chore: import upstream snapshot with attribution

This commit is contained in:
wehub-resource-sync
2026-07-13 12:47:42 +08:00
commit be3ef883e1
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# Copyright 2025-present the zvec project
#
# 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.
from __future__ import annotations
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING
from ..model.doc import Doc, DocList
if TYPE_CHECKING:
from ..model.schema import FieldSchema, VectorSchema
class RerankFunction(ABC):
"""Abstract base class for reranker parameter containers.
Subclasses define rerank parameters and implement _to_cpp_params()
for conversion to C++ parameter structs (used by collection fast path).
Each subclass also provides a standalone rerank() implementation.
"""
def _to_cpp_params(self):
"""Return C++ reranker params. Override in subclasses that use C++ path."""
raise NotImplementedError
@abstractmethod
def rerank(
self,
query_results: list[list[Doc]],
topn: int = 10,
*,
fields: list[FieldSchema | VectorSchema] | None = None,
) -> DocList:
"""Execute rerank on sub-query results.
Args:
query_results: List of per-sub-query document lists.
topn: Maximum number of results to return.
fields: Per-sub-query Python FieldSchema/VectorSchema objects
(required for WeightedReRanker score normalization).
Returns:
Re-ranked document list.
"""
...