108 lines
3.3 KiB
Python
108 lines
3.3 KiB
Python
from __future__ import annotations
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from collections.abc import Mapping
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from typing import TYPE_CHECKING, Any, TypeVar, cast
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from attrs import define as _attrs_define
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from attrs import field as _attrs_field
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from ..types import UNSET, Unset
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if TYPE_CHECKING:
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from ..models.think_fact import ThinkFact
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T = TypeVar("T", bound="ThinkResponse")
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@_attrs_define
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class ThinkResponse:
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"""Response model for think endpoint.
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Example:
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{'based_on': [{'activation': 0.9, 'id': '123', 'text': 'AI is used in healthcare', 'type': 'world'},
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{'activation': 0.85, 'id': '456', 'text': 'I discussed AI applications last week', 'type': 'agent'}],
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'new_opinions': ['AI has great potential when used responsibly'], 'text': 'Based on my understanding, AI is a
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transformative technology...'}
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Attributes:
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text (str):
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based_on (list[ThinkFact] | Unset):
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new_opinions (list[str] | Unset):
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"""
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text: str
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based_on: list[ThinkFact] | Unset = UNSET
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new_opinions: list[str] | Unset = UNSET
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additional_properties: dict[str, Any] = _attrs_field(init=False, factory=dict)
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def to_dict(self) -> dict[str, Any]:
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text = self.text
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based_on: list[dict[str, Any]] | Unset = UNSET
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if not isinstance(self.based_on, Unset):
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based_on = []
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for based_on_item_data in self.based_on:
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based_on_item = based_on_item_data.to_dict()
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based_on.append(based_on_item)
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new_opinions: list[str] | Unset = UNSET
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if not isinstance(self.new_opinions, Unset):
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new_opinions = self.new_opinions
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field_dict: dict[str, Any] = {}
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field_dict.update(self.additional_properties)
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field_dict.update(
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{
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"text": text,
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}
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)
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if based_on is not UNSET:
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field_dict["based_on"] = based_on
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if new_opinions is not UNSET:
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field_dict["new_opinions"] = new_opinions
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return field_dict
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@classmethod
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def from_dict(cls: type[T], src_dict: Mapping[str, Any]) -> T:
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from ..models.think_fact import ThinkFact
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d = dict(src_dict)
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text = d.pop("text")
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_based_on = d.pop("based_on", UNSET)
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based_on: list[ThinkFact] | Unset = UNSET
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if _based_on is not UNSET:
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based_on = []
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for based_on_item_data in _based_on:
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based_on_item = ThinkFact.from_dict(based_on_item_data)
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based_on.append(based_on_item)
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new_opinions = cast(list[str], d.pop("new_opinions", UNSET))
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think_response = cls(
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text=text,
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based_on=based_on,
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new_opinions=new_opinions,
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)
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think_response.additional_properties = d
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return think_response
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@property
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def additional_keys(self) -> list[str]:
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return list(self.additional_properties.keys())
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def __getitem__(self, key: str) -> Any:
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return self.additional_properties[key]
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def __setitem__(self, key: str, value: Any) -> None:
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self.additional_properties[key] = value
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def __delitem__(self, key: str) -> None:
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del self.additional_properties[key]
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def __contains__(self, key: str) -> bool:
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return key in self.additional_properties
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