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   "source": [
    "# PromptLayer OpenAI\n",
    "\n",
    "`PromptLayer` is the first platform that allows you to track, manage, and share your GPT prompt engineering. `PromptLayer` acts a middleware between your code and `OpenAI’s` python library.\n",
    "\n",
    "`PromptLayer` records all your `OpenAI API` requests, allowing you to search and explore request history in the `PromptLayer` dashboard.\n",
    "\n",
    "\n",
    "This example showcases how to connect to [PromptLayer](https://www.promptlayer.com) to start recording your OpenAI requests.\n",
    "\n",
    "Another example is [here](https://python.langchain.com/en/latest/ecosystem/promptlayer.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a45943e",
   "metadata": {},
   "source": [
    "## Install PromptLayer\n",
    "The `promptlayer` package is required to use PromptLayer with OpenAI. Install `promptlayer` using pip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "metadata": {
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   "source": [
    "!pip install promptlayer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "536c1dfa",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c16da3b5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from langchain.llms import PromptLayerOpenAI\n",
    "import promptlayer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8564ce7d",
   "metadata": {},
   "source": [
    "## Set the Environment API Key\n",
    "You can create a PromptLayer API Key at [www.promptlayer.com](https://www.promptlayer.com) by clicking the settings cog in the navbar.\n",
    "\n",
    "Set it as an environment variable called `PROMPTLAYER_API_KEY`.\n",
    "\n",
    "You also need an OpenAI Key, called `OPENAI_API_KEY`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1df96674-a9fb-4126-bb87-541082782240",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      " ········\n"
     ]
    }
   ],
   "source": [
    "from getpass import getpass\n",
    "\n",
    "PROMPTLAYER_API_KEY = getpass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "46ba25dc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "os.environ[\"PROMPTLAYER_API_KEY\"] = PROMPTLAYER_API_KEY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9aa68c46-4d88-45ba-8a83-18fa41b4daed",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      " ········\n"
     ]
    }
   ],
   "source": [
    "from getpass import getpass\n",
    "\n",
    "OPENAI_API_KEY = getpass()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6023b6fa-d9db-49d6-b713-0e19686119b0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf0294de",
   "metadata": {},
   "source": [
    "## Use the PromptLayerOpenAI LLM like normal\n",
    "*You can optionally pass in `pl_tags` to track your requests with PromptLayer's tagging feature.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3acf0069",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "llm = PromptLayerOpenAI(pl_tags=[\"langchain\"])\n",
    "llm(\"I am a cat and I want\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2d76826",
   "metadata": {},
   "source": [
    "**The above request should now appear on your [PromptLayer dashboard](https://www.promptlayer.com).**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05e9e2fe",
   "metadata": {},
   "source": [
    "## Using PromptLayer Track\n",
    "If you would like to use any of the [PromptLayer tracking features](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9), you need to pass the argument `return_pl_id` when instantializing the PromptLayer LLM to get the request id.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a7315b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "llm = PromptLayerOpenAI(return_pl_id=True)\n",
    "llm_results = llm.generate([\"Tell me a joke\"])\n",
    "\n",
    "for res in llm_results.generations:\n",
    "    pl_request_id = res[0].generation_info[\"pl_request_id\"]\n",
    "    promptlayer.track.score(request_id=pl_request_id, score=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7eb19139",
   "metadata": {},
   "source": [
    "Using this allows you to track the performance of your model in the PromptLayer dashboard. If you are using a prompt template, you can attach a template to a request as well.\n",
    "Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard."
   ]
  }
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