Source code for camel.datasets.models
# ========= 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 typing import Any, Dict, Optional
from pydantic import BaseModel, Field
[docs]
class DataPoint(BaseModel):
r"""A single data point in the dataset.
Attributes:
question (str): The primary question or issue to be addressed.
final_answer (str): The final answer.
rationale (Optional[str]): Logical reasoning or explanation behind the
answer. (default: :obj:`None`)
metadata Optional[Dict[str, Any]]: Additional metadata about the data
point. (default: :obj:`None`)
"""
question: str = Field(
..., description="The primary question or issue to be addressed."
)
final_answer: str = Field(..., description="The final answer.")
rationale: Optional[str] = Field(
default=None,
description="Logical reasoning or explanation behind the answer.",
)
metadata: Optional[Dict[str, Any]] = Field(
default=None, description="Additional metadata about the data point."
)
[docs]
def to_dict(self) -> Dict[str, Any]:
r"""Convert DataPoint to a dictionary.
Returns:
Dict[str, Any]: Dictionary representation of the DataPoint.
"""
return self.dict()
[docs]
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> 'DataPoint':
r"""Create a DataPoint from a dictionary.
Args:
data (Dict[str, Any]): Dictionary containing DataPoint fields.
Returns:
DataPoint: New DataPoint instance.
"""
return cls(**data)