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如何从工具流式传输事件

Prerequisites

本指南假设您熟悉以下概念：

如果您有调用工具的聊天模型、检索器或其他可运行对象，您可能希望访问这些可运行对象的内部事件或使用其他属性配置它们。本指南向您展示如何正确手动传递参数，以便您可以使用astream_events()方法实现这一点。

Compatibility

LangChain 无法自动传播配置，包括 astream_events() 所需的回调，如果您在 python<=3.10 中运行 async 代码，则无法传播到子可运行对象。这是您可能无法看到自定义可运行对象或工具发出事件的常见原因。

如果您正在运行python<=3.10，您将需要在异步环境中手动传播RunnableConfig对象到子可运行对象。有关如何手动传播配置的示例，请参见下面bar RunnableLambda的实现。

如果您正在运行python>=3.11，RunnableConfig将自动传播到异步环境中的子可运行对象。然而，如果您的代码可能在较旧的Python版本中运行，手动传播RunnableConfig仍然是一个好主意。

本指南还需要 langchain-core>=0.2.16。

假设你有一个自定义工具，它调用一个链，通过提示聊天模型只返回10个单词来压缩其输入，然后反转输出。首先，以简单的方式定义它：

pip install -qU langchain-openai
import getpass
import os

if not os.environ.get("OPENAI_API_KEY"):
  os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter API key for OpenAI: ")

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="gpt-4o-mini")
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.tools import tool


@tool
async def special_summarization_tool(long_text: str) -> str:
    """A tool that summarizes input text using advanced techniques."""
    prompt = ChatPromptTemplate.from_template(
        "You are an expert writer. Summarize the following text in 10 words or less:\n\n{long_text}"
    )

    def reverse(x: str):
        return x[::-1]

    chain = prompt | model | StrOutputParser() | reverse
    summary = await chain.ainvoke({"long_text": long_text})
    return summary

直接调用工具效果很好：

LONG_TEXT = """
NARRATOR:
(Black screen with text; The sound of buzzing bees can be heard)
According to all known laws of aviation, there is no way a bee should be able to fly. Its wings are too small to get its fat little body off the ground. The bee, of course, flies anyway because bees don't care what humans think is impossible.
BARRY BENSON:
(Barry is picking out a shirt)
Yellow, black. Yellow, black. Yellow, black. Yellow, black. Ooh, black and yellow! Let's shake it up a little.
JANET BENSON:
Barry! Breakfast is ready!
BARRY:
Coming! Hang on a second.
"""

await special_summarization_tool.ainvoke({"long_text": LONG_TEXT})
'.yad noitaudarg rof tiftuo sesoohc yrraB ;scisyhp seifed eeB'

但如果你想访问聊天模型的原始输出而不是完整的工具，你可能会尝试使用astream_events()方法并寻找一个on_chat_model_end事件。以下是会发生的情况：

stream = special_summarization_tool.astream_events(
    {"long_text": LONG_TEXT}, version="v2"
)

async for event in stream:
    if event["event"] == "on_chat_model_end":
        # Never triggers in python<=3.10!
        print(event)

你会注意到（除非你在python>=3.11中运行本指南），子运行中没有发出聊天模型事件！

这是因为上面的示例没有将工具的配置对象传递到内部链中。要解决这个问题，请重新定义您的工具以接受一个类型为RunnableConfig的特殊参数（有关更多详细信息，请参阅本指南）。在执行时，您还需要将该参数传递到内部链中：

from langchain_core.runnables import RunnableConfig


@tool
async def special_summarization_tool_with_config(
    long_text: str, config: RunnableConfig
) -> str:
    """A tool that summarizes input text using advanced techniques."""
    prompt = ChatPromptTemplate.from_template(
        "You are an expert writer. Summarize the following text in 10 words or less:\n\n{long_text}"
    )

    def reverse(x: str):
        return x[::-1]

    chain = prompt | model | StrOutputParser() | reverse
    # Pass the "config" object as an argument to any executed runnables
    summary = await chain.ainvoke({"long_text": long_text}, config=config)
    return summary
API Reference:RunnableConfig

现在尝试使用你的新工具进行与之前相同的 astream_events() 调用：

stream = special_summarization_tool_with_config.astream_events(
    {"long_text": LONG_TEXT}, version="v2"
)

async for event in stream:
    if event["event"] == "on_chat_model_end":
        print(event)
{'event': 'on_chat_model_end', 'data': {'output': AIMessage(content='Bee defies physics; Barry chooses outfit for graduation day.', response_metadata={'stop_reason': 'end_turn', 'stop_sequence': None}, id='run-d23abc80-0dce-4f74-9d7b-fb98ca4f2a9e', usage_metadata={'input_tokens': 182, 'output_tokens': 16, 'total_tokens': 198}), 'input': {'messages': [[HumanMessage(content="You are an expert writer. Summarize the following text in 10 words or less:\n\n\nNARRATOR:\n(Black screen with text; The sound of buzzing bees can be heard)\nAccording to all known laws of aviation, there is no way a bee should be able to fly. Its wings are too small to get its fat little body off the ground. The bee, of course, flies anyway because bees don't care what humans think is impossible.\nBARRY BENSON:\n(Barry is picking out a shirt)\nYellow, black. Yellow, black. Yellow, black. Yellow, black. Ooh, black and yellow! Let's shake it up a little.\nJANET BENSON:\nBarry! Breakfast is ready!\nBARRY:\nComing! Hang on a second.\n")]]}}, 'run_id': 'd23abc80-0dce-4f74-9d7b-fb98ca4f2a9e', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['f25c41fe-8972-4893-bc40-cecf3922c1fa']}

太棒了！这次有一个事件被触发了。

对于流式处理，astream_events() 如果可能的话，会自动在启用了流式处理的链中调用内部可运行对象，因此如果你想在聊天模型生成令牌时获取令牌流，你可以简单地过滤以查找 on_chat_model_stream 事件，而无需进行其他更改：

stream = special_summarization_tool_with_config.astream_events(
    {"long_text": LONG_TEXT}, version="v2"
)

async for event in stream:
    if event["event"] == "on_chat_model_stream":
        print(event)
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42', usage_metadata={'input_tokens': 182, 'output_tokens': 0, 'total_tokens': 182})}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='Bee', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' def', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='ies physics', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=';', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' Barry', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' cho', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='oses outfit', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' for', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' graduation', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content=' day', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='.', id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42')}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}
{'event': 'on_chat_model_stream', 'data': {'chunk': AIMessageChunk(content='', response_metadata={'stop_reason': 'end_turn', 'stop_sequence': None}, id='run-f24ab147-0b82-4e63-810a-b12bd8d1fb42', usage_metadata={'input_tokens': 0, 'output_tokens': 16, 'total_tokens': 16})}, 'run_id': 'f24ab147-0b82-4e63-810a-b12bd8d1fb42', 'name': 'ChatAnthropic', 'tags': ['seq:step:2'], 'metadata': {'ls_provider': 'anthropic', 'ls_model_name': 'claude-3-5-sonnet-20240620', 'ls_model_type': 'chat', 'ls_temperature': 0.0, 'ls_max_tokens': 1024}, 'parent_ids': ['385f3612-417c-4a70-aae0-cce3a5ba6fb6']}

下一步​

你现在已经了解了如何从工具中流式传输事件。接下来，查看以下指南以获取更多关于使用工具的信息：

你也可以查看一些更具体的工具调用用途：

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