qdrant_client.http.models.models module¶

class AbortShardTransfer(*, shard_id: int, to_peer_id: int, from_peer_id: int)[source]¶

Bases: BaseModel

from_peer_id: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'from_peer_id': FieldInfo(annotation=int, required=True, description=''), 'shard_id': FieldInfo(annotation=int, required=True, description=''), 'to_peer_id': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_id: int¶

to_peer_id: int¶

class AbortTransferOperation(*, abort_transfer: AbortShardTransfer)[source]¶

Bases: BaseModel

abort_transfer: AbortShardTransfer¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'abort_transfer': FieldInfo(annotation=AbortShardTransfer, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class AliasDescription(*, alias_name: str, collection_name: str)[source]¶

Bases: BaseModel

alias_name: str¶

collection_name: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'alias_name': FieldInfo(annotation=str, required=True, description=''), 'collection_name': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class AppBuildTelemetry(*, name: str, version: str, features: Optional[AppFeaturesTelemetry] = None, system: Optional[RunningEnvironmentTelemetry] = None, jwt_rbac: Optional[bool] = None, startup: Union[datetime, date])[source]¶

Bases: BaseModel

features: Optional[AppFeaturesTelemetry]¶

jwt_rbac: Optional[bool]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'features': FieldInfo(annotation=Union[AppFeaturesTelemetry, NoneType], required=False, default=None, description=''), 'jwt_rbac': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description=''), 'name': FieldInfo(annotation=str, required=True, description=''), 'startup': FieldInfo(annotation=Union[datetime, date], required=True, description=''), 'system': FieldInfo(annotation=Union[RunningEnvironmentTelemetry, NoneType], required=False, default=None, description=''), 'version': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

startup: Union[datetime.datetime, datetime.date]¶

system: Optional[RunningEnvironmentTelemetry]¶

version: str¶

class AppFeaturesTelemetry(*, debug: bool, web_feature: bool, service_debug_feature: bool, recovery_mode: bool)[source]¶

Bases: BaseModel

debug: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'debug': FieldInfo(annotation=bool, required=True, description=''), 'recovery_mode': FieldInfo(annotation=bool, required=True, description=''), 'service_debug_feature': FieldInfo(annotation=bool, required=True, description=''), 'web_feature': FieldInfo(annotation=bool, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

recovery_mode: bool¶

service_debug_feature: bool¶

web_feature: bool¶

class Batch(*, ids: List[Union[int[int], str[str]]], vectors: Union[List[List[float[float]]], Dict[str[str], List[Union[List[float[float]], SparseVector]]]], payloads: Optional[List[Dict[str, Any]]] = None)[source]¶

Bases: BaseModel

ids: List[ExtendedPointId]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'ids': FieldInfo(annotation=List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], required=True, description=''), 'payloads': FieldInfo(annotation=Union[List[Dict[str, Any]], NoneType], required=False, default=None, description=''), 'vectors': FieldInfo(annotation=Union[List[List[Annotated[float, Strict(strict=True)]]], Dict[Annotated[str, Strict(strict=True)], List[Union[List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]]]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payloads: Optional[List[Payload]]¶

vectors: BatchVectorStruct¶

class BinaryQuantization(*, binary: BinaryQuantizationConfig)[source]¶

Bases: BaseModel

binary: BinaryQuantizationConfig¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'binary': FieldInfo(annotation=BinaryQuantizationConfig, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class BinaryQuantizationConfig(*, always_ram: Optional[bool] = None)[source]¶

Bases: BaseModel

always_ram: Optional[bool]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'always_ram': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ChangeAliasesOperation(*, actions: List[Union[CreateAliasOperation, DeleteAliasOperation, RenameAliasOperation]])[source]¶

Bases: BaseModel

Operation for performing changes of collection aliases. Alias changes are atomic, meaning that no collection modifications can happen between alias operations.

actions: List[AliasOperations]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'actions': FieldInfo(annotation=List[Union[qdrant_client.http.models.models.CreateAliasOperation, qdrant_client.http.models.models.DeleteAliasOperation, qdrant_client.http.models.models.RenameAliasOperation]], required=True, description='Operation for performing changes of collection aliases. Alias changes are atomic, meaning that no collection modifications can happen between alias operations.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ClearPayloadOperation(*, clear_payload: Union[PointIdsList, FilterSelector])[source]¶

Bases: BaseModel

clear_payload: PointsSelector¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'clear_payload': FieldInfo(annotation=Union[PointIdsList, FilterSelector], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ClusterConfigTelemetry(*, grpc_timeout_ms: int, p2p: P2pConfigTelemetry, consensus: ConsensusConfigTelemetry)[source]¶

Bases: BaseModel

consensus: ConsensusConfigTelemetry¶

grpc_timeout_ms: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'consensus': FieldInfo(annotation=ConsensusConfigTelemetry, required=True, description=''), 'grpc_timeout_ms': FieldInfo(annotation=int, required=True, description=''), 'p2p': FieldInfo(annotation=P2pConfigTelemetry, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

p2p: P2pConfigTelemetry¶

class ClusterStatusOneOf(*, status: Literal['disabled'])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'status': FieldInfo(annotation=Literal['disabled'], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

status: Literal['disabled']¶

class ClusterStatusOneOf1(*, status: Literal['enabled'], peer_id: int, peers: Dict[str, PeerInfo], raft_info: RaftInfo, consensus_thread_status: Union[ConsensusThreadStatusOneOf, ConsensusThreadStatusOneOf1, ConsensusThreadStatusOneOf2], message_send_failures: Dict[str, MessageSendErrors])[source]¶

Bases: BaseModel

Description of enabled cluster

consensus_thread_status: ConsensusThreadStatus¶

message_send_failures: Dict[str, MessageSendErrors]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'consensus_thread_status': FieldInfo(annotation=Union[ConsensusThreadStatusOneOf, ConsensusThreadStatusOneOf1, ConsensusThreadStatusOneOf2], required=True, description='Description of enabled cluster'), 'message_send_failures': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.MessageSendErrors], required=True, description='Consequent failures of message send operations in consensus by peer address. On the first success to send to that peer - entry is removed from this hashmap.'), 'peer_id': FieldInfo(annotation=int, required=True, description='ID of this peer'), 'peers': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.PeerInfo], required=True, description='Peers composition of the cluster with main information'), 'raft_info': FieldInfo(annotation=RaftInfo, required=True, description='Description of enabled cluster'), 'status': FieldInfo(annotation=Literal['enabled'], required=True, description='Description of enabled cluster')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

peer_id: int¶

peers: Dict[str, PeerInfo]¶

raft_info: RaftInfo¶

status: Literal['enabled']¶

class ClusterStatusTelemetry(*, number_of_peers: int, term: int, commit: int, pending_operations: int, role: Optional[StateRole] = None, is_voter: bool, peer_id: Optional[int] = None, consensus_thread_status: Union[ConsensusThreadStatusOneOf, ConsensusThreadStatusOneOf1, ConsensusThreadStatusOneOf2])[source]¶

Bases: BaseModel

commit: int¶

consensus_thread_status: ConsensusThreadStatus¶

is_voter: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'commit': FieldInfo(annotation=int, required=True, description=''), 'consensus_thread_status': FieldInfo(annotation=Union[ConsensusThreadStatusOneOf, ConsensusThreadStatusOneOf1, ConsensusThreadStatusOneOf2], required=True, description=''), 'is_voter': FieldInfo(annotation=bool, required=True, description=''), 'number_of_peers': FieldInfo(annotation=int, required=True, description=''), 'peer_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'pending_operations': FieldInfo(annotation=int, required=True, description=''), 'role': FieldInfo(annotation=Union[StateRole, NoneType], required=False, default=None, description=''), 'term': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

number_of_peers: int¶

peer_id: Optional[int]¶

pending_operations: int¶

role: Optional[StateRole]¶

term: int¶

class ClusterTelemetry(*, enabled: bool, status: Optional[ClusterStatusTelemetry] = None, config: Optional[ClusterConfigTelemetry] = None)[source]¶

Bases: BaseModel

config: Optional[ClusterConfigTelemetry]¶

enabled: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'config': FieldInfo(annotation=Union[ClusterConfigTelemetry, NoneType], required=False, default=None, description=''), 'enabled': FieldInfo(annotation=bool, required=True, description=''), 'status': FieldInfo(annotation=Union[ClusterStatusTelemetry, NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

status: Optional[ClusterStatusTelemetry]¶

class CollectionClusterInfo(*, peer_id: int, shard_count: int, local_shards: List[LocalShardInfo], remote_shards: List[RemoteShardInfo], shard_transfers: List[ShardTransferInfo])[source]¶

Bases: BaseModel

Current clustering distribution for the collection

local_shards: List[LocalShardInfo]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'local_shards': FieldInfo(annotation=List[qdrant_client.http.models.models.LocalShardInfo], required=True, description='Local shards'), 'peer_id': FieldInfo(annotation=int, required=True, description='ID of this peer'), 'remote_shards': FieldInfo(annotation=List[qdrant_client.http.models.models.RemoteShardInfo], required=True, description='Remote shards'), 'shard_count': FieldInfo(annotation=int, required=True, description='Total number of shards'), 'shard_transfers': FieldInfo(annotation=List[qdrant_client.http.models.models.ShardTransferInfo], required=True, description='Shard transfers')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

peer_id: int¶

remote_shards: List[RemoteShardInfo]¶

shard_count: int¶

shard_transfers: List[ShardTransferInfo]¶

class CollectionConfig(*, params: CollectionParams, hnsw_config: HnswConfig, optimizer_config: OptimizersConfig, wal_config: WalConfig, quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization]] = None)[source]¶

Bases: BaseModel

hnsw_config: HnswConfig¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hnsw_config': FieldInfo(annotation=HnswConfig, required=True, description=''), 'optimizer_config': FieldInfo(annotation=OptimizersConfig, required=True, description=''), 'params': FieldInfo(annotation=CollectionParams, required=True, description=''), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization], NoneType], required=False, default=None, description=''), 'wal_config': FieldInfo(annotation=WalConfig, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizer_config: OptimizersConfig¶

params: CollectionParams¶

quantization_config: Optional[QuantizationConfig]¶

wal_config: WalConfig¶

class CollectionDescription(*, name: str)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

class CollectionExistence(*, exists: bool)[source]¶

Bases: BaseModel

State of existence of a collection, true = exists, false = does not exist

exists: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'exists': FieldInfo(annotation=bool, required=True, description='State of existence of a collection, true = exists, false = does not exist')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CollectionInfo(*, status: CollectionStatus, optimizer_status: Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], vectors_count: Optional[int] = None, indexed_vectors_count: Optional[int] = None, points_count: Optional[int] = None, segments_count: int, config: CollectionConfig, payload_schema: Dict[str, PayloadIndexInfo])[source]¶

Bases: BaseModel

Current statistics and configuration of the collection

config: CollectionConfig¶

indexed_vectors_count: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'config': FieldInfo(annotation=CollectionConfig, required=True, description='Current statistics and configuration of the collection'), 'indexed_vectors_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Approximate number of indexed vectors in the collection. Indexed vectors in large segments are faster to query, as it is stored in a specialized vector index.'), 'optimizer_status': FieldInfo(annotation=Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], required=True, description='Current statistics and configuration of the collection'), 'payload_schema': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.PayloadIndexInfo], required=True, description='Types of stored payload'), 'points_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Approximate number of points (vectors + payloads) in collection. Each point could be accessed by unique id.'), 'segments_count': FieldInfo(annotation=int, required=True, description='Number of segments in collection. Each segment has independent vector as payload indexes'), 'status': FieldInfo(annotation=CollectionStatus, required=True, description='Current statistics and configuration of the collection'), 'vectors_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='DEPRECATED: Approximate number of vectors in collection. All vectors in collection are available for querying. Calculated as `points_count x vectors_per_point`. Where `vectors_per_point` is a number of named vectors in schema.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizer_status: OptimizersStatus¶

payload_schema: Dict[str, PayloadIndexInfo]¶

points_count: Optional[int]¶

segments_count: int¶

status: CollectionStatus¶

vectors_count: Optional[int]¶

class CollectionParams(*, vectors: Optional[Union[VectorParams, Dict[str[str], VectorParams]]] = None, shard_number: Optional[int] = 1, sharding_method: Optional[ShardingMethod] = None, replication_factor: Optional[int] = 1, write_consistency_factor: Optional[int] = 1, read_fan_out_factor: Optional[int] = None, on_disk_payload: Optional[bool] = False, sparse_vectors: Optional[Dict[str, SparseVectorParams]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'on_disk_payload': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, description='If true - point's payload will not be stored in memory. It will be read from the disk every time it is requested. This setting saves RAM by (slightly) increasing the response time. Note: those payload values that are involved in filtering and are indexed - remain in RAM.'), 'read_fan_out_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Defines how many additional replicas should be processing read request at the same time. Default value is Auto, which means that fan-out will be determined automatically based on the busyness of the local replica. Having more than 0 might be useful to smooth latency spikes of individual nodes.'), 'replication_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=1, description='Number of replicas for each shard'), 'shard_number': FieldInfo(annotation=Union[int, NoneType], required=False, default=1, description='Number of shards the collection has'), 'sharding_method': FieldInfo(annotation=Union[ShardingMethod, NoneType], required=False, default=None, description='Sharding method Default is Auto - points are distributed across all available shards Custom - points are distributed across shards according to shard key'), 'sparse_vectors': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.SparseVectorParams], NoneType], required=False, default=None, description='Configuration of the sparse vector storage'), 'vectors': FieldInfo(annotation=Union[Union[VectorParams, Dict[Annotated[str, Strict(strict=True)], qdrant_client.http.models.models.VectorParams]], NoneType], required=False, default=None, description=''), 'write_consistency_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=1, description='Defines how many replicas should apply the operation for us to consider it successful. Increasing this number will make the collection more resilient to inconsistencies, but will also make it fail if not enough replicas are available. Does not have any performance impact.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk_payload: Optional[bool]¶

read_fan_out_factor: Optional[int]¶

replication_factor: Optional[int]¶

shard_number: Optional[int]¶

sharding_method: Optional[ShardingMethod]¶

sparse_vectors: Optional[Dict[str, SparseVectorParams]]¶

vectors: Optional[VectorsConfig]¶

write_consistency_factor: Optional[int]¶

class CollectionParamsDiff(*, replication_factor: Optional[int] = None, write_consistency_factor: Optional[int] = None, read_fan_out_factor: Optional[int] = None, on_disk_payload: Optional[bool] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'on_disk_payload': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true - point's payload will not be stored in memory. It will be read from the disk every time it is requested. This setting saves RAM by (slightly) increasing the response time. Note: those payload values that are involved in filtering and are indexed - remain in RAM.'), 'read_fan_out_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Fan-out every read request to these many additional remote nodes (and return first available response)'), 'replication_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of replicas for each shard'), 'write_consistency_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Minimal number successful responses from replicas to consider operation successful')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk_payload: Optional[bool]¶

read_fan_out_factor: Optional[int]¶

replication_factor: Optional[int]¶

write_consistency_factor: Optional[int]¶

class CollectionStatus(value)[source]¶

Bases: str, Enum

Current state of the collection. Green - all good. Yellow - optimization is running, Red - some operations failed and was not recovered

GREEN = 'green'¶

GREY = 'grey'¶

RED = 'red'¶

YELLOW = 'yellow'¶

class CollectionTelemetry(*, id: str, init_time_ms: int, config: CollectionConfig, shards: List[ReplicaSetTelemetry], transfers: List[ShardTransferInfo])[source]¶

Bases: BaseModel

config: CollectionConfig¶

id: str¶

init_time_ms: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'config': FieldInfo(annotation=CollectionConfig, required=True, description=''), 'id': FieldInfo(annotation=str, required=True, description=''), 'init_time_ms': FieldInfo(annotation=int, required=True, description=''), 'shards': FieldInfo(annotation=List[qdrant_client.http.models.models.ReplicaSetTelemetry], required=True, description=''), 'transfers': FieldInfo(annotation=List[qdrant_client.http.models.models.ShardTransferInfo], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shards: List[ReplicaSetTelemetry]¶

transfers: List[ShardTransferInfo]¶

class CollectionsAggregatedTelemetry(*, vectors: int, optimizers_status: Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], params: CollectionParams)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'optimizers_status': FieldInfo(annotation=Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], required=True, description=''), 'params': FieldInfo(annotation=CollectionParams, required=True, description=''), 'vectors': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizers_status: OptimizersStatus¶

params: CollectionParams¶

vectors: int¶

class CollectionsAliasesResponse(*, aliases: List[AliasDescription])[source]¶

Bases: BaseModel

aliases: List[AliasDescription]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'aliases': FieldInfo(annotation=List[qdrant_client.http.models.models.AliasDescription], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CollectionsResponse(*, collections: List[CollectionDescription])[source]¶

Bases: BaseModel

collections: List[CollectionDescription]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'collections': FieldInfo(annotation=List[qdrant_client.http.models.models.CollectionDescription], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CollectionsTelemetry(*, number_of_collections: int, collections: Optional[List[Union[CollectionTelemetry, CollectionsAggregatedTelemetry]]] = None)[source]¶

Bases: BaseModel

collections: Optional[List[CollectionTelemetryEnum]]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'collections': FieldInfo(annotation=Union[List[Union[qdrant_client.http.models.models.CollectionTelemetry, qdrant_client.http.models.models.CollectionsAggregatedTelemetry]], NoneType], required=False, default=None, description=''), 'number_of_collections': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

number_of_collections: int¶

class CompressionRatio(value)[source]¶

Bases: str, Enum

An enumeration.

X16 = 'x16'¶

X32 = 'x32'¶

X4 = 'x4'¶

X64 = 'x64'¶

X8 = 'x8'¶

class ConsensusConfigTelemetry(*, max_message_queue_size: int, tick_period_ms: int, bootstrap_timeout_sec: int)[source]¶

Bases: BaseModel

bootstrap_timeout_sec: int¶

max_message_queue_size: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'bootstrap_timeout_sec': FieldInfo(annotation=int, required=True, description=''), 'max_message_queue_size': FieldInfo(annotation=int, required=True, description=''), 'tick_period_ms': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

tick_period_ms: int¶

class ConsensusThreadStatusOneOf(*, consensus_thread_status: Literal['working'], last_update: Union[datetime, date])[source]¶

Bases: BaseModel

consensus_thread_status: Literal['working']¶

last_update: Union[datetime.datetime, datetime.date]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'consensus_thread_status': FieldInfo(annotation=Literal['working'], required=True, description=''), 'last_update': FieldInfo(annotation=Union[datetime, date], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ConsensusThreadStatusOneOf1(*, consensus_thread_status: Literal['stopped'])[source]¶

Bases: BaseModel

consensus_thread_status: Literal['stopped']¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'consensus_thread_status': FieldInfo(annotation=Literal['stopped'], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ConsensusThreadStatusOneOf2(*, consensus_thread_status: Literal['stopped_with_err'], err: str)[source]¶

Bases: BaseModel

consensus_thread_status: Literal['stopped_with_err']¶

err: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'consensus_thread_status': FieldInfo(annotation=Literal['stopped_with_err'], required=True, description=''), 'err': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ContextExamplePair(*, positive: Union[int[int], str[str], List[float[float]], SparseVector], negative: Union[int[int], str[str], List[float[float]], SparseVector])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'negative': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], SparseVector], required=True, description=''), 'positive': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], SparseVector], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

negative: RecommendExample¶

positive: RecommendExample¶

class CountRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, filter: Optional[Filter] = None, exact: Optional[bool] = True)[source]¶

Bases: BaseModel

Count Request Counts the number of points which satisfy the given filter. If filter is not provided, the count of all points in the collection will be returned.

exact: Optional[bool]¶

filter: Optional[Filter]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'exact': FieldInfo(annotation=Union[bool, NoneType], required=False, default=True, description='If true, count exact number of points. If false, count approximate number of points faster. Approximate count might be unreliable during the indexing process. Default: true'), 'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: Optional[ShardKeySelector]¶

class CountResult(*, count: int)[source]¶

Bases: BaseModel

count: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'count': FieldInfo(annotation=int, required=True, description='Number of points which satisfy the conditions')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CreateAlias(*, collection_name: str, alias_name: str)[source]¶

Bases: BaseModel

Create alternative name for a collection. Collection will be available under both names for search, retrieve,

alias_name: str¶

collection_name: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'alias_name': FieldInfo(annotation=str, required=True, description='Create alternative name for a collection. Collection will be available under both names for search, retrieve,'), 'collection_name': FieldInfo(annotation=str, required=True, description='Create alternative name for a collection. Collection will be available under both names for search, retrieve,')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CreateAliasOperation(*, create_alias: CreateAlias)[source]¶

Bases: BaseModel

create_alias: CreateAlias¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'create_alias': FieldInfo(annotation=CreateAlias, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CreateCollection(*, vectors: Optional[Union[VectorParams, Dict[str[str], VectorParams]]] = None, shard_number: Optional[int] = None, sharding_method: Optional[ShardingMethod] = None, replication_factor: Optional[int] = None, write_consistency_factor: Optional[int] = None, on_disk_payload: Optional[bool] = None, hnsw_config: Optional[HnswConfigDiff] = None, wal_config: Optional[WalConfigDiff] = None, optimizers_config: Optional[OptimizersConfigDiff] = None, init_from: Optional[InitFrom] = None, quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization]] = None, sparse_vectors: Optional[Dict[str, SparseVectorParams]] = None)[source]¶

Bases: BaseModel

Operation for creating new collection and (optionally) specify index params

hnsw_config: Optional[HnswConfigDiff]¶

init_from: Optional[InitFrom]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hnsw_config': FieldInfo(annotation=Union[HnswConfigDiff, NoneType], required=False, default=None, description='Custom params for HNSW index. If none - values from service configuration file are used.'), 'init_from': FieldInfo(annotation=Union[InitFrom, NoneType], required=False, default=None, description='Specify other collection to copy data from.'), 'on_disk_payload': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true - point's payload will not be stored in memory. It will be read from the disk every time it is requested. This setting saves RAM by (slightly) increasing the response time. Note: those payload values that are involved in filtering and are indexed - remain in RAM.'), 'optimizers_config': FieldInfo(annotation=Union[OptimizersConfigDiff, NoneType], required=False, default=None, description='Custom params for Optimizers. If none - values from service configuration file are used.'), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization], NoneType], required=False, default=None, description='Quantization parameters. If none - quantization is disabled.'), 'replication_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of shards replicas. Default is 1 Minimum is 1'), 'shard_number': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='For auto sharding: Number of shards in collection. - Default is 1 for standalone, otherwise equal to the number of nodes - Minimum is 1 For custom sharding: Number of shards in collection per shard group. - Default is 1, meaning that each shard key will be mapped to a single shard - Minimum is 1'), 'sharding_method': FieldInfo(annotation=Union[ShardingMethod, NoneType], required=False, default=None, description='Sharding method Default is Auto - points are distributed across all available shards Custom - points are distributed across shards according to shard key'), 'sparse_vectors': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.SparseVectorParams], NoneType], required=False, default=None, description='Sparse vector data config.'), 'vectors': FieldInfo(annotation=Union[Union[VectorParams, Dict[Annotated[str, Strict(strict=True)], qdrant_client.http.models.models.VectorParams]], NoneType], required=False, default=None, description='Operation for creating new collection and (optionally) specify index params'), 'wal_config': FieldInfo(annotation=Union[WalConfigDiff, NoneType], required=False, default=None, description='Custom params for WAL. If none - values from service configuration file are used.'), 'write_consistency_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Defines how many replicas should apply the operation for us to consider it successful. Increasing this number will make the collection more resilient to inconsistencies, but will also make it fail if not enough replicas are available. Does not have any performance impact.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk_payload: Optional[bool]¶

optimizers_config: Optional[OptimizersConfigDiff]¶

quantization_config: Optional[QuantizationConfig]¶

replication_factor: Optional[int]¶

shard_number: Optional[int]¶

sharding_method: Optional[ShardingMethod]¶

sparse_vectors: Optional[Dict[str, SparseVectorParams]]¶

vectors: Optional[VectorsConfig]¶

wal_config: Optional[WalConfigDiff]¶

write_consistency_factor: Optional[int]¶

class CreateFieldIndex(*, field_name: str, field_schema: Optional[Union[PayloadSchemaType, TextIndexParams, IntegerIndexParams]] = None)[source]¶

Bases: BaseModel

field_name: str¶

field_schema: Optional[PayloadFieldSchema]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'field_name': FieldInfo(annotation=str, required=True, description=''), 'field_schema': FieldInfo(annotation=Union[Union[PayloadSchemaType, TextIndexParams, IntegerIndexParams], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class CreateShardingKey(*, shard_key: Union[str[str], int[int]], shards_number: Optional[int] = None, replication_factor: Optional[int] = None, placement: Optional[List[int]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'placement': FieldInfo(annotation=Union[List[int], NoneType], required=False, default=None, description='Placement of shards for this key List of peer ids, that can be used to place shards for this key If not specified, will be randomly placed among all peers'), 'replication_factor': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='How many replicas to create for each shard If not specified, will use the default value from config'), 'shard_key': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], required=True, description=''), 'shards_number': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='How many shards to create for this key If not specified, will use the default value from config')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

placement: Optional[List[int]]¶

replication_factor: Optional[int]¶

shard_key: ShardKey¶

shards_number: Optional[int]¶

class CreateShardingKeyOperation(*, create_sharding_key: CreateShardingKey)[source]¶

Bases: BaseModel

create_sharding_key: CreateShardingKey¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'create_sharding_key': FieldInfo(annotation=CreateShardingKey, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class Datatype(value)[source]¶

Bases: str, Enum

Defines which datatype should be used to represent vectors in the storage. Choosing different datatypes allows to optimize memory usage and performance vs accuracy. - For float32 datatype - vectors are stored as single-precision floating point numbers, 4bytes. - For uint8 datatype - vectors are stored as unsigned 8-bit integers, 1byte. It expects vector elements to be in range [0, 255].

FLOAT32 = 'float32'¶

UINT8 = 'uint8'¶

class DatetimeRange(*, lt: Optional[Union[datetime, date]] = None, gt: Optional[Union[datetime, date]] = None, gte: Optional[Union[datetime, date]] = None, lte: Optional[Union[datetime, date]] = None)[source]¶

Bases: BaseModel

Range filter request

gt: Optional[Union[datetime.datetime, datetime.date]]¶

gte: Optional[Union[datetime.datetime, datetime.date]]¶

lt: Optional[Union[datetime.datetime, datetime.date]]¶

lte: Optional[Union[datetime.datetime, datetime.date]]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'gt': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='point.key > range.gt'), 'gte': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='point.key >= range.gte'), 'lt': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='point.key < range.lt'), 'lte': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='point.key <= range.lte')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DeleteAlias(*, alias_name: str)[source]¶

Bases: BaseModel

Delete alias if exists

alias_name: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'alias_name': FieldInfo(annotation=str, required=True, description='Delete alias if exists')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DeleteAliasOperation(*, delete_alias: DeleteAlias)[source]¶

Bases: BaseModel

Delete alias if exists

delete_alias: DeleteAlias¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'delete_alias': FieldInfo(annotation=DeleteAlias, required=True, description='Delete alias if exists')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DeleteOperation(*, delete: Union[PointIdsList, FilterSelector])[source]¶

Bases: BaseModel

delete: PointsSelector¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'delete': FieldInfo(annotation=Union[PointIdsList, FilterSelector], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DeletePayload(*, keys: List[str], points: Optional[List[Union[int[int], str[str]]]] = None, filter: Optional[Filter] = None, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

This data structure is used in API interface and applied across multiple shards

filter: Optional[Filter]¶

keys: List[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Deletes values from points that satisfy this filter condition'), 'keys': FieldInfo(annotation=List[str], required=True, description='List of payload keys to remove from payload'), 'points': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Deletes values from each point in this list'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='This data structure is used in API interface and applied across multiple shards')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: Optional[List[ExtendedPointId]]¶

shard_key: Optional[ShardKeySelector]¶

class DeletePayloadOperation(*, delete_payload: DeletePayload)[source]¶

Bases: BaseModel

delete_payload: DeletePayload¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'delete_payload': FieldInfo(annotation=DeletePayload, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DeleteVectors(*, points: Optional[List[Union[int[int], str[str]]]] = None, filter: Optional[Filter] = None, vector: List[str], shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

filter: Optional[Filter]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Deletes values from points that satisfy this filter condition'), 'points': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Deletes values from each point in this list'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description=''), 'vector': FieldInfo(annotation=List[str], required=True, description='Vector names')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: Optional[List[ExtendedPointId]]¶

shard_key: Optional[ShardKeySelector]¶

vector: List[str]¶

class DeleteVectorsOperation(*, delete_vectors: DeleteVectors)[source]¶

Bases: BaseModel

delete_vectors: DeleteVectors¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'delete_vectors': FieldInfo(annotation=DeleteVectors, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class Direction(value)[source]¶

Bases: str, Enum

An enumeration.

ASC = 'asc'¶

DESC = 'desc'¶

class Disabled(value)[source]¶

Bases: str, Enum

An enumeration.

DISABLED = 'Disabled'¶

class DiscoverRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, target: Optional[Union[int[int], str[str], List[float[float]], SparseVector]] = None, context: Optional[List[ContextExamplePair]] = None, filter: Optional[Filter] = None, params: Optional[SearchParams] = None, limit: int, offset: Optional[int] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, using: Optional[str[str]] = None, lookup_from: Optional[LookupLocation] = None)[source]¶

Bases: BaseModel

Use context and a target to find the most similar points, constrained by the context.

context: Optional[List[ContextExamplePair]]¶

filter: Optional[Filter]¶

limit: int¶

lookup_from: Optional[LookupLocation]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'context': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.ContextExamplePair], NoneType], required=False, default=None, description='Pairs of { positive, negative } examples to constrain the search. When using only the context (without a target), a special search - called context search - is performed where pairs of points are used to generate a loss that guides the search towards the zone where most positive examples overlap. This means that the score minimizes the scenario of finding a point closer to a negative than to a positive part of a pair. Since the score of a context relates to loss, the maximum score a point can get is 0.0, and it becomes normal that many points can have a score of 0.0. For discovery search (when including a target), the context part of the score for each pair is calculated +1 if the point is closer to a positive than to a negative part of a pair, and -1 otherwise.'), 'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'limit': FieldInfo(annotation=int, required=True, description='Max number of result to return'), 'lookup_from': FieldInfo(annotation=Union[LookupLocation, NoneType], required=False, default=None, description='The location used to lookup vectors. If not specified - use current collection. Note: the other collection should have the same vector size as the current collection'), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.'), 'params': FieldInfo(annotation=Union[SearchParams, NoneType], required=False, default=None, description='Additional search params'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'target': FieldInfo(annotation=Union[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], SparseVector], NoneType], required=False, default=None, description='Look for vectors closest to this. When using the target (with or without context), the integer part of the score represents the rank with respect to the context, while the decimal part of the score relates to the distance to the target.'), 'using': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None, description='Define which vector to use for recommendation, if not specified - try to use default vector'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: None'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Whether to return the point vector with the result?')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

offset: Optional[int]¶

params: Optional[SearchParams]¶

shard_key: Optional[ShardKeySelector]¶

target: Optional[RecommendExample]¶

using: Optional[UsingVector]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class DiscoverRequestBatch(*, searches: List[DiscoverRequest])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'searches': FieldInfo(annotation=List[qdrant_client.http.models.models.DiscoverRequest], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

searches: List[DiscoverRequest]¶

class Distance(value)[source]¶

Bases: str, Enum

Type of internal tags, build from payload Distance function types used to compare vectors

COSINE = 'Cosine'¶

DOT = 'Dot'¶

EUCLID = 'Euclid'¶

MANHATTAN = 'Manhattan'¶

class DropReplicaOperation(*, drop_replica: Replica)[source]¶

Bases: BaseModel

drop_replica: Replica¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'drop_replica': FieldInfo(annotation=Replica, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class DropShardingKey(*, shard_key: Union[str[str], int[int]])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'shard_key': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: ShardKey¶

class DropShardingKeyOperation(*, drop_sharding_key: DropShardingKey)[source]¶

Bases: BaseModel

drop_sharding_key: DropShardingKey¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'drop_sharding_key': FieldInfo(annotation=DropShardingKey, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ErrorResponse(*, time: Optional[float] = None, status: Optional[ErrorResponseStatus] = None, result: Optional[Any] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[ErrorResponseStatus, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[Any]¶

status: Optional[ErrorResponseStatus]¶

time: Optional[float]¶

class ErrorResponseStatus(*, error: Optional[str] = None)[source]¶

Bases: BaseModel

error: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'error': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Description of the occurred error.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class FieldCondition(*, key: str, match: Optional[Union[MatchValue, MatchText, MatchAny, MatchExcept]] = None, range: Optional[Union[Range, DatetimeRange]] = None, geo_bounding_box: Optional[GeoBoundingBox] = None, geo_radius: Optional[GeoRadius] = None, geo_polygon: Optional[GeoPolygon] = None, values_count: Optional[ValuesCount] = None)[source]¶

Bases: BaseModel

All possible payload filtering conditions

geo_bounding_box: Optional[GeoBoundingBox]¶

geo_polygon: Optional[GeoPolygon]¶

geo_radius: Optional[GeoRadius]¶

key: str¶

match: Optional[Match]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'geo_bounding_box': FieldInfo(annotation=Union[GeoBoundingBox, NoneType], required=False, default=None, description='Check if points geo location lies in a given area'), 'geo_polygon': FieldInfo(annotation=Union[GeoPolygon, NoneType], required=False, default=None, description='Check if geo point is within a given polygon'), 'geo_radius': FieldInfo(annotation=Union[GeoRadius, NoneType], required=False, default=None, description='Check if geo point is within a given radius'), 'key': FieldInfo(annotation=str, required=True, description='Payload key'), 'match': FieldInfo(annotation=Union[Union[MatchValue, MatchText, MatchAny, MatchExcept], NoneType], required=False, default=None, description='Check if point has field with a given value'), 'range': FieldInfo(annotation=Union[Union[Range, DatetimeRange], NoneType], required=False, default=None, description='Check if points value lies in a given range'), 'values_count': FieldInfo(annotation=Union[ValuesCount, NoneType], required=False, default=None, description='Check number of values of the field')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

range: Optional[RangeInterface]¶

values_count: Optional[ValuesCount]¶

class Filter(*, should: Optional[List[Union[FieldCondition, IsEmptyCondition, IsNullCondition, HasIdCondition, NestedCondition, Filter]]] = None, min_should: Optional[MinShould] = None, must: Optional[List[Union[FieldCondition, IsEmptyCondition, IsNullCondition, HasIdCondition, NestedCondition, Filter]]] = None, must_not: Optional[List[Union[FieldCondition, IsEmptyCondition, IsNullCondition, HasIdCondition, NestedCondition, Filter]]] = None)[source]¶

Bases: BaseModel

min_should: Optional[MinShould]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'min_should': FieldInfo(annotation=Union[MinShould, NoneType], required=False, default=None, description='At least minimum amount of given conditions should match'), 'must': FieldInfo(annotation=Union[List[Union[qdrant_client.http.models.models.FieldCondition, qdrant_client.http.models.models.IsEmptyCondition, qdrant_client.http.models.models.IsNullCondition, qdrant_client.http.models.models.HasIdCondition, qdrant_client.http.models.models.NestedCondition, qdrant_client.http.models.models.Filter]], NoneType], required=False, default=None, description='All conditions must match'), 'must_not': FieldInfo(annotation=Union[List[Union[qdrant_client.http.models.models.FieldCondition, qdrant_client.http.models.models.IsEmptyCondition, qdrant_client.http.models.models.IsNullCondition, qdrant_client.http.models.models.HasIdCondition, qdrant_client.http.models.models.NestedCondition, qdrant_client.http.models.models.Filter]], NoneType], required=False, default=None, description='All conditions must NOT match'), 'should': FieldInfo(annotation=Union[List[Union[qdrant_client.http.models.models.FieldCondition, qdrant_client.http.models.models.IsEmptyCondition, qdrant_client.http.models.models.IsNullCondition, qdrant_client.http.models.models.HasIdCondition, qdrant_client.http.models.models.NestedCondition, qdrant_client.http.models.models.Filter]], NoneType], required=False, default=None, description='At least one of those conditions should match')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

must: Optional[List[Condition]]¶

must_not: Optional[List[Condition]]¶

should: Optional[List[Condition]]¶

class FilterSelector(*, filter: Filter, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

filter: Filter¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Filter, required=True, description=''), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: Optional[ShardKeySelector]¶

class GeoBoundingBox(*, top_left: GeoPoint, bottom_right: GeoPoint)[source]¶

Bases: BaseModel

Geo filter request Matches coordinates inside the rectangle, described by coordinates of lop-left and bottom-right edges

bottom_right: GeoPoint¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'bottom_right': FieldInfo(annotation=GeoPoint, required=True, description='Geo filter request Matches coordinates inside the rectangle, described by coordinates of lop-left and bottom-right edges'), 'top_left': FieldInfo(annotation=GeoPoint, required=True, description='Geo filter request Matches coordinates inside the rectangle, described by coordinates of lop-left and bottom-right edges')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

top_left: GeoPoint¶

class GeoLineString(*, points: List[GeoPoint])[source]¶

Bases: BaseModel

Ordered sequence of GeoPoints representing the line

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'points': FieldInfo(annotation=List[qdrant_client.http.models.models.GeoPoint], required=True, description='Ordered sequence of GeoPoints representing the line')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: List[GeoPoint]¶

class GeoPoint(*, lon: float, lat: float)[source]¶

Bases: BaseModel

Geo point payload schema

lat: float¶

lon: float¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'lat': FieldInfo(annotation=float, required=True, description='Geo point payload schema'), 'lon': FieldInfo(annotation=float, required=True, description='Geo point payload schema')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class GeoPolygon(*, exterior: GeoLineString, interiors: Optional[List[GeoLineString]] = None)[source]¶

Bases: BaseModel

Geo filter request Matches coordinates inside the polygon, defined by exterior and interiors

exterior: GeoLineString¶

interiors: Optional[List[GeoLineString]]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'exterior': FieldInfo(annotation=GeoLineString, required=True, description='Geo filter request Matches coordinates inside the polygon, defined by `exterior` and `interiors`'), 'interiors': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.GeoLineString], NoneType], required=False, default=None, description='Interior lines (if present) bound holes within the surface each GeoLineString must consist of a minimum of 4 points, and the first and last points must be the same.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class GeoRadius(*, center: GeoPoint, radius: float)[source]¶

Bases: BaseModel

Geo filter request Matches coordinates inside the circle of radius and center with coordinates center

center: GeoPoint¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'center': FieldInfo(annotation=GeoPoint, required=True, description='Geo filter request Matches coordinates inside the circle of `radius` and center with coordinates `center`'), 'radius': FieldInfo(annotation=float, required=True, description='Radius of the area in meters')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

radius: float¶

class GroupsResult(*, groups: List[PointGroup])[source]¶

Bases: BaseModel

groups: List[PointGroup]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'groups': FieldInfo(annotation=List[qdrant_client.http.models.models.PointGroup], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class GrpcTelemetry(*, responses: Dict[str, OperationDurationStatistics])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'responses': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.OperationDurationStatistics], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

responses: Dict[str, OperationDurationStatistics]¶

class HasIdCondition(*, has_id: List[Union[int[int], str[str]]])[source]¶

Bases: BaseModel

ID-based filtering condition

has_id: List[ExtendedPointId]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'has_id': FieldInfo(annotation=List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], required=True, description='ID-based filtering condition')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class HnswConfig(*, m: int, ef_construct: int, full_scan_threshold: int, max_indexing_threads: Optional[int] = 0, on_disk: Optional[bool] = None, payload_m: Optional[int] = None)[source]¶

Bases: BaseModel

Config of HNSW index

ef_construct: int¶

full_scan_threshold: int¶

m: int¶

max_indexing_threads: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'ef_construct': FieldInfo(annotation=int, required=True, description='Number of neighbours to consider during the index building. Larger the value - more accurate the search, more time required to build index.'), 'full_scan_threshold': FieldInfo(annotation=int, required=True, description='Minimal size (in KiloBytes) of vectors for additional payload-based indexing. If payload chunk is smaller than `full_scan_threshold_kb` additional indexing won't be used - in this case full-scan search should be preferred by query planner and additional indexing is not required. Note: 1Kb = 1 vector of size 256'), 'm': FieldInfo(annotation=int, required=True, description='Number of edges per node in the index graph. Larger the value - more accurate the search, more space required.'), 'max_indexing_threads': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, description='Number of parallel threads used for background index building. If 0 - automatically select from 8 to 16. Best to keep between 8 and 16 to prevent likelihood of slow building or broken/inefficient HNSW graphs. On small CPUs, less threads are used.'), 'on_disk': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='Store HNSW index on disk. If set to false, index will be stored in RAM. Default: false'), 'payload_m': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Custom M param for hnsw graph built for payload index. If not set, default M will be used.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk: Optional[bool]¶

payload_m: Optional[int]¶

class HnswConfigDiff(*, m: Optional[int] = None, ef_construct: Optional[int] = None, full_scan_threshold: Optional[int] = None, max_indexing_threads: Optional[int] = None, on_disk: Optional[bool] = None, payload_m: Optional[int] = None)[source]¶

Bases: BaseModel

ef_construct: Optional[int]¶

full_scan_threshold: Optional[int]¶

m: Optional[int]¶

max_indexing_threads: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'ef_construct': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of neighbours to consider during the index building. Larger the value - more accurate the search, more time required to build the index.'), 'full_scan_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Minimal size (in kilobytes) of vectors for additional payload-based indexing. If payload chunk is smaller than `full_scan_threshold_kb` additional indexing won't be used - in this case full-scan search should be preferred by query planner and additional indexing is not required. Note: 1Kb = 1 vector of size 256'), 'm': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of edges per node in the index graph. Larger the value - more accurate the search, more space required.'), 'max_indexing_threads': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of parallel threads used for background index building. If 0 - automatically select from 8 to 16. Best to keep between 8 and 16 to prevent likelihood of building broken/inefficient HNSW graphs. On small CPUs, less threads are used.'), 'on_disk': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='Store HNSW index on disk. If set to false, the index will be stored in RAM. Default: false'), 'payload_m': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Custom M param for additional payload-aware HNSW links. If not set, default M will be used.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk: Optional[bool]¶

payload_m: Optional[int]¶

class IndexesOneOf(*, type: Literal['plain'], options: Any)[source]¶

Bases: BaseModel

Do not use any index, scan whole vector collection during search. Guarantee 100% precision, but may be time consuming on large collections.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'options': FieldInfo(annotation=Any, required=True, description='Do not use any index, scan whole vector collection during search. Guarantee 100% precision, but may be time consuming on large collections.'), 'type': FieldInfo(annotation=Literal['plain'], required=True, description='Do not use any index, scan whole vector collection during search. Guarantee 100% precision, but may be time consuming on large collections.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

options: Any¶

type: Literal['plain']¶

class IndexesOneOf1(*, type: Literal['hnsw'], options: HnswConfig)[source]¶

Bases: BaseModel

Use filterable HNSW index for approximate search. Is very fast even on a very huge collections, but require additional space to store index and additional time to build it.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'options': FieldInfo(annotation=HnswConfig, required=True, description='Use filterable HNSW index for approximate search. Is very fast even on a very huge collections, but require additional space to store index and additional time to build it.'), 'type': FieldInfo(annotation=Literal['hnsw'], required=True, description='Use filterable HNSW index for approximate search. Is very fast even on a very huge collections, but require additional space to store index and additional time to build it.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

options: HnswConfig¶

type: Literal['hnsw']¶

class InitFrom(*, collection: str)[source]¶

Bases: BaseModel

Operation for creating new collection and (optionally) specify index params

collection: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'collection': FieldInfo(annotation=str, required=True, description='Operation for creating new collection and (optionally) specify index params')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class InlineResponse200(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[bool] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[bool]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2001(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[VersionInfo] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[VersionInfo, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[VersionInfo]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20010(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CollectionsAliasesResponse] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CollectionsAliasesResponse, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CollectionsAliasesResponse]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20011(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[List[SnapshotDescription]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.SnapshotDescription], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[List[SnapshotDescription]]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20012(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[SnapshotDescription] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[SnapshotDescription, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[SnapshotDescription]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20013(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[Record] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[Record, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[Record]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20014(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[List[Record]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.Record], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[List[Record]]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20015(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[List[UpdateResult]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.UpdateResult], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[List[UpdateResult]]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20016(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[ScrollResult] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[ScrollResult, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[ScrollResult]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20017(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[List[ScoredPoint]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[List[qdrant_client.http.models.models.ScoredPoint], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[List[ScoredPoint]]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20018(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[List[List[ScoredPoint]]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[List[List[qdrant_client.http.models.models.ScoredPoint]], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[List[List[ScoredPoint]]]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20019(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[GroupsResult] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[GroupsResult, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[GroupsResult]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2002(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[TelemetryData] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[TelemetryData, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[TelemetryData]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse20020(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CountResult] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CountResult, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CountResult]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2003(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[LocksOption] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[LocksOption, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[LocksOption]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2004(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[Union[ClusterStatusOneOf, ClusterStatusOneOf1]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[Union[ClusterStatusOneOf, ClusterStatusOneOf1], NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[ClusterStatus]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2005(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CollectionsResponse] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CollectionsResponse, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CollectionsResponse]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2006(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CollectionInfo] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CollectionInfo, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CollectionInfo]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2007(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[UpdateResult] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[UpdateResult, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[UpdateResult]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2008(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CollectionExistence] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CollectionExistence, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CollectionExistence]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse2009(*, time: Optional[float] = None, status: Optional[str] = None, result: Optional[CollectionClusterInfo] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'result': FieldInfo(annotation=Union[CollectionClusterInfo, NoneType], required=False, default=None, description=''), 'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

result: Optional[CollectionClusterInfo]¶

status: Optional[str]¶

time: Optional[float]¶

class InlineResponse202(*, time: Optional[float] = None, status: Optional[str] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'status': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'time': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Time spent to process this request')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

status: Optional[str]¶

time: Optional[float]¶

class IntegerIndexParams(*, type: IntegerIndexType, lookup: bool, range: bool)[source]¶

Bases: BaseModel

lookup: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'lookup': FieldInfo(annotation=bool, required=True, description='If true - support direct lookups.'), 'range': FieldInfo(annotation=bool, required=True, description='If true - support ranges filters.'), 'type': FieldInfo(annotation=IntegerIndexType, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

range: bool¶

type: IntegerIndexType¶

class IntegerIndexType(value)[source]¶

Bases: str, Enum

An enumeration.

INTEGER = 'integer'¶

class IsEmptyCondition(*, is_empty: PayloadField)[source]¶

Bases: BaseModel

Select points with empty payload for a specified field

is_empty: PayloadField¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'is_empty': FieldInfo(annotation=PayloadField, required=True, description='Select points with empty payload for a specified field')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class IsNullCondition(*, is_null: PayloadField)[source]¶

Bases: BaseModel

Select points with null payload for a specified field

is_null: PayloadField¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'is_null': FieldInfo(annotation=PayloadField, required=True, description='Select points with null payload for a specified field')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class LocalShardInfo(*, shard_id: int, shard_key: Optional[Union[str[str], int[int]]] = None, points_count: int, state: ReplicaState)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'points_count': FieldInfo(annotation=int, required=True, description='Number of points in the shard'), 'shard_id': FieldInfo(annotation=int, required=True, description='Local shard id'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], NoneType], required=False, default=None, description='User-defined sharding key'), 'state': FieldInfo(annotation=ReplicaState, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points_count: int¶

shard_id: int¶

shard_key: Optional[ShardKey]¶

state: ReplicaState¶

class LocalShardTelemetry(*, variant_name: Optional[str] = None, segments: List[SegmentTelemetry], optimizations: OptimizerTelemetry)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'optimizations': FieldInfo(annotation=OptimizerTelemetry, required=True, description=''), 'segments': FieldInfo(annotation=List[qdrant_client.http.models.models.SegmentTelemetry], required=True, description=''), 'variant_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizations: OptimizerTelemetry¶

segments: List[SegmentTelemetry]¶

variant_name: Optional[str]¶

class LocksOption(*, error_message: Optional[str] = None, write: bool)[source]¶

Bases: BaseModel

error_message: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'error_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'write': FieldInfo(annotation=bool, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

write: bool¶

class LookupLocation(*, collection: str, vector: Optional[str] = None, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

Defines a location to use for looking up the vector. Specifies collection and vector field name.

collection: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'collection': FieldInfo(annotation=str, required=True, description='Name of the collection used for lookup'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'vector': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Optional name of the vector field within the collection. If not provided, the default vector field will be used.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: Optional[ShardKeySelector]¶

vector: Optional[str]¶

class MatchAny(*, any: Union[List[str[str]], List[int[int]]])[source]¶

Bases: BaseModel

Exact match on any of the given values

any: AnyVariants¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'any': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], List[Annotated[int, Strict(strict=True)]]], required=True, description='Exact match on any of the given values')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class MatchExcept(*, except_: Union[List[str[str]], List[int[int]]])[source]¶

Bases: BaseModel

Should have at least one value not matching the any given values

except_: AnyVariants¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'except_': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], List[Annotated[int, Strict(strict=True)]]], required=True, alias='except', alias_priority=2, description='Should have at least one value not matching the any given values')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class MatchText(*, text: str)[source]¶

Bases: BaseModel

Full-text match of the strings.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'text': FieldInfo(annotation=str, required=True, description='Full-text match of the strings.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

text: str¶

class MatchValue(*, value: Union[str[str], int[int], bool[bool]])[source]¶

Bases: BaseModel

Exact match of the given value

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'value': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], Annotated[bool, Strict(strict=True)]], required=True, description='Exact match of the given value')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

value: ValueVariants¶

class MessageSendErrors(*, count: int, latest_error: Optional[str] = None, latest_error_timestamp: Optional[Union[datetime, date]] = None)[source]¶

Bases: BaseModel

Message send failures for a particular peer

count: int¶

latest_error: Optional[str]¶

latest_error_timestamp: Optional[Union[datetime.datetime, datetime.date]]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'count': FieldInfo(annotation=int, required=True, description='Message send failures for a particular peer'), 'latest_error': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Message send failures for a particular peer'), 'latest_error_timestamp': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='Timestamp of the latest error')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class MinShould(*, conditions: List[Union[FieldCondition, IsEmptyCondition, IsNullCondition, HasIdCondition, NestedCondition, Filter]], min_count: int)[source]¶

Bases: BaseModel

conditions: List[Condition]¶

min_count: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'conditions': FieldInfo(annotation=List[Union[qdrant_client.http.models.models.FieldCondition, qdrant_client.http.models.models.IsEmptyCondition, qdrant_client.http.models.models.IsNullCondition, qdrant_client.http.models.models.HasIdCondition, qdrant_client.http.models.models.NestedCondition, qdrant_client.http.models.models.Filter]], required=True, description=''), 'min_count': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class MoveShard(*, shard_id: int, to_peer_id: int, from_peer_id: int, method: Optional[Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2]] = None)[source]¶

Bases: BaseModel

from_peer_id: int¶

method: Optional[ShardTransferMethod]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'from_peer_id': FieldInfo(annotation=int, required=True, description=''), 'method': FieldInfo(annotation=Union[Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2], NoneType], required=False, default=None, description='Method for transferring the shard from one node to another'), 'shard_id': FieldInfo(annotation=int, required=True, description=''), 'to_peer_id': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_id: int¶

to_peer_id: int¶

class MoveShardOperation(*, move_shard: MoveShard)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'move_shard': FieldInfo(annotation=MoveShard, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

move_shard: MoveShard¶

MultiVectorConfig¶: alias of MultiVectorConfigOneOf

class MultiVectorConfigOneOf(*, max_sim: Any)[source]¶

Bases: BaseModel

max_sim: Any¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'max_sim': FieldInfo(annotation=Any, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class NamedSparseVector(*, name: str, vector: SparseVector)[source]¶

Bases: BaseModel

Sparse vector data with name

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, description='Name of vector data'), 'vector': FieldInfo(annotation=SparseVector, required=True, description='Sparse vector data with name')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

vector: SparseVector¶

class NamedVector(*, name: str, vector: List[float])[source]¶

Bases: BaseModel

Dense vector data with name

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, description='Name of vector data'), 'vector': FieldInfo(annotation=List[float], required=True, description='Vector data')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

vector: List[float]¶

class Nested(*, key: str, filter: Filter)[source]¶

Bases: BaseModel

Select points with payload for a specified nested field

filter: Filter¶

key: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Filter, required=True, description='Select points with payload for a specified nested field'), 'key': FieldInfo(annotation=str, required=True, description='Select points with payload for a specified nested field')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class NestedCondition(*, nested: Nested)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'nested': FieldInfo(annotation=Nested, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

nested: Nested¶

class OperationDurationStatistics(*, count: int, fail_count: Optional[int] = None, avg_duration_micros: Optional[float] = None, min_duration_micros: Optional[float] = None, max_duration_micros: Optional[float] = None, total_duration_micros: int, last_responded: Optional[Union[datetime, date]] = None)[source]¶

Bases: BaseModel

avg_duration_micros: Optional[float]¶

count: int¶

fail_count: Optional[int]¶

last_responded: Optional[Union[datetime.datetime, datetime.date]]¶

max_duration_micros: Optional[float]¶

min_duration_micros: Optional[float]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'avg_duration_micros': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The average time taken by 128 latest operations, calculated as a weighted mean.'), 'count': FieldInfo(annotation=int, required=True, description=''), 'fail_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'last_responded': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description=''), 'max_duration_micros': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The maximum duration of the operations across all the measurements.'), 'min_duration_micros': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The minimum duration of the operations across all the measurements.'), 'total_duration_micros': FieldInfo(annotation=int, required=True, description='The total duration of all operations in microseconds.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

total_duration_micros: int¶

class OptimizerTelemetry(*, status: Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], optimizations: OperationDurationStatistics, log: List[TrackerTelemetry])[source]¶

Bases: BaseModel

log: List[TrackerTelemetry]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'log': FieldInfo(annotation=List[qdrant_client.http.models.models.TrackerTelemetry], required=True, description=''), 'optimizations': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'status': FieldInfo(annotation=Union[OptimizersStatusOneOf, OptimizersStatusOneOf1], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizations: OperationDurationStatistics¶

status: OptimizersStatus¶

class OptimizersConfig(*, deleted_threshold: float, vacuum_min_vector_number: int, default_segment_number: int, max_segment_size: Optional[int] = None, memmap_threshold: Optional[int] = None, indexing_threshold: Optional[int] = None, flush_interval_sec: int, max_optimization_threads: Optional[int] = None)[source]¶

Bases: BaseModel

default_segment_number: int¶

deleted_threshold: float¶

flush_interval_sec: int¶

indexing_threshold: Optional[int]¶

max_optimization_threads: Optional[int]¶

max_segment_size: Optional[int]¶

memmap_threshold: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'default_segment_number': FieldInfo(annotation=int, required=True, description='Target amount of segments optimizer will try to keep. Real amount of segments may vary depending on multiple parameters: - Amount of stored points - Current write RPS It is recommended to select default number of segments as a factor of the number of search threads, so that each segment would be handled evenly by one of the threads. If `default_segment_number = 0`, will be automatically selected by the number of available CPUs.'), 'deleted_threshold': FieldInfo(annotation=float, required=True, description='The minimal fraction of deleted vectors in a segment, required to perform segment optimization'), 'flush_interval_sec': FieldInfo(annotation=int, required=True, description='Minimum interval between forced flushes.'), 'indexing_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Maximum size (in kilobytes) of vectors allowed for plain index, exceeding this threshold will enable vector indexing Default value is 20,000, based on <https://github.com/google-research/google-research/blob/master/scann/docs/algorithms.md>. To disable vector indexing, set to `0`. Note: 1kB = 1 vector of size 256.'), 'max_optimization_threads': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Max number of threads (jobs) for running optimizations per shard. Note: each optimization job will also use `max_indexing_threads` threads by itself for index building. If null - have no limit and choose dynamically to saturate CPU. If 0 - no optimization threads, optimizations will be disabled.'), 'max_segment_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Do not create segments larger this size (in kilobytes). Large segments might require disproportionately long indexation times, therefore it makes sense to limit the size of segments. If indexing speed is more important - make this parameter lower. If search speed is more important - make this parameter higher. Note: 1Kb = 1 vector of size 256 If not set, will be automatically selected considering the number of available CPUs.'), 'memmap_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Maximum size (in kilobytes) of vectors to store in-memory per segment. Segments larger than this threshold will be stored as read-only memmaped file. Memmap storage is disabled by default, to enable it, set this threshold to a reasonable value. To disable memmap storage, set this to `0`. Internally it will use the largest threshold possible. Note: 1Kb = 1 vector of size 256'), 'vacuum_min_vector_number': FieldInfo(annotation=int, required=True, description='The minimal number of vectors in a segment, required to perform segment optimization')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

vacuum_min_vector_number: int¶

class OptimizersConfigDiff(*, deleted_threshold: Optional[float] = None, vacuum_min_vector_number: Optional[int] = None, default_segment_number: Optional[int] = None, max_segment_size: Optional[int] = None, memmap_threshold: Optional[int] = None, indexing_threshold: Optional[int] = None, flush_interval_sec: Optional[int] = None, max_optimization_threads: Optional[int] = None)[source]¶

Bases: BaseModel

default_segment_number: Optional[int]¶

deleted_threshold: Optional[float]¶

flush_interval_sec: Optional[int]¶

indexing_threshold: Optional[int]¶

max_optimization_threads: Optional[int]¶

max_segment_size: Optional[int]¶

memmap_threshold: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'default_segment_number': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Target amount of segments optimizer will try to keep. Real amount of segments may vary depending on multiple parameters: - Amount of stored points - Current write RPS It is recommended to select default number of segments as a factor of the number of search threads, so that each segment would be handled evenly by one of the threads If `default_segment_number = 0`, will be automatically selected by the number of available CPUs'), 'deleted_threshold': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='The minimal fraction of deleted vectors in a segment, required to perform segment optimization'), 'flush_interval_sec': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Minimum interval between forced flushes.'), 'indexing_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Maximum size (in kilobytes) of vectors allowed for plain index, exceeding this threshold will enable vector indexing Default value is 20,000, based on <https://github.com/google-research/google-research/blob/master/scann/docs/algorithms.md>. To disable vector indexing, set to `0`. Note: 1kB = 1 vector of size 256.'), 'max_optimization_threads': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Max number of threads (jobs) for running optimizations per shard. Note: each optimization job will also use `max_indexing_threads` threads by itself for index building. If null - have no limit and choose dynamically to saturate CPU. If 0 - no optimization threads, optimizations will be disabled.'), 'max_segment_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Do not create segments larger this size (in kilobytes). Large segments might require disproportionately long indexation times, therefore it makes sense to limit the size of segments. If indexation speed have more priority for your - make this parameter lower. If search speed is more important - make this parameter higher. Note: 1Kb = 1 vector of size 256'), 'memmap_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Maximum size (in kilobytes) of vectors to store in-memory per segment. Segments larger than this threshold will be stored as read-only memmaped file. Memmap storage is disabled by default, to enable it, set this threshold to a reasonable value. To disable memmap storage, set this to `0`. Note: 1Kb = 1 vector of size 256'), 'vacuum_min_vector_number': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='The minimal number of vectors in a segment, required to perform segment optimization')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

vacuum_min_vector_number: Optional[int]¶

class OptimizersStatusOneOf(value)[source]¶

Bases: str, Enum

Optimizers are reporting as expected

OK = 'ok'¶

class OptimizersStatusOneOf1(*, error: str)[source]¶

Bases: BaseModel

Something wrong happened with optimizers

error: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'error': FieldInfo(annotation=str, required=True, description='Something wrong happened with optimizers')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class OrderBy(*, key: str, direction: Optional[Direction] = None, start_from: Optional[Union[int[int], float[float], datetime, date]] = None)[source]¶

Bases: BaseModel

direction: Optional[Direction]¶

key: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'direction': FieldInfo(annotation=Union[Direction, NoneType], required=False, default=None, description='Direction of ordering: `asc` or `desc`. Default is ascending.'), 'key': FieldInfo(annotation=str, required=True, description='Payload key to order by'), 'start_from': FieldInfo(annotation=Union[Union[Annotated[int, Strict(strict=True)], Annotated[float, Strict(strict=True)], datetime, date], NoneType], required=False, default=None, description='Which payload value to start scrolling from. Default is the lowest value for `asc` and the highest for `desc`')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

start_from: Optional[StartFrom]¶

class OverwritePayloadOperation(*, overwrite_payload: SetPayload)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'overwrite_payload': FieldInfo(annotation=SetPayload, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

overwrite_payload: SetPayload¶

class P2pConfigTelemetry(*, connection_pool_size: int)[source]¶

Bases: BaseModel

connection_pool_size: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'connection_pool_size': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class PayloadField(*, key: str)[source]¶

Bases: BaseModel

Payload field

key: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'key': FieldInfo(annotation=str, required=True, description='Payload field name')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class PayloadIndexInfo(*, data_type: PayloadSchemaType, params: Optional[Union[TextIndexParams, IntegerIndexParams]] = None, points: int)[source]¶

Bases: BaseModel

Display payload field type & index information

data_type: PayloadSchemaType¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'data_type': FieldInfo(annotation=PayloadSchemaType, required=True, description='Display payload field type & index information'), 'params': FieldInfo(annotation=Union[Union[TextIndexParams, IntegerIndexParams], NoneType], required=False, default=None, description='Display payload field type & index information'), 'points': FieldInfo(annotation=int, required=True, description='Number of points indexed with this index')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

params: Optional[PayloadSchemaParams]¶

points: int¶

class PayloadIndexTelemetry(*, field_name: Optional[str] = None, points_values_count: int, points_count: int, histogram_bucket_size: Optional[int] = None)[source]¶

Bases: BaseModel

field_name: Optional[str]¶

histogram_bucket_size: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'field_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'histogram_bucket_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'points_count': FieldInfo(annotation=int, required=True, description=''), 'points_values_count': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points_count: int¶

points_values_count: int¶

class PayloadSchemaType(value)[source]¶

Bases: str, Enum

All possible names of payload types

BOOL = 'bool'¶

DATETIME = 'datetime'¶

FLOAT = 'float'¶

GEO = 'geo'¶

INTEGER = 'integer'¶

KEYWORD = 'keyword'¶

TEXT = 'text'¶

class PayloadSelectorExclude(*, exclude: List[str])[source]¶

Bases: BaseModel

exclude: List[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'exclude': FieldInfo(annotation=List[str], required=True, description='Exclude this fields from returning payload')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class PayloadSelectorInclude(*, include: List[str])[source]¶

Bases: BaseModel

include: List[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'include': FieldInfo(annotation=List[str], required=True, description='Only include this payload keys')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class PayloadStorageTypeOneOf(*, type: Literal['in_memory'])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['in_memory'], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

type: Literal['in_memory']¶

class PayloadStorageTypeOneOf1(*, type: Literal['on_disk'])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['on_disk'], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

type: Literal['on_disk']¶

class PeerInfo(*, uri: str)[source]¶

Bases: BaseModel

Information of a peer in the cluster

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'uri': FieldInfo(annotation=str, required=True, description='Information of a peer in the cluster')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

uri: str¶

class PointGroup(*, hits: List[ScoredPoint], id: Union[str[str], int[int]], lookup: Optional[Record] = None)[source]¶

Bases: BaseModel

hits: List[ScoredPoint]¶

id: GroupId¶

lookup: Optional[Record]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hits': FieldInfo(annotation=List[qdrant_client.http.models.models.ScoredPoint], required=True, description='Scored points that have the same value of the group_by key'), 'id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], required=True, description=''), 'lookup': FieldInfo(annotation=Union[Record, NoneType], required=False, default=None, description='Record that has been looked up using the group id')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class PointIdsList(*, points: List[Union[int[int], str[str]]], shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'points': FieldInfo(annotation=List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], required=True, description=''), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: List[ExtendedPointId]¶

shard_key: Optional[ShardKeySelector]¶

class PointRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, ids: List[Union[int[int], str[str]]], with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None)[source]¶

Bases: BaseModel

ids: List[ExtendedPointId]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'ids': FieldInfo(annotation=List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], required=True, description='Look for points with ids'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: All'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: Optional[ShardKeySelector]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class PointStruct(*, id: Union[int[int], str[str]], vector: Union[List[float[float]], Dict[str[str], Union[List[float[float]], SparseVector]]], payload: Optional[Dict[str, Any]] = None)[source]¶

Bases: BaseModel

id: ExtendedPointId¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'id': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], required=True, description=''), 'payload': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None, description='Payload values (optional)'), 'vector': FieldInfo(annotation=Union[List[Annotated[float, Strict(strict=True)]], Dict[Annotated[str, Strict(strict=True)], Union[List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload: Optional[Payload]¶

vector: VectorStruct¶

class PointVectors(*, id: Union[int[int], str[str]], vector: Union[List[float[float]], Dict[str[str], Union[List[float[float]], SparseVector]]])[source]¶

Bases: BaseModel

id: ExtendedPointId¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'id': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], required=True, description=''), 'vector': FieldInfo(annotation=Union[List[Annotated[float, Strict(strict=True)]], Dict[Annotated[str, Strict(strict=True)], Union[List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

vector: VectorStruct¶

class PointsBatch(*, batch: Batch, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

batch: Batch¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'batch': FieldInfo(annotation=Batch, required=True, description=''), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_key: Optional[ShardKeySelector]¶

class PointsList(*, points: List[PointStruct], shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'points': FieldInfo(annotation=List[qdrant_client.http.models.models.PointStruct], required=True, description=''), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: List[PointStruct]¶

shard_key: Optional[ShardKeySelector]¶

class ProductQuantization(*, product: ProductQuantizationConfig)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'product': FieldInfo(annotation=ProductQuantizationConfig, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

product: ProductQuantizationConfig¶

class ProductQuantizationConfig(*, compression: CompressionRatio, always_ram: Optional[bool] = None)[source]¶

Bases: BaseModel

always_ram: Optional[bool]¶

compression: CompressionRatio¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'always_ram': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description=''), 'compression': FieldInfo(annotation=CompressionRatio, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class QuantizationSearchParams(*, ignore: Optional[bool] = False, rescore: Optional[bool] = None, oversampling: Optional[float] = None)[source]¶

Bases: BaseModel

Additional parameters of the search

ignore: Optional[bool]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'ignore': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, description='If true, quantized vectors are ignored. Default is false.'), 'oversampling': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Oversampling factor for quantization. Default is 1.0. Defines how many extra vectors should be pre-selected using quantized index, and then re-scored using original vectors. For example, if `oversampling` is 2.4 and `limit` is 100, then 240 vectors will be pre-selected using quantized index, and then top-100 will be returned after re-scoring.'), 'rescore': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true, use original vectors to re-score top-k results. Might require more time in case if original vectors are stored on disk. If not set, qdrant decides automatically apply rescoring or not.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

oversampling: Optional[float]¶

rescore: Optional[bool]¶

class RaftInfo(*, term: int, commit: int, pending_operations: int, leader: Optional[int] = None, role: Optional[StateRole] = None, is_voter: bool)[source]¶

Bases: BaseModel

Summary information about the current raft state

commit: int¶

is_voter: bool¶

leader: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'commit': FieldInfo(annotation=int, required=True, description='The index of the latest committed (finalized) operation that this peer is aware of.'), 'is_voter': FieldInfo(annotation=bool, required=True, description='Is this peer a voter or a learner'), 'leader': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Leader of the current term'), 'pending_operations': FieldInfo(annotation=int, required=True, description='Number of consensus operations pending to be applied on this peer'), 'role': FieldInfo(annotation=Union[StateRole, NoneType], required=False, default=None, description='Role of this peer in the current term'), 'term': FieldInfo(annotation=int, required=True, description='Raft divides time into terms of arbitrary length, each beginning with an election. If a candidate wins the election, it remains the leader for the rest of the term. The term number increases monotonically. Each server stores the current term number which is also exchanged in every communication.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

pending_operations: int¶

role: Optional[StateRole]¶

term: int¶

class Range(*, lt: Optional[float] = None, gt: Optional[float] = None, gte: Optional[float] = None, lte: Optional[float] = None)[source]¶

Bases: BaseModel

Range filter request

gt: Optional[float]¶

gte: Optional[float]¶

lt: Optional[float]¶

lte: Optional[float]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'gt': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='point.key > range.gt'), 'gte': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='point.key >= range.gte'), 'lt': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='point.key < range.lt'), 'lte': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='point.key <= range.lte')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class ReadConsistencyType(value)[source]¶

Bases: str, Enum

majority - send N/2+1 random request and return points, which present on all of them * quorum - send requests to all nodes and return points which present on majority of nodes * all - send requests to all nodes and return points which present on all nodes

ALL = 'all'¶

MAJORITY = 'majority'¶

QUORUM = 'quorum'¶

class RecommendGroupsRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, positive: Optional[List[Union[int[int], str[str], List[float[float]], SparseVector]]] = [], negative: Optional[List[Union[int[int], str[str], List[float[float]], SparseVector]]] = [], strategy: Optional[RecommendStrategy] = None, filter: Optional[Filter] = None, params: Optional[SearchParams] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, score_threshold: Optional[float] = None, using: Optional[str[str]] = None, lookup_from: Optional[LookupLocation] = None, group_by: str, group_size: int, limit: int, with_lookup: Optional[Union[str[str], WithLookup]] = None)[source]¶

Bases: BaseModel

filter: Optional[Filter]¶

group_by: str¶

group_size: int¶

limit: int¶

lookup_from: Optional[LookupLocation]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'group_by': FieldInfo(annotation=str, required=True, description='Payload field to group by, must be a string or number field. If the field contains more than 1 value, all values will be used for grouping. One point can be in multiple groups.'), 'group_size': FieldInfo(annotation=int, required=True, description='Maximum amount of points to return per group'), 'limit': FieldInfo(annotation=int, required=True, description='Maximum amount of groups to return'), 'lookup_from': FieldInfo(annotation=Union[LookupLocation, NoneType], required=False, default=None, description='The location used to lookup vectors. If not specified - use current collection. Note: the other collection should have the same vector size as the current collection'), 'negative': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]], NoneType], required=False, default=[], description='Try to avoid vectors like this'), 'params': FieldInfo(annotation=Union[SearchParams, NoneType], required=False, default=None, description='Additional search params'), 'positive': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]], NoneType], required=False, default=[], description='Look for vectors closest to those'), 'score_threshold': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'strategy': FieldInfo(annotation=Union[RecommendStrategy, NoneType], required=False, default=None, description='How to use positive and negative examples to find the results'), 'using': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None, description='Define which vector to use for recommendation, if not specified - try to use default vector'), 'with_lookup': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], WithLookup], NoneType], required=False, default=None, description='Look for points in another collection using the group ids'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: None'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Whether to return the point vector with the result?')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

negative: Optional[List[RecommendExample]]¶

params: Optional[SearchParams]¶

positive: Optional[List[RecommendExample]]¶

score_threshold: Optional[float]¶

shard_key: Optional[ShardKeySelector]¶

strategy: Optional[RecommendStrategy]¶

using: Optional[UsingVector]¶

with_lookup: Optional[WithLookupInterface]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class RecommendRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, positive: Optional[List[Union[int[int], str[str], List[float[float]], SparseVector]]] = [], negative: Optional[List[Union[int[int], str[str], List[float[float]], SparseVector]]] = [], strategy: Optional[RecommendStrategy] = None, filter: Optional[Filter] = None, params: Optional[SearchParams] = None, limit: int, offset: Optional[int] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, score_threshold: Optional[float] = None, using: Optional[str[str]] = None, lookup_from: Optional[LookupLocation] = None)[source]¶

Bases: BaseModel

Recommendation request. Provides positive and negative examples of the vectors, which can be ids of points that are already stored in the collection, raw vectors, or even ids and vectors combined. Service should look for the points which are closer to positive examples and at the same time further to negative examples. The concrete way of how to compare negative and positive distances is up to the strategy chosen.

filter: Optional[Filter]¶

limit: int¶

lookup_from: Optional[LookupLocation]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'limit': FieldInfo(annotation=int, required=True, description='Max number of result to return'), 'lookup_from': FieldInfo(annotation=Union[LookupLocation, NoneType], required=False, default=None, description='The location used to lookup vectors. If not specified - use current collection. Note: the other collection should have the same vector size as the current collection'), 'negative': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]], NoneType], required=False, default=[], description='Try to avoid vectors like this'), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.'), 'params': FieldInfo(annotation=Union[SearchParams, NoneType], required=False, default=None, description='Additional search params'), 'positive': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)], List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]], NoneType], required=False, default=[], description='Look for vectors closest to those'), 'score_threshold': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'strategy': FieldInfo(annotation=Union[RecommendStrategy, NoneType], required=False, default=None, description='How to use positive and negative examples to find the results'), 'using': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, default=None, description='Define which vector to use for recommendation, if not specified - try to use default vector'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: None'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Whether to return the point vector with the result?')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

negative: Optional[List[RecommendExample]]¶

offset: Optional[int]¶

params: Optional[SearchParams]¶

positive: Optional[List[RecommendExample]]¶

score_threshold: Optional[float]¶

shard_key: Optional[ShardKeySelector]¶

strategy: Optional[RecommendStrategy]¶

using: Optional[UsingVector]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class RecommendRequestBatch(*, searches: List[RecommendRequest])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'searches': FieldInfo(annotation=List[qdrant_client.http.models.models.RecommendRequest], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

searches: List[RecommendRequest]¶

class RecommendStrategy(value)[source]¶

Bases: str, Enum

How to use positive and negative examples to find the results, default is average_vector: * average_vector - Average positive and negative vectors and create a single query with the formula query = avg_pos + avg_pos - avg_neg. Then performs normal search. * best_score - Uses custom search objective. Each candidate is compared against all examples, its score is then chosen from the max(max_pos_score, max_neg_score). If the max_neg_score is chosen then it is squared and negated, otherwise it is just the max_pos_score.

AVERAGE_VECTOR = 'average_vector'¶

BEST_SCORE = 'best_score'¶

class Record(*, id: Union[int[int], str[str]], payload: Optional[Dict[str, Any]] = None, vector: Optional[Union[List[float[float]], Dict[str[str], Union[List[float[float]], SparseVector]]]] = None, shard_key: Optional[Union[str[str], int[int]]] = None)[source]¶

Bases: BaseModel

Point data

id: ExtendedPointId¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'id': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], required=True, description='Point data'), 'payload': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None, description='Payload - values assigned to the point'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], NoneType], required=False, default=None, description='Shard Key'), 'vector': FieldInfo(annotation=Union[Union[List[Annotated[float, Strict(strict=True)]], Dict[Annotated[str, Strict(strict=True)], Union[List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]]], NoneType], required=False, default=None, description='Vector of the point')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload: Optional[Payload]¶

shard_key: Optional[ShardKey]¶

vector: Optional[VectorStruct]¶

class RemoteShardInfo(*, shard_id: int, shard_key: Optional[Union[str[str], int[int]]] = None, peer_id: int, state: ReplicaState)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'peer_id': FieldInfo(annotation=int, required=True, description='Remote peer id'), 'shard_id': FieldInfo(annotation=int, required=True, description='Remote shard id'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], NoneType], required=False, default=None, description='User-defined sharding key'), 'state': FieldInfo(annotation=ReplicaState, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

peer_id: int¶

shard_id: int¶

shard_key: Optional[ShardKey]¶

state: ReplicaState¶

class RemoteShardTelemetry(*, shard_id: int, peer_id: Optional[int] = None, searches: OperationDurationStatistics, updates: OperationDurationStatistics)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'peer_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'searches': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'shard_id': FieldInfo(annotation=int, required=True, description=''), 'updates': FieldInfo(annotation=OperationDurationStatistics, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

peer_id: Optional[int]¶

searches: OperationDurationStatistics¶

shard_id: int¶

updates: OperationDurationStatistics¶

class RenameAlias(*, old_alias_name: str, new_alias_name: str)[source]¶

Bases: BaseModel

Change alias to a new one

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'new_alias_name': FieldInfo(annotation=str, required=True, description='Change alias to a new one'), 'old_alias_name': FieldInfo(annotation=str, required=True, description='Change alias to a new one')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

new_alias_name: str¶

old_alias_name: str¶

class RenameAliasOperation(*, rename_alias: RenameAlias)[source]¶

Bases: BaseModel

Change alias to a new one

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'rename_alias': FieldInfo(annotation=RenameAlias, required=True, description='Change alias to a new one')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

rename_alias: RenameAlias¶

class Replica(*, shard_id: int, peer_id: int)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'peer_id': FieldInfo(annotation=int, required=True, description=''), 'shard_id': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

peer_id: int¶

shard_id: int¶

class ReplicaSetTelemetry(*, id: int, local: Optional[LocalShardTelemetry] = None, remote: List[RemoteShardTelemetry], replicate_states: Dict[str, ReplicaState])[source]¶

Bases: BaseModel

id: int¶

local: Optional[LocalShardTelemetry]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, description=''), 'local': FieldInfo(annotation=Union[LocalShardTelemetry, NoneType], required=False, default=None, description=''), 'remote': FieldInfo(annotation=List[qdrant_client.http.models.models.RemoteShardTelemetry], required=True, description=''), 'replicate_states': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.ReplicaState], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

remote: List[RemoteShardTelemetry]¶

replicate_states: Dict[str, ReplicaState]¶

class ReplicaState(value)[source]¶

Bases: str, Enum

State of the single shard within a replica set.

ACTIVE = 'Active'¶

DEAD = 'Dead'¶

INITIALIZING = 'Initializing'¶

LISTENER = 'Listener'¶

PARTIAL = 'Partial'¶

PARTIALSNAPSHOT = 'PartialSnapshot'¶

RECOVERY = 'Recovery'¶

class ReplicateShardOperation(*, replicate_shard: MoveShard)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'replicate_shard': FieldInfo(annotation=MoveShard, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

replicate_shard: MoveShard¶

class RequestsTelemetry(*, rest: WebApiTelemetry, grpc: GrpcTelemetry)[source]¶

Bases: BaseModel

grpc: GrpcTelemetry¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'grpc': FieldInfo(annotation=GrpcTelemetry, required=True, description=''), 'rest': FieldInfo(annotation=WebApiTelemetry, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

rest: WebApiTelemetry¶

class RestartTransfer(*, shard_id: int, from_peer_id: int, to_peer_id: int, method: Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2])[source]¶

Bases: BaseModel

from_peer_id: int¶

method: ShardTransferMethod¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'from_peer_id': FieldInfo(annotation=int, required=True, description=''), 'method': FieldInfo(annotation=Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2], required=True, description=''), 'shard_id': FieldInfo(annotation=int, required=True, description=''), 'to_peer_id': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_id: int¶

to_peer_id: int¶

class RestartTransferOperation(*, restart_transfer: RestartTransfer)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'restart_transfer': FieldInfo(annotation=RestartTransfer, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

restart_transfer: RestartTransfer¶

class RunningEnvironmentTelemetry(*, distribution: Optional[str] = None, distribution_version: Optional[str] = None, is_docker: bool, cores: Optional[int] = None, ram_size: Optional[int] = None, disk_size: Optional[int] = None, cpu_flags: str)[source]¶

Bases: BaseModel

cores: Optional[int]¶

cpu_flags: str¶

disk_size: Optional[int]¶

distribution: Optional[str]¶

distribution_version: Optional[str]¶

is_docker: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'cores': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'cpu_flags': FieldInfo(annotation=str, required=True, description=''), 'disk_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'distribution': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'distribution_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'is_docker': FieldInfo(annotation=bool, required=True, description=''), 'ram_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

ram_size: Optional[int]¶

class ScalarQuantization(*, scalar: ScalarQuantizationConfig)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'scalar': FieldInfo(annotation=ScalarQuantizationConfig, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

scalar: ScalarQuantizationConfig¶

class ScalarQuantizationConfig(*, type: ScalarType, quantile: Optional[float] = None, always_ram: Optional[bool] = None)[source]¶

Bases: BaseModel

always_ram: Optional[bool]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'always_ram': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true - quantized vectors always will be stored in RAM, ignoring the config of main storage'), 'quantile': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Quantile for quantization. Expected value range in [0.5, 1.0]. If not set - use the whole range of values'), 'type': FieldInfo(annotation=ScalarType, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

quantile: Optional[float]¶

type: ScalarType¶

class ScalarType(value)[source]¶

Bases: str, Enum

An enumeration.

INT8 = 'int8'¶

class ScoredPoint(*, id: Union[int[int], str[str]], version: int, score: float, payload: Optional[Dict[str, Any]] = None, vector: Optional[Union[List[float[float]], Dict[str[str], Union[List[float[float]], SparseVector]]]] = None, shard_key: Optional[Union[str[str], int[int]]] = None)[source]¶

Bases: BaseModel

Search result

id: ExtendedPointId¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'id': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], required=True, description='Search result'), 'payload': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None, description='Payload - values assigned to the point'), 'score': FieldInfo(annotation=float, required=True, description='Points vector distance to the query vector'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]], NoneType], required=False, default=None, description='Shard Key'), 'vector': FieldInfo(annotation=Union[Union[List[Annotated[float, Strict(strict=True)]], Dict[Annotated[str, Strict(strict=True)], Union[List[Annotated[float, Strict(strict=True)]], qdrant_client.http.models.models.SparseVector]]], NoneType], required=False, default=None, description='Vector of the point'), 'version': FieldInfo(annotation=int, required=True, description='Point version')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload: Optional[Payload]¶

score: float¶

shard_key: Optional[ShardKey]¶

vector: Optional[VectorStruct]¶

version: int¶

class ScrollRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, offset: Optional[Union[int[int], str[str]]] = None, limit: Optional[int] = None, filter: Optional[Filter] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, order_by: Optional[Union[str[str], OrderBy]] = None)[source]¶

Bases: BaseModel

Scroll request - paginate over all points which matches given condition

filter: Optional[Filter]¶

limit: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions. If not provided - all points.'), 'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Page size. Default: 10'), 'offset': FieldInfo(annotation=Union[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], NoneType], required=False, default=None, description='Start ID to read points from.'), 'order_by': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], OrderBy], NoneType], required=False, default=None, description='Order the records by a payload field.'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: All'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Scroll request - paginate over all points which matches given condition')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

offset: Optional[ExtendedPointId]¶

order_by: Optional[OrderByInterface]¶

shard_key: Optional[ShardKeySelector]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class ScrollResult(*, points: List[Record], next_page_offset: Optional[Union[int[int], str[str]]] = None)[source]¶

Bases: BaseModel

Result of the points read request

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'next_page_offset': FieldInfo(annotation=Union[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]], NoneType], required=False, default=None, description='Offset which should be used to retrieve a next page result'), 'points': FieldInfo(annotation=List[qdrant_client.http.models.models.Record], required=True, description='List of retrieved points')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

next_page_offset: Optional[ExtendedPointId]¶

points: List[Record]¶

class SearchGroupsRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, vector: Union[List[float[float]], NamedVector, NamedSparseVector], filter: Optional[Filter] = None, params: Optional[SearchParams] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, score_threshold: Optional[float] = None, group_by: str, group_size: int, limit: int, with_lookup: Optional[Union[str[str], WithLookup]] = None)[source]¶

Bases: BaseModel

filter: Optional[Filter]¶

group_by: str¶

group_size: int¶

limit: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'group_by': FieldInfo(annotation=str, required=True, description='Payload field to group by, must be a string or number field. If the field contains more than 1 value, all values will be used for grouping. One point can be in multiple groups.'), 'group_size': FieldInfo(annotation=int, required=True, description='Maximum amount of points to return per group'), 'limit': FieldInfo(annotation=int, required=True, description='Maximum amount of groups to return'), 'params': FieldInfo(annotation=Union[SearchParams, NoneType], required=False, default=None, description='Additional search params'), 'score_threshold': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'vector': FieldInfo(annotation=Union[List[Annotated[float, Strict(strict=True)]], NamedVector, NamedSparseVector], required=True, description=''), 'with_lookup': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], WithLookup], NoneType], required=False, default=None, description='Look for points in another collection using the group ids'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: None'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Whether to return the point vector with the result?')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

params: Optional[SearchParams]¶

score_threshold: Optional[float]¶

shard_key: Optional[ShardKeySelector]¶

vector: NamedVectorStruct¶

with_lookup: Optional[WithLookupInterface]¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class SearchParams(*, hnsw_ef: Optional[int] = None, exact: Optional[bool] = False, quantization: Optional[QuantizationSearchParams] = None, indexed_only: Optional[bool] = False)[source]¶

Bases: BaseModel

Additional parameters of the search

exact: Optional[bool]¶

hnsw_ef: Optional[int]¶

indexed_only: Optional[bool]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'exact': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, description='Search without approximation. If set to true, search may run long but with exact results.'), 'hnsw_ef': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Params relevant to HNSW index Size of the beam in a beam-search. Larger the value - more accurate the result, more time required for search.'), 'indexed_only': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, description='If enabled, the engine will only perform search among indexed or small segments. Using this option prevents slow searches in case of delayed index, but does not guarantee that all uploaded vectors will be included in search results'), 'quantization': FieldInfo(annotation=Union[QuantizationSearchParams, NoneType], required=False, default=None, description='Quantization params')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

quantization: Optional[QuantizationSearchParams]¶

class SearchRequest(*, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, vector: Union[List[float[float]], NamedVector, NamedSparseVector], filter: Optional[Filter] = None, params: Optional[SearchParams] = None, limit: int, offset: Optional[int] = None, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vector: Optional[Union[bool[bool], List[str[str]]]] = None, score_threshold: Optional[float] = None)[source]¶

Bases: BaseModel

Search request. Holds all conditions and parameters for the search of most similar points by vector similarity given the filtering restrictions.

filter: Optional[Filter]¶

limit: int¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Look only for points which satisfies this conditions'), 'limit': FieldInfo(annotation=int, required=True, description='Max number of result to return'), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.'), 'params': FieldInfo(annotation=Union[SearchParams, NoneType], required=False, default=None, description='Additional search params'), 'score_threshold': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, description='Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='Specify in which shards to look for the points, if not specified - look in all shards'), 'vector': FieldInfo(annotation=Union[List[Annotated[float, Strict(strict=True)]], NamedVector, NamedSparseVector], required=True, description='Search request. Holds all conditions and parameters for the search of most similar points by vector similarity given the filtering restrictions.'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Select which payload to return with the response. Default: None'), 'with_vector': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Whether to return the point vector with the result?')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

offset: Optional[int]¶

params: Optional[SearchParams]¶

score_threshold: Optional[float]¶

shard_key: Optional[ShardKeySelector]¶

vector: NamedVectorStruct¶

with_payload: Optional[WithPayloadInterface]¶

with_vector: Optional[WithVector]¶

class SearchRequestBatch(*, searches: List[SearchRequest])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'searches': FieldInfo(annotation=List[qdrant_client.http.models.models.SearchRequest], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

searches: List[SearchRequest]¶

class SegmentConfig(*, vector_data: Optional[Dict[str, VectorDataConfig]] = {}, sparse_vector_data: Optional[Dict[str, SparseVectorDataConfig]] = None, payload_storage_type: Union[PayloadStorageTypeOneOf, PayloadStorageTypeOneOf1])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'payload_storage_type': FieldInfo(annotation=Union[PayloadStorageTypeOneOf, PayloadStorageTypeOneOf1], required=True, description=''), 'sparse_vector_data': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.SparseVectorDataConfig], NoneType], required=False, default=None, description=''), 'vector_data': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.VectorDataConfig], NoneType], required=False, default={}, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload_storage_type: PayloadStorageType¶

sparse_vector_data: Optional[Dict[str, SparseVectorDataConfig]]¶

vector_data: Optional[Dict[str, VectorDataConfig]]¶

class SegmentInfo(*, segment_type: SegmentType, num_vectors: int, num_points: int, num_indexed_vectors: int, num_deleted_vectors: int, ram_usage_bytes: int, disk_usage_bytes: int, is_appendable: bool, index_schema: Dict[str, PayloadIndexInfo], vector_data: Dict[str, VectorDataInfo])[source]¶

Bases: BaseModel

Aggregated information about segment

disk_usage_bytes: int¶

index_schema: Dict[str, PayloadIndexInfo]¶

is_appendable: bool¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'disk_usage_bytes': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'index_schema': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.PayloadIndexInfo], required=True, description='Aggregated information about segment'), 'is_appendable': FieldInfo(annotation=bool, required=True, description='Aggregated information about segment'), 'num_deleted_vectors': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'num_indexed_vectors': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'num_points': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'num_vectors': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'ram_usage_bytes': FieldInfo(annotation=int, required=True, description='Aggregated information about segment'), 'segment_type': FieldInfo(annotation=SegmentType, required=True, description='Aggregated information about segment'), 'vector_data': FieldInfo(annotation=Dict[str, qdrant_client.http.models.models.VectorDataInfo], required=True, description='Aggregated information about segment')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

num_deleted_vectors: int¶

num_indexed_vectors: int¶

num_points: int¶

num_vectors: int¶

ram_usage_bytes: int¶

segment_type: SegmentType¶

vector_data: Dict[str, VectorDataInfo]¶

class SegmentTelemetry(*, info: SegmentInfo, config: SegmentConfig, vector_index_searches: List[VectorIndexSearchesTelemetry], payload_field_indices: List[PayloadIndexTelemetry])[source]¶

Bases: BaseModel

config: SegmentConfig¶

info: SegmentInfo¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'config': FieldInfo(annotation=SegmentConfig, required=True, description=''), 'info': FieldInfo(annotation=SegmentInfo, required=True, description=''), 'payload_field_indices': FieldInfo(annotation=List[qdrant_client.http.models.models.PayloadIndexTelemetry], required=True, description=''), 'vector_index_searches': FieldInfo(annotation=List[qdrant_client.http.models.models.VectorIndexSearchesTelemetry], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload_field_indices: List[PayloadIndexTelemetry]¶

vector_index_searches: List[VectorIndexSearchesTelemetry]¶

class SegmentType(value)[source]¶

Bases: str, Enum

Type of segment

INDEXED = 'indexed'¶

PLAIN = 'plain'¶

SPECIAL = 'special'¶

class SetPayload(*, payload: Dict[str, Any], points: Optional[List[Union[int[int], str[str]]]] = None, filter: Optional[Filter] = None, shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None, key: Optional[str] = None)[source]¶

Bases: BaseModel

This data structure is used in API interface and applied across multiple shards

filter: Optional[Filter]¶

key: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filter': FieldInfo(annotation=Union[Filter, NoneType], required=False, default=None, description='Assigns payload to each point that satisfy this filter condition'), 'key': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Assigns payload to each point that satisfy this path of property'), 'payload': FieldInfo(annotation=Dict[str, Any], required=True, description='This data structure is used in API interface and applied across multiple shards'), 'points': FieldInfo(annotation=Union[List[Union[Annotated[int, Strict(strict=True)], Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Assigns payload to each point in this list'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='This data structure is used in API interface and applied across multiple shards')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

payload: Payload¶

points: Optional[List[ExtendedPointId]]¶

shard_key: Optional[ShardKeySelector]¶

class SetPayloadOperation(*, set_payload: SetPayload)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'set_payload': FieldInfo(annotation=SetPayload, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

set_payload: SetPayload¶

class ShardSnapshotRecover(*, location: str[str], priority: Optional[SnapshotPriority] = None, checksum: Optional[str] = None)[source]¶

Bases: BaseModel

checksum: Optional[str]¶

location: ShardSnapshotLocation¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'checksum': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Optional SHA256 checksum to verify snapshot integrity before recovery.'), 'location': FieldInfo(annotation=str, required=True, description='', metadata=[Strict(strict=True)]), 'priority': FieldInfo(annotation=Union[SnapshotPriority, NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

priority: Optional[SnapshotPriority]¶

class ShardTransferInfo(*, shard_id: int, from_: int, to: int, sync: bool, method: Optional[Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2]] = None, comment: Optional[str] = None)[source]¶

Bases: BaseModel

comment: Optional[str]¶

from_: int¶

method: Optional[ShardTransferMethod]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'comment': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='A human-readable report of the transfer progress. Available only on the source peer.'), 'from_': FieldInfo(annotation=int, required=True, alias='from', alias_priority=2, description='Source peer id'), 'method': FieldInfo(annotation=Union[Union[ShardTransferMethodOneOf, ShardTransferMethodOneOf1, ShardTransferMethodOneOf2], NoneType], required=False, default=None, description=''), 'shard_id': FieldInfo(annotation=int, required=True, description=''), 'sync': FieldInfo(annotation=bool, required=True, description='If `true` transfer is a synchronization of a replicas If `false` transfer is a moving of a shard from one peer to another'), 'to': FieldInfo(annotation=int, required=True, description='Destination peer id')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

shard_id: int¶

sync: bool¶

to: int¶

class ShardTransferMethodOneOf(value)[source]¶

Bases: str, Enum

Stream all shard records in batches until the whole shard is transferred.

STREAM_RECORDS = 'stream_records'¶

class ShardTransferMethodOneOf1(value)[source]¶

Bases: str, Enum

Snapshot the shard, transfer and restore it on the receiver.

SNAPSHOT = 'snapshot'¶

class ShardTransferMethodOneOf2(value)[source]¶

Bases: str, Enum

Attempt to transfer shard difference by WAL delta.

WAL_DELTA = 'wal_delta'¶

class ShardingMethod(value)[source]¶

Bases: str, Enum

An enumeration.

AUTO = 'auto'¶

CUSTOM = 'custom'¶

class SnapshotDescription(*, name: str, creation_time: Optional[str] = None, size: int, checksum: Optional[str] = None)[source]¶

Bases: BaseModel

checksum: Optional[str]¶

creation_time: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'checksum': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'creation_time': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'name': FieldInfo(annotation=str, required=True, description=''), 'size': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

size: int¶

class SnapshotPriority(value)[source]¶

Bases: str, Enum

Defines source of truth for snapshot recovery: NoSync means - restore snapshot without any additional synchronization. Snapshot means - prefer snapshot data over the current state. Replica means - prefer existing data over the snapshot.

NO_SYNC = 'no_sync'¶

REPLICA = 'replica'¶

SNAPSHOT = 'snapshot'¶

class SnapshotRecover(*, location: str, priority: Optional[SnapshotPriority] = None, checksum: Optional[str] = None)[source]¶

Bases: BaseModel

checksum: Optional[str]¶

location: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'checksum': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Optional SHA256 checksum to verify snapshot integrity before recovery.'), 'location': FieldInfo(annotation=str, required=True, description='Examples: - URL `http://localhost:8080/collections/my_collection/snapshots/my_snapshot` - Local path `file:///qdrant/snapshots/test_collection-2022-08-04-10-49-10.snapshot`'), 'priority': FieldInfo(annotation=Union[SnapshotPriority, NoneType], required=False, default=None, description='Defines which data should be used as a source of truth if there are other replicas in the cluster. If set to `Snapshot`, the snapshot will be used as a source of truth, and the current state will be overwritten. If set to `Replica`, the current state will be used as a source of truth, and after recovery if will be synchronized with the snapshot.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

priority: Optional[SnapshotPriority]¶

class SparseIndexConfig(*, full_scan_threshold: Optional[int] = None, index_type: Union[SparseIndexTypeOneOf, SparseIndexTypeOneOf1, SparseIndexTypeOneOf2])[source]¶

Bases: BaseModel

Configuration for sparse inverted index.

full_scan_threshold: Optional[int]¶

index_type: SparseIndexType¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'full_scan_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='We prefer a full scan search upto (excluding) this number of vectors. Note: this is number of vectors, not KiloBytes.'), 'index_type': FieldInfo(annotation=Union[SparseIndexTypeOneOf, SparseIndexTypeOneOf1, SparseIndexTypeOneOf2], required=True, description='Configuration for sparse inverted index.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class SparseIndexParams(*, full_scan_threshold: Optional[int] = None, on_disk: Optional[bool] = None)[source]¶

Bases: BaseModel

Configuration for sparse inverted index.

full_scan_threshold: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'full_scan_threshold': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='We prefer a full scan search upto (excluding) this number of vectors. Note: this is number of vectors, not KiloBytes.'), 'on_disk': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='Store index on disk. If set to false, the index will be stored in RAM. Default: false')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk: Optional[bool]¶

class SparseIndexTypeOneOf(value)[source]¶

Bases: str, Enum

Mutable RAM sparse index

MUTABLERAM = 'MutableRam'¶

class SparseIndexTypeOneOf1(value)[source]¶

Bases: str, Enum

Immutable RAM sparse index

IMMUTABLERAM = 'ImmutableRam'¶

class SparseIndexTypeOneOf2(value)[source]¶

Bases: str, Enum

Mmap sparse index

MMAP = 'Mmap'¶

class SparseVector(*, indices: List[int], values: List[float])[source]¶

Bases: BaseModel

Sparse vector structure

indices: List[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'indices': FieldInfo(annotation=List[int], required=True, description='indices must be unique'), 'values': FieldInfo(annotation=List[float], required=True, description='values and indices must be the same length')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

values: List[float]¶

class SparseVectorDataConfig(*, index: SparseIndexConfig)[source]¶

Bases: BaseModel

Config of single sparse vector data storage

index: SparseIndexConfig¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'index': FieldInfo(annotation=SparseIndexConfig, required=True, description='Config of single sparse vector data storage')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class SparseVectorParams(*, index: Optional[SparseIndexParams] = None)[source]¶

Bases: BaseModel

Params of single sparse vector data storage

index: Optional[SparseIndexParams]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'index': FieldInfo(annotation=Union[SparseIndexParams, NoneType], required=False, default=None, description='Custom params for index. If none - values from collection configuration are used.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class StateRole(value)[source]¶

Bases: str, Enum

Role of the peer in the consensus

CANDIDATE = 'Candidate'¶

FOLLOWER = 'Follower'¶

LEADER = 'Leader'¶

PRECANDIDATE = 'PreCandidate'¶

class TelemetryData(*, id: str, app: AppBuildTelemetry, collections: CollectionsTelemetry, cluster: ClusterTelemetry, requests: RequestsTelemetry)[source]¶

Bases: BaseModel

app: AppBuildTelemetry¶

cluster: ClusterTelemetry¶

collections: CollectionsTelemetry¶

id: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'app': FieldInfo(annotation=AppBuildTelemetry, required=True, description=''), 'cluster': FieldInfo(annotation=ClusterTelemetry, required=True, description=''), 'collections': FieldInfo(annotation=CollectionsTelemetry, required=True, description=''), 'id': FieldInfo(annotation=str, required=True, description=''), 'requests': FieldInfo(annotation=RequestsTelemetry, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

requests: RequestsTelemetry¶

class TextIndexParams(*, type: TextIndexType, tokenizer: Optional[TokenizerType] = None, min_token_len: Optional[int] = None, max_token_len: Optional[int] = None, lowercase: Optional[bool] = None)[source]¶

Bases: BaseModel

lowercase: Optional[bool]¶

max_token_len: Optional[int]¶

min_token_len: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'lowercase': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true, lowercase all tokens. Default: true'), 'max_token_len': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'min_token_len': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description=''), 'tokenizer': FieldInfo(annotation=Union[TokenizerType, NoneType], required=False, default=None, description=''), 'type': FieldInfo(annotation=TextIndexType, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

tokenizer: Optional[TokenizerType]¶

type: TextIndexType¶

class TextIndexType(value)[source]¶

Bases: str, Enum

An enumeration.

TEXT = 'text'¶

class TokenizerType(value)[source]¶

Bases: str, Enum

An enumeration.

MULTILINGUAL = 'multilingual'¶

PREFIX = 'prefix'¶

WHITESPACE = 'whitespace'¶

WORD = 'word'¶

class TrackerStatusOneOf(value)[source]¶

Bases: str, Enum

An enumeration.

DONE = 'done'¶

OPTIMIZING = 'optimizing'¶

class TrackerStatusOneOf1(*, cancelled: str)[source]¶

Bases: BaseModel

cancelled: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'cancelled': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class TrackerStatusOneOf2(*, error: str)[source]¶

Bases: BaseModel

error: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'error': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class TrackerTelemetry(*, name: str, segment_ids: List[int], status: Union[TrackerStatusOneOf, TrackerStatusOneOf1, TrackerStatusOneOf2], start_at: Union[datetime, date], end_at: Optional[Union[datetime, date]] = None)[source]¶

Bases: BaseModel

Tracker object used in telemetry

end_at: Optional[Union[datetime.datetime, datetime.date]]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'end_at': FieldInfo(annotation=Union[datetime, date, NoneType], required=False, default=None, description='End time of the optimizer'), 'name': FieldInfo(annotation=str, required=True, description='Name of the optimizer'), 'segment_ids': FieldInfo(annotation=List[int], required=True, description='Segment IDs being optimized'), 'start_at': FieldInfo(annotation=Union[datetime, date], required=True, description='Start time of the optimizer'), 'status': FieldInfo(annotation=Union[TrackerStatusOneOf, TrackerStatusOneOf1, TrackerStatusOneOf2], required=True, description='Tracker object used in telemetry')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

name: str¶

segment_ids: List[int]¶

start_at: Union[datetime.datetime, datetime.date]¶

status: TrackerStatus¶

class UpdateCollection(*, vectors: Optional[Dict[str, VectorParamsDiff]] = None, optimizers_config: Optional[OptimizersConfigDiff] = None, params: Optional[CollectionParamsDiff] = None, hnsw_config: Optional[HnswConfigDiff] = None, quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization, Disabled]] = None, sparse_vectors: Optional[Dict[str, SparseVectorParams]] = None)[source]¶

Bases: BaseModel

Operation for updating parameters of the existing collection

hnsw_config: Optional[HnswConfigDiff]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hnsw_config': FieldInfo(annotation=Union[HnswConfigDiff, NoneType], required=False, default=None, description='HNSW parameters to update for the collection index. If none - it is left unchanged.'), 'optimizers_config': FieldInfo(annotation=Union[OptimizersConfigDiff, NoneType], required=False, default=None, description='Custom params for Optimizers. If none - it is left unchanged. This operation is blocking, it will only proceed once all current optimizations are complete'), 'params': FieldInfo(annotation=Union[CollectionParamsDiff, NoneType], required=False, default=None, description='Collection base params. If none - it is left unchanged.'), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization, Disabled], NoneType], required=False, default=None, description='Quantization parameters to update. If none - it is left unchanged.'), 'sparse_vectors': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.SparseVectorParams], NoneType], required=False, default=None, description='Map of sparse vector data parameters to update for each sparse vector.'), 'vectors': FieldInfo(annotation=Union[Dict[str, qdrant_client.http.models.models.VectorParamsDiff], NoneType], required=False, default=None, description='Map of vector data parameters to update for each named vector. To update parameters in a collection having a single unnamed vector, use an empty string as name.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

optimizers_config: Optional[OptimizersConfigDiff]¶

params: Optional[CollectionParamsDiff]¶

quantization_config: Optional[QuantizationConfigDiff]¶

sparse_vectors: Optional[SparseVectorsConfig]¶

vectors: Optional[VectorsConfigDiff]¶

class UpdateOperations(*, operations: List[Union[UpsertOperation, DeleteOperation, SetPayloadOperation, OverwritePayloadOperation, DeletePayloadOperation, ClearPayloadOperation, UpdateVectorsOperation, DeleteVectorsOperation]])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'operations': FieldInfo(annotation=List[Union[qdrant_client.http.models.models.UpsertOperation, qdrant_client.http.models.models.DeleteOperation, qdrant_client.http.models.models.SetPayloadOperation, qdrant_client.http.models.models.OverwritePayloadOperation, qdrant_client.http.models.models.DeletePayloadOperation, qdrant_client.http.models.models.ClearPayloadOperation, qdrant_client.http.models.models.UpdateVectorsOperation, qdrant_client.http.models.models.DeleteVectorsOperation]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

operations: List[UpdateOperation]¶

class UpdateResult(*, operation_id: Optional[int] = None, status: UpdateStatus)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'operation_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Sequential number of the operation'), 'status': FieldInfo(annotation=UpdateStatus, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

operation_id: Optional[int]¶

status: UpdateStatus¶

class UpdateStatus(value)[source]¶

Bases: str, Enum

Acknowledged - Request is saved to WAL and will be process in a queue. Completed - Request is completed, changes are actual.

ACKNOWLEDGED = 'acknowledged'¶

COMPLETED = 'completed'¶

class UpdateVectors(*, points: List[PointVectors], shard_key: Optional[Union[str[str], int[int], List[Union[str[str], int[int]]]]] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'points': FieldInfo(annotation=List[qdrant_client.http.models.models.PointVectors], required=True, description='Points with named vectors'), 'shard_key': FieldInfo(annotation=Union[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)], List[Union[Annotated[str, Strict(strict=True)], Annotated[int, Strict(strict=True)]]]], NoneType], required=False, default=None, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

points: List[PointVectors]¶

shard_key: Optional[ShardKeySelector]¶

class UpdateVectorsOperation(*, update_vectors: UpdateVectors)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'update_vectors': FieldInfo(annotation=UpdateVectors, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

update_vectors: UpdateVectors¶

class UpsertOperation(*, upsert: Union[PointsBatch, PointsList])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'upsert': FieldInfo(annotation=Union[PointsBatch, PointsList], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

upsert: PointInsertOperations¶

class ValuesCount(*, lt: Optional[int] = None, gt: Optional[int] = None, gte: Optional[int] = None, lte: Optional[int] = None)[source]¶

Bases: BaseModel

Values count filter request

gt: Optional[int]¶

gte: Optional[int]¶

lt: Optional[int]¶

lte: Optional[int]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'gt': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='point.key.length() > values_count.gt'), 'gte': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='point.key.length() >= values_count.gte'), 'lt': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='point.key.length() < values_count.lt'), 'lte': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='point.key.length() <= values_count.lte')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

class VectorDataConfig(*, size: int, distance: Distance, storage_type: Union[VectorStorageTypeOneOf, VectorStorageTypeOneOf1, VectorStorageTypeOneOf2], index: Union[IndexesOneOf, IndexesOneOf1], quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization]] = None, multi_vec_config: Optional[MultiVectorConfigOneOf] = None, datatype: Optional[VectorStorageDatatype] = None)[source]¶

Bases: BaseModel

Config of single vector data storage

datatype: Optional[VectorStorageDatatype]¶

distance: Distance¶

index: Indexes¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'datatype': FieldInfo(annotation=Union[VectorStorageDatatype, NoneType], required=False, default=None, description='Vector specific configuration to set specific storage element type'), 'distance': FieldInfo(annotation=Distance, required=True, description='Config of single vector data storage'), 'index': FieldInfo(annotation=Union[IndexesOneOf, IndexesOneOf1], required=True, description='Config of single vector data storage'), 'multi_vec_config': FieldInfo(annotation=Union[MultiVectorConfigOneOf, NoneType], required=False, default=None, description='Vector specific configuration to enable multiple vectors per point'), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization], NoneType], required=False, default=None, description='Vector specific quantization config that overrides collection config'), 'size': FieldInfo(annotation=int, required=True, description='Size/dimensionality of the vectors used'), 'storage_type': FieldInfo(annotation=Union[VectorStorageTypeOneOf, VectorStorageTypeOneOf1, VectorStorageTypeOneOf2], required=True, description='Config of single vector data storage')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

multi_vec_config: Optional[MultiVectorConfig]¶

quantization_config: Optional[QuantizationConfig]¶

size: int¶

storage_type: VectorStorageType¶

class VectorDataInfo(*, num_vectors: int, num_indexed_vectors: int, num_deleted_vectors: int)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'num_deleted_vectors': FieldInfo(annotation=int, required=True, description=''), 'num_indexed_vectors': FieldInfo(annotation=int, required=True, description=''), 'num_vectors': FieldInfo(annotation=int, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

num_deleted_vectors: int¶

num_indexed_vectors: int¶

num_vectors: int¶

class VectorIndexSearchesTelemetry(*, index_name: Optional[str] = None, unfiltered_plain: OperationDurationStatistics, unfiltered_hnsw: OperationDurationStatistics, unfiltered_sparse: OperationDurationStatistics, filtered_plain: OperationDurationStatistics, filtered_small_cardinality: OperationDurationStatistics, filtered_large_cardinality: OperationDurationStatistics, filtered_exact: OperationDurationStatistics, filtered_sparse: OperationDurationStatistics, unfiltered_exact: OperationDurationStatistics)[source]¶

Bases: BaseModel

filtered_exact: OperationDurationStatistics¶

filtered_large_cardinality: OperationDurationStatistics¶

filtered_plain: OperationDurationStatistics¶

filtered_small_cardinality: OperationDurationStatistics¶

filtered_sparse: OperationDurationStatistics¶

index_name: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'filtered_exact': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'filtered_large_cardinality': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'filtered_plain': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'filtered_small_cardinality': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'filtered_sparse': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'index_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'unfiltered_exact': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'unfiltered_hnsw': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'unfiltered_plain': FieldInfo(annotation=OperationDurationStatistics, required=True, description=''), 'unfiltered_sparse': FieldInfo(annotation=OperationDurationStatistics, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

unfiltered_exact: OperationDurationStatistics¶

unfiltered_hnsw: OperationDurationStatistics¶

unfiltered_plain: OperationDurationStatistics¶

unfiltered_sparse: OperationDurationStatistics¶

class VectorParams(*, size: int, distance: Distance, hnsw_config: Optional[HnswConfigDiff] = None, quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization]] = None, on_disk: Optional[bool] = None, datatype: Optional[Datatype] = None)[source]¶

Bases: BaseModel

Params of single vector data storage

datatype: Optional[Datatype]¶

distance: Distance¶

hnsw_config: Optional[HnswConfigDiff]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'datatype': FieldInfo(annotation=Union[Datatype, NoneType], required=False, default=None, description='Params of single vector data storage'), 'distance': FieldInfo(annotation=Distance, required=True, description='Params of single vector data storage'), 'hnsw_config': FieldInfo(annotation=Union[HnswConfigDiff, NoneType], required=False, default=None, description='Custom params for HNSW index. If none - values from collection configuration are used.'), 'on_disk': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true, vectors are served from disk, improving RAM usage at the cost of latency Default: false'), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization], NoneType], required=False, default=None, description='Custom params for quantization. If none - values from collection configuration are used.'), 'size': FieldInfo(annotation=int, required=True, description='Size of a vectors used')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk: Optional[bool]¶

quantization_config: Optional[QuantizationConfig]¶

size: int¶

class VectorParamsDiff(*, hnsw_config: Optional[HnswConfigDiff] = None, quantization_config: Optional[Union[ScalarQuantization, ProductQuantization, BinaryQuantization, Disabled]] = None, on_disk: Optional[bool] = None)[source]¶

Bases: BaseModel

hnsw_config: Optional[HnswConfigDiff]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'hnsw_config': FieldInfo(annotation=Union[HnswConfigDiff, NoneType], required=False, default=None, description='Update params for HNSW index. If empty object - it will be unset.'), 'on_disk': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, description='If true, vectors are served from disk, improving RAM usage at the cost of latency'), 'quantization_config': FieldInfo(annotation=Union[Union[ScalarQuantization, ProductQuantization, BinaryQuantization, Disabled], NoneType], required=False, default=None, description='Update params for quantization. If none - it is left unchanged.')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

on_disk: Optional[bool]¶

quantization_config: Optional[QuantizationConfigDiff]¶

class VectorStorageDatatype(value)[source]¶

Bases: str, Enum

Storage types for vectors

FLOAT32 = 'float32'¶

UINT8 = 'uint8'¶

class VectorStorageTypeOneOf(value)[source]¶

Bases: str, Enum

Storage in memory (RAM) Will be very fast at the cost of consuming a lot of memory.

MEMORY = 'Memory'¶

class VectorStorageTypeOneOf1(value)[source]¶

Bases: str, Enum

Storage in mmap file, not appendable Search performance is defined by disk speed and the fraction of vectors that fit in memory.

MMAP = 'Mmap'¶

class VectorStorageTypeOneOf2(value)[source]¶

Bases: str, Enum

Storage in chunked mmap files, appendable Search performance is defined by disk speed and the fraction of vectors that fit in memory.

CHUNKEDMMAP = 'ChunkedMmap'¶

class VersionInfo(*, title: str, version: str, commit: Optional[str] = None)[source]¶

Bases: BaseModel

commit: Optional[str]¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'commit': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description=''), 'title': FieldInfo(annotation=str, required=True, description=''), 'version': FieldInfo(annotation=str, required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

title: str¶

version: str¶

class WalConfig(*, wal_capacity_mb: int, wal_segments_ahead: int)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'wal_capacity_mb': FieldInfo(annotation=int, required=True, description='Size of a single WAL segment in MB'), 'wal_segments_ahead': FieldInfo(annotation=int, required=True, description='Number of WAL segments to create ahead of actually used ones')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

wal_capacity_mb: int¶

wal_segments_ahead: int¶

class WalConfigDiff(*, wal_capacity_mb: Optional[int] = None, wal_segments_ahead: Optional[int] = None)[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'wal_capacity_mb': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Size of a single WAL segment in MB'), 'wal_segments_ahead': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, description='Number of WAL segments to create ahead of actually used ones')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

wal_capacity_mb: Optional[int]¶

wal_segments_ahead: Optional[int]¶

class WebApiTelemetry(*, responses: Dict[str, Dict[str, OperationDurationStatistics]])[source]¶

Bases: BaseModel

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'responses': FieldInfo(annotation=Dict[str, Dict[str, qdrant_client.http.models.models.OperationDurationStatistics]], required=True, description='')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

responses: Dict[str, Dict[str, OperationDurationStatistics]]¶

class WithLookup(*, collection: str, with_payload: Optional[Union[bool[bool], List[str[str]], PayloadSelectorInclude, PayloadSelectorExclude]] = None, with_vectors: Optional[Union[bool[bool], List[str[str]]]] = None)[source]¶

Bases: BaseModel

collection: str¶

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}¶: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'collection': FieldInfo(annotation=str, required=True, description='Name of the collection to use for points lookup'), 'with_payload': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]], PayloadSelectorInclude, PayloadSelectorExclude], NoneType], required=False, default=None, description='Options for specifying which payload to include (or not)'), 'with_vectors': FieldInfo(annotation=Union[Union[Annotated[bool, Strict(strict=True)], List[Annotated[str, Strict(strict=True)]]], NoneType], required=False, default=None, description='Options for specifying which vectors to include (or not)')}¶

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

with_payload: Optional[WithPayloadInterface]¶

with_vectors: Optional[WithVector]¶

class WriteOrdering(value)[source]¶

Bases: str, Enum

Defines write ordering guarantees for collection operations * weak - write operations may be reordered, works faster, default * medium - write operations go through dynamically selected leader, may be inconsistent for a short period of time in case of leader change * strong - Write operations go through the permanent leader, consistent, but may be unavailable if leader is down

MEDIUM = 'medium'¶

STRONG = 'strong'¶

WEAK = 'weak'¶

qdrant_client.http.models.models module¶

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