{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "959300d4",
   "metadata": {},
   "source": [
    "# PromptLayer ChatOpenAI\n",
    "\n",
    ">[PromptLayer](https://docs.promptlayer.com/what-is-promptlayer/wxpF9EZkUwvdkwvVE9XEvC/how-promptlayer-works/dvgGSxNe6nB1jj8mUVbG8r) \n",
    "> is a devtool that allows you to track, manage, and share your GPT prompt engineering. \n",
    "> It acts as a middleware between your code and OpenAI's python library, recording all your API requests \n",
    "> and saving relevant metadata for easy exploration and search in the [PromptLayer](https://www.promptlayer.com) dashboard."
   ]
  },
  {
   "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,
   "id": "dbe09bd8",
   "metadata": {
    "vscode": {
     "languageId": "powershell"
    }
   },
   "outputs": [],
   "source": [
    "pip install promptlayer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "536c1dfa",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c16da3b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from langchain.chat_models import PromptLayerChatOpenAI\n",
    "from langchain.schema import HumanMessage"
   ]
  },
  {
   "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`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "46ba25dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ[\"PROMPTLAYER_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": 4,
   "id": "3acf0069",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='to take a nap in a cozy spot. I search around for a suitable place and finally settle on a soft cushion on the window sill. I curl up into a ball and close my eyes, relishing the warmth of the sun on my fur. As I drift off to sleep, I can hear the birds chirping outside and feel the gentle breeze blowing through the window. This is the life of a contented cat.', additional_kwargs={})"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat = PromptLayerChatOpenAI(pl_tags=[\"langchain\"])\n",
    "chat([HumanMessage(content=\"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": []
  },
  {
   "cell_type": "markdown",
   "id": "c43803d1",
   "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": "b7d4db01",
   "metadata": {},
   "outputs": [],
   "source": [
    "chat = PromptLayerChatOpenAI(return_pl_id=True)\n",
    "chat_results = chat.generate([[HumanMessage(content=\"I am a cat and I want\")]])\n",
    "\n",
    "for res in chat_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": "13e56507",
   "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."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "vscode": {
   "interpreter": {
    "hash": "8a5edab282632443219e051e4ade2d1d5bbc671c781051bf1437897cbdfea0f1"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}