@validate_call 是一个功能强大的装饰器,用来验证函数的输入参数是否符合预期类型。例如,我们可以确保传递给函数的参数符合指定的数据类型: from pydantic import validate_call @validate_call def greet(name: str, age: int): return f"Hello {name}, you are {age} years old!" # 正确调用 print(greet("...
File "D:\venv_dir\Lib\site-packages\pydantic\validate_call_decorator.py", line 60, in wrapper_function return validate_call_wrapper(*args, **kwargs) ^^^ File "D:\venv_dir\Lib\site-packages\pydantic\_internal\_validate_call.py", line 96, in __call__ res = self.__pydantic_validator...
Initial Checks I confirm that I'm using Pydantic V2 installed directly from the main branch, or equivalent Description When wrapping a method in validate_call it alters the assumption that a bound method is equal to itself. Running the e...
Initial Checks I confirm that I'm using Pydantic V2 Description validate_call should catch wrong types being passed to any function/method; however, it breaks when used with parametrized generic methods. A similar issue occurs when gener...
Traceback (most recent call last): File"D:\code\fastapi-main\example\5-14.py", line3,in<module> dragon = Creature( File"C:\Users\xuron\AppData\Roaming\Python\Python310\site-packages\pydantic\main.py", line176,in__init__ self.__pydantic_validator__.validate_python(data, self_instance...
By working through this quiz, you’ll revisit how to work with data schemas with Pydantic’s BaseModel, write custom validators for complex use cases, validate function arguments with Pydantic’s @validate_call, and manage settings and configure applications with pydantic-settings....
("must be startswith 小")returnvclassUser(BaseModel):id:intname:str="小卤蛋"age:intemail:EmailStrsignup_ts:Optional[datetime]=Nonefriends:List[str]=[]validate_fields=field_validator("name")(check_name)@field_validator("age")@classmethoddefcheck_age(cls,age):ifage<18:raiseValueError("用户...
validate_call – a decorator to perform validation when calling a function. Customisation Website:docs.pydantic.dev/latest Support:GitHub Code Repository Developer:Pydantic Services Inc. and individual contributors License:MIT License Pydantic is written in Python. Learn Python with our recommendedfree bo...
# `tool` let you register functions which the LLM may call while responding to a user. # Again, dependencies are carried via `RunContext`, any other arguments become the tool schema passed to the LLM. # Pydantic is used to validate these arguments, and errors are passed back to the LLM...
不要在输出中包含任何额外的信息,只需返回json字符串。你的输出将被使用LLMOutput.model_validate_json建立一个LLMOutput对象 每次输出之进行一步操作,不要在一个输出中包含多个操作。 """ 通过以上方式,ReAct 利用大模型的能力,结合 Python 的强大后端处理,实现了从非结构化文本到结构化数据的转换,提高了信息的可...