Configuration for cluster execution when trigger fires. Defines what clustering algorithm and parameters to use when the trigger executes. Examples: K-means clustering on 3 collections: { "collection_ids": ["col_abc123", "col_def456", "col_ghi789"], "config": { "algorithm": "kmeans", "n_clusters": 5, "min_cluster_size": 2 } } HDBSCAN clustering on single collection: { "collection_ids": ["col_products"], "config": { "algorithm": "hdbscan", "min_cluster_size": 10, "min_samples": 5 } }
| Name | Type | Description | Notes |
|---|---|---|---|
| collection_ids | List[str] | REQUIRED. List of collection IDs to cluster when trigger fires. Must contain at least one collection ID. All collections will be clustered together using the specified algorithm. | |
| config | Dict[str, object] | REQUIRED. Clustering algorithm configuration. Must include 'algorithm' field ('kmeans', 'hdbscan', 'hierarchical'). Additional fields depend on algorithm choice. K-means requires 'n_clusters'. HDBSCAN requires 'min_cluster_size'. |
from mixpeek.models.trigger_execution_config import TriggerExecutionConfig
# TODO update the JSON string below
json = "{}"
# create an instance of TriggerExecutionConfig from a JSON string
trigger_execution_config_instance = TriggerExecutionConfig.from_json(json)
# print the JSON string representation of the object
print(TriggerExecutionConfig.to_json())
# convert the object into a dict
trigger_execution_config_dict = trigger_execution_config_instance.to_dict()
# create an instance of TriggerExecutionConfig from a dict
trigger_execution_config_from_dict = TriggerExecutionConfig.from_dict(trigger_execution_config_dict)