Langchain Callback Handler

The following code example demonstrates how to pass a callback handler:

llm = OpenAI(temperature=0)
llm_math = LLMMathChain.from_llm(llm=llm)

@cl.on_message
async def main(message: cl.Message):

    res = await llm_math.acall(message.content, callbacks=[cl.LangchainCallbackHandler()])

    await cl.Message(content="Hello").send()

Final Answer streaming

If streaming is enabled at the LLM level, Langchain will only stream the intermediate steps. You can enable final answer streaming by passing stream_final_answer=True to the callback handler.

# Optionally, you can also pass the prefix tokens that will be used to identify the final answer
answer_prefix_tokens=["FINAL", "ANSWER"]

cl.LangchainCallbackHandler(
        stream_final_answer=True,
        answer_prefix_tokens=answer_prefix_tokens,
    )

Final answer streaming will only work with prompts that have a consistent final answer pattern. It will also not work with AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION

AskElementMessage LlamaIndex Callback Handler

Life Cycle Hooks

Chat

Elements

Ask User

Integrations

Misceallaneous

Input Widgets

Langchain Callback Handler

Final Answer streaming

​Final Answer streaming

Final Answer streaming