{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define requirement boto3 clients"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import boto3\n",
    "\n",
    "sm_client = boto3.client(service_name=\"sagemaker\")\n",
    "runtime_sm_client = boto3.client(service_name=\"sagemaker-runtime\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define endpoint name\n",
    "\n",
    "This endpoint is previously deployed and ready to test. Change the name here if you want to test your own endpoint."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "endpoint_name = \"<YOUR_ENDPOINT_NAME_HERE>\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define input data\n",
    "\n",
    "The data here is consistent with the sample endpoint above. If you deployed with different dataset, copy the Data Wrangler input data here instead"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "payload_str = '5,166.0,72.0,19.0,175.0,25.8,0.587,51'\n",
    "payload = payload_str.encode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = runtime_sm_client.invoke_endpoint(\n",
    "    EndpointName=endpoint_name,\n",
    "    ContentType=\"text/csv\",\n",
    "#     Accept=\"text/csv\",\n",
    "    Body=payload,\n",
    ")\n",
    "response[\"Body\"].read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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