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38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
from __future__ import annotations
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import abc
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from typing import Any, Dict
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import numpy as np
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class VectorDatabase(abc.ABC):
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@abc.abstractmethod
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async def add_embeddings(
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self,
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collection: str,
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ids: list[str],
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embeddings_list: list[list[float]],
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metadatas: list[dict[str, Any]],
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documents: list[str],
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) -> None:
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"""向指定 collection 添加向量数据。"""
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pass
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@abc.abstractmethod
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async def search(self, collection: str, query_embedding: np.ndarray, k: int = 5) -> Dict[str, Any]:
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"""在指定 collection 中检索最相似的向量。"""
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pass
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@abc.abstractmethod
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async def delete_by_file_id(self, collection: str, file_id: str) -> None:
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"""根据 file_id 删除指定 collection 中的向量。"""
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pass
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@abc.abstractmethod
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async def get_or_create_collection(self, collection: str):
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"""获取或创建 collection。"""
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pass
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@abc.abstractmethod
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async def delete_collection(self, collection: str):
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pass
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