from langchain.agents import create_agent

def get_weather(city: str) -> str:
    """获取指定城市的天气"""
    return f"{city} 天气总是晴朗！"

agent = create_agent(
    model="anthropic:claude-sonnet-4-5",
    tools=[get_weather],
    system_prompt="你是一个乐于助人的助手",
)

# 执行代理
agent.invoke(
    {"messages": [{"role": "user", "content": "旧金山天气如何？"}]}
)

• 在 Python 开发中，使用 LangChain 时，执行上述代码时，出现如下错误信息

D:\PythonCode\LangChainTest\.venv\Scripts\python.exe D:\PythonCode\LangChainTest\main.py 
D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\_api\deprecation.py:26: UserWarning: Core Pydantic V1 functionality isn't compatible with Python 3.14 or greater.
  from pydantic.v1.fields import FieldInfo as FieldInfoV1
Traceback (most recent call last):
  File "D:\PythonCode\LangChainTest\main.py", line 14, in <module>
    agent.invoke(
    ~~~~~~~~~~~~^
        {"messages": [{"role": "user", "content": "旧金山天气如何？"}]}
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\pregel\main.py", line 3068, in invoke
    for chunk in self.stream(
                 ~~~~~~~~~~~^
        input,
        ^^^^^^
    ...<10 lines>...
        **kwargs,
        ^^^^^^^^^
    ):
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\pregel\main.py", line 2643, in stream
    for _ in runner.tick(
             ~~~~~~~~~~~^
        [t for t in loop.tasks.values() if not t.writes],
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<2 lines>...
        schedule_task=loop.accept_push,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ):
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\pregel\_runner.py", line 167, in tick
    run_with_retry(
    ~~~~~~~~~~~~~~^
        t,
        ^^
    ...<10 lines>...
        },
        ^^
    )
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\pregel\_retry.py", line 42, in run_with_retry
    return task.proc.invoke(task.input, config)
           ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\_internal\_runnable.py", line 656, in invoke
    input = context.run(step.invoke, input, config, **kwargs)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langgraph\_internal\_runnable.py", line 400, in invoke
    ret = self.func(*args, **kwargs)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain\agents\factory.py", line 1131, in model_node
    response = _execute_model_sync(request)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain\agents\factory.py", line 1102, in _execute_model_sync
    output = model_.invoke(messages)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\runnables\base.py", line 5548, in invoke
    return self.bound.invoke(
           ~~~~~~~~~~~~~~~~~^
        input,
        ^^^^^^
        self._merge_configs(config),
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        **{**self.kwargs, **kwargs},
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\language_models\chat_models.py", line 398, in invoke
    self.generate_prompt(
    ~~~~~~~~~~~~~~~~~~~~^
        [self._convert_input(input)],
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    ...<6 lines>...
        **kwargs,
        ^^^^^^^^^
    ).generations[0][0],
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\language_models\chat_models.py", line 1117, in generate_prompt
    return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)
           ~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\language_models\chat_models.py", line 927, in generate
    self._generate_with_cache(
    ~~~~~~~~~~~~~~~~~~~~~~~~~^
        m,
        ^^
    ...<2 lines>...
        **kwargs,
        ^^^^^^^^^
    )
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_core\language_models\chat_models.py", line 1221, in _generate_with_cache
    result = self._generate(
        messages, stop=stop, run_manager=run_manager, **kwargs
    )
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_anthropic\chat_models.py", line 1915, in _generate
    data = self._create(payload)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\langchain_anthropic\chat_models.py", line 1777, in _create
    return self._client.messages.create(**payload)
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_utils\_utils.py", line 282, in wrapper
    return func(*args, **kwargs)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\resources\messages\messages.py", line 930, in create
    return self._post(
           ~~~~~~~~~~^
        "/v1/messages",
        ^^^^^^^^^^^^^^^
    ...<26 lines>...
        stream_cls=Stream[RawMessageStreamEvent],
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_base_client.py", line 1326, in post
    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
                           ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_base_client.py", line 1035, in request
    request = self._build_request(options, retries_taken=retries_taken)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_base_client.py", line 506, in _build_request
    headers = self._build_headers(options, retries_taken=retries_taken)
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_base_client.py", line 447, in _build_headers
    self._validate_headers(headers_dict, custom_headers)
    ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\PythonCode\LangChainTest\.venv\Lib\site-packages\anthropic\_client.py", line 200, in _validate_headers
    raise TypeError(
        '"Could not resolve authentication method. Expected either api_key or auth_token to be set. Or for one of the `X-Api-Key` or `Authorization` headers to be explicitly omitted"'
    )
TypeError: "Could not resolve authentication method. Expected either api_key or auth_token to be set. Or for one of the `X-Api-Key` or `Authorization` headers to be explicitly omitted"
During task with name 'model' and id '9c34258b-c90f-d21b-f23b-504e5fe2b3f1'

Process finished with exit code 1

问题原因

• 需要设置一个 Claude（Anthropic）账户并获取 API 密钥