text: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsAnthropicAzureGoogle Cloud Platform Vertex AI PaLMJinaChatLlama APIOpenAIPromptLayer ChatOpenAIDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsChat modelsAnthropicOn this pageAnthropicThis notebook covers how to get started with Anthropic chat models.from langchain.chat_models import ChatAnthropicfrom langchain.prompts.chat import (    ChatPromptTemplate,    SystemMessagePromptTemplate,    AIMessagePromptTemplate,    HumanMessagePromptTemplate,)from langchain.schema import AIMessage, HumanMessage, SystemMessagechat = ChatAnthropic()messages = [    HumanMessage(        content="Translate this sentence from English to French. I love programming."    )]chat(messages)    AIMessage(content=" J'aime la programmation.", additional_kwargs={}, example=False)ChatAnthropic also supports async and streaming functionality:â€‹from langchain.callbacks.manager import CallbackManagerfrom langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandlerawait chat.agenerate([messages])    LLMResult(generations=[[ChatGeneration(text=" J'aime programmer.", generation_info=None, message=AIMessage(content=" J'aime programmer.", additional_kwargs={}, example=False))]], llm_output={}, run=[RunInfo(run_id=UUID('8cc8fb68-1c35-439c-96a0-695036a93652'))])chat = ChatAnthropic(    streaming=True,    verbose=True,    callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),)chat(messages)