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    " <h2 style=\"color:#900;\">MAIL SUBJECT CREATION -</h2>\n",
    "\n",
    "<table style=\"margin: 0; text-align: left;\">\n",
    "    <tr>\n",
    "        <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
    "            <img src=\"../../important.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
    "        </td>\n",
    "        <td>\n",
    "            <h3 style=\"color:#900;\">Write something that will take the contents of an email, and will suggest an appropriate short subject line for the email. That's the kind of feature that might be built into a commercial email tool.</h3>\n",
    "        </td>\n",
    "    </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "76822a8b-d6e0-4dd9-a801-2d34bd104b7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports\n",
    "\n",
    "import os\n",
    "import requests\n",
    "from dotenv import load_dotenv\n",
    "from openai import OpenAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1a9de873-d24b-42fb-8f4a-a08f429050f5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "API key found and looks good so far!\n"
     ]
    }
   ],
   "source": [
    "load_dotenv(override=True)\n",
    "api_key = os.getenv('OPENAI_API_KEY')\n",
    "\n",
    "# Check the key\n",
    "\n",
    "if not api_key:\n",
    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
    "elif not api_key.startswith(\"sk-proj-\"):\n",
    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
    "elif api_key.strip() != api_key:\n",
    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
    "else:\n",
    "    print(\"API key found and looks good so far!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "122af5d6-4727-4229-b85a-ea5246ff540c",
   "metadata": {},
   "outputs": [],
   "source": [
    "openai = OpenAI()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b9a2c2c2-ac10-4019-aeef-2bfe6cc7b1f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Subject: Missing API Logs for June 22nd: Scheduled Meeting to Address Issue\n"
     ]
    }
   ],
   "source": [
    "system_prompt = \"You are an assistant which can generate a subject line as output by taking email of content as input. Subject line should be self explanatrory\"\n",
    "user_prompt = \"\"\"\n",
    " Below is the content of the text which I am giving as input\n",
    " Mail Content - 'Hi Team,\n",
    "\n",
    "We have observed that the API logs for June 22nd between 6:00 AM and 12:00 PM are missing in Kibana.\n",
    "\n",
    "The SA team has confirmed that there were no errors reported on their end during this period.\n",
    "\n",
    "The DevOps team has verified that logs were being sent as expected.\n",
    "\n",
    "Upon checking the Fluentd pods, no errors were found.\n",
    "\n",
    "Logs were being shipped to td-agent as usual.\n",
    "\n",
    "No configuration changes or pod restarts were detected.\n",
    "\n",
    "We have also confirmed that no code changes were deployed from our side during this time.\n",
    "\n",
    "Bucket: api_application_log\n",
    "Ticket\n",
    "\n",
    "We have scheduled a meeting with the SA and DevOps teams to restore the missing logs, as they are critical for our weekly report and analysis.'\n",
    "\"\"\"\n",
    "\n",
    "# Step 2: Make the messages list\n",
    "\n",
    "messages = [  {\"role\": \"system\", \"content\": system_prompt},\n",
    "        {\"role\": \"user\", \"content\": user_prompt}] # fill this in\n",
    "\n",
    "# Step 3: Call OpenAI\n",
    "\n",
    "response = openai.chat.completions.create(\n",
    "        model = \"gpt-4o-mini\",\n",
    "        messages = messages\n",
    "    )\n",
    "\n",
    "# Step 4: print the result\n",
    "\n",
    "print(response.choices[0].message.content)"
   ]
  }
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