chore: import upstream snapshot with attribution

This commit is contained in:
wehub-resource-sync
2026-07-13 12:47:42 +08:00
commit be3ef883e1
1214 changed files with 431743 additions and 0 deletions
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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 .constants import DenseVectorType, SparseVectorType, VectorType
__all__ = ["DenseVectorType", "SparseVectorType", "VectorType"]
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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 typing import Optional, TypeVar, Union
import numpy as np
# VectorType: DenseVectorType | SparseVectorType
DenseVectorType = Union[list[float], list[int], np.ndarray]
SparseVectorType = dict[int, float]
VectorType = Optional[Union[DenseVectorType, SparseVectorType]]
# Embeddable: Text | Image | Audio
TEXT = str
IMAGE = Union[str, bytes, np.ndarray] # file path, raw bytes, or numpy array
AUDIO = Union[str, bytes, np.ndarray] # file path, raw bytes, or numpy array
Embeddable = Optional[Union[TEXT, IMAGE, AUDIO]]
# Multimodal Embeddable
MD = TypeVar("MD", bound=Embeddable, contravariant=True)