mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-08-01 23:50:57 -05:00
0b499b0fd5
* upd version * enable CI on all PRs * update client - json as a payload + typed index (#31) * update client - json as a payload + typed index * refactor * upd docker version in tests * New condition filters (#33) * upd rest for new filter conditions * update gprc client * proper shutdown on upload error * rm debug print
744 lines
22 KiB
Python
744 lines
22 KiB
Python
# flake8: noqa E501
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from enum import Enum
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from pathlib import PurePath
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from types import GeneratorType
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from typing import TYPE_CHECKING, Any, Callable, Dict, List, Set, Tuple, Union
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from pydantic.json import ENCODERS_BY_TYPE
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from pydantic.main import BaseModel
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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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def generate_encoders_by_class_tuples(type_encoder_map: Dict[Any, Callable]) -> Dict[Callable, Tuple]:
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encoders_by_classes: Dict[Callable, List] = {}
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for type_, encoder in type_encoder_map.items():
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encoders_by_classes.setdefault(encoder, []).append(type_)
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encoders_by_class_tuples: Dict[Callable, Tuple] = {}
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for encoder, classes in encoders_by_classes.items():
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encoders_by_class_tuples[encoder] = tuple(classes)
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return encoders_by_class_tuples
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encoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)
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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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include_none: bool = True,
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custom_encoder=None,
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sqlalchemy_safe: bool = True,
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) -> Any:
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if exclude is None:
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exclude = set()
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if custom_encoder is None:
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custom_encoder = {}
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if include is not None and not isinstance(include, set):
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include = set(include)
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if exclude is not None and not isinstance(exclude, set):
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exclude = set(exclude)
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if isinstance(obj, BaseModel):
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encoder = getattr(obj.Config, "json_encoders", {})
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if custom_encoder:
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encoder.update(custom_encoder)
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obj_dict = 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 jsonable_encoder(
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obj_dict,
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include_none=include_none,
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custom_encoder=encoder,
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sqlalchemy_safe=sqlalchemy_safe,
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)
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if isinstance(obj, Enum):
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return obj.value
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if isinstance(obj, PurePath):
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return str(obj)
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if isinstance(obj, (str, int, float, type(None))):
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return obj
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if isinstance(obj, dict):
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encoded_dict = {}
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for key, value in obj.items():
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if (
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(not sqlalchemy_safe or (not isinstance(key, str)) or (not key.startswith("_sa")))
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and (value is not None or include_none)
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and ((include and key in include) or key not in exclude)
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):
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encoded_key = jsonable_encoder(
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key,
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by_alias=by_alias,
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exclude_unset=exclude_unset,
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include_none=include_none,
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custom_encoder=custom_encoder,
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sqlalchemy_safe=sqlalchemy_safe,
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)
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encoded_value = jsonable_encoder(
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value,
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by_alias=by_alias,
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exclude_unset=exclude_unset,
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include_none=include_none,
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custom_encoder=custom_encoder,
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sqlalchemy_safe=sqlalchemy_safe,
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)
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encoded_dict[encoded_key] = encoded_value
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return encoded_dict
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if isinstance(obj, (list, set, frozenset, GeneratorType, tuple)):
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encoded_list = []
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for item in obj:
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encoded_list.append(
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jsonable_encoder(
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item,
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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=exclude_unset,
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include_none=include_none,
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custom_encoder=custom_encoder,
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sqlalchemy_safe=sqlalchemy_safe,
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)
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)
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return encoded_list
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if custom_encoder:
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if type(obj) in custom_encoder:
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return custom_encoder[type(obj)](obj)
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else:
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for encoder_type, encoder in custom_encoder.items():
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if isinstance(obj, encoder_type):
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return encoder(obj)
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if type(obj) in ENCODERS_BY_TYPE:
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return ENCODERS_BY_TYPE[type(obj)](obj)
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for encoder, classes_tuple in encoders_by_class_tuples.items():
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if isinstance(obj, classes_tuple):
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return encoder(obj)
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errors: List[Exception] = []
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try:
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data = dict(obj)
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except Exception as e:
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errors.append(e)
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try:
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data = vars(obj)
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except Exception as e:
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errors.append(e)
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raise ValueError(errors)
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return jsonable_encoder(
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data,
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by_alias=by_alias,
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exclude_unset=exclude_unset,
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include_none=include_none,
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custom_encoder=custom_encoder,
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sqlalchemy_safe=sqlalchemy_safe,
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)
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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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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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body = jsonable_encoder(points_selector)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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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_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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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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body = jsonable_encoder(delete_payload)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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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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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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body = jsonable_encoder(points_selector)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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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_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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):
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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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return self.api_client.request(
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type_=m.InlineResponse2007,
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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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)
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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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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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body = jsonable_encoder(point_request)
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return self.api_client.request(
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type_=m.InlineResponse2004,
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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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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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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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body = jsonable_encoder(recommend_request)
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return self.api_client.request(
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type_=m.InlineResponse2005,
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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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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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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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body = jsonable_encoder(scroll_request)
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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/scroll",
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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_search_points(
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self,
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collection_name: str,
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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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body = jsonable_encoder(search_request)
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return self.api_client.request(
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type_=m.InlineResponse2005,
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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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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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set_payload: m.SetPayload = None,
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):
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"""
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Set 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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body = jsonable_encoder(set_payload)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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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_points(
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self,
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collection_name: str,
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wait: bool = None,
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collection_update_operations: m.CollectionUpdateOperations = None,
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):
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"""
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Perform point update operation (vectors, payloads, indexes) in collection
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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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body = jsonable_encoder(collection_update_operations)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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method="POST",
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url="/collections/{collection_name}",
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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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point_insert_operations: m.PointInsertOperations = None,
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):
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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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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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body = jsonable_encoder(point_insert_operations)
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return self.api_client.request(
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type_=m.InlineResponse2003,
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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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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,
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points_selector: m.PointsSelector = None,
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) -> m.InlineResponse2003:
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"""
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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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points_selector=points_selector,
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)
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async def 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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delete_payload: m.DeletePayload = None,
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) -> m.InlineResponse2003:
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"""
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Delete specified key payload for points
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"""
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return await self._build_for_delete_payload(
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collection_name=collection_name,
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wait=wait,
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delete_payload=delete_payload,
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)
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async def 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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points_selector: m.PointsSelector = None,
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) -> m.InlineResponse2003:
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"""
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Delete points
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"""
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return await self._build_for_delete_points(
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collection_name=collection_name,
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wait=wait,
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points_selector=points_selector,
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)
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async def 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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) -> m.InlineResponse2007:
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"""
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Retrieve full information of single point by id
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"""
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return await self._build_for_get_point(
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collection_name=collection_name,
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id=id,
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)
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async def get_points(
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self,
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collection_name: str,
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point_request: m.PointRequest = None,
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) -> m.InlineResponse2004:
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"""
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Retrieve multiple points by specified IDs
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"""
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return await self._build_for_get_points(
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collection_name=collection_name,
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point_request=point_request,
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)
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async def recommend_points(
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self,
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collection_name: str,
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recommend_request: m.RecommendRequest = None,
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) -> m.InlineResponse2005:
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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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return await self._build_for_recommend_points(
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collection_name=collection_name,
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recommend_request=recommend_request,
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)
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async def scroll_points(
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self,
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collection_name: str,
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scroll_request: m.ScrollRequest = None,
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) -> m.InlineResponse2006:
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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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return await self._build_for_scroll_points(
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collection_name=collection_name,
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scroll_request=scroll_request,
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)
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async def search_points(
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self,
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collection_name: str,
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search_request: m.SearchRequest = None,
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) -> m.InlineResponse2005:
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"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions
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"""
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return await self._build_for_search_points(
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collection_name=collection_name,
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search_request=search_request,
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)
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async def 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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set_payload: m.SetPayload = None,
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) -> m.InlineResponse2003:
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"""
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Set payload for points
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"""
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return await self._build_for_set_payload(
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collection_name=collection_name,
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wait=wait,
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set_payload=set_payload,
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)
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async def update_points(
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self,
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collection_name: str,
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wait: bool = None,
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collection_update_operations: m.CollectionUpdateOperations = None,
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) -> m.InlineResponse2003:
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"""
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Perform point update operation (vectors, payloads, indexes) in collection
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"""
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return await self._build_for_update_points(
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collection_name=collection_name,
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wait=wait,
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collection_update_operations=collection_update_operations,
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)
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async def upsert_points(
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self,
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collection_name: str,
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|
wait: bool = None,
|
|
point_insert_operations: m.PointInsertOperations = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
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,
|
|
point_insert_operations=point_insert_operations,
|
|
)
|
|
|
|
|
|
class SyncPointsApi(_PointsApi):
|
|
def clear_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
points_selector: m.PointsSelector = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
Remove all payload for specified points
|
|
"""
|
|
return self._build_for_clear_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
points_selector=points_selector,
|
|
)
|
|
|
|
def delete_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
delete_payload: m.DeletePayload = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
Delete specified key payload for points
|
|
"""
|
|
return self._build_for_delete_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
delete_payload=delete_payload,
|
|
)
|
|
|
|
def delete_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
points_selector: m.PointsSelector = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
Delete points
|
|
"""
|
|
return self._build_for_delete_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
points_selector=points_selector,
|
|
)
|
|
|
|
def get_point(
|
|
self,
|
|
collection_name: str,
|
|
id: m.ExtendedPointId,
|
|
) -> m.InlineResponse2007:
|
|
"""
|
|
Retrieve full information of single point by id
|
|
"""
|
|
return self._build_for_get_point(
|
|
collection_name=collection_name,
|
|
id=id,
|
|
)
|
|
|
|
def get_points(
|
|
self,
|
|
collection_name: str,
|
|
point_request: m.PointRequest = None,
|
|
) -> m.InlineResponse2004:
|
|
"""
|
|
Retrieve multiple points by specified IDs
|
|
"""
|
|
return self._build_for_get_points(
|
|
collection_name=collection_name,
|
|
point_request=point_request,
|
|
)
|
|
|
|
def recommend_points(
|
|
self,
|
|
collection_name: str,
|
|
recommend_request: m.RecommendRequest = None,
|
|
) -> m.InlineResponse2005:
|
|
"""
|
|
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,
|
|
recommend_request=recommend_request,
|
|
)
|
|
|
|
def scroll_points(
|
|
self,
|
|
collection_name: str,
|
|
scroll_request: m.ScrollRequest = None,
|
|
) -> m.InlineResponse2006:
|
|
"""
|
|
Scroll request - paginate over all points which matches given filtering condition
|
|
"""
|
|
return self._build_for_scroll_points(
|
|
collection_name=collection_name,
|
|
scroll_request=scroll_request,
|
|
)
|
|
|
|
def search_points(
|
|
self,
|
|
collection_name: str,
|
|
search_request: m.SearchRequest = None,
|
|
) -> m.InlineResponse2005:
|
|
"""
|
|
Retrieve closest points based on vector similarity and given filtering conditions
|
|
"""
|
|
return self._build_for_search_points(
|
|
collection_name=collection_name,
|
|
search_request=search_request,
|
|
)
|
|
|
|
def set_payload(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
set_payload: m.SetPayload = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
Set payload for points
|
|
"""
|
|
return self._build_for_set_payload(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
set_payload=set_payload,
|
|
)
|
|
|
|
def update_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
collection_update_operations: m.CollectionUpdateOperations = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
Perform point update operation (vectors, payloads, indexes) in collection
|
|
"""
|
|
return self._build_for_update_points(
|
|
collection_name=collection_name,
|
|
wait=wait,
|
|
collection_update_operations=collection_update_operations,
|
|
)
|
|
|
|
def upsert_points(
|
|
self,
|
|
collection_name: str,
|
|
wait: bool = None,
|
|
point_insert_operations: m.PointInsertOperations = None,
|
|
) -> m.InlineResponse2003:
|
|
"""
|
|
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,
|
|
point_insert_operations=point_insert_operations,
|
|
)
|