ComponentsChat models🚅 LiteLLMOn this page🚅 LiteLLMLiteLLM is a library that simplifies calling Anthropic, Azure, Huggingface, Replicate, etc. This notebook covers how to get started with using Langchain + the LiteLLM I/O library. from langchain.chat_models import ChatLiteLLMfrom langchain.prompts.chat import (    ChatPromptTemplate,    SystemMessagePromptTemplate,    AIMessagePromptTemplate,    HumanMessagePromptTemplate,)from langchain.schema import AIMessage, HumanMessage, SystemMessagechat = ChatLiteLLM(model="gpt-3.5-turbo")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)ChatLiteLLM also supports async and streaming functionality:​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 = ChatLiteLLM(    streaming=True,    verbose=True,    callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),)chat(messages)     J'aime la programmation.    AIMessage(content=" J'aime la programmation.", additional_kwargs={}, example=False)PreviousKonkoNextLlama APIChatLiteLLM also supports async and streaming functionality: