Centroid information from a clustering execution. Represents a single cluster center from a clustering run, including LLM-generated semantic labels for human understanding. Use Cases: - Display cluster information in dashboards - Show cluster labels and summaries in UI - Group documents by semantic meaning - Filter/search by cluster keywords Note: This model is for execution metadata only (no visualization coordinates). For scatter plot coordinates, use ArtifactCentroid from the artifacts endpoint.
| Name | Type | Description | Notes |
|---|---|---|---|
| cluster_id | str | REQUIRED. Unique identifier for this cluster within the execution. Format: 'cl_' prefix followed by numeric index (e.g., 'cl_0', 'cl_1'). Used to reference this specific cluster in queries and enrichments. Consistent across executions if algorithm deterministic. | |
| num_members | int | REQUIRED. Number of documents/points assigned to this cluster. Indicates cluster size for sizing bubbles in visualizations. Minimum: 1 (K-Means forces assignment). Can be 0 for noise clusters in HDBSCAN (cluster_id = -1). | |
| label | str | OPTIONAL. Human-readable label generated by LLM (e.g., GPT-4o-mini). Automatically generated when llm_labeling.enabled = true in cluster config. NOT REQUIRED when LLM labeling disabled. Describes the semantic meaning of documents in this cluster. Example: 'Product Reviews', 'Technical Documentation', 'Customer Support'. | [optional] |
| summary | str | OPTIONAL. Detailed description generated by LLM. Automatically generated when llm_labeling.include_summary = true. NOT REQUIRED when LLM labeling disabled or summary not requested. Provides context about what types of documents are in this cluster. Useful for tooltips, expanded views, or detailed explanations. | [optional] |
| keywords | List[str] | OPTIONAL. List of semantic keywords generated by LLM. Automatically generated when llm_labeling.include_keywords = true. NOT REQUIRED when LLM labeling disabled or keywords not requested. Useful for search, filtering, and quick cluster understanding. Typically 3-5 keywords per cluster. | [optional] |
from mixpeek.models.cluster_execution_centroid import ClusterExecutionCentroid
# TODO update the JSON string below
json = "{}"
# create an instance of ClusterExecutionCentroid from a JSON string
cluster_execution_centroid_instance = ClusterExecutionCentroid.from_json(json)
# print the JSON string representation of the object
print(ClusterExecutionCentroid.to_json())
# convert the object into a dict
cluster_execution_centroid_dict = cluster_execution_centroid_instance.to_dict()
# create an instance of ClusterExecutionCentroid from a dict
cluster_execution_centroid_from_dict = ClusterExecutionCentroid.from_dict(cluster_execution_centroid_dict)