fleet-memory/memora-clients/python/models/search_response.py
Nicolò Boschi c82fff949b add profiles
2025-11-13 13:22:27 +01:00

117 lines
3.7 KiB
Python

from __future__ import annotations
from collections.abc import Mapping
from typing import TYPE_CHECKING, Any, TypeVar, cast
from attrs import define as _attrs_define
from attrs import field as _attrs_field
from ..types import UNSET, Unset
if TYPE_CHECKING:
from ..models.search_response_trace_type_0 import SearchResponseTraceType0
from ..models.search_result import SearchResult
T = TypeVar("T", bound="SearchResponse")
@_attrs_define
class SearchResponse:
"""Response model for search endpoints.
Example:
{'results': [{'activation': 0.95, 'context': 'work info', 'event_date': '2024-01-15T10:30:00Z', 'id':
'123e4567-e89b-12d3-a456-426614174000', 'text': 'Alice works at Google on the AI team', 'type': 'world'}],
'trace': {'num_results': 1, 'query': 'What did Alice say about machine learning?', 'time_seconds': 0.123}}
Attributes:
results (list[SearchResult]):
trace (None | SearchResponseTraceType0 | Unset):
"""
results: list[SearchResult]
trace: None | SearchResponseTraceType0 | Unset = UNSET
additional_properties: dict[str, Any] = _attrs_field(init=False, factory=dict)
def to_dict(self) -> dict[str, Any]:
from ..models.search_response_trace_type_0 import SearchResponseTraceType0
results = []
for results_item_data in self.results:
results_item = results_item_data.to_dict()
results.append(results_item)
trace: dict[str, Any] | None | Unset
if isinstance(self.trace, Unset):
trace = UNSET
elif isinstance(self.trace, SearchResponseTraceType0):
trace = self.trace.to_dict()
else:
trace = self.trace
field_dict: dict[str, Any] = {}
field_dict.update(self.additional_properties)
field_dict.update(
{
"results": results,
}
)
if trace is not UNSET:
field_dict["trace"] = trace
return field_dict
@classmethod
def from_dict(cls: type[T], src_dict: Mapping[str, Any]) -> T:
from ..models.search_response_trace_type_0 import SearchResponseTraceType0
from ..models.search_result import SearchResult
d = dict(src_dict)
results = []
_results = d.pop("results")
for results_item_data in _results:
results_item = SearchResult.from_dict(results_item_data)
results.append(results_item)
def _parse_trace(data: object) -> None | SearchResponseTraceType0 | Unset:
if data is None:
return data
if isinstance(data, Unset):
return data
try:
if not isinstance(data, dict):
raise TypeError()
trace_type_0 = SearchResponseTraceType0.from_dict(data)
return trace_type_0
except (TypeError, ValueError, AttributeError, KeyError):
pass
return cast(None | SearchResponseTraceType0 | Unset, data)
trace = _parse_trace(d.pop("trace", UNSET))
search_response = cls(
results=results,
trace=trace,
)
search_response.additional_properties = d
return search_response
@property
def additional_keys(self) -> list[str]:
return list(self.additional_properties.keys())
def __getitem__(self, key: str) -> Any:
return self.additional_properties[key]
def __setitem__(self, key: str, value: Any) -> None:
self.additional_properties[key] = value
def __delitem__(self, key: str) -> None:
del self.additional_properties[key]
def __contains__(self, key: str) -> bool:
return key in self.additional_properties