fix: rebrand

notebooks/community/matching_engine/matching_engine_for_indexing.ipynb

@@ -24,7 +24,6 @@
       ]
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@@ -50,11 +49,10 @@
         "      Open in Vertex AI Workbench\n",
         "    </a>\n",
         "  </td>                                                                                               \n",
-        "</table>"
+        "</table>\n"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "tvgnzT1CKxrO"
@@ -62,11 +60,10 @@
       "source": [
         "## Overview\n",
         "\n",
-        "This example demonstrates how to use Vertex AI Matching Engine. It is a high scale, low latency solution, to find similar vectors (or more specifically \"embeddings\") for a large corpus. Moreover, it is a fully managed offering, further reducing operational overhead. It is built upon [Approximate Nearest Neighbor (ANN) technology](https://ai.googleblog.com/2020/07/announcing-scann-efficient-vector.html) developed by Google Research."
+        "This example demonstrates how to use Vertex AI Vector Search. It is a high scale, low latency solution, to find similar vectors (or more specifically \"embeddings\") for a large corpus. Moreover, it is a fully managed offering, further reducing operational overhead. It is built upon [Approximate Nearest Neighbor (ANN) technology](https://ai.googleblog.com/2020/07/announcing-scann-efficient-vector.html) developed by Google Research."
       ]
     },
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       "cell_type": "markdown",
       "metadata": {
         "id": "56e5f9699c6c"
@@ -78,16 +75,15 @@
         "\n",
         "The steps performed include:\n",
         "\n",
-        "* Create a Vertex AI Matching Engine Index and Brute Force Index\n",
+        "* Create a Vertex AI Vector Search Index and Brute Force Index\n",
         "* Create an IndexEndpoint with VPC Network\n",
-        "* Deploy a Vertex AI Matching Engine Index and Brute Force Index\n",
+        "* Deploy a Vertex AI Vector Search Index and Brute Force Index\n",
         "* Perform online queries\n",
         "* Submit batch queries\n",
         "* Compute recall metric"
       ]
     },
     {
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       "cell_type": "markdown",
       "metadata": {
         "id": "0aaef374550b"
@@ -99,7 +95,6 @@
       ]
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         "id": "5e2eba58ad71"
@@ -120,7 +115,6 @@
       ]
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@@ -142,7 +136,6 @@
       ]
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         "id": "4700b0e39c5d"
@@ -165,7 +158,6 @@
       ]
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@@ -221,7 +213,6 @@
       ]
     },
     {
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         "id": "249da91c1011"
@@ -250,7 +241,6 @@
       ]
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         "id": "3fbfae3ff12a"
@@ -261,7 +251,7 @@
         "You can also change the `REGION` variable used by Vertex AI. Learn more about [Vertex AI regions](https://cloud.google.com/vertex-ai/docs/general/locations).\n",
         "* **WARNING:** \n",
         "    *  **Make sure to [choose a region where Vertex AI services are available](https://cloud.google.com/vertex-ai/docs/general/locations#available_regions).**\n",
-        "    *  **If you use Vertex Workbench, the Notebook instance needs to be in the same region where your Vertex AI Matching Engine is deployed.** (for example, if you set `REGION = \"us-central1\"` as same as the tutorial, the notebook instance has to be in `us-central1`)."
+        "    *  **If you use Vertex Workbench, the Notebook instance needs to be in the same region where your Vertex AI Vector Search is deployed.** (for example, if you set `REGION = \"us-central1\"` as same as the tutorial, the notebook instance has to be in `us-central1`)."
       ]
     },
     {
@@ -279,7 +269,6 @@
       ]
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         "id": "60c5a0f69ad8"
@@ -291,7 +280,6 @@
       ]
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         "id": "d118c95af93f"
@@ -302,7 +290,6 @@
       ]
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@@ -323,7 +310,6 @@
       ]
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         "id": "5097f3233d53"
@@ -345,7 +331,6 @@
       ]
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@@ -356,7 +341,6 @@
       ]
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@@ -364,10 +348,10 @@
       "source": [
         "### Prepare a VPC network\n",
         "\n",
-        "To reduce any network overhead that might lead to unnecessary increase in overhead latency, it is best to call the Vertex AI Matching Engine endpoints from your VPC via a direct [VPC Peering](https://cloud.google.com/vertex-ai/docs/general/vpc-peering) connection. The following section describes how to setup a VPC Peering connection if you don't have one. This is a one-time initial setup task. You can also reuse existing VPC network and skip this section.\n",
+        "To reduce any network overhead that might lead to unnecessary increase in overhead latency, it is best to call the Vertex AI Vector Search endpoints from your VPC via a direct [VPC Peering](https://cloud.google.com/vertex-ai/docs/general/vpc-peering) connection. The following section describes how to setup a VPC Peering connection if you don't have one. This is a one-time initial setup task. You can also reuse existing VPC network and skip this section.\n",
         "\n",
         "* **WARNING:** The match service gRPC API (to create online queries against your deployed index) has to be executed in a Google Cloud Notebook instance that is created with the following requirements:\n",
-        "    * **Make sure you select the VPC network you created for Vertex AI Matching Engine service** (instead of using the \"default\" one). That is, you will have to create the VPC network below and then create a new notebook instance that uses that VPC.  \n",
+        "    * **Make sure you select the VPC network you created for Vertex AI Vector Search service** (instead of using the \"default\" one). That is, you will have to create the VPC network below and then create a new notebook instance that uses that VPC.  \n",
         "    * If you run it in the colab or a Google Cloud Notebook instance in a different VPC network or region, the gRPC API will fail to peer the network (InactiveRPCError)."
       ]
     },
@@ -408,7 +392,6 @@
       ]
     },
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@@ -430,7 +413,6 @@
       ]
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@@ -661,7 +643,6 @@
       ]
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@@ -706,7 +687,6 @@
       ]
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@@ -716,13 +696,12 @@
       ]
     },
     {
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       "cell_type": "markdown",
       "metadata": {
         "id": "qhIBCQ7dDSbW"
       },
       "source": [
-        "### Create Vertex AI Matching Engine index (for production usage)"
+        "### Create Vertex AI Vector Search index (for production usage)"
       ]
     },
     {
@@ -739,7 +718,6 @@
       ]
     },
     {
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@@ -762,13 +740,12 @@
       ]
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     {
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       },
       "source": [
-        "#### Create the Vertex AI Matching Engine index configuration\n",
+        "#### Create the Vertex AI Vector Search index configuration\n",
         "\n",
         "Please read the [documentation](https://cloud.google.com/vertex-ai/docs/matching-engine/configuring-indexes) to understand the various configuration parameters that can be used to tune the index"
       ]
@@ -810,7 +787,7 @@
         "\n",
         "matching_engine_index = {\n",
         "    \"display_name\": DISPLAY_NAME,\n",
-        "    \"description\": \"Glove 100 Vertex AI Matching Engine Index\",\n",
+        "    \"description\": \"Glove 100 Vertex AI Vector Search Index\",\n",
         "    \"metadata\": struct_pb2.Value(struct_value=metadata),\n",
         "}"
       ]
@@ -859,7 +836,6 @@
       ]
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       "metadata": {
         "id": "kSsqZuyoA1SG"
@@ -949,7 +925,6 @@
       ]
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       "metadata": {
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@@ -1020,7 +995,7 @@
         "matching_engine_index = {\n",
         "    \"name\": INDEX_RESOURCE_NAME,\n",
         "    \"display_name\": DISPLAY_NAME,\n",
-        "    \"description\": \"Glove 100 Vertex AI Matching Engine Index\",\n",
+        "    \"description\": \"Glove 100 Vertex AI Vector Search Index\",\n",
         "    \"metadata\": struct_pb2.Value(struct_value=metadata),\n",
         "}"
       ]
@@ -1067,7 +1042,6 @@
       ]
     },
     {
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       "metadata": {
         "id": "qV2xjAnDDObD"
@@ -1152,7 +1126,6 @@
       ]
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         "id": "np2cgVuuIe9k"
@@ -1162,13 +1135,12 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "8Ew1UgcIIiJG"
       },
       "source": [
-        "### Deploy a Vertex AI Matching Engine index"
+        "### Deploy a Vertex AI Vector Search index"
       ]
     },
     {
@@ -1198,7 +1170,6 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "cb6d956d7419"
@@ -1249,7 +1220,6 @@
       ]
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@@ -1326,7 +1296,6 @@
       ]
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@@ -1528,7 +1497,6 @@
       ]
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         "id": "8wXTSgz1Bl0x"
@@ -1699,7 +1667,6 @@
       ]
     },
     {
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       "cell_type": "markdown",
       "metadata": {
         "id": "_mNwdU9_B_Ez"
@@ -1964,7 +1931,6 @@
       ]
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         "id": "_mNwdU9_B_Ez"
@@ -1972,7 +1938,7 @@
       "source": [
         "### Compute the recall metric\n",
         "\n",
-        "Use the deployed brute force index as the ground truth to calculate the recall of the Vertex AI Matching Engine index:"
+        "Use the deployed brute force index as the ground truth to calculate the recall of the Vertex AI Vector Search index:"
       ]
     },
     {
@@ -2003,21 +1969,20 @@
         "# This will take 5-10 min\n",
         "\n",
         "recall = sum(\n",
-        "    [\n",
+        "    \n",
         "        len(\n",
         "            set(get_neighbors(test[i], DEPLOYED_BRUTE_FORCE_INDEX_ID)).intersection(\n",
         "                set(get_neighbors(test[i], DEPLOYED_INDEX_ID))\n",
         "            )\n",
         "        )\n",
         "        for i in range(len(test))\n",
-        "    ]\n",
+        "    \n",
         ") / (1.0 * len(test) * k)\n",
         "\n",
         "print(\"Recall: {}\".format(recall))"
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "TpV-iwP9qw9c"
@@ -2032,13 +1997,12 @@
       ]
     },
     {
-      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "390c331dc7d9"
       },
       "source": [
-        "### Delete the Vertex AI Matching Engine resources"
+        "### Delete the Vertex AI Vector Search resources"
       ]
     },
     {
@@ -2065,7 +2029,6 @@
       ]
     },
     {
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       "cell_type": "markdown",
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