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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
from __future__ import annotations
import inspect
import json
from typing import Callable, Type, Union
from pydantic import BaseModel, create_model
def get_pydantic_model(
input_data: Union[str, Type[BaseModel], Callable],
) -> Type[BaseModel]:
r"""A multi-purpose function that can be used as a normal function,
a class decorator, or a function decorator.
Args:
input_data (Union[str, type, Callable]):
- If a string is provided, it should be a JSON-encoded string
that will be converted into a BaseModel.
- If a function is provided, it will be decorated such that
its arguments are converted into a BaseModel.
- If a BaseModel class is provided, it will be returned directly.
Returns:
Type[BaseModel]: The BaseModel class that will be used to
structure the input data.
"""
if isinstance(input_data, str):
data_dict = json.loads(input_data)
TemporaryModel = create_model( # type: ignore[call-overload]
"TemporaryModel",
**{key: (type(value), None) for key, value in data_dict.items()},
)
return TemporaryModel(**data_dict).__class__
elif callable(input_data):
WrapperClass = create_model( # type: ignore[call-overload]
f"{input_data.__name__.capitalize()}Model",
**{
name: (param.annotation, ...)
for name, param in inspect.signature(
input_data
).parameters.items()
},
)
return WrapperClass
if issubclass(input_data, BaseModel):
return input_data
raise ValueError("Invalid input data provided.")
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