docs[minor]: Add how to guide for rate limiting a chat model (#24686)

Add how-to guide for rate limiting a chat model.

docs/docs/how_to/chat_model_rate_limiting.ipynb

@@ -0,0 +1,146 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "dcf87b32",
+   "metadata": {},
+   "source": [
+    "# How to handle rate limits\n",
+    "\n",
+    ":::info Prerequisites\n",
+    "\n",
+    "This guide assumes familiarity with the following concepts:\n",
+    "- [Chat models](/docs/concepts/#chat-models)\n",
+    "- [LLMs](/docs/concepts/#llms)\n",
+    ":::\n",
+    "\n",
+    "\n",
+    "You may find yourself in a situation where you are getting rate limited by the model provider API because you're making too many requests.\n",
+    "\n",
+    "For example, this might happen if you are running many parallel queries to benchmark the chat model on a test dataset.\n",
+    "\n",
+    "If you are facing such a situation, you can use a rate limiter to help match the rate at which you're making request to the rate allowed\n",
+    "by the API.\n",
+    "\n",
+    ":::info Requires ``langchain-core >= 0.2.24``\n",
+    "\n",
+    "This functionality was added in ``langchain-core == 0.2.24``. Please make sure your package is up to date.\n",
+    ":::"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cbc3c873-6109-4e03-b775-b73c1003faea",
+   "metadata": {},
+   "source": [
+    "## Initialize a rate limiter\n",
+    "\n",
+    "Langchain comes with a built-in in memory rate limiter. This rate limiter is thread safe and can be shared by multiple threads in the same process.\n",
+    "\n",
+    "The provided rate limiter can only limit the number of requests per unit time. It will not help if you need to also limited based on the size\n",
+    "of the requests."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "aa9c3c8c-0464-4190-a8c5-d69d173505a6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_core.rate_limiters import InMemoryRateLimiter\n",
+    "\n",
+    "rate_limiter = InMemoryRateLimiter(\n",
+    "    requests_per_second=0.1,  # <-- Super slow! We can only make a request once every 10 seconds!!\n",
+    "    check_every_n_seconds=0.1,  # Wake up every 100 ms to check whether allowed to make a request,\n",
+    "    max_bucket_size=10,  # Controls the maximum burst size.\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8e058bde-9413-4b08-8cc6-0c9cb638f19f",
+   "metadata": {},
+   "source": [
+    "## Choose a model\n",
+    "\n",
+    "Choose any model and pass to it the rate_limiter via the `rate_limiter` attribute."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0f880a3a-c047-4e94-a323-fff2a4c0e96d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import time\n",
+    "from getpass import getpass\n",
+    "\n",
+    "if \"ANTHROPIC_API_KEY\" not in os.environ:\n",
+    "    os.environ[\"ANTHROPIC_API_KEY\"] = getpass()\n",
+    "\n",
+    "\n",
+    "from langchain_anthropic import ChatAnthropic\n",
+    "\n",
+    "model = ChatAnthropic(model_name=\"claude-3-opus-20240229\", rate_limiter=rate_limiter)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "80c9ab3a-299a-460f-985c-90280a046f52",
+   "metadata": {},
+   "source": [
+    "Let's confirm that the rate limiter works. We should only be able to invoke the model once per 10 seconds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d074265c-9f32-4c5f-b914-944148993c4d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "11.599073648452759\n",
+      "10.7502121925354\n",
+      "10.244257926940918\n",
+      "8.83088755607605\n",
+      "11.645203590393066\n"
+     ]
+    }
+   ],
+   "source": [
+    "for _ in range(5):\n",
+    "    tic = time.time()\n",
+    "    model.invoke(\"hello\")\n",
+    "    toc = time.time()\n",
+    "    print(toc - tic)"
+   ]
+  }
+ ],
+ "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

docs/docs/how_to/index.mdx

@@ -83,6 +83,7 @@ These are the core building blocks you can use when building applications.
 - [How to: track response metadata across providers](/docs/how_to/response_metadata)
 - [How to: use chat model to call tools](/docs/how_to/tool_calling)
 - [How to: stream tool calls](/docs/how_to/tool_streaming)
+- [How to: handle rate limits](/docs/how_to/chat_model_rate_limiting)
 - [How to: few shot prompt tool behavior](/docs/how_to/tools_few_shot)
 - [How to: bind model-specific formatted tools](/docs/how_to/tools_model_specific)
 - [How to: force a specific tool call](/docs/how_to/tool_choice)