langchain/docs/modules/models/chat/integrations/anthropic.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# Anthropic\n",
    "\n",
    "This notebook covers how to get started with Anthropic chat models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d4a7c55d-b235-4ca4-a579-c90cc9570da9",
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    "tags": []
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   "source": [
    "from langchain.chat_models import ChatAnthropic\n",
    "from langchain.prompts.chat import (\n",
    "    ChatPromptTemplate,\n",
    "    SystemMessagePromptTemplate,\n",
    "    AIMessagePromptTemplate,\n",
    "    HumanMessagePromptTemplate,\n",
    ")\n",
    "from langchain.schema import (\n",
    "    AIMessage,\n",
    "    HumanMessage,\n",
    "    SystemMessage\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70cf04e8-423a-4ff6-8b09-f11fb711c817",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "chat = ChatAnthropic()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8199ef8f-eb8b-4253-9ea0-6c24a013ca4c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content=\" J'adore programmer.\", additional_kwargs={})"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages = [\n",
    "    HumanMessage(content=\"Translate this sentence from English to French. I love programming.\")\n",
    "]\n",
    "chat(messages)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c361ab1e-8c0c-4206-9e3c-9d1424a12b9c",
   "metadata": {},
   "source": [
    "## `ChatAnthropic` also supports async and streaming functionality:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "93a21c5c-6ef9-4688-be60-b2e1f94842fb",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain.callbacks.base import CallbackManager\n",
    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LLMResult(generations=[[ChatGeneration(text=\" J'aime programmer.\", generation_info=None, message=AIMessage(content=\" J'aime programmer.\", additional_kwargs={}))]], llm_output={})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "await chat.agenerate([messages])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "025be980-e50d-4a68-93dc-c9c7b500ce34",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " J'aime la programmation."
     ]
    },
    {
     "data": {
      "text/plain": [
       "AIMessage(content=\" J'aime la programmation.\", additional_kwargs={})"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat = ChatAnthropic(streaming=True, verbose=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]))\n",
    "chat(messages)"
   ]
  }
 ],
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