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NamespaceModel.md

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NamespaceModel

Namespace model.

Properties

Name Type Description Notes
namespace_id str Unique identifier for the namespace [optional]
namespace_name str Name of the namespace
namespace_type NamespaceType Type of namespace. STANDARD for regular namespaces, MARKETPLACE for curated datasets that can be subscribed to. [optional]
infrastructure NamespaceInfrastructure Infrastructure configuration for the namespace (Ray, Qdrant). [optional]
cluster_id str Infrastructure cluster ID for this namespace (Enterprise only). When set, this namespace uses dedicated Anyscale/Ray + Qdrant cluster. If None, uses shared infrastructure or organization-level infrastructure. Format: iclstr_xxx [optional]
description str Description of the namespace [optional]
feature_extractors List[BaseFeatureExtractorModelOutput] List of feature extractors configured for this namespace [optional]
payload_indexes List[PayloadIndexConfigOutput] Custom payload indexes configured for this namespace [optional]
document_count int Total number of documents in this namespace (from Qdrant collection) [optional]
bucket_count int Total number of buckets in this namespace [optional]
collection_count int Total number of collections in this namespace [optional]
object_count int Total number of objects across all buckets in this namespace [optional]
auto_create_indexes bool Enable automatic creation of Qdrant payload indexes based on filter usage patterns. When enabled, the system tracks which fields are most frequently filtered (>100 queries/24h) and automatically creates indexes to improve query performance. Background task runs every 6 hours. Expected performance improvement: 50-90% latency reduction for filtered queries. [optional] [default to False]
vector_inference_map Dict[str, str] Mapping of vector index names to inference service names. Built at namespace creation based on extractor configurations. Used by feature search to determine correct inference service for queries. Example: {'image_extractor_v1_embedding': 'google_siglip_base_v1'} [optional]
created_at datetime When the namespace was created [optional]
updated_at datetime When the namespace was last updated [optional]

Example

from mixpeek.models.namespace_model import NamespaceModel

# TODO update the JSON string below
json = "{}"
# create an instance of NamespaceModel from a JSON string
namespace_model_instance = NamespaceModel.from_json(json)
# print the JSON string representation of the object
print(NamespaceModel.to_json())

# convert the object into a dict
namespace_model_dict = namespace_model_instance.to_dict()
# create an instance of NamespaceModel from a dict
namespace_model_from_dict = NamespaceModel.from_dict(namespace_model_dict)

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