.51 | category: 'Baby' | description:\n",
      "'Body Glove baby carrier is an innovative baby carrier made for water and land. The Body Glove baby carrier securely snuggles baby to your body safely during water play. The Body Glove baby carrier is made of neoprene which helps regulate baby's body temperature for comfort. The Body Glove baby carrier has Padded Shoulder Straps that provide comfort and quick release buckle for safety. This baby carrier can be used as a front carrier or side sling with choice of two positions: criss - cross strapping or around the neck. The Body Glove baby carrier has Adjustable leg straps for a better fit. Rolls up for quick and easy storage and travel.4 Months to 2 Years - up to 25 lbs.Features:Hands FreeWater FriendlyCan be used as a front carrier or side sling'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[MatchNeighbor(id='1589946987', distance=682.5783081054688),\n",
       "  MatchNeighbor(id='1589780604', distance=661.2794189453125),\n",
       "  MatchNeighbor(id='B000CA2JQ6', distance=658.1710205078125),\n",
       "  MatchNeighbor(id='B0000AX6EE', distance=655.8359375),\n",
       "  MatchNeighbor(id='B000813EQ8', distance=650.5066528320312)]]"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# not specifying allow/deny tokens\n",
    "CAT_ALLOWS = [] # ['Toys & Games']\n",
    "CAT_DENIES = [] # ['Arts, Crafts & Sewing']\n",
    "\n",
    "TAG_ALLOWS = [] # [\"even\",\"odd\"]\n",
    "TAG_DENIES = [] # [\"even\",\"odd\"]\n",
    "\n",
    "QUERY_IMG_ID = cleaned_test_ids[:1][0]\n",
    "QUERY_IMG_EMB = cleaned_test_embs[:1]\n",
    "\n",
    "\n",
    "response = single_query_retrieval(\n",
    "    index_endpoint_resource=my_ann_IndexEndpoint, \n",
    "    deployed_index_id='ann_1280_deployed_index_v5', \n",
    "    num_neighbs=5, \n",
    "    test_query=QUERY_IMG_EMB,\n",
    "    query_id=QUERY_IMG_ID,\n",
    "    cat_allows=CAT_ALLOWS, \n",
    "    cat_denies=CAT_DENIES, \n",
    "    tag_1_allows=TAG_ALLOWS,\n",
    "    tag_1_denies=TAG_DENIES,\n",
    ")\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d5f0d55-4db5-4ec9-ac77-9232dda2680c",
   "metadata": {},
   "source": [
    "### restrict a nearest neighbor's category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "4e31e538-c2f4-4bc0-8f11-d12de04ca194",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restricts...\n",
      " cat_allows: [], cat_denies: ['Baby'],\n",
      "tag_1_allows: [], tag_1_denies: []\n",
      "\n",
      "Elapsed time querying index-endpoint: 0.04 seconds\n",
      "\n",
      "--> query item...\n",
      "\n",
      "id: 098415096X | title: Malifaux: 2nd Edition Rulebook | description:\n",
      "The next level of hurt is here. They've bringing back Malifaux with bigger guns, sharper teeth, and more chest-pounding action than you can believe. They've added new characters to the game and a new way to build each character using their brand new upgrade system. It doesn't stop there, new stories will keep you on your toes, while reliving past events from your favorite characters!\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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SjSVvQ+Yn7GVd2Vl2PLPEXhTx38c9cn17w3AP7Jt5Vto7ySRlhtU5IihiYiRwwy+8qN7FiSmNouXvwy0fSfDjeFxp2QmWla5BEkkhGC+4crz0A+UAAEHktci1vWfCfiBNW0OaWNVZftECSsEuY8/NE4BwykE9uDgjBGa9H8Q+GbXV7aHWNAmPl3Vus1lOxPKMuSpUgjcDlT2JHBIr21KUZxjtHoYYio+a72Por9njw0rfATwYMyDZ4Zs4+SM/JEqc8c/dorqf2W9Miuf2fPC/mwFHjspY2VgvBW4lH8gKK45Qg5M+qoc7oxa7I7H9pHVptX+PuvX9xbYEl/cQwoWyFEVxJEcfVlLfVj6165/wTt8DeK/EXi7WZbPwfd3FpdWCxjV47dvKhKSqzRlywXYw5OAz7o0GQu8HU/aa/ZqttS13UfGPhyym+0Ra9dNqFrKwISKW5kIdOMgCRgCM/wDLTPABruPEHxyHwu8DeG/BcFvJ9ui8J6akEcxJi2JCIS7BWB5aJyAPrkVyTrxxdNUaau3o/LzOrC0ueo1Uly6X2v2PUfH37Il5rEza/wCFrK1W9ki2Xca7YxIuQTtZsANkAlcgEqDnPXidH/ZT8e+HLxtU1PSJltVf95HY27XTZzj5RBvJPPYdq83Px3+JF1dG/T4h6nE5Uc2uovEgA4AVEIC/QD65PNPuv2mvizotl5l58U9YJLEky6i77fqSTWlPKal1ao/v/wCAE41FfXT0/wCCelftA6Prnwpl07xHpWk3s1p/Y0Ms2omwmijzvkQxuZY12OFWP5HAO3bjtnxD4h/FrwHrnhW5u7ZNKW7kGbgTWwEzHB6uhU/g2QPas/xV/wAFNP2jPBaXcOmeM2vVigbMWoRbxgc7g/3geOCCR9a+Ov2m/wBtH46/Er4g23xh8WePr64urfMWkwpDAsNiAB8qAxFXxncN+5+mWOM1p/ZkotLqi6WYVKVFLe2hR+OPhjXPGd9LJ4W0DUdRiAcyroulS3D4POFWJSRkfxHA+pIB+hvgL4d+HHwz+DmlfDS51u3s73TdNhn1ma+he2hN7cILiWJZ5kjS4aPzRGXQsp24BJVwvyh46/b/AP2lfHiow8XWlnF5mf3OnxBgznby8gZuWOAM4yR3OT5x4j+Mn7QfiGY/Y/Hmq3LlWFyvkxK0TBtrDCljtBBycDGDnGCavF5RWxtBUpSUVueJi3Rrzd2z708Vaz8KtFtxqX/CwNEeNmAxZ6hHcH67YSzY98V82/tJ3+jeOPEv9saNDG+m6ZZeTDMq4Z8MWeRgRuQEnADAE4zgbq+dUk+LviKBNYb4h4D7yhbUpAwKEAh1iUleoPz7QVIbO0g1S8IeNfEieI4lv/F+rQ6nDq0am+fUpAtrMJSUeNyR5Qbh15HGBxjavNh+HfqcvaRqNv8AryPPjh6DmtWm+rNrxXYIlyY/suyTaGKnOSCPSvZfhd8PNSb4Q6WtxaG3MvmTiF1/1is+5X69GXb+XTrXz38Qf2ovjbrfxV1fxF4o8X+JbHVG1GeHVVvNUuReptkYG1bzDmIIfk2Ffl24wMYpLD9r341abpp0HSPGUFtbnJD6jZx3DZ9A7ROxY9OeOT0r2nhsS6cVocNfmlG6P0T/AGfHj0v4RaTp8ylXia5DK3b/AEmU/wAqK439jzx5qfxH/Zx8N+MdZkCXd0t0lyUUYdo7uaLfjAA3bM4HAJOKK43GzsfTYao1h4X7I+9PhJ8VtW1/9oj4hfC7x3Z3GpaRp3ibXmivXlUGytIryYPA7tz5OG2xkt+6ZgB8pO3yb9pfxDdeIdU0/wAW3t+txcxXFzp8xt8rDDbFzLaxIvBCAm5VRgYWILxjFXPjX46T4eePfiT4Z8P2kFrNqXjnV73U725m2vdf6S7RxxlwIwse4kICz7nL8EJs8d8a+NLTVrW+jtr28uZTsk8xBst0KHK7d6rJIDHLITlYthB4kDBlzw9DD0cR7SOjlbT+tv8AgGtOVWck1HRGtY+KCn+sby8dT5hXp25Ncl8TvHd0LaUR3Jzj+F8/qM1lp4jmhRckE455rnfGV615bk468DJr24zTZtUqJ02cB43+IGsPpFzaC6dl8iQqueh2Hnr6f09K8X+J/i6ebwzYwwROxLZlbPBfDjjj09c+uew9A8WmRGlt9xbKuv1BUjH615V42jjn0+1RVZFEjZBOeRu7fj61o7dTyVUaT+Zytl4j1yytXt7W+McczbpozCjBsE4B3A5XnO37pOMg4GHaf4m1OKJ7C68RajZ2it50MFlcNDF5jyrvby0BUna0jdASR1P3WsWWmWF6WS/n2qseYyZdgznkHg54+lRXGn6YlyYWWLysJ5RF27BOob5gvzfdz9GGCa6IJR1OFuS1MrVtYvJbZXTxDeXEnmyBle8nb92BHtOGxgFjIOefl57ZzdKaFL0yz2pZBBL8q/wkoVUnJ6BmX8q37hPDWwxWsMcASFdreTJIZGLrknnA2qCenO8gdAazrp7aK4knsblWR5EiJSDywM7mxt5P/LMHr1Jq37yM3sbCaBrfxZ8NxWUdpHdazo0SQWN404WS4sVUKttKT95ofkERbkRMYwSkUaR+e+IdK1nw7efZtY0t4ZI3xtkQ9fqOK73wh4tl8G6+msxNGvmfu7iIE+VMnowxlTk8MvI54bcRXq3jBPB/jjw0twLdJYLiPcoVlIXjqCCcMOe+eOa5a1aVGfLbRnJJ33Pcv+Cf1xNc/skeFbmNVRZJdSIRRgD/AImV1x0oqb9ibSToX7Mvh3S0lBWK41LaQOoOo3JH6GivFrUqbqyv3Po6H8GPofZH7S3gTw1aftS+N9S1SOOSWfWPOZWGNxkhifnHu1eS/FDUdAS1Nr9kiigKtGyxuqE5GDzjjjv+dd1/wUM8fL4X/a08X2c0/loI9PmKhgCwawtzz68/yr5U8c/FPWPESq9pp0kducolxLGQrH+6rdCfoa5cNCdSaf8AW59BLE0aOCin2/Q2b+6hindbC9W6iU/egYOyj/ax/P8Al0rJ1HVXmgKbRjPBx14NZeiRixgO9GkZuTJGgZl9jnpUGvFnuUlibjb8owV4/TNe1CEo2uz5+WK5nZLQydZ8HPr0TSt4j02zkMpCQXk0kTEYyG3eWUAP+9njkCsDxZp3jXSYA3iDTdJ8TWbjaXBWZox6ghQxOOc4P1HUdneabbXyxoUH70ZJLBSB/LNY2o+A2acSafLcWRzgO8YIf6kYH6/hUVXaWrMo1HZ8i9dTyDxD4VsLsvq3hy32Ix+ezBYtC3cAsSTz2PI7ccDl7rT2kBzEQR1wMGvetT8Kraxs99ZQPM4+WWJuuPfFef8AiXwdcJJLdRxKSzFmHce+O4ralWs7M5K1OUIpnmN5p7OpkRDxzhV/xrN1G2e2hicpgmUkhhzwABn2+Y12t/ocqRnK4KkhlArItfCV94i1iDRNPEUUtwSFnnfbHCACzSO3ZFUFmPUKpwCa71O6OVvTQxIYA0W6RiQQfl9Kk8L+Jbrw9qUmkC8zZXQZlicZ2ygHbtOflJIC/jXt2lfsKeNdc+I2k+A9Q+KnhnT9L1Xwvca4PFeqSXEVpaC2a6jutPZDCJWvo5bG7Xy0yCsEkoJRSR84eKrO40bUJ9KTUYZ5bV8NNbOxjcgA7kZwrMvPG4ZqZqNSJzv3dz9Av2JTczfsv+F7t4PmuPt8pwP71/ckfpiir/7IQa1/Zk8F7bYfv9JNwcjoZJpJCPzY0V4s4RlNt7nv0qs1SiltY9h/4K3W0cP7cWpXQy32jw3pbvGxym4Q7d2PXCj8q+bvELST6dFJLIx8sqUBPAzkf0oorfA/7ujXEfCvRfkiSwmbYqkDAI9e/NTXiJJFvdAT1BPY5oorpOIsQ2dsLKJ2iDbkGQ31pqyywTi3jkby2BJQnI/WiisqvwFQbUkUdTgjlkkDjIABGa568t4fIacIAwz9OtFFZrYuoch4ktLWVJJXt0LGMjLLuwPQZztH0xXNwSx6JfQ6hotrHa3NufNjuY8s24Z4IckFT0K4wQSCCDRRW1M4Jpc7N0/tj/E7S21JbvRNE1OKC91J44tWiubhvtbqyS3vmtP5vnyMBI537HcZKEZU/PXiPUJ/EN1c65eZWW7mmuZFEruA7ZY/NIzO3XGWYnAGSaKK72lyXOKyuz9JP2Y9Ntov2bvAO0H5vCNi5ye5iBP6miiivDh8KPcpfw0f/9k=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> 5 nearest neighbors...\n",
      "\n",
      "title: 'Warhammer Fantasy Roleplay: The Gathering Storm'\n",
      "id: 1589946987 | dist: 682.58 | category: 'Toys & Games' | description:\n",
      "'FFGWHF04 The Gathering Storm Warhammer Fantasy Roleplay Game by Fantasy Flight GamesDeath. Misery. Peril. Suffering. Disaster. And that is just the weather! The Gathering Storm is a complete campaign for Warhammer Fantasy Roleplay that centers around a series of bizarre events that bring the heroes face-to-face with dangerous enemies, moral dilemmas, and the raw fury of nature. In addition to introducing many sessions of exciting adventure, this campaign guide provides detailed information on the town of Stromdorf and a number of its odd citizens, as well as colorful maps that bring Stromdorf and the surrounding region to life.'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Once Upon a Time: Dark Tales'\n",
      "id: 1589780604 | dist: 661.28 | category: 'Toys & Games' | description:\n",
      "'Explore the grim side of your stories with the addition of the Dark Tales expansion to your Once Upon a Time storytelling card game. The 56 cards included in the set are designed to be mixed in with the original Once Upon a Time game, to provide new story elements and endings. In these stories, trolls lurk under every footbridge, inconsolable wraiths search for their lost loves, fiends tempt the innocent, and evil stepmothers serve up children in tasty stews.Not every fairy tale has a happy ending...'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'A Woman's View... Through Child Eyes'\n",
      "id: B000CA2JQ6 | dist: 658.17 | category: 'Baby Products' | description:\n",
      "'JACKIE RICHARDSON has been involved in Canada s blues, jazz and theatre scenes for more than 35 years.  A Woman s View...  features her diverse talent-extraordinary vocal prowess singing jazz, blues and gospel, along with sensitive readings of poems by Colina Philips and Salome Bey.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Chipper Jones Atlanta Braves All-Star 12x18 Lithograph'\n",
      "id: B0000AX6EE | dist: 655.84 | category: 'Sports & Outdoors' | description:\n",
      "'Get the Big Picture! A great collector's item for MLB fans. Large 12 x 18 lithograph.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Living Stone'\n",
      "id: 1932697810 | dist: 640.95 | category: 'Toys & Games' | description:\n",
      "'Africa, 1855, The Scottish missionary, Dr. David Livingstone, has been researching African tribes and the flora and fauna of the area. As part of the Livingstone expedition, strategically set up tents in various regions, while collecting gemstones found along the Zambezi River bank. Gain the most victory points and the favor of Queen Victoria to win. 2 to 5 players. 35 minutes. In this game you follow in the footsteps of David Livingstone to the roaring Victoria Falls. On your way you may want to try your luck in the Diamond mining or you may prefer to seek a more calculable risk.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[MatchNeighbor(id='1589946987', distance=682.5783081054688),\n",
       "  MatchNeighbor(id='1589780604', distance=661.2794189453125),\n",
       "  MatchNeighbor(id='B000CA2JQ6', distance=658.1710205078125),\n",
       "  MatchNeighbor(id='B0000AX6EE', distance=655.8359375),\n",
       "  MatchNeighbor(id='1932697810', distance=640.9542236328125)]]"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CAT_ALLOWS = [] # ['Toys & Games']\n",
    "CAT_DENIES = ['Baby'] # ['Arts, Crafts & Sewing']\n",
    "\n",
    "TAG_ALLOWS = [] # [\"even\",\"odd\"]\n",
    "TAG_DENIES = [] # [\"even\",\"odd\"]\n",
    "\n",
    "QUERY_IMG_ID = cleaned_test_ids[:1][0]\n",
    "QUERY_IMG_EMB = cleaned_test_embs[:1]\n",
    "\n",
    "\n",
    "response = single_query_retrieval(\n",
    "    index_endpoint_resource=my_ann_IndexEndpoint, \n",
    "    deployed_index_id='ann_1280_deployed_index_v5', \n",
    "    num_neighbs=5, \n",
    "    test_query=QUERY_IMG_EMB,\n",
    "    query_id=QUERY_IMG_ID,\n",
    "    cat_allows=CAT_ALLOWS, \n",
    "    cat_denies=CAT_DENIES, \n",
    "    tag_1_allows=TAG_ALLOWS,\n",
    "    tag_1_denies=TAG_DENIES,\n",
    ")\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c34a8d9-0915-48ba-ba1f-95a9bd1a04c8",
   "metadata": {},
   "source": [
    "### restrict tag_1 namespace tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "f1164034-4a7d-49dc-a4f4-ce89548c4d29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restricts...\n",
      " cat_allows: [], cat_denies: ['Baby'],\n",
      "tag_1_allows: ['even'], tag_1_denies: ['odd']\n",
      "\n",
      "Elapsed time querying index-endpoint: 0.02 seconds\n",
      "\n",
      "--> query item...\n",
      "\n",
      "id: 098415096X | title: Malifaux: 2nd Edition Rulebook | description:\n",
      "The next level of hurt is here. They've bringing back Malifaux with bigger guns, sharper teeth, and more chest-pounding action than you can believe. They've added new characters to the game and a new way to build each character using their brand new upgrade system. It doesn't stop there, new stories will keep you on your toes, while reliving past events from your favorite characters!\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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SjSVvQ+Yn7GVd2Vl2PLPEXhTx38c9cn17w3AP7Jt5Vto7ySRlhtU5IihiYiRwwy+8qN7FiSmNouXvwy0fSfDjeFxp2QmWla5BEkkhGC+4crz0A+UAAEHktci1vWfCfiBNW0OaWNVZftECSsEuY8/NE4BwykE9uDgjBGa9H8Q+GbXV7aHWNAmPl3Vus1lOxPKMuSpUgjcDlT2JHBIr21KUZxjtHoYYio+a72Por9njw0rfATwYMyDZ4Zs4+SM/JEqc8c/dorqf2W9Miuf2fPC/mwFHjspY2VgvBW4lH8gKK45Qg5M+qoc7oxa7I7H9pHVptX+PuvX9xbYEl/cQwoWyFEVxJEcfVlLfVj6165/wTt8DeK/EXi7WZbPwfd3FpdWCxjV47dvKhKSqzRlywXYw5OAz7o0GQu8HU/aa/ZqttS13UfGPhyym+0Ra9dNqFrKwISKW5kIdOMgCRgCM/wDLTPABruPEHxyHwu8DeG/BcFvJ9ui8J6akEcxJi2JCIS7BWB5aJyAPrkVyTrxxdNUaau3o/LzOrC0ueo1Uly6X2v2PUfH37Il5rEza/wCFrK1W9ki2Xca7YxIuQTtZsANkAlcgEqDnPXidH/ZT8e+HLxtU1PSJltVf95HY27XTZzj5RBvJPPYdq83Px3+JF1dG/T4h6nE5Uc2uovEgA4AVEIC/QD65PNPuv2mvizotl5l58U9YJLEky6i77fqSTWlPKal1ao/v/wCAE41FfXT0/wCCelftA6Prnwpl07xHpWk3s1p/Y0Ms2omwmijzvkQxuZY12OFWP5HAO3bjtnxD4h/FrwHrnhW5u7ZNKW7kGbgTWwEzHB6uhU/g2QPas/xV/wAFNP2jPBaXcOmeM2vVigbMWoRbxgc7g/3geOCCR9a+Ov2m/wBtH46/Er4g23xh8WePr64urfMWkwpDAsNiAB8qAxFXxncN+5+mWOM1p/ZkotLqi6WYVKVFLe2hR+OPhjXPGd9LJ4W0DUdRiAcyroulS3D4POFWJSRkfxHA+pIB+hvgL4d+HHwz+DmlfDS51u3s73TdNhn1ma+he2hN7cILiWJZ5kjS4aPzRGXQsp24BJVwvyh46/b/AP2lfHiow8XWlnF5mf3OnxBgznby8gZuWOAM4yR3OT5x4j+Mn7QfiGY/Y/Hmq3LlWFyvkxK0TBtrDCljtBBycDGDnGCavF5RWxtBUpSUVueJi3Rrzd2z708Vaz8KtFtxqX/CwNEeNmAxZ6hHcH67YSzY98V82/tJ3+jeOPEv9saNDG+m6ZZeTDMq4Z8MWeRgRuQEnADAE4zgbq+dUk+LviKBNYb4h4D7yhbUpAwKEAh1iUleoPz7QVIbO0g1S8IeNfEieI4lv/F+rQ6nDq0am+fUpAtrMJSUeNyR5Qbh15HGBxjavNh+HfqcvaRqNv8AryPPjh6DmtWm+rNrxXYIlyY/suyTaGKnOSCPSvZfhd8PNSb4Q6WtxaG3MvmTiF1/1is+5X69GXb+XTrXz38Qf2ovjbrfxV1fxF4o8X+JbHVG1GeHVVvNUuReptkYG1bzDmIIfk2Ffl24wMYpLD9r341abpp0HSPGUFtbnJD6jZx3DZ9A7ROxY9OeOT0r2nhsS6cVocNfmlG6P0T/AGfHj0v4RaTp8ylXia5DK3b/AEmU/wAqK439jzx5qfxH/Zx8N+MdZkCXd0t0lyUUYdo7uaLfjAA3bM4HAJOKK43GzsfTYao1h4X7I+9PhJ8VtW1/9oj4hfC7x3Z3GpaRp3ibXmivXlUGytIryYPA7tz5OG2xkt+6ZgB8pO3yb9pfxDdeIdU0/wAW3t+txcxXFzp8xt8rDDbFzLaxIvBCAm5VRgYWILxjFXPjX46T4eePfiT4Z8P2kFrNqXjnV73U725m2vdf6S7RxxlwIwse4kICz7nL8EJs8d8a+NLTVrW+jtr28uZTsk8xBst0KHK7d6rJIDHLITlYthB4kDBlzw9DD0cR7SOjlbT+tv8AgGtOVWck1HRGtY+KCn+sby8dT5hXp25Ncl8TvHd0LaUR3Jzj+F8/qM1lp4jmhRckE455rnfGV615bk468DJr24zTZtUqJ02cB43+IGsPpFzaC6dl8iQqueh2Hnr6f09K8X+J/i6ebwzYwwROxLZlbPBfDjjj09c+uew9A8WmRGlt9xbKuv1BUjH615V42jjn0+1RVZFEjZBOeRu7fj61o7dTyVUaT+Zytl4j1yytXt7W+McczbpozCjBsE4B3A5XnO37pOMg4GHaf4m1OKJ7C68RajZ2it50MFlcNDF5jyrvby0BUna0jdASR1P3WsWWmWF6WS/n2qseYyZdgznkHg54+lRXGn6YlyYWWLysJ5RF27BOob5gvzfdz9GGCa6IJR1OFuS1MrVtYvJbZXTxDeXEnmyBle8nb92BHtOGxgFjIOefl57ZzdKaFL0yz2pZBBL8q/wkoVUnJ6BmX8q37hPDWwxWsMcASFdreTJIZGLrknnA2qCenO8gdAazrp7aK4knsblWR5EiJSDywM7mxt5P/LMHr1Jq37yM3sbCaBrfxZ8NxWUdpHdazo0SQWN404WS4sVUKttKT95ofkERbkRMYwSkUaR+e+IdK1nw7efZtY0t4ZI3xtkQ9fqOK73wh4tl8G6+msxNGvmfu7iIE+VMnowxlTk8MvI54bcRXq3jBPB/jjw0twLdJYLiPcoVlIXjqCCcMOe+eOa5a1aVGfLbRnJJ33Pcv+Cf1xNc/skeFbmNVRZJdSIRRgD/AImV1x0oqb9ibSToX7Mvh3S0lBWK41LaQOoOo3JH6GivFrUqbqyv3Po6H8GPofZH7S3gTw1aftS+N9S1SOOSWfWPOZWGNxkhifnHu1eS/FDUdAS1Nr9kiigKtGyxuqE5GDzjjjv+dd1/wUM8fL4X/a08X2c0/loI9PmKhgCwawtzz68/yr5U8c/FPWPESq9pp0kducolxLGQrH+6rdCfoa5cNCdSaf8AW59BLE0aOCin2/Q2b+6hindbC9W6iU/egYOyj/ax/P8Al0rJ1HVXmgKbRjPBx14NZeiRixgO9GkZuTJGgZl9jnpUGvFnuUlibjb8owV4/TNe1CEo2uz5+WK5nZLQydZ8HPr0TSt4j02zkMpCQXk0kTEYyG3eWUAP+9njkCsDxZp3jXSYA3iDTdJ8TWbjaXBWZox6ghQxOOc4P1HUdneabbXyxoUH70ZJLBSB/LNY2o+A2acSafLcWRzgO8YIf6kYH6/hUVXaWrMo1HZ8i9dTyDxD4VsLsvq3hy32Ix+ezBYtC3cAsSTz2PI7ccDl7rT2kBzEQR1wMGvetT8Kraxs99ZQPM4+WWJuuPfFef8AiXwdcJJLdRxKSzFmHce+O4ralWs7M5K1OUIpnmN5p7OpkRDxzhV/xrN1G2e2hicpgmUkhhzwABn2+Y12t/ocqRnK4KkhlArItfCV94i1iDRNPEUUtwSFnnfbHCACzSO3ZFUFmPUKpwCa71O6OVvTQxIYA0W6RiQQfl9Kk8L+Jbrw9qUmkC8zZXQZlicZ2ygHbtOflJIC/jXt2lfsKeNdc+I2k+A9Q+KnhnT9L1Xwvca4PFeqSXEVpaC2a6jutPZDCJWvo5bG7Xy0yCsEkoJRSR84eKrO40bUJ9KTUYZ5bV8NNbOxjcgA7kZwrMvPG4ZqZqNSJzv3dz9Av2JTczfsv+F7t4PmuPt8pwP71/ckfpiir/7IQa1/Zk8F7bYfv9JNwcjoZJpJCPzY0V4s4RlNt7nv0qs1SiltY9h/4K3W0cP7cWpXQy32jw3pbvGxym4Q7d2PXCj8q+bvELST6dFJLIx8sqUBPAzkf0oorfA/7ujXEfCvRfkiSwmbYqkDAI9e/NTXiJJFvdAT1BPY5oorpOIsQ2dsLKJ2iDbkGQ31pqyywTi3jkby2BJQnI/WiisqvwFQbUkUdTgjlkkDjIABGa568t4fIacIAwz9OtFFZrYuoch4ktLWVJJXt0LGMjLLuwPQZztH0xXNwSx6JfQ6hotrHa3NufNjuY8s24Z4IckFT0K4wQSCCDRRW1M4Jpc7N0/tj/E7S21JbvRNE1OKC91J44tWiubhvtbqyS3vmtP5vnyMBI537HcZKEZU/PXiPUJ/EN1c65eZWW7mmuZFEruA7ZY/NIzO3XGWYnAGSaKK72lyXOKyuz9JP2Y9Ntov2bvAO0H5vCNi5ye5iBP6miiivDh8KPcpfw0f/9k=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> 5 nearest neighbors...\n",
      "\n",
      "title: 'Warhammer Fantasy Roleplay: The Gathering Storm'\n",
      "id: 1589946987 | dist: 682.58 | category: 'Toys & Games' | description:\n",
      "'FFGWHF04 The Gathering Storm Warhammer Fantasy Roleplay Game by Fantasy Flight GamesDeath. Misery. Peril. Suffering. Disaster. And that is just the weather! The Gathering Storm is a complete campaign for Warhammer Fantasy Roleplay that centers around a series of bizarre events that bring the heroes face-to-face with dangerous enemies, moral dilemmas, and the raw fury of nature. In addition to introducing many sessions of exciting adventure, this campaign guide provides detailed information on the town of Stromdorf and a number of its odd citizens, as well as colorful maps that bring Stromdorf and the surrounding region to life.'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Once Upon a Time: Dark Tales'\n",
      "id: 1589780604 | dist: 661.28 | category: 'Toys & Games' | description:\n",
      "'Explore the grim side of your stories with the addition of the Dark Tales expansion to your Once Upon a Time storytelling card game. The 56 cards included in the set are designed to be mixed in with the original Once Upon a Time game, to provide new story elements and endings. In these stories, trolls lurk under every footbridge, inconsolable wraiths search for their lost loves, fiends tempt the innocent, and evil stepmothers serve up children in tasty stews.Not every fairy tale has a happy ending...'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'A Woman's View... Through Child Eyes'\n",
      "id: B000CA2JQ6 | dist: 658.17 | category: 'Baby Products' | description:\n",
      "'JACKIE RICHARDSON has been involved in Canada s blues, jazz and theatre scenes for more than 35 years.  A Woman s View...  features her diverse talent-extraordinary vocal prowess singing jazz, blues and gospel, along with sensitive readings of poems by Colina Philips and Salome Bey.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Lunch Money'\n",
      "id: 1887801472 | dist: 631.37 | category: 'Toys & Games' | description:\n",
      "'Lunch Money is an exciting, fast-paced, multi-player card game that combines dark, psychological images with the raw dynamics of a merciless street fight. This set is a complete game for two or more people. The two decks that come in the box are sufficient for at least four people. If you have more players, you may want to combine another set of cards, or simply be willing to reshuffle the discard pile when the draw pile runs out.'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Huggies Overnites Diapers, Size 4, 31-Count (Pack of 2)'\n",
      "id: B000FKETWU | dist: 628.51 | category: 'Baby Products' | description:\n",
      "'A good nights rest starts with Huggies Overnites diapers. Sweet dreams for a baby who wakes up happy and dry.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[MatchNeighbor(id='1589946987', distance=682.5783081054688),\n",
       "  MatchNeighbor(id='1589780604', distance=661.2794189453125),\n",
       "  MatchNeighbor(id='B000CA2JQ6', distance=658.1710205078125),\n",
       "  MatchNeighbor(id='1887801472', distance=631.3718872070312),\n",
       "  MatchNeighbor(id='B000FKETWU', distance=628.5054931640625)]]"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CAT_ALLOWS = [] # ['Toys & Games']\n",
    "CAT_DENIES = ['Baby'] # ['Arts, Crafts & Sewing']\n",
    "\n",
    "TAG_ALLOWS = [\"even\"] # [\"even\",\"odd\"]\n",
    "TAG_DENIES = [\"odd\"] # [\"even\",\"odd\"]\n",
    "\n",
    "QUERY_IMG_ID = cleaned_test_ids[:1][0]\n",
    "QUERY_IMG_EMB = cleaned_test_embs[:1]\n",
    "\n",
    "\n",
    "response = single_query_retrieval(\n",
    "    index_endpoint_resource=my_ann_IndexEndpoint, \n",
    "    deployed_index_id='ann_1280_deployed_index_v5', \n",
    "    num_neighbs=5, \n",
    "    test_query=QUERY_IMG_EMB,\n",
    "    query_id=QUERY_IMG_ID,\n",
    "    cat_allows=CAT_ALLOWS, \n",
    "    cat_denies=CAT_DENIES, \n",
    "    tag_1_allows=TAG_ALLOWS,\n",
    "    tag_1_denies=TAG_DENIES,\n",
    ")\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "e204e5d3-0545-4977-8afd-6dfef9009da3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Restricts...\n",
      " cat_allows: [], cat_denies: ['Baby'],\n",
      "tag_1_allows: ['odd'], tag_1_denies: ['even']\n",
      "\n",
      "Elapsed time querying index-endpoint: 0.02 seconds\n",
      "\n",
      "--> query item...\n",
      "\n",
      "id: 098415096X | title: Malifaux: 2nd Edition Rulebook | description:\n",
      "The next level of hurt is here. They've bringing back Malifaux with bigger guns, sharper teeth, and more chest-pounding action than you can believe. They've added new characters to the game and a new way to build each character using their brand new upgrade system. It doesn't stop there, new stories will keep you on your toes, while reliving past events from your favorite characters!\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> 5 nearest neighbors...\n",
      "\n",
      "title: 'Chipper Jones Atlanta Braves All-Star 12x18 Lithograph'\n",
      "id: B0000AX6EE | dist: 655.84 | category: 'Sports & Outdoors' | description:\n",
      "'Get the Big Picture! A great collector's item for MLB fans. Large 12 x 18 lithograph.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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VNpYahqUrXKtmRLS3luHWLAxuMUT7fMMablYMwXk/op+zD4X+EPw4/ZZ8M/BL4ZavY+LzeFdRuk1TRWik1GbV7e5jhAEKCRbiaGQQKXMkq2UTiT/R0+T6fi/FZZz1MLGPtKUlro7NS79n2t29bfk3AfC+ZTnHMVN04xlpJ2+Ja8qV+3WwvwS+H8UfhXTtQ+IMT3tzq8AZ9OsLuQW5DxmQZljYtJsQrukhbYCCEklVlL8n+1v/AME3dX/aGNx8Wf2VfixP8HfiRY6E+nrP4Yj+waXrMBjdRDdizVJvMIMcYn3SKIo443hmWKHyur+JfibR/iR8U7HTNC11ZVgFvJ4VFlOY11Ey7QJtwMZjhKrH5Khh5/7vy28tnZe48I/Gzw78Lvhr4j+L3xC1W5h8NaJe3Nul69t+81G3SQRQyrHuP76R2WMr8gDAlhGAQv4TwvluKyDOo16MOSlUdktE3Fp+8090rd30tof0I8ZSzmi8Mo81SNlG13d9l6vbufnB/wAE1/2LotN+LGs6B+31psWjN4f1G306y+G+r2qww6nqsNrFC0nnQErOD50c8a28gTPlTBnTbnz/APa+/Zf+F/x3/ag074Vfs/8AxQuvGHgfTYPtN7BFrNpcTxXZunP9i6WYIUW9d5riNN8ckkpeWVMNLFK8v3h8cvi/8Fv2wfGGleHPBttdbfFMc+g6/pes+C7Vb3wrcrKIbbULmSFPNhuRd3BgEE900LiEJEIpJkeb8m/if8P/AIq/AHx74g+DXxM8Yrf+IHlnubnVU1aSQX8ctxcpJeQOXjuIg0o3YkQsskjxyLHKkkZ/fcHUrZxiuepO0krJO/L11X46aep4uYYXE8PYSMORrnd5rZ8t2t9db33WqXmfrFp3wp8Z6H8H4hB4thufEl34YFzLZ2MjSXj3yTNczwGRbt4/LjW4S0Q7FbMSM7r5yRr8c/H5tT8L6cumeIbG80+WYlhBs3RzRklWLlfmGNjnOdynaSnzIy4vwR/4K++Jvhloun/C344+LNf8X2caqLDxZY+I3a8sY+IiZT8zzrFGWEcYdWXzJCpJWNI2fEf4l/DXxn4A1DTvCzaPfWVzrj3+keI9E1C4ma7mSVvPa5FxMZI38mYjbLGJc+UQCjCavCo+HNDLuIZ4qhFKV/aScUuV6b20tyu2iTVtWrpt/PcQ53jc3wUXVUnyqybeyW3d6239Ln7f/snu3/DJfwjw3H/CpvDHTj/mD2lFO/Zbt7XT/wBlT4T2NtOGjh+FPhlI23dVGkWoB/IUV9GuSS5tHfr3/EdH2qpRSVtF+R8D/wDBZA6gv7TOn3cUJaJPAtmGZEBKj7RdHJ/2R1zz+FfICW73NzE1gjSzSMkdrHbDczljhQo/iPTAByc9+lfbH/BWWZZP2pNMiE8VsYvBFp++lfaiKJrss7seiKMsxPAUMTxXzd8Hvjr+zD+yp4s0f40/EXxFF4n0DV7J7S91rSHh1EeEp3lmms7n7HDHI8bNHp7O7E7wNQiWIN5Evn9dfF06uV1ISp87Ssk9E/K/Q+p4V8S83jOpgZQUVQaUKi6JO2qe7t2362OV1Xx14m+Cl7Z3/i9b3QLrz57HyZd9nP5sYMc0flsQyMnmYJZVA347gHzj4yeNtO+IV/N4vvtYsLTT7WFJJtPtZk33smNpV3DI4aUhlP2dopGL8NkgDF/ax+E3xf8AiZ8Zbn4i+EIbG5024u3mtrJ9WiaOJ9xLOhjLBkkU5Eij7xLLjIK+i237B9/4/wDDmieIpoNC0GZ9Ehs/Fuh3hlhQAHcLu2mHmtc3xUhXWa3RFbO0gxea/wA9Ww/BvB6jWxdCPtGrKom9Ou17Ptf7zfiPijMuMK/vYv8AdxsnBwjJN9Veza11t2Plf4e/thn4FfGXwZ8Z7LRbia98G+JdOvmEF+LSXVbO0MiS6aWEUgjW5gmeCZsOJRIWlWQqpH2RaftHfBXxHM/jX4IWkuq+GNWvJrvwbo+vmcSaHI0uWs5pWJlcQLHsjAlUrFJ8pAdzJw3jT/gkvPpsc3jTwX8XbHX7HYW1TSb+4a3voi0oAeOSSMC54OXIWAglgpOxSe2/Z3/Y88B6FpumeA77UY/DFvcXM0tnPBZedBfERoxMROGebYqr96RypHoAPG/144Iqy+se3vBXUkua9lrZqybXVJaP0uzkjkma5xGeXwpcsXC8JJRUVJJ8sla+urTe9m+ps/Dv4g/G/wCLPxFj8H+HYLrXde8R6l5kkVskA+1NuaSTzH2LFCmwMDxHGq46BQB9O/tuXPiGbw3oP7OfhkabqWmWfhqW68QT6rI1pE815Lb6Raym4SR3sQsl3ezGVVnkjVHVY35lj5K8/Zbi/ZvbT/jN8P8AxxfO2k6hbrqy3jxpG9rPtgaRhHHnakrrIQdwCZIZWjUnr9a/Z0+P6/Df4p3HjfSNL8UWnjBIIfDev2N5m+0/Sba6lvba4+yoIgyyPdHfAkivGYXMTFBC0jzLijhzixYfMMnq3wcE4Nte9zq104tXSs01bpq9Ui+EMr/1SVRZm7VY2fu8zun7t1Z7x1b89FoeKa3+1feeGPhza6XH4y/t3xhrOi6dqN5f3Wnm+bTo57/WtTVWeG2MEOoyXtyx+1wKsluJpgWtxA7r5ZJ4Pn/av1y18F6j8VvDElx4t1TRtT1LxbrHhv7JrlhDqd9aaHHrkZdVOoXB8tYLm2mxbvI0kzO949tcJd/Z/wD2RviX4x8R63rus/Ae4n0nT9BvorfxR4q023vrGOO0a4aOa2S/u4LSafm2hJJ/dRSDPEcinA8VeIPFfw3gs7r4mpfW0Om3Wn2mq+HrbWI9OgkRLy2vDFbSRSmGPzILaVuMDY+5Vmkt4Eb6bLKUa9Cfs1dximml9nS7T6r/AIc+kxuMwGMoQc6lP95unq3fZWUWotPlVnLTVaNn55/HzwB48+HfxV8Q+FvHM1kl9pGqzWc15pEaCyuzAwi82B4cxyKwUMJFLKc8MRivZf8Agmzpuu6/8WYPB/i6K9l8PatfWf2uGAZ85Y7y0idyuCSyW9xcMOOVdzkAZHfj4Vp8ZdP1Pw/8ENN061RbfS0W3v5WlTULmSRIDD8iL5cNwWl/eu+VEEUTA5Dj3j9kz9kH4gfszeA08Q+Jb2Ia/dzyXgV5fNEIMLwoix/NGqiN2G4/NlVwFCKK8XPuLKPD+Xc86ijVmnGC6ttNJ27X37Hl/wCr8cJmUqavOlC6k0rr4fhv13P2q/Z9tXtP2dvhtaQySbYfhr4cQbyQxxpNqOQScGipvgdcyH4BfDp5cu7fDjw8zsT1J0u2J/yKK9fBVE8HSvZvlj+SPl5QipNJnwH/AMFfrPWdQ/ap02aLV47e1j8H6exSK0EkjSJcXTAln3Jtz1TZg/KSeAR+e3gz9kbSPCsoi8U+IU1azilt3isEsGWOaWBpvKnnaWRyXMUxiZFwhCKSWIQx/od/wV21Kwsv2nLGCbxLp9tO3g6z3WdzcBJEzNc4OMHr/wDE+vHyfbalo05YXvxN8LWY83aPtF7M5JPIYeXEwAwepPrz1wqlR04yahNp9oya+TsfnePp8XSxs1Rko027L3qa0113TT11vr3G+GT9ijaC6jMdqoZv9HcII14GNijAHT0HQdwDs2njbXPDlgraPqRTTorQizguLhVjt4iCgMY3D5SF4CZU456YG74A8CeDLSNtf/4aT8A295FNb3MenyXqy2s7JKDHHO2QY1J+cgBsiNQV5zH5h+1R4J8dy+LINaGjRxW4002sqWN6s1uIZWFwjxyRzvEqGOQbYkCKEf5UyWLfKLiXB5hmiyyvhuaCTu5xktV0V0rt909Nj9U4H8M6qSxlfGR5m1eF0/ivd25vx106HoPhX4vx6fdsviGZmtJolJ8x/wB7GRhSA7feB/usemcHmvYdM+Nnhfxz4Ofwz418jXLGaDETXaDzBuBAVxuTGOTnJ2lMkEk18R+Dtb1LTY9StfFWoQCK0hhW1tLzUBwcPnarcFBgKwDDY0sTttRJCvQ/D/xTrJtX17wjrNtf2DSB47SaMkQuAmVIODG/HOCM4weleHxJ4cYHOcP9ayyk04226Pff9Uft2G4JpY/EujluJ9jioO0qbfuTS6rr2s9emp9x2d34jvfh5N4V8QvLPY6z4a1Cz0uKWYAS3rW8/wBnw/DqxupbZMMwUF0RWC7EHqn7NHxE0/wl8PtN8L61rrm2E8kenyPAkX2LdJxAVXGIxgbWfLZZV3n5N3w5+zBr3xj+If7Q/hv4P+APFGnaPqOq6x/bBN4XZWOnI99uIRg7jFq64+ZTxwNoYesfGLxdq/w1+KM/iOxtrrRtN1O8uobi3tpPL/s+4BAuLX90Vyo8xZI5I2+aCWJ0KupJ8LKOH89yfKpYKKSXO6nKla7aS23v7vz12PgPEfCf6mZnSqYmv7VTSVS2rhrZP0vdfnufQfxE8G+N5vFuoeAvg8Xsn8Y2eoRWkUS7VXVZrR40jwcKvmFYgMkDlwQQefhHxJoT/E3SrPTLiO11IKLeLUbW6g81GMD/ALl3VlKsAgUK2SV2dvlLfUepfHBR8IJxrsa3/iKw0C4ufDE9yJca8RH9lNqspAdp45Li1EpyGcXSyKxO5Yvn9fCmq+CfGNx4H199j2NnbbzFHtxfz2nmu33AQgjubYMpOEeKRc7kYt+veHlf20nh5/E7K1+m/wAr32/4B+N8a4SvhYwxMXeg02ntdSdOzXo18tTa/ZU/Zx8JXFz4e1rRfCUek3UfiTUbvWPsnKmBLeI2jvG4IjVp1lTCLGCCNpLAGvfta8AWel6dcSau0jrFIBZxSYkab5sdFBIyWQADleS3cjiP2Q2h8OeNdU8Gtdz3stxpM13DM8zJFb28U0QVEhHALC4XcSCcxnGAzZ9f8ZHbZOl5PHCmw7izEEKeOO49c9eK/lLx4xWZYLxGeXxTVOEYW1u/fvUf4ya9Ef0DwBXhmHCuHrJuTkrXe7cVyddfs7v1PsX4ZXD3Hwn8G3MUIVZfBOiuqBcbQdPtzjGBge2KKZ8Mks1+E/gyJIQVj8E6Ki/QafbgdaK/rDJk3lOHf9yP/pKPyjF04/W6l19qX5s/LH/gt/HPdfto2yWmiatfzn4f2BSDSbJp3XE8ylmCj5RmRRyRk4VcsQD8Z63Hd6QZtJvGubO7tZFjubW4tmDRMY0kAI34B2yIcHnnnkGvsn/gsbe6LD/wU18Iax4ln1WHTvDvh2znur/w5rUdjf6XcmJ2guoZjFMyvHIySAJHvO0hXjY71+RPjP4r8I3/AMQ9TvtD8R2M1ncQ6d9mC2LWcUaxadZ2xjSGSWSSFVaFlCSO7KEAMs2BPL+ucPZjmCxFLCyhaj7OLUrdbaq+x8diMup1lKtze9zNW8vQ5mbUXlRSdWiwowBLYu3HGAd0vqOvPXv1qO5+KPjG2jtNHi8SxTWdiwNnp8m5o7YiTe3k78vbMWOS0Lo2QDuyAazbvXdPvQiR3EOIEDyIJMkAcnODx256dKwNV8Q6IzBxqdnKEwDm5TP1PP4fhX2VbC5djFy1oxl6pO337F4Ok8LrTbTO58cePPBviLQrbVINOvoddt7wtNFqjrOsiFj80dwm05yS2DGrgICZpTIduV4S8eahoWpNqWjwiCVpf31tG5KTZ5bcmeckdRkg8+hHJR6robE+TqlmCVyMXC9PTrioptQ0cTAf2tYqNv8AHcAEkdBnPX+WK8WpwnlfJ+5k4O91Z/hbt+J9jlXG+c5RiFVUua21916S3XTTZ9UfWv7Ifxj8Q+Cv2ifC/wASvBng601zWX1ZLOz0fzsHUXuY2tDFG6gsJCkjbQwfDBWKsBivq74+fEv4ffEj4st8HvFUX2bxJ4yhQQeD9S1uztr+C8ikKxS25aRhdPFk7oLeaTes0siLKDDDJxX/AARM+HFn4xt9a+MmpTjVLbR7iOw0O7kYj7NeiJnnUyKwLukUsWFbdhZ+Nnyk+hftJfsA/CH4kftYfDr41XviPXovEPhzxUuuaEYbyKWOQ2U0V2bR4ZSokjkw8YcGNlM4JLpEqH8U4szzC4POXQxduemkozin7zuuVS6dd7Jp9TXM6dLO8OqkHLkq/HGTTSbvdx0vZt7Xe+ljwOz1H43fBWXwp4V8cfB7VYhoHxS0XxF4Y1DWfD0wLCG48l4Ld3C5tZy8DllcKxtkc/3lTxR8Zte+KV/4u1/X9YsmWwv50a6htk88zC1trN2eXczHEdkqjftOE3ctIxPH/tgfBbxP8Of2mPi34q0z4taLod/8SdONzp2v+GZ72z1LT7W41CAyxuyTRpN5tvbT2hIkKmC/uQQqhYm8U8LQ+KvCb6XbnxdFJof2W5WZJNWgnn85j8rhmBmKqpdDuKryh2HGT9XlmWV8XFY+hSVGUnTfurdXV7LXdb66bnylB4e2HyOpW9pTXPGN7Pl5tVfsk1ppfXszt/ij4h+LWleAbHV/h3rerLfC+l8690aeSOdLMKi7X2DDRO64CtkEw4x8teS3PxU/aL01ltLjxn4ht2UgmCfUJCwDEFQVY5GeDkjB2jHI49c+B0PxE0r4T6ZewfEDTLvV9CkvLzVXa/eRJvMmlMCTeaBnyRdYC5aPdGQh3MFfoPhl4c+Efijwv46s/wBrH9ovRr/XP7d0vUfhtZeH/Cv2i8aKG1vUurN5DHbQWwvVOlOJC05hjMoeJJVWSuKfEmGq5piMJjcDTl7N3bl707fZVnC2icV8Wx7Uo4zBqEcPWdONko291ee0n1u9tT9nP2TdRvtR/ZF+D+o6nPLNc3Hwh8KyXMpJy8jaNaFiemTuzzRUP7K9y0X7LPwwtreIBbf4caFBgPnBj0+CPqeT93qeT170V5q+ozXMlZPVLsnstOxl7RrSp8XXS+vXU9VstU1LT8wWF/NAnL7YZCvJwCePoPyFTx+KPERXP9t3WR0Pnt9PWiit4xi4LQ2cYqK06k1l4j8QyAO2uXeev+vbr6/Wmv4p8SRjy1127x15uGP9aKKTjHlbsOy5mI3ivxK/3tdu+ORm4Y/1qNfFHiTG8a9dgk8/6Q3+NFFZUknuXHVkFxqup35R72/mlMZzGZJCdp9RnpUf2m5jgaCO4cRuRvQMcN9RRRXLVSdBSe+hM9CUeINdc+U+sXRUqDgzt6/Wo18T+IfnQa3dABc4Fw3J9+eaKK7KWtGPojOKXOn5DZvE3iJZk/4nl1nPB89uMnPHPqKifxX4lBcDXbr5gS2J25J/GiionGKqSsuv6Dh70mmU5pZr25lurud5ZXfLyO5LMcDkk9aKKK7qEIulG6FZM//Z\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Living Stone'\n",
      "id: 1932697810 | dist: 640.95 | category: 'Toys & Games' | description:\n",
      "'Africa, 1855, The Scottish missionary, Dr. David Livingstone, has been researching African tribes and the flora and fauna of the area. As part of the Livingstone expedition, strategically set up tents in various regions, while collecting gemstones found along the Zambezi River bank. Gain the most victory points and the favor of Queen Victoria to win. 2 to 5 players. 35 minutes. In this game you follow in the footsteps of David Livingstone to the roaring Victoria Falls. On your way you may want to try your luck in the Diamond mining or you may prefer to seek a more calculable risk.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
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     "text": [
      "\n",
      "\n",
      "title: 'Minigame Library'\n",
      "id: 1936920107 | dist: 635.12 | category: 'Toys & Games' | description:\n",
      "'Why does a good game have to fill a gigantic box and weigh 10 pounds? The Level 99 Games Minigame Library is a collection of games small enough to fit in your pocket, but big enough to enjoy over and over again with friends and family. Each game fills a different niche, and each provides a different play experience. This means that no matter what group you're together with or what genre or style of game you're looking for, you'll be able to find pull out a game that provides 15-45 minutes of fun for a party of any size.Minigames are easy enough to teach in 5-10 minutes, but provide hours of repeated play and excitement. In a minigame, we look for a product that is simple to learn, deep to master, and extensively replayable and enjoyable. We guarantee that your fellow gamers will be requesting to play these games over and over again.Games include:\n",
      "\n",
      "    NOIR - A deductive mystery thriller for 2-4 players.Grimoire Shuffle - A team-based puzzle relay race for 4 or 6 players.Pixel Tactics - A game of tactical combat for 2 players.Infinity Dungeon - Delve through a trap-filled dungeon in this absurd storytelling game. For 4-8 players.Infinity Dungeon 2 - Additional rooms and characters for use with Infinity Dungeon.Blades of Legend - An epic secret roles game with variable powers. For 6-11 players.Master Plan - A gameshow for supervillains that plays on a real-space tabletop. For 3-6 players.'\n"
     ]
    },
    {
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\n",
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     "text": [
      "\n",
      "\n",
      "title: 'L'Oreal Paris Superior Preference Hair Color, 6A Light Ash Brown'\n",
      "id: B00006JN4I | dist: 628.03 | category: 'Beauty' | description:\n",
      "'Ultra Long-Lasting Coloring System. 20% More Fade-Resistant Color. Superior Fade-Resistant Colorant: 20% More color gel with Patented Fade-Resistant Colorants deeply replenishes every strand with rich, long-lasting color that shines. Brilliantly balanced shades stay true to the tone week after week - won't fade-out, turn dull or brassy. Patented Fade-Resistant Colorants for true color. Color-Saving Conditioning Creme: Care Supreme super-rich conditioning is more advanced than ever with a Color-Saving Complex. Enriched with Anti-Oxidant Vitamin E and UV Filters to help color defy fade-out and dry-out. Now, your color braves the elements - water, sun, wind. Hair stays silky and resilient. Up to 6 luxurious treatments to help keep first-day color vibrancy. Vitamin E and UV filters. Up to 6 weekly color-saving treatments. Luxurious Color Experience: All you need for superior coloring - Superior Colorist Gloves, simple instructions, rich color gel technology for no-mess application and a luxurious scent. Preference Color Matching System: More than 50% Gray - Your results will be slightly lighter-looking than the haircolor results shown on box; Red Hair - Your color results will be light brown with soft red tones. Ultra Long-Lasting Coloring System Includes: No-Mess Fade-Resistant Color Gel; Color Optimizing Creme in Applicator; Care Supreme Multi-Dose Conditioner with Vitamin E and UV Filters; Superior Colorist Gloves; Instruction Insert.'\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "title: 'Cover Your Gray Lipstick For The Hair - Dark Brown'\n",
      "id: B0000XMQSQ | dist: 622.17 | category: 'Beauty' | description:\n",
      "'DKNY GOLDEN DELICIOUS by Donna Karan for WOMEN EAU DE PARFUM SPRAY 1.7 OZ (UNBOXED) Launched by the design house of Donna Karan in 2011, DKNY GOLDEN DELICIOUS by Donna Karan possesses a blend of juicy fruits with its fresh opening notes of apple and lily of the valley. It is recommended for casual wear.'\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/jpeg": {
       "height": 200,
       "width": 200
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[MatchNeighbor(id='B0000AX6EE', distance=655.8359375),\n",
       "  MatchNeighbor(id='1932697810', distance=640.9542236328125),\n",
       "  MatchNeighbor(id='1936920107', distance=635.1223754882812),\n",
       "  MatchNeighbor(id='B00006JN4I', distance=628.032958984375),\n",
       "  MatchNeighbor(id='B0000XMQSQ', distance=622.167724609375)]]"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CAT_ALLOWS = [] # ['Toys & Games']\n",
    "CAT_DENIES = ['Baby'] # ['Arts, Crafts & Sewing']\n",
    "\n",
    "TAG_ALLOWS = [\"odd\"] # [\"even\",\"odd\"]\n",
    "TAG_DENIES = [\"even\"] # [\"even\",\"odd\"]\n",
    "\n",
    "QUERY_IMG_ID = cleaned_test_ids[:1][0]\n",
    "QUERY_IMG_EMB = cleaned_test_embs[:1]\n",
    "\n",
    "\n",
    "response = single_query_retrieval(\n",
    "    index_endpoint_resource=my_ann_IndexEndpoint, \n",
    "    deployed_index_id='ann_1280_deployed_index_v5', \n",
    "    num_neighbs=5, \n",
    "    test_query=QUERY_IMG_EMB,\n",
    "    query_id=QUERY_IMG_ID,\n",
    "    cat_allows=CAT_ALLOWS, \n",
    "    cat_denies=CAT_DENIES, \n",
    "    tag_1_allows=TAG_ALLOWS,\n",
    "    tag_1_denies=TAG_DENIES,\n",
    ")\n",
    "\n",
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6d11975-b528-4ccc-96b8-dbb7ecc9b4fb",
   "metadata": {},
   "source": [
    "# Compute Recall"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed25d883-368b-436b-b63f-a8c0eddf0772",
   "metadata": {},
   "source": [
    "make the identical request to both indexes..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "3976e732-a5ee-4499-b30c-fb03177842c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "NUM_NEIGHBOURS=10\n",
    "\n",
    "# ANN INDEX ENDPOINT\n",
    "ann_matches = my_ann_IndexEndpoint.match(\n",
    "    deployed_index_id='ann_1280_deployed_index_v5',\n",
    "    queries=cleaned_test_embs, # [:1],\n",
    "    num_neighbors=NUM_NEIGHBOURS,\n",
    ")\n",
    "\n",
    "# BRUTE FORCE INDEX ENDPOINT\n",
    "exact_matches = my_bf_IndexEndpoint.match(\n",
    "    deployed_index_id='brute_force_1280_deployed_index_v5',\n",
    "    queries=cleaned_test_embs, # [:1],\n",
    "    num_neighbors=NUM_NEIGHBOURS,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cc8be30-dad1-49ba-95a7-fbd62cf34832",
   "metadata": {},
   "source": [
    "Calculate recall by determining how many neighbors were correctly retrieved as compared to the brute-force index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "0a09d277-033d-424a-beed-03b42546c948",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recall: 1.0\n"
     ]
    }
   ],
   "source": [
    "correct_neighbors = 0\n",
    "\n",
    "for tree_ah_neighbors, brute_force_neighbors in zip(ann_matches, exact_matches):\n",
    "    tree_ah_neighbor_ids = [neighbor.id for neighbor in tree_ah_neighbors]\n",
    "    brute_force_neighbor_ids = [neighbor.id for neighbor in brute_force_neighbors]\n",
    "\n",
    "    correct_neighbors += len(\n",
    "        set(tree_ah_neighbor_ids).intersection(brute_force_neighbor_ids)\n",
    "    )\n",
    "\n",
    "recall = correct_neighbors / (len(cleaned_test_ids) * NUM_NEIGHBOURS)\n",
    "\n",
    "print(\"Recall: {}\".format(recall))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "41decb18-ddb9-4d67-98b7-a5912f397885",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'Length of ann_matches: 10'\n",
      "'Length of exact_matches: 10'\n",
      "'correct_neighbors: 100'\n"
     ]
    }
   ],
   "source": [
    "# pprint(ann_matches)\n",
    "# pprint(exact_matches)\n",
    "\n",
    "pprint(f\"Length of ann_matches: {len(ann_matches)}\")\n",
    "pprint(f\"Length of exact_matches: {len(exact_matches)}\")\n",
    "\n",
    "pprint(f\"correct_neighbors: {correct_neighbors}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "274ed2d7-7723-43ef-8d08-7f2d8d0b3335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correct_neighbors"
   ]
  }
 ],
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