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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.") | |