mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-07-23 11:11:01 -05:00
e9ec2c0d2b
* new: update models to 1.18, add create_named_vector and delete_named_vector * fix: add missing strict mode config updates * fix: fix local mode create and delete vector name * new: update turbo quant fields * fix: persist vector deletion
448 lines
13 KiB
Python
448 lines
13 KiB
Python
from typing import Any, Iterable, Mapping, Sequence
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from qdrant_client.conversions import common_types as types
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class QdrantBase:
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def __init__(self, **kwargs: Any):
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pass
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def search_matrix_offsets(
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self,
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collection_name: str,
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query_filter: types.Filter | None = None,
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limit: int = 3,
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sample: int = 10,
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using: str | None = None,
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**kwargs: Any,
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) -> types.SearchMatrixOffsetsResponse:
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raise NotImplementedError()
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def search_matrix_pairs(
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self,
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collection_name: str,
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query_filter: types.Filter | None = None,
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limit: int = 3,
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sample: int = 10,
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using: str | None = None,
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**kwargs: Any,
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) -> types.SearchMatrixPairsResponse:
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raise NotImplementedError()
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def query_batch_points(
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self,
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collection_name: str,
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requests: Sequence[types.QueryRequest],
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**kwargs: Any,
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) -> list[types.QueryResponse]:
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raise NotImplementedError()
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def query_points(
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self,
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collection_name: str,
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query: types.PointId
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| list[float]
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| list[list[float]]
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| types.SparseVector
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| types.Query
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| types.NumpyArray
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| types.Document
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| types.Image
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| types.InferenceObject
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| None = None,
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using: str | None = None,
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prefetch: types.Prefetch | list[types.Prefetch] | None = None,
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query_filter: types.Filter | None = None,
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search_params: types.SearchParams | None = None,
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limit: int = 10,
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offset: int | None = None,
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with_payload: bool | Sequence[str] | types.PayloadSelector = True,
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with_vectors: bool | Sequence[str] = False,
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score_threshold: float | None = None,
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lookup_from: types.LookupLocation | None = None,
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**kwargs: Any,
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) -> types.QueryResponse:
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raise NotImplementedError()
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def query_points_groups(
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self,
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collection_name: str,
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group_by: str,
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query: types.PointId
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| list[float]
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| list[list[float]]
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| types.SparseVector
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| types.Query
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| types.NumpyArray
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| types.Document
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| types.Image
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| types.InferenceObject
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| None = None,
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using: str | None = None,
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prefetch: types.Prefetch | list[types.Prefetch] | None = None,
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query_filter: types.Filter | None = None,
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search_params: types.SearchParams | None = None,
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limit: int = 10,
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group_size: int = 3,
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with_payload: bool | Sequence[str] | types.PayloadSelector = True,
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with_vectors: bool | Sequence[str] = False,
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score_threshold: float | None = None,
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with_lookup: types.WithLookupInterface | None = None,
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lookup_from: types.LookupLocation | None = None,
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**kwargs: Any,
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) -> types.GroupsResult:
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raise NotImplementedError()
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def scroll(
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self,
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collection_name: str,
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scroll_filter: types.Filter | None = None,
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limit: int = 10,
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order_by: types.OrderBy | None = None,
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offset: types.PointId | None = None,
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with_payload: bool | Sequence[str] | types.PayloadSelector = True,
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with_vectors: bool | Sequence[str] = False,
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**kwargs: Any,
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) -> tuple[list[types.Record], types.PointId | None]:
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raise NotImplementedError()
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def count(
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self,
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collection_name: str,
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count_filter: types.Filter | None = None,
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exact: bool = True,
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**kwargs: Any,
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) -> types.CountResult:
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raise NotImplementedError()
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def facet(
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self,
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collection_name: str,
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key: str,
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facet_filter: types.Filter | None = None,
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limit: int = 10,
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exact: bool = False,
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**kwargs: Any,
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) -> types.FacetResponse:
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raise NotImplementedError()
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def upsert(
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self,
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collection_name: str,
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points: types.Points,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def update_vectors(
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self,
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collection_name: str,
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points: Sequence[types.PointVectors],
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def delete_vectors(
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self,
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collection_name: str,
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vectors: Sequence[str],
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points: types.PointsSelector,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def retrieve(
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self,
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collection_name: str,
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ids: Sequence[types.PointId],
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with_payload: bool | Sequence[str] | types.PayloadSelector = True,
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with_vectors: bool | Sequence[str] = False,
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**kwargs: Any,
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) -> list[types.Record]:
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raise NotImplementedError()
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def delete(
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self,
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collection_name: str,
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points_selector: types.PointsSelector,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def set_payload(
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self,
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collection_name: str,
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payload: types.Payload,
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points: types.PointsSelector,
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key: str | None = None,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def overwrite_payload(
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self,
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collection_name: str,
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payload: types.Payload,
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points: types.PointsSelector,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def delete_payload(
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self,
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collection_name: str,
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keys: Sequence[str],
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points: types.PointsSelector,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def clear_payload(
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self,
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collection_name: str,
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points_selector: types.PointsSelector,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def batch_update_points(
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self,
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collection_name: str,
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update_operations: Sequence[types.UpdateOperation],
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**kwargs: Any,
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) -> list[types.UpdateResult]:
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raise NotImplementedError()
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def update_collection_aliases(
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self,
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change_aliases_operations: Sequence[types.AliasOperations],
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def get_collection_aliases(
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self, collection_name: str, **kwargs: Any
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) -> types.CollectionsAliasesResponse:
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raise NotImplementedError()
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def get_aliases(self, **kwargs: Any) -> types.CollectionsAliasesResponse:
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raise NotImplementedError()
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def get_collections(self, **kwargs: Any) -> types.CollectionsResponse:
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raise NotImplementedError()
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def get_collection(self, collection_name: str, **kwargs: Any) -> types.CollectionInfo:
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raise NotImplementedError()
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def collection_exists(self, collection_name: str, **kwargs: Any) -> bool:
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raise NotImplementedError()
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def update_collection(
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self,
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collection_name: str,
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def delete_collection(self, collection_name: str, **kwargs: Any) -> bool:
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raise NotImplementedError()
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def create_collection(
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self,
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collection_name: str,
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vectors_config: types.VectorParams | Mapping[str, types.VectorParams],
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def recreate_collection(
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self,
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collection_name: str,
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vectors_config: types.VectorParams | Mapping[str, types.VectorParams],
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def upload_points(
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self,
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collection_name: str,
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points: Iterable[types.PointStruct],
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**kwargs: Any,
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) -> None:
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raise NotImplementedError()
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def upload_collection(
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self,
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collection_name: str,
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vectors: dict[str, types.NumpyArray] | types.NumpyArray | Iterable[types.VectorStruct],
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payload: Iterable[dict[Any, Any]] | None = None,
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ids: Iterable[types.PointId] | None = None,
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**kwargs: Any,
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) -> None:
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raise NotImplementedError()
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def create_payload_index(
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self,
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collection_name: str,
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field_name: str,
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field_schema: types.PayloadSchemaType | None = None,
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field_type: types.PayloadSchemaType | None = None,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def delete_payload_index(
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self,
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collection_name: str,
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field_name: str,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def create_vector_name(
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self,
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collection_name: str,
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vector_name: str,
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vector_name_config: types.VectorNameConfig,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def delete_vector_name(
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self,
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collection_name: str,
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vector_name: str,
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**kwargs: Any,
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) -> types.UpdateResult:
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raise NotImplementedError()
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def list_snapshots(
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self, collection_name: str, **kwargs: Any
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) -> list[types.SnapshotDescription]:
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raise NotImplementedError()
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def create_snapshot(
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self, collection_name: str, **kwargs: Any
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) -> types.SnapshotDescription | None:
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raise NotImplementedError()
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def delete_snapshot(
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self, collection_name: str, snapshot_name: str, **kwargs: Any
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) -> bool | None:
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raise NotImplementedError()
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def list_full_snapshots(self, **kwargs: Any) -> list[types.SnapshotDescription]:
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raise NotImplementedError()
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def create_full_snapshot(self, **kwargs: Any) -> types.SnapshotDescription | None:
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raise NotImplementedError()
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def delete_full_snapshot(self, snapshot_name: str, **kwargs: Any) -> bool | None:
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raise NotImplementedError()
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def recover_snapshot(
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self,
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collection_name: str,
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location: str,
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**kwargs: Any,
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) -> bool | None:
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raise NotImplementedError()
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def list_shard_snapshots(
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self, collection_name: str, shard_id: int, **kwargs: Any
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) -> list[types.SnapshotDescription]:
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raise NotImplementedError()
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def create_shard_snapshot(
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self, collection_name: str, shard_id: int, **kwargs: Any
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) -> types.SnapshotDescription | None:
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raise NotImplementedError()
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def delete_shard_snapshot(
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self, collection_name: str, shard_id: int, snapshot_name: str, **kwargs: Any
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) -> bool | None:
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raise NotImplementedError()
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def recover_shard_snapshot(
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self,
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collection_name: str,
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shard_id: int,
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location: str,
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**kwargs: Any,
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) -> bool | None:
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raise NotImplementedError()
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def close(self, **kwargs: Any) -> None:
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pass
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def migrate(
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self,
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dest_client: "QdrantBase",
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collection_names: list[str] | None = None,
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batch_size: int = 100,
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recreate_on_collision: bool = False,
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) -> None:
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raise NotImplementedError()
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def create_shard_key(
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self,
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collection_name: str,
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shard_key: types.ShardKey,
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shards_number: int | None = None,
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replication_factor: int | None = None,
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placement: list[int] | None = None,
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def delete_shard_key(
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self,
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collection_name: str,
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shard_key: types.ShardKey,
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def info(self) -> types.VersionInfo:
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raise NotImplementedError()
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def cluster_collection_update(
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self,
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collection_name: str,
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cluster_operation: types.ClusterOperations,
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**kwargs: Any,
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) -> bool:
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raise NotImplementedError()
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def collection_cluster_info(self, collection_name: str) -> types.CollectionClusterInfo:
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raise NotImplementedError()
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def cluster_status(self) -> types.ClusterStatus:
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raise NotImplementedError()
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def recover_current_peer(self) -> bool:
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raise NotImplementedError()
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def remove_peer(self, peer_id: int, **kwargs: Any) -> bool:
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raise NotImplementedError()
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def get_optimizations(
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self,
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collection_name: str,
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**kwargs: Any,
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) -> types.OptimizationsResponse:
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raise NotImplementedError()
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def list_shard_keys(
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self,
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collection_name: str,
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**kwargs: Any,
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) -> types.ShardKeysResponse:
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raise NotImplementedError()
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def cluster_telemetry(
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self,
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**kwargs: Any,
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) -> types.DistributedTelemetryData:
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raise NotImplementedError()
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