Adding Docs for `PromptLayerCallbackHandler`
diff --git a/docs/extras/modules/callbacks/integrations/promptlayer.ipynb b/docs/extras/modules/callbacks/integrations/promptlayer.ipynb
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+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# PromptLayer\n",
+    "\n",
+    "![PromptLayer](https://promptlayer.com/text_logo.png)\n",
+    "\n",
+    "[PromptLayer](https://promptlayer.com) is a an LLM observability platform that lets you visualize requests, version prompts, and track usage. In this guide we will go over how to setup the `PromptLayerCallbackHandler`. \n",
+    "\n",
+    "While PromptLayer does have LLMs that integrate directly with LangChain (eg [`PromptLayerOpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/promptlayer_openai)), this callback is the recommended way to integrate PromptLayer with LangChain.\n",
+    "\n",
+    "See [our docs](https://docs.promptlayer.com/languages/langchain) for more information."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Installation and Setup"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install promptlayer --upgrade"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Getting API Credentials\n",
+    "\n",
+    "If you do not have a PromptLayer account, create one on [promptlayer.com](https://www.promptlayer.com). Then get an API key by clicking on the settings cog in the navbar and\n",
+    "set it as an environment variabled called `PROMPTLAYER_API_KEY`\n"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Usage\n",
+    "\n",
+    "Getting started with `PromptLayerCallbackHandler` is fairly simple, it takes two optional arguments:\n",
+    "1. `pl_tags` - an optional list of strings that will be tracked as tags on PromptLayer.\n",
+    "2. `pl_id_callback` - an optional function that will take `promptlayer_request_id` as an argument. This ID can be used with all of PromptLayer's tracking features to track, metadata, scores, and prompt usage."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Simple OpenAI Example\n",
+    "\n",
+    "In this simple example we use `PromptLayerCallbackHandler` with `ChatOpenAI`. We add a PromptLayer tag named `chatopenai`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import promptlayer  # Don't forget this 🍰\n",
+    "from langchain.callbacks import PromptLayerCallbackHandler\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema import (\n",
+    "    HumanMessage,\n",
+    ")\n",
+    "\n",
+    "chat_llm = ChatOpenAI(\n",
+    "    temperature=0,\n",
+    "    callbacks=[PromptLayerCallbackHandler(pl_tags=[\"chatopenai\"])],\n",
+    ")\n",
+    "llm_results = chat_llm(\n",
+    "    [\n",
+    "        HumanMessage(content=\"What comes after 1,2,3 ?\"),\n",
+    "        HumanMessage(content=\"Tell me another joke?\"),\n",
+    "    ]\n",
+    ")\n",
+    "print(llm_results)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### GPT4All Example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import promptlayer  # Don't forget this 🍰\n",
+    "from langchain.callbacks import PromptLayerCallbackHandler\n",
+    "\n",
+    "from langchain.llms import GPT4All\n",
+    "\n",
+    "model = GPT4All(model=\"./models/gpt4all-model.bin\", n_ctx=512, n_threads=8)\n",
+    "\n",
+    "response = model(\n",
+    "    \"Once upon a time, \",\n",
+    "    callbacks=[PromptLayerCallbackHandler(pl_tags=[\"langchain\", \"gpt4all\"])],\n",
+    ")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Full Featured Example\n",
+    "\n",
+    "In this example we unlock more of the power of PromptLayer.\n",
+    "\n",
+    "PromptLayer allows you to visually create, version, and track prompt templates. Using the [Prompt Registry](https://docs.promptlayer.com/features/prompt-registry), we can programatically fetch the prompt template called `example`.\n",
+    "\n",
+    "We also define a `pl_id_callback` function which takes in the `promptlayer_request_id` and logs a score, metadata and links the prompt template used. Read more about tracking on [our docs](https://docs.promptlayer.com/features/prompt-history/request-id)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import promptlayer  # Don't forget this 🍰\n",
+    "from langchain.callbacks import PromptLayerCallbackHandler\n",
+    "from langchain.llms import OpenAI\n",
+    "\n",
+    "\n",
+    "def pl_id_callback(promptlayer_request_id):\n",
+    "    print(\"prompt layer id \", promptlayer_request_id)\n",
+    "    promptlayer.track.score(\n",
+    "        request_id=promptlayer_request_id, score=100\n",
+    "    )  # score is an integer 0-100\n",
+    "    promptlayer.track.metadata(\n",
+    "        request_id=promptlayer_request_id, metadata={\"foo\": \"bar\"}\n",
+    "    )  # metadata is a dictionary of key value pairs that is tracked on PromptLayer\n",
+    "    promptlayer.track.prompt(\n",
+    "        request_id=promptlayer_request_id,\n",
+    "        prompt_name=\"example\",\n",
+    "        prompt_input_variables={\"product\": \"toasters\"},\n",
+    "        version=1,\n",
+    "    )  # link the request to a prompt template\n",
+    "\n",
+    "\n",
+    "openai_llm = OpenAI(\n",
+    "    model_name=\"text-davinci-002\",\n",
+    "    callbacks=[PromptLayerCallbackHandler(pl_id_callback=pl_id_callback)],\n",
+    ")\n",
+    "\n",
+    "example_prompt = promptlayer.prompts.get(\"example\", version=1, langchain=True)\n",
+    "openai_llm(example_prompt.format(product=\"toasters\"))"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That is all it takes! After setup all your requests will show up on the PromptLayer dashboard.\n",
+    "This callback also works with any LLM implemented on LangChain."
+   ]
+  }
+ ],
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+}

@baskaryan
Here I am adding documentation for the `PromptLayerCallbackHandler`.
When we created the initial PR for the callback handler the docs were causing issues, so we merged without the docs.