chore: delete the connection requirement in llm (#330)

Author: ashleyxuu

notebooks/generative_ai/bq_dataframes_llm_code_generation.ipynb

@@ -370,83 +370,6 @@
         "This section walks through a few steps required in order to use the model in your notebook."
       ]
     },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "rS4VO1TGiO4G"
-      },
-      "source": [
-        "## Create a BigQuery Cloud resource connection\n",
-        "\n",
-        "You need to create a [Cloud resource connection](https://cloud.google.com/bigquery/docs/create-cloud-resource-connection) to enable BigQuery DataFrames to interact with Vertex AI services."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "KFPjDM4LVh96"
-      },
-      "outputs": [],
-      "source": [
-        "CONN_NAME = \"bqdf-llm\"\n",
-        "\n",
-        "client = bq_connection.ConnectionServiceClient()\n",
-        "new_conn_parent = f\"projects/{PROJECT_ID}/locations/{REGION}\"\n",
-        "exists_conn_parent = f\"projects/{PROJECT_ID}/locations/{REGION}/connections/{CONN_NAME}\"\n",
-        "cloud_resource_properties = bq_connection.CloudResourceProperties({})\n",
-        "\n",
-        "try:\n",
-        "    request = client.get_connection(\n",
-        "        request=bq_connection.GetConnectionRequest(name=exists_conn_parent)\n",
-        "    )\n",
-        "    CONN_SERVICE_ACCOUNT = f\"serviceAccount:{request.cloud_resource.service_account_id}\"\n",
-        "except Exception:\n",
-        "    connection = bq_connection.types.Connection(\n",
-        "        {\"friendly_name\": CONN_NAME, \"cloud_resource\": cloud_resource_properties}\n",
-        "    )\n",
-        "    request = bq_connection.CreateConnectionRequest(\n",
-        "        {\n",
-        "            \"parent\": new_conn_parent,\n",
-        "            \"connection_id\": CONN_NAME,\n",
-        "            \"connection\": connection,\n",
-        "        }\n",
-        "    )\n",
-        "    response = client.create_connection(request)\n",
-        "    CONN_SERVICE_ACCOUNT = (\n",
-        "        f\"serviceAccount:{response.cloud_resource.service_account_id}\"\n",
-        "    )\n",
-        "print(CONN_SERVICE_ACCOUNT)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "W6l6Ol2biU9h"
-      },
-      "source": [
-        "## Set permissions for the service account\n",
-        "\n",
-        "The resource connection service account requires certain project-level permissions:\n",
-        " - `roles/aiplatform.user` and `roles/bigquery.connectionUser`: These roles are required for the connection to create a model definition using the LLM model in Vertex AI ([documentation](https://cloud.google.com/bigquery/docs/generate-text#give_the_service_account_access)).\n",
-        " - `roles/run.invoker`: This role is required for the connection to have read-only access to Cloud Run services that back custom/remote functions ([documentation](https://cloud.google.com/bigquery/docs/remote-functions#grant_permission_on_function)).\n",
-        "\n",
-        "Set these permissions by running the following `gcloud` commands:"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "d8wja24SVq6s"
-      },
-      "outputs": [],
-      "source": [
-        "!gcloud projects add-iam-policy-binding {PROJECT_ID} --condition=None --no-user-output-enabled --member={CONN_SERVICE_ACCOUNT} --role='roles/bigquery.connectionUser'\n",
-        "!gcloud projects add-iam-policy-binding {PROJECT_ID} --condition=None --no-user-output-enabled --member={CONN_SERVICE_ACCOUNT} --role='roles/aiplatform.user'\n",
-        "!gcloud projects add-iam-policy-binding {PROJECT_ID} --condition=None --no-user-output-enabled --member={CONN_SERVICE_ACCOUNT} --role='roles/run.invoker'"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -468,9 +391,7 @@
       "source": [
         "from bigframes.ml.llm import PaLM2TextGenerator\n",
         "\n",
-        "session = bf.get_global_session()\n",
-        "connection = f\"{PROJECT_ID}.{REGION}.{CONN_NAME}\"\n",
-        "model = PaLM2TextGenerator(session=session, connection_name=connection)"
+        "model = PaLM2TextGenerator()"
       ]
     },
     {
@@ -651,7 +572,7 @@
       },
       "outputs": [],
       "source": [
-        "@bf.remote_function([str], str, bigquery_connection=CONN_NAME)\n",
+        "@bf.remote_function([str], str)\n",
         "def extract_code(text: str):\n",
         "  try:\n",
         "    res = text[text.find('\\n')+1:text.find('```', 3)]\n",