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62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, Field
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class DataPoint(BaseModel):
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r"""A single data point in the dataset.
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Attributes:
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question (str): The primary question or issue to be addressed.
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final_answer (str): The final answer.
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rationale (Optional[str]): Logical reasoning or explanation behind the
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answer. (default: :obj:`None`)
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metadata (Optional[Dict[str, Any]]): Additional metadata about the data
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point. (default: :obj:`None`)
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"""
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question: str = Field(
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..., description="The primary question or issue to be addressed."
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)
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final_answer: str = Field(..., description="The final answer.")
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rationale: Optional[str] = Field(
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default=None,
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description="Logical reasoning or explanation behind the answer.",
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)
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metadata: Optional[Dict[str, Any]] = Field(
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default=None, description="Additional metadata about the data point."
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)
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def to_dict(self) -> Dict[str, Any]:
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r"""Convert DataPoint to a dictionary.
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Returns:
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Dict[str, Any]: Dictionary representation of the DataPoint.
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"""
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return self.dict()
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> 'DataPoint':
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r"""Create a DataPoint from a dictionary.
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Args:
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data (Dict[str, Any]): Dictionary containing DataPoint fields.
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Returns:
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DataPoint: New DataPoint instance.
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"""
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return cls(**data)
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