langchain/docs/versioned_docs/version-0.2.x/integrations/llms/anthropic.ipynb

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    "---\n",
    "sidebar_label: Anthropic\n",
    "---"
   ]
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   "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"
   ]
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   "source": [
    "%pip install -qU langchain-anthropic"
   ]
  },
  {
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    "collapsed": false
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   "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:"
   ]
  },
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   "execution_count": 4,
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   "source": [
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "os.environ[\"ANTHROPIC_API_KEY\"] = getpass()"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Usage"
   ]
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    {
     "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"
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   ],
   "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",
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