感谢指出问题。我能够重现延迟。
看起来我们在解析json值上花费了过多的时间，这是我们可以改进的地方(我认为通过避免重复工作，尽管还没有深入研究过)。感谢引起我们的注意。
之前的运行统计概要。

附带的cprofile文件。

7    0.001    0.000   39.557    5.651 python3.11/sit
e-packages/langchain_core/language_models/chat_models.py:771(_agenerate_with_cache)
        1    0.011    0.011   39.537   39.537 python3.11/sit
e-packages/langchain_core/language_models/chat_models.py:79(generate_from_stream)
     4013    0.014    0.000   39.525    0.010 langchain_core/outputs/chat_generation.py:83(__add__)
     4013    0.023    0.000   39.413    0.010 langchain_core/messages/ai.py:232(__add__)
12050/8035    0.022    0.000   39.381    0.005 pydantic/v1/main.py:332(__init__)
12050/8035    0.139    0.000   39.360    0.005 pydantic/v1/main.py:1030(validate_model)
     4016    0.008    0.000   39.300    0.010 langchain_core/messages/ai.py:78(__init__)
     4016    0.007    0.000   39.292    0.010 langchain_core/messages/base.py:57(__init__)
     4015    0.014    0.000   38.904    0.010 langchain_core/messages/ai.py:178(init_tool_calls)
     4014   11.357    0.003   38.890    0.010 langchain_core/utils/json.py:44(parse_partial_json)
  2158964    2.544    0.000   27.532    0.000 python3.11/json/__init__.py:299(loads)
  2158964    1.206    0.000   21.431    0.000 python3.11/json/decoder.py:332(decode)
  2158964   16.069    0.000   19.615    0.000 /U

profiles.tgz
重现脚本：

import asyncio
import cProfile
import io
import pstats
from datetime import datetime
from typing import Literal

from langchain.tools import tool
from langchain_core.messages import HumanMessage
from langchain_openai import ChatOpenAI

from langgraph.graph import END, MessageGraph
from pyinstrument import Profiler

@tool
def file_saver(text: str) -> str:
    """Persist the given string to disk"""
    pass

model = ChatOpenAI(
    model="gpt-4o",
    streaming=True,
    temperature=0.1,
)

tools = [file_saver]
model = model.bind_tools(tools)

def get_agent_executor():
    def should_continue(messages):
        print(f"{datetime.now()}: Starting should_continue")
        return "end"

    async def call_model(messages):
        response = await model.ainvoke(messages)
        return response

    workflow = MessageGraph()

    workflow.add_node("agent", call_model)

    workflow.set_entry_point("agent")

    workflow.add_conditional_edges(
        "agent",
        should_continue,
        {
            "end": END,
        },
    )
    return workflow.compile()

agent_executor = get_agent_executor()

messages = [
    HumanMessage(
        content="Think of a ballad with 300 verses and save it"
        " to a file. Do not print it to me first. At the end of the poem, sign it as 's.b. Anonymous'."
        " You must write every line, do not skip."
    )
]

async def run():
    saw_cme = False
    py_profiler = None
    cprofiler = None
    evs = None
    async for event in agent_executor.astream_events(messages, version="v1"):
        kind = event["event"]
        if saw_cme:
            continue
        if kind == "on_chat_model_stream":
            if tc := event["data"]["chunk"].additional_kwargs.get("tool_calls"):
                if "Anonymous" in str(tc[0]["function"]):
                    if py_profiler:
                        py_profiler.stop()
                    py_profiler = Profiler(interval=0.0001, async_mode="disabled")
                    py_profiler.start()
                    if cprofiler:
                        cprofiler.disable()
                    cprofiler = cProfile.Profile()
                    cprofiler.enable()

        if kind == "on_chat_model_end":
            saw_cme = True
            if py_profiler:
                py_profiler.stop()
                py_profiler.write_html("profile.html", show_all=True)
                cprofiler.disable()
                s = io.StringIO()
                ps = pstats.Stats(cprofiler, stream=s).sort_stats(
                    pstats.SortKey.CUMULATIVE
                )
                ps.print_stats()
                with open("profile.txt", "w") as f:
                    f.write(s.getvalue())
            else:
                print("No profiling data")
            print(evs)
        evs = f"{datetime.now()}: Received event: {kind}"
        if kind == "on_chat_model_end":
            print(evs)

asyncio.run(run())

将要转移到langchain repo,但由于底层问题仍然存在。将向团队报告。