{
 "cells": [
  {
   "cell_type": "raw",
   "id": "602a52a4",
   "metadata": {},
   "source": [
    "---\n",
    "sidebar_label: Anthropic\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9597802c",
   "metadata": {},
   "source": [
    "# AnthropicLLM\n",
    "\n",
    "This example goes over how to use LangChain to interact with `Anthropic` models.\n",
    "\n",
    "NOTE: AnthropicLLM only supports legacy Claude 2 models. To use the newest Claude 3 models, please use [`ChatAnthropic`](/docs/integrations/chat/anthropic) instead.\n",
    "\n",
    "## Installation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59c710c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install -qU langchain-anthropic"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560a2f9254963fd7",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Environment Setup\n",
    "\n",
    "We'll need to get an [Anthropic](https://console.anthropic.com/settings/keys) API key and set the `ANTHROPIC_API_KEY` environment variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "035dea0f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "os.environ[\"ANTHROPIC_API_KEY\"] = getpass()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1891df96eb076e1a",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "98f70927a87e4745",
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nLangChain is a decentralized blockchain network that leverages AI and machine learning to provide language translation services.'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain_anthropic import AnthropicLLM\n",
    "from langchain_core.prompts import PromptTemplate\n",
    "\n",
    "template = \"\"\"Question: {question}\n",
    "\n",
    "Answer: Let's think step by step.\"\"\"\n",
    "\n",
    "prompt = PromptTemplate.from_template(template)\n",
    "\n",
    "model = AnthropicLLM(model=\"claude-2.1\")\n",
    "\n",
    "chain = prompt | model\n",
    "\n",
    "chain.invoke({\"question\": \"What is LangChain?\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a52f765c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.11.1 64-bit",
   "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"
  },
  "vscode": {
   "interpreter": {
    "hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}