diff --git a/learn/search/semantic-search/hello-pinecone-aws.ipynb b/learn/search/semantic-search/hello-pinecone-aws.ipynb
index 0bdfef98..de68c939 100644
--- a/learn/search/semantic-search/hello-pinecone-aws.ipynb
+++ b/learn/search/semantic-search/hello-pinecone-aws.ipynb
@@ -1,18 +1,16 @@
 {
   "cells": [
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "023d771c",
       "metadata": {
         "id": "023d771c"
       },
       "source": [
-        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/quick-tour/hello-pinecone.ipynb)"
+        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/learn/search/semantic-search/hello-pinecone-aws.ipynb)"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "conceptual-belfast",
       "metadata": {
@@ -33,7 +31,6 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "first-affairs",
       "metadata": {
@@ -52,7 +49,6 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "banned-huntington",
       "metadata": {
@@ -89,19 +85,34 @@
           "start_time": "2021-04-16T15:08:30.762518",
           "status": "completed"
         },
-        "tags": []
+        "tags": [],
+        "outputId": "8dc9dc6d-5a02-4699-df31-fe28da170865",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/421.4 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m \u001b[32m419.8/421.4 kB\u001b[0m \u001b[31m14.4 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m421.4/421.4 kB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h"
+          ]
+        }
+      ],
       "source": [
         "!pip install -qU \\\n",
-        "  pinecone-client==3.1.0 \\\n",
-        "  pandas==2.0.3"
+        "  pinecone==6.0.1 \\\n",
+        "  pandas==2.2.2"
       ]
     },
     {
       "cell_type": "markdown",
       "id": "191793df",
-      "metadata": {},
+      "metadata": {
+        "id": "191793df"
+      },
       "source": [
         "## Initializing the Index\n",
         "\n",
@@ -110,23 +121,38 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 2,
       "id": "3f0a5ee4",
-      "metadata": {},
-      "outputs": [],
+      "metadata": {
+        "id": "3f0a5ee4",
+        "outputId": "f26b6f73-7da4-43c7-eeb0-07c5fdfe5cff",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Enter your Pinecone API key··········\n"
+          ]
+        }
+      ],
       "source": [
         "import os\n",
         "from pinecone import Pinecone\n",
+        "from getpass import getpass\n",
         "\n",
         "# initialize connection to pinecone (get API key at app.pinecone.io)\n",
-        "api_key = os.environ.get('PINECONE_API_KEY') or 'PINECONE_API_KEY'\n",
+        "api_key = os.environ.get('PINECONE_API_KEY') or \\\n",
+        "    getpass(\"Enter your Pinecone API key\")\n",
         "\n",
         "# configure client\n",
         "pc = Pinecone(api_key=api_key)"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "forbidden-indication",
       "metadata": {
@@ -146,37 +172,27 @@
         "With Pinecone you can create a vector index where you can store and search through your vectors."
       ]
     },
-    {
-      "cell_type": "code",
-      "execution_count": 2,
-      "id": "EA2EcZsCoWS3",
-      "metadata": {
-        "id": "EA2EcZsCoWS3",
-        "tags": [
-          "parameters"
-        ]
-      },
-      "outputs": [],
-      "source": [
-        "# Giving our index a name\n",
-        "index_name = \"hello-pinecone\""
-      ]
-    },
     {
       "cell_type": "code",
       "execution_count": 3,
       "id": "774014f4",
-      "metadata": {},
+      "metadata": {
+        "id": "774014f4",
+        "outputId": "f5bfef00-6fdc-4754-9fc3-ce00b8d4cb88",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "[]"
             ]
           },
-          "execution_count": 3,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 3
         }
       ],
       "source": [
@@ -186,6 +202,22 @@
     {
       "cell_type": "code",
       "execution_count": 4,
+      "id": "EA2EcZsCoWS3",
+      "metadata": {
+        "id": "EA2EcZsCoWS3",
+        "tags": [
+          "parameters"
+        ]
+      },
+      "outputs": [],
+      "source": [
+        "# Giving our index a name\n",
+        "index_name = \"hello-pinecone\""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
       "id": "synthetic-essex",
       "metadata": {
         "execution": {
@@ -207,55 +239,32 @@
       "outputs": [],
       "source": [
         "# Delete the index, if an index of the same name already exists\n",
-        "if index_name in pc.list_indexes().names():\n",
-        "    pc.delete_index(index_name)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "05707670",
-      "metadata": {},
-      "source": [
-        "We define a `spec` object to define the cloud region we'd like to create an index within. You can find a list of all [available providers and regions here](https://docs.pinecone.io/docs/projects)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "8ebeab38",
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "from pinecone import ServerlessSpec\n",
-        "\n",
-        "cloud = os.environ.get('PINECONE_CLOUD') or 'aws'\n",
-        "region = os.environ.get('PINECONE_REGION') or 'us-east-1'\n",
-        "\n",
-        "spec = ServerlessSpec(cloud=cloud, region=region)"
+        "if pc.has_index(name=index_name):\n",
+        "    pc.delete_index(name=index_name)"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
-      "id": "94LRI2H8Ch2B",
+      "id": "786a88df",
       "metadata": {
-        "id": "94LRI2H8Ch2B",
-        "papermill": {
-          "duration": 0.021764,
-          "end_time": "2021-04-16T15:08:50.446400",
-          "exception": false,
-          "start_time": "2021-04-16T15:08:50.424636",
-          "status": "completed"
-        },
-        "tags": []
+        "id": "786a88df"
       },
       "source": [
-        "Creating a Pinecone Index."
+        "### Creating a Pinecone Index\n",
+        "\n",
+        "When creating the index we need to define several configuration properties.\n",
+        "\n",
+        "- `name` can be anything we like. The name is used as an identifier for the index when performing other operations such as `describe_index`, `delete_index`, and so on.\n",
+        "- `metric` specifies the similarity metric that will be used later when you make queries to the index.\n",
+        "- `dimension` should correspond to the dimension of the dense vectors produced by your embedding model. In this quick start, we are using made-up data so a small value is simplest.\n",
+        "- `spec` holds a specification which tells Pinecone how you would like to deploy our index. You can find a list of all [available providers and regions here](https://docs.pinecone.io/docs/projects).\n",
+        "\n",
+        "There are more configurations available, but this minimal set will get us started."
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 5,
+      "execution_count": 6,
       "id": "4YwC8livCrn2",
       "metadata": {
         "execution": {
@@ -272,27 +281,59 @@
           "start_time": "2021-04-16T15:08:50.467779",
           "status": "completed"
         },
-        "tags": []
+        "tags": [],
+        "outputId": "5de1d905-2c7a-425e-8c30-60fc84c2e5b7",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "{\n",
+              "    \"name\": \"hello-pinecone\",\n",
+              "    \"metric\": \"cosine\",\n",
+              "    \"host\": \"hello-pinecone-rjeaip3.svc.aped-4627-b74a.pinecone.io\",\n",
+              "    \"spec\": {\n",
+              "        \"serverless\": {\n",
+              "            \"cloud\": \"aws\",\n",
+              "            \"region\": \"us-east-1\"\n",
+              "        }\n",
+              "    },\n",
+              "    \"status\": {\n",
+              "        \"ready\": true,\n",
+              "        \"state\": \"Ready\"\n",
+              "    },\n",
+              "    \"vector_type\": \"dense\",\n",
+              "    \"dimension\": 3,\n",
+              "    \"deletion_protection\": \"disabled\",\n",
+              "    \"tags\": null\n",
+              "}"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 6
+        }
+      ],
       "source": [
-        "import time\n",
+        "from pinecone import ServerlessSpec, CloudProvider, AwsRegion, Metric\n",
         "\n",
-        "dimensions = 3\n",
         "pc.create_index(\n",
         "    name=index_name,\n",
-        "    dimension=dimensions,\n",
-        "    metric=\"cosine\"\n",
-        ")\n",
-        "\n",
-        "# wait for index to be ready before connecting\n",
-        "while not pc.describe_index(index_name).status['ready']:\n",
-        "    time.sleep(1)"
+        "    metric=Metric.COSINE,\n",
+        "    dimension=3,\n",
+        "    spec=ServerlessSpec(\n",
+        "        cloud=CloudProvider.AWS,\n",
+        "        region=AwsRegion.US_EAST_1\n",
+        "    )\n",
+        ")"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 6,
+      "execution_count": 7,
       "id": "toy-VhU4LO_O",
       "metadata": {
         "execution": {
@@ -313,11 +354,10 @@
       },
       "outputs": [],
       "source": [
-        "index = pc.Index(index_name=index_name)"
+        "index = pc.Index(name=index_name)"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "j1F8SLx6C2HH",
       "metadata": {
@@ -337,12 +377,12 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 7,
+      "execution_count": 8,
       "id": "indirect-lafayette",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 112
+          "height": 125
         },
         "execution": {
           "iopub.execute_input": "2021-04-16T15:09:05.206498Z",
@@ -351,7 +391,7 @@
           "shell.execute_reply": "2021-04-16T15:09:05.403743Z"
         },
         "id": "indirect-lafayette",
-        "outputId": "5bd49b0e-0187-4de2-e564-1d41c61b7bc9",
+        "outputId": "45d4e1c9-0364-4440-9d2d-23db95b74339",
         "papermill": {
           "duration": 0.227373,
           "end_time": "2021-04-16T15:09:05.404700",
@@ -363,9 +403,17 @@
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
+            "text/plain": [
+              "  id           vector\n",
+              "0  A  [1.0, 1.0, 1.0]\n",
+              "1  B  [1.0, 2.0, 3.0]"
+            ],
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-c392925a-8c2b-4f49-ae9f-34a02d371937\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -400,17 +448,280 @@
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
-              "</div>"
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c392925a-8c2b-4f49-ae9f-34a02d371937')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-c392925a-8c2b-4f49-ae9f-34a02d371937 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-c392925a-8c2b-4f49-ae9f-34a02d371937');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-5433f1a8-2218-43d4-8e0c-ca9dc5119930\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5433f1a8-2218-43d4-8e0c-ca9dc5119930')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-5433f1a8-2218-43d4-8e0c-ca9dc5119930 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_d3b238c9-ce87-4958-a184-2b61b563ccf7\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_d3b238c9-ce87-4958-a184-2b61b563ccf7 button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ],
-            "text/plain": [
-              "  id           vector\n",
-              "0  A  [1.0, 1.0, 1.0]\n",
-              "1  B  [1.0, 2.0, 3.0]"
-            ]
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 2,\n  \"fields\": [\n    {\n      \"column\": \"id\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"B\",\n          \"A\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"vector\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
           },
-          "execution_count": 7,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 8
         }
       ],
       "source": [
@@ -425,7 +736,6 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "oiJKXWxoDjhK",
       "metadata": {
@@ -445,7 +755,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": 9,
       "id": "efficient-parliament",
       "metadata": {
         "colab": {
@@ -458,7 +768,7 @@
           "shell.execute_reply": "2021-04-16T15:09:06.179012Z"
         },
         "id": "efficient-parliament",
-        "outputId": "0d9fbac4-4f8a-421e-95a9-0f441d2dcc16",
+        "outputId": "d85df98f-9f86-40de-e545-d62d6ad1c13c",
         "papermill": {
           "duration": 0.704503,
           "end_time": "2021-04-16T15:09:06.180549",
@@ -470,23 +780,26 @@
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'upserted_count': 2}"
             ]
           },
-          "execution_count": 8,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 9
         }
       ],
       "source": [
-        "index.upsert(vectors=zip(df.id, df.vector))  # insert vectors"
+        "# insert vectors\n",
+        "index.upsert(\n",
+        "    vectors=zip(df.id, df.vector)\n",
+        ")"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 9,
+      "execution_count": 13,
       "id": "enclosed-performer",
       "metadata": {
         "colab": {
@@ -499,7 +812,7 @@
           "shell.execute_reply": "2021-04-16T15:09:06.351713Z"
         },
         "id": "enclosed-performer",
-        "outputId": "5b67ec13-6863-4b1a-ac45-b57c569923ee",
+        "outputId": "8ede74dc-8ad2-4954-910b-eba701b7090a",
         "papermill": {
           "duration": 0.140473,
           "end_time": "2021-04-16T15:09:06.352169",
@@ -511,17 +824,19 @@
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'dimension': 3,\n",
               " 'index_fullness': 0.0,\n",
+              " 'metric': 'cosine',\n",
               " 'namespaces': {'': {'vector_count': 2}},\n",
-              " 'total_vector_count': 2}"
+              " 'total_vector_count': 2,\n",
+              " 'vector_type': 'dense'}"
             ]
           },
-          "execution_count": 9,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 13
         }
       ],
       "source": [
@@ -530,7 +845,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 11,
+      "execution_count": 14,
       "id": "leading-shape",
       "metadata": {
         "colab": {
@@ -543,7 +858,7 @@
           "shell.execute_reply": "2021-04-16T15:09:08.563202Z"
         },
         "id": "leading-shape",
-        "outputId": "fb512e95-ebf4-4e1d-b9c7-74afc3cdd0c2",
+        "outputId": "f3440980-cb64-48bf-e5fd-7b15bf0171da",
         "papermill": {
           "duration": 2.177493,
           "end_time": "2021-04-16T15:09:08.564594",
@@ -555,27 +870,28 @@
       },
       "outputs": [
         {
+          "output_type": "execute_result",
           "data": {
             "text/plain": [
               "{'matches': [{'id': 'A', 'score': 1.0, 'values': [1.0, 1.0, 1.0]}],\n",
-              " 'namespace': ''}"
+              " 'namespace': '',\n",
+              " 'usage': {'read_units': 6}}"
             ]
           },
-          "execution_count": 11,
           "metadata": {},
-          "output_type": "execute_result"
+          "execution_count": 14
         }
       ],
       "source": [
+        "# returns top_k matches\n",
         "index.query(\n",
         "    vector=[2., 2., 2.],\n",
         "    top_k=1,\n",
         "    include_values=True\n",
-        ") # returns top_k matches"
+        ")"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "z5jcU5_SLMFC",
       "metadata": {
@@ -596,7 +912,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 12,
+      "execution_count": 15,
       "id": "indian-broadcast",
       "metadata": {
         "execution": {
@@ -617,14 +933,15 @@
       },
       "outputs": [],
       "source": [
-        "pc.delete_index(index_name)"
+        "pc.delete_index(name=index_name)"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "id": "e84d82ee",
-      "metadata": {},
+      "metadata": {
+        "id": "e84d82ee"
+      },
       "source": [
         "---"
       ]
@@ -649,7 +966,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.12"
+      "version": "3.9.6"
     },
     "papermill": {
       "default_parameters": {},
@@ -666,4 +983,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}
\ No newline at end of file