and toolkitsMemoryCallbacksChat loadersProvidersMoreArthurArthurArthur is a model monitoring and observability platform.The following guide shows how to run a registered chat LLM with the Arthur callback handler to automatically log model inferences to Arthur.If you do not have a model currently onboarded to Arthur, visit our onboarding guide for generative text models. For more information about how to use the Arthur SDK, visit our docs.from langchain.callbacks import ArthurCallbackHandlerfrom langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandlerfrom langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagePlace Arthur credentials herearthur_url = "https://app.arthur.ai"arthur_login = "your-arthur-login-username-here"arthur_model_id = "your-arthur-model-id-here"Create Langchain LLM with Arthur callback handlerdef make_langchain_chat_llm(chat_model=):    return ChatOpenAI(        streaming=True,        temperature=0.1,        callbacks=[            StreamingStdOutCallbackHandler(),            ArthurCallbackHandler.from_credentials(                arthur_model_id,                 arthur_url=arthur_url,                 arthur_login=arthur_login)        ])chatgpt = make_langchain_chat_llm()    Please enter password for admin: ¬∑¬∑¬∑¬∑¬∑¬∑¬∑¬∑Running the chat LLM with this run function will save the chat history in an ongoing list so that the conversation can reference earlier messages and log each response to the Arthur platform. You can view the history of this model's inferences on your model dashboard page.Enter q to quit the run loopdef run(llm):    history = []    while True:        user_input = input("\n>>> input >>>\n>>>: ")        if user_input == "q":            break        history.append(HumanMessage(content=user_input))        history.append(llm(history))run(chatgpt)        >>> input >>>    >>>: What is a callback handler?    A callback handler, also known as a callback function or callback method, is a piece of
Arthur is a model monitoring and observability platform.
Arthur is a model monitoring and observability platform. ->: and toolkitsMemoryCallbacksChat loadersProvidersMoreArthurArthurArthur is a model monitoring and observability platform.The following guide shows how to run a registered chat LLM with the Arthur callback handler to automatically log model inferences to Arthur.If you do not have a model currently onboarded to Arthur, visit our onboarding guide for generative text models. For more information about how to use the Arthur SDK, visit our docs.from langchain.callbacks import ArthurCallbackHandlerfrom langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandlerfrom langchain.chat_models import ChatOpenAIfrom langchain.schema import HumanMessagePlace Arthur credentials herearthur_url = "https://app.arthur.ai"arthur_login = "your-arthur-login-username-here"arthur_model_id = "your-arthur-model-id-here"Create Langchain LLM with Arthur callback handlerdef make_langchain_chat_llm(chat_model=):    return ChatOpenAI(        streaming=True,        temperature=0.1,        callbacks=[            StreamingStdOutCallbackHandler(),            ArthurCallbackHandler.from_credentials(                arthur_model_id,                 arthur_url=arthur_url,                 arthur_login=arthur_login)        ])chatgpt = make_langchain_chat_llm()    Please enter password for admin: ¬∑¬∑¬∑¬∑¬∑¬∑¬∑¬∑Running the chat LLM with this run function will save the chat history in an ongoing list so that the conversation can reference earlier messages and log each response to the Arthur platform. You can view the history of this model's inferences on your model dashboard page.Enter q to quit the run loopdef run(llm):    history = []    while True:        user_input = input("\n>>> input >>>\n>>>: ")        if user_input == "q":            break        history.append(HumanMessage(content=user_input))        history.append(llm(history))run(chatgpt)        >>> input >>>    >>>: What is a callback handler?    A callback handler, also known as a callback function or callback method, is a piece of