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Anthropic

This notebook covers how to get started with Anthropic chat models.

from langchain.chat_models import ChatAnthropic
from langchain.prompts.chat import (
    ChatPromptTemplate,
    SystemMessagePromptTemplate,
    AIMessagePromptTemplate,
    HumanMessagePromptTemplate,
)
from langchain.schema import AIMessage, HumanMessage, SystemMessage
chat = 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:​

from langchain.callbacks.manager import CallbackManager
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
await 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)
     J'aime la programmation.




    AIMessage(content=" J'aime la programmation.", additional_kwargs={}, example=False)