mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-07-26 20:51:09 -05:00
1130 lines
34 KiB
Python
1130 lines
34 KiB
Python
# flake8: noqa E501
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from typing import TYPE_CHECKING, Any, Dict, Set, Union
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from qdrant_client.http.models import *
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from qdrant_client.http.models import models as m
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SetIntStr = Set[Union[int, str]]
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DictIntStrAny = Dict[Union[int, str], Any]
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file = None
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def jsonable_encoder(
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obj: Any,
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include: Union[SetIntStr, DictIntStrAny] = None,
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exclude=None,
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by_alias: bool = True,
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skip_defaults: bool = None,
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exclude_unset: bool = False,
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):
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if hasattr(obj, "dict"):
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return obj.dict(
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include=include,
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exclude=exclude,
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by_alias=by_alias,
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exclude_unset=bool(exclude_unset or skip_defaults),
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)
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return obj
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if TYPE_CHECKING:
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from qdrant_client.http.api_client import ApiClient
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class _PointsApi:
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def __init__(self, api_client: "Union[ApiClient, AsyncApiClient]"):
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self.api_client = api_client
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def _build_for_clear_payload(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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points_selector: m.PointsSelector = None,
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):
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"""
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Remove all payload for specified points
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(points_selector)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="POST",
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url="/collections/{collection_name}/points/payload/clear",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_count_points(
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self,
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collection_name: str,
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count_request: m.CountRequest = None,
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):
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"""
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Count points which matches given filtering condition
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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body = jsonable_encoder(count_request)
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return self.api_client.request(
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type_=m.InlineResponse20017,
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method="POST",
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url="/collections/{collection_name}/points/count",
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path_params=path_params,
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json=body,
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)
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def _build_for_delete_payload(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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delete_payload: m.DeletePayload = None,
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):
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"""
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Delete specified key payload for points
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(delete_payload)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="POST",
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url="/collections/{collection_name}/points/payload/delete",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_delete_points(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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points_selector: m.PointsSelector = None,
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):
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"""
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Delete points
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(points_selector)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="POST",
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url="/collections/{collection_name}/points/delete",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_delete_vectors(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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delete_vectors: m.DeleteVectors = None,
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):
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"""
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Delete named vectors from the given points.
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(delete_vectors)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="POST",
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url="/collections/{collection_name}/points/vectors/delete",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_get_point(
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self,
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collection_name: str,
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id: m.ExtendedPointId,
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consistency: m.ReadConsistency = None,
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):
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"""
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Retrieve full information of single point by id
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"""
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path_params = {
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"collection_name": str(collection_name),
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"id": str(id),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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return self.api_client.request(
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type_=m.InlineResponse20011,
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method="GET",
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url="/collections/{collection_name}/points/{id}",
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path_params=path_params,
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params=query_params,
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)
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def _build_for_get_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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point_request: m.PointRequest = None,
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):
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"""
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Retrieve multiple points by specified IDs
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(point_request)
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return self.api_client.request(
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type_=m.InlineResponse20012,
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method="POST",
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url="/collections/{collection_name}/points",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_overwrite_payload(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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set_payload: m.SetPayload = None,
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):
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"""
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Replace full payload of points with new one
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(set_payload)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="PUT",
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url="/collections/{collection_name}/points/payload",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_recommend_batch_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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recommend_request_batch: m.RecommendRequestBatch = None,
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):
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"""
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Look for the points which are closer to stored positive examples and at the same time further to negative examples.
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(recommend_request_batch)
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return self.api_client.request(
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type_=m.InlineResponse20015,
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method="POST",
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url="/collections/{collection_name}/points/recommend/batch",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_recommend_point_groups(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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recommend_groups_request: m.RecommendGroupsRequest = None,
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):
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"""
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Look for the points which are closer to stored positive examples and at the same time further to negative examples, grouped by a given payload field.
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(recommend_groups_request)
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return self.api_client.request(
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type_=m.InlineResponse20016,
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method="POST",
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url="/collections/{collection_name}/points/recommend/groups",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_recommend_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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recommend_request: m.RecommendRequest = None,
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):
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"""
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Look for the points which are closer to stored positive examples and at the same time further to negative examples.
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(recommend_request)
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return self.api_client.request(
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type_=m.InlineResponse20014,
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method="POST",
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url="/collections/{collection_name}/points/recommend",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_scroll_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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scroll_request: m.ScrollRequest = None,
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):
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"""
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Scroll request - paginate over all points which matches given filtering condition
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(scroll_request)
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return self.api_client.request(
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type_=m.InlineResponse20013,
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method="POST",
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url="/collections/{collection_name}/points/scroll",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_search_batch_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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search_request_batch: m.SearchRequestBatch = None,
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):
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"""
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Retrieve by batch the closest points based on vector similarity and given filtering conditions
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(search_request_batch)
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return self.api_client.request(
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type_=m.InlineResponse20015,
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method="POST",
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url="/collections/{collection_name}/points/search/batch",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_search_point_groups(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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search_groups_request: m.SearchGroupsRequest = None,
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):
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"""
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Retrieve closest points based on vector similarity and given filtering conditions, grouped by a given payload field
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(search_groups_request)
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return self.api_client.request(
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type_=m.InlineResponse20016,
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method="POST",
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url="/collections/{collection_name}/points/search/groups",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_search_points(
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self,
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collection_name: str,
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consistency: m.ReadConsistency = None,
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search_request: m.SearchRequest = None,
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):
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"""
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Retrieve closest points based on vector similarity and given filtering conditions
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if consistency is not None:
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query_params["consistency"] = str(consistency)
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body = jsonable_encoder(search_request)
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return self.api_client.request(
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type_=m.InlineResponse20014,
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method="POST",
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url="/collections/{collection_name}/points/search",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_set_payload(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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set_payload: m.SetPayload = None,
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):
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"""
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Set payload values for points
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(set_payload)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="POST",
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url="/collections/{collection_name}/points/payload",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_update_vectors(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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update_vectors: m.UpdateVectors = None,
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):
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"""
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Update specified named vectors on points, keep unspecified vectors intact.
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"""
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path_params = {
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"collection_name": str(collection_name),
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}
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query_params = {}
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if wait is not None:
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query_params["wait"] = str(wait).lower()
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(update_vectors)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="PUT",
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url="/collections/{collection_name}/points/vectors",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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def _build_for_upsert_points(
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self,
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collection_name: str,
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wait: bool = None,
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ordering: WriteOrdering = None,
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point_insert_operations: m.PointInsertOperations = None,
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):
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"""
|
|
Perform insert + updates on points. If point with given ID already exists - it will be overwritten.
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"""
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|
path_params = {
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"collection_name": str(collection_name),
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}
|
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|
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query_params = {}
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|
if wait is not None:
|
|
query_params["wait"] = str(wait).lower()
|
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if ordering is not None:
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query_params["ordering"] = str(ordering)
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body = jsonable_encoder(point_insert_operations)
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return self.api_client.request(
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type_=m.InlineResponse2006,
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method="PUT",
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url="/collections/{collection_name}/points",
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path_params=path_params,
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params=query_params,
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json=body,
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)
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|
|
|
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class AsyncPointsApi(_PointsApi):
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async def clear_payload(
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self,
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collection_name: str,
|
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wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
points_selector: m.PointsSelector = None,
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) -> m.InlineResponse2006:
|
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"""
|
|
Remove all payload for specified points
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"""
|
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return await self._build_for_clear_payload(
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collection_name=collection_name,
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wait=wait,
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ordering=ordering,
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points_selector=points_selector,
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)
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async def count_points(
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self,
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collection_name: str,
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count_request: m.CountRequest = None,
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) -> m.InlineResponse20017:
|
|
"""
|
|
Count points which matches given filtering condition
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|
"""
|
|
return await self._build_for_count_points(
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collection_name=collection_name,
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count_request=count_request,
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)
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|
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async def delete_payload(
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self,
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|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
delete_payload: m.DeletePayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete specified key payload for points
|
|
"""
|
|
return await self._build_for_delete_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
delete_payload=delete_payload,
|
|
)
|
|
|
|
async def delete_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
points_selector: m.PointsSelector = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete points
|
|
"""
|
|
return await self._build_for_delete_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
points_selector=points_selector,
|
|
)
|
|
|
|
async def delete_vectors(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
delete_vectors: m.DeleteVectors = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete named vectors from the given points.
|
|
"""
|
|
return await self._build_for_delete_vectors(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
delete_vectors=delete_vectors,
|
|
)
|
|
|
|
async def get_point(
|
|
self,
|
|
collection_name: str,
|
|
id: m.ExtendedPointId,
|
|
consistency: m.ReadConsistency = None,
|
|
) -> m.InlineResponse20011:
|
|
"""
|
|
Retrieve full information of single point by id
|
|
"""
|
|
return await self._build_for_get_point(
|
|
collection_name=collection_name,
|
|
id=id,
|
|
consistency=consistency,
|
|
)
|
|
|
|
async def get_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
point_request: m.PointRequest = None,
|
|
) -> m.InlineResponse20012:
|
|
"""
|
|
Retrieve multiple points by specified IDs
|
|
"""
|
|
return await self._build_for_get_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
point_request=point_request,
|
|
)
|
|
|
|
async def overwrite_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
set_payload: m.SetPayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Replace full payload of points with new one
|
|
"""
|
|
return await self._build_for_overwrite_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
set_payload=set_payload,
|
|
)
|
|
|
|
async def recommend_batch_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_request_batch: m.RecommendRequestBatch = None,
|
|
) -> m.InlineResponse20015:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples.
|
|
"""
|
|
return await self._build_for_recommend_batch_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_request_batch=recommend_request_batch,
|
|
)
|
|
|
|
async def recommend_point_groups(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_groups_request: m.RecommendGroupsRequest = None,
|
|
) -> m.InlineResponse20016:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples, grouped by a given payload field.
|
|
"""
|
|
return await self._build_for_recommend_point_groups(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_groups_request=recommend_groups_request,
|
|
)
|
|
|
|
async def recommend_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_request: m.RecommendRequest = None,
|
|
) -> m.InlineResponse20014:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples.
|
|
"""
|
|
return await self._build_for_recommend_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_request=recommend_request,
|
|
)
|
|
|
|
async def scroll_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
scroll_request: m.ScrollRequest = None,
|
|
) -> m.InlineResponse20013:
|
|
"""
|
|
Scroll request - paginate over all points which matches given filtering condition
|
|
"""
|
|
return await self._build_for_scroll_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
scroll_request=scroll_request,
|
|
)
|
|
|
|
async def search_batch_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_request_batch: m.SearchRequestBatch = None,
|
|
) -> m.InlineResponse20015:
|
|
"""
|
|
Retrieve by batch the closest points based on vector similarity and given filtering conditions
|
|
"""
|
|
return await self._build_for_search_batch_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_request_batch=search_request_batch,
|
|
)
|
|
|
|
async def search_point_groups(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_groups_request: m.SearchGroupsRequest = None,
|
|
) -> m.InlineResponse20016:
|
|
"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions, grouped by a given payload field
|
|
"""
|
|
return await self._build_for_search_point_groups(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_groups_request=search_groups_request,
|
|
)
|
|
|
|
async def search_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_request: m.SearchRequest = None,
|
|
) -> m.InlineResponse20014:
|
|
"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions
|
|
"""
|
|
return await self._build_for_search_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_request=search_request,
|
|
)
|
|
|
|
async def set_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
set_payload: m.SetPayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Set payload values for points
|
|
"""
|
|
return await self._build_for_set_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
set_payload=set_payload,
|
|
)
|
|
|
|
async def update_vectors(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
update_vectors: m.UpdateVectors = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Update specified named vectors on points, keep unspecified vectors intact.
|
|
"""
|
|
return await self._build_for_update_vectors(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
update_vectors=update_vectors,
|
|
)
|
|
|
|
async def upsert_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
point_insert_operations: m.PointInsertOperations = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Perform insert + updates on points. If point with given ID already exists - it will be overwritten.
|
|
"""
|
|
return await self._build_for_upsert_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
point_insert_operations=point_insert_operations,
|
|
)
|
|
|
|
|
|
class SyncPointsApi(_PointsApi):
|
|
def clear_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
points_selector: m.PointsSelector = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Remove all payload for specified points
|
|
"""
|
|
return self._build_for_clear_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
points_selector=points_selector,
|
|
)
|
|
|
|
def count_points(
|
|
self,
|
|
collection_name: str,
|
|
count_request: m.CountRequest = None,
|
|
) -> m.InlineResponse20017:
|
|
"""
|
|
Count points which matches given filtering condition
|
|
"""
|
|
return self._build_for_count_points(
|
|
collection_name=collection_name,
|
|
count_request=count_request,
|
|
)
|
|
|
|
def delete_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
delete_payload: m.DeletePayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete specified key payload for points
|
|
"""
|
|
return self._build_for_delete_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
delete_payload=delete_payload,
|
|
)
|
|
|
|
def delete_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
points_selector: m.PointsSelector = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete points
|
|
"""
|
|
return self._build_for_delete_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
points_selector=points_selector,
|
|
)
|
|
|
|
def delete_vectors(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
delete_vectors: m.DeleteVectors = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Delete named vectors from the given points.
|
|
"""
|
|
return self._build_for_delete_vectors(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
delete_vectors=delete_vectors,
|
|
)
|
|
|
|
def get_point(
|
|
self,
|
|
collection_name: str,
|
|
id: m.ExtendedPointId,
|
|
consistency: m.ReadConsistency = None,
|
|
) -> m.InlineResponse20011:
|
|
"""
|
|
Retrieve full information of single point by id
|
|
"""
|
|
return self._build_for_get_point(
|
|
collection_name=collection_name,
|
|
id=id,
|
|
consistency=consistency,
|
|
)
|
|
|
|
def get_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
point_request: m.PointRequest = None,
|
|
) -> m.InlineResponse20012:
|
|
"""
|
|
Retrieve multiple points by specified IDs
|
|
"""
|
|
return self._build_for_get_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
point_request=point_request,
|
|
)
|
|
|
|
def overwrite_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
set_payload: m.SetPayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Replace full payload of points with new one
|
|
"""
|
|
return self._build_for_overwrite_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
set_payload=set_payload,
|
|
)
|
|
|
|
def recommend_batch_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_request_batch: m.RecommendRequestBatch = None,
|
|
) -> m.InlineResponse20015:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples.
|
|
"""
|
|
return self._build_for_recommend_batch_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_request_batch=recommend_request_batch,
|
|
)
|
|
|
|
def recommend_point_groups(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_groups_request: m.RecommendGroupsRequest = None,
|
|
) -> m.InlineResponse20016:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples, grouped by a given payload field.
|
|
"""
|
|
return self._build_for_recommend_point_groups(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_groups_request=recommend_groups_request,
|
|
)
|
|
|
|
def recommend_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
recommend_request: m.RecommendRequest = None,
|
|
) -> m.InlineResponse20014:
|
|
"""
|
|
Look for the points which are closer to stored positive examples and at the same time further to negative examples.
|
|
"""
|
|
return self._build_for_recommend_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
recommend_request=recommend_request,
|
|
)
|
|
|
|
def scroll_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
scroll_request: m.ScrollRequest = None,
|
|
) -> m.InlineResponse20013:
|
|
"""
|
|
Scroll request - paginate over all points which matches given filtering condition
|
|
"""
|
|
return self._build_for_scroll_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
scroll_request=scroll_request,
|
|
)
|
|
|
|
def search_batch_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_request_batch: m.SearchRequestBatch = None,
|
|
) -> m.InlineResponse20015:
|
|
"""
|
|
Retrieve by batch the closest points based on vector similarity and given filtering conditions
|
|
"""
|
|
return self._build_for_search_batch_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_request_batch=search_request_batch,
|
|
)
|
|
|
|
def search_point_groups(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_groups_request: m.SearchGroupsRequest = None,
|
|
) -> m.InlineResponse20016:
|
|
"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions, grouped by a given payload field
|
|
"""
|
|
return self._build_for_search_point_groups(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_groups_request=search_groups_request,
|
|
)
|
|
|
|
def search_points(
|
|
self,
|
|
collection_name: str,
|
|
consistency: m.ReadConsistency = None,
|
|
search_request: m.SearchRequest = None,
|
|
) -> m.InlineResponse20014:
|
|
"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions
|
|
"""
|
|
return self._build_for_search_points(
|
|
collection_name=collection_name,
|
|
consistency=consistency,
|
|
search_request=search_request,
|
|
)
|
|
|
|
def set_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
set_payload: m.SetPayload = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Set payload values for points
|
|
"""
|
|
return self._build_for_set_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
set_payload=set_payload,
|
|
)
|
|
|
|
def update_vectors(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
update_vectors: m.UpdateVectors = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Update specified named vectors on points, keep unspecified vectors intact.
|
|
"""
|
|
return self._build_for_update_vectors(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
update_vectors=update_vectors,
|
|
)
|
|
|
|
def upsert_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
ordering: WriteOrdering = None,
|
|
point_insert_operations: m.PointInsertOperations = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Perform insert + updates on points. If point with given ID already exists - it will be overwritten.
|
|
"""
|
|
return self._build_for_upsert_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
ordering=ordering,
|
|
point_insert_operations=point_insert_operations,
|
|
)
|