Create a clustering job for one or more collections.
| Name | Type | Description | Notes |
|---|---|---|---|
| collection_ids | List[str] | Collections to cluster together | |
| cluster_name | str | Optional human-friendly name for the clustering job | [optional] |
| cluster_type | ClusterType | Vector or attribute clustering | [optional] |
| vector_config | VectorBasedConfigInput | Required when cluster_type is 'vector' | [optional] |
| attribute_config | AttributeBasedConfig | Required when cluster_type is 'attribute' | [optional] |
| filters | LogicalOperatorInput | Optional filters to pre-filter documents before clustering (same format as list documents). Applied during Qdrant scroll before parquet export. Useful for clustering subsets like: status='active', category='electronics', etc. | [optional] |
| llm_labeling | LLMLabelingInput | Optional configuration for LLM-based cluster labeling. When provided with enabled=True, clusters will have semantic labels generated by LLM instead of generic labels like 'Cluster 0'. When not provided or enabled=False, uses fallback labels. | [optional] |
| enrich_source_collection | bool | If True, cluster results are written back to source collection(s) in-place instead of creating new output collections. Documents will be enriched with cluster_id, cluster_label, distance_to_centroid, and optionally other metadata. Similar to taxonomy enrichment pattern. | [optional] [default to False] |
| source_enrichment_config | SourceEnrichmentConfig | Configuration for source collection enrichment (only used if enrich_source_collection=True). Controls which fields are added to source documents and field naming conventions. | [optional] |
from mixpeek.models.create_cluster_request import CreateClusterRequest
# TODO update the JSON string below
json = "{}"
# create an instance of CreateClusterRequest from a JSON string
create_cluster_request_instance = CreateClusterRequest.from_json(json)
# print the JSON string representation of the object
print(CreateClusterRequest.to_json())
# convert the object into a dict
create_cluster_request_dict = create_cluster_request_instance.to_dict()
# create an instance of CreateClusterRequest from a dict
create_cluster_request_from_dict = CreateClusterRequest.from_dict(create_cluster_request_dict)