Execute Clustering

Execution mode:

• full: Run complete clustering pipeline (default)
• assign: Incremental assignment — assign new documents to existing cluster centroids without re-clustering. Requires a previous successful execution with centroids.
• composite: Cluster centroids from multiple prior executions to create cross-execution cluster groupings. Requires source_execution_ids pointing to completed runs with centroids.

Minimum cosine similarity to assign a document to a cluster (only used when mode='assign'). Documents below this threshold are marked as noise (cluster_id=-1). Range: 0.0-1.0.

Optional per-execution document cap. When provided, overrides the cluster's stored sample_size for this execution only. The override is not persisted on the cluster. KMeans supports up to 1M; O(N²) algorithms (HDBSCAN, Spectral, Agglomerative) are capped at 50K by the engine.

Number of dimensions for visualization coordinates (2 or 3). When 3, the z coordinate is populated for depth-based rendering.

When True, skip inline UMAP during clustering and compute the scatter coordinates lazily at /visualization time. UMAP is ~90% of the clustering critical path at scale, so this makes large runs complete much faster; the first scatter load pays a one-time bounded cost. The override is not persisted on the cluster.

Optional layout-stability override for this execution (LS-5). 'align' registers the new layout onto the previous run's coordinates (default when the cluster stores nothing), 'transform' reuses the previous run's saved projection reducer when compatible, 'none' re-layouts independently. The override is not persisted on the cluster.

Unique identifier for the task. REQUIRED. Used to poll task status via GET /v1/tasks/{task_id}. This ID is also stored on parent resources (batches, clusters, etc.) for cross-referencing. Format: UUID v4 or custom string identifier.

Types of asynchronous tasks that can be performed in the system.

Task types identify the specific operation being performed. This helps with tracking, debugging, and filtering tasks by operation type.

Categories: API Tasks: User-initiated operations via API endpoints Engine Tasks: Background processing tasks Inference Tasks: Specialized inference operations

API Task Types: API_NAMESPACES_CREATE: Creating a new namespace API_NAMESPACES_MIGRATIONS_RUN: Running a namespace migration API_BUCKETS_OBJECTS_CREATE: Creating objects in a bucket API_BUCKETS_DELETE: Deleting a bucket and its contents API_BUCKETS_BATCHES_PROCESS: Processing a batch of objects API_BUCKETS_BATCHES_SUBMIT: Submitting a batch for processing API_BUCKETS_UPLOADS_CREATE: Creating an upload session API_BUCKETS_UPLOADS_CONFIRM: Confirming an upload completion API_BUCKETS_UPLOADS_BATCH_CONFIRM: Confirming batch upload completion API_TAXONOMIES_CREATE: Creating a new taxonomy API_TAXONOMIES_EXECUTE: Executing taxonomy classification API_TAXONOMIES_MATERIALIZE: Materializing taxonomy results API_RETRIEVERS_PUBLISH: Publishing retriever assets (OG images, etc.)

Engine Task Types: ENGINE_FEATURE_EXTRACTOR_RUN: Running feature extraction on data ENGINE_INFERENCE_RUN: Running inference operations ENGINE_OBJECT_PROCESSING: Processing object data ENGINE_CLUSTER_BUILD: Building clusters from data

Inference Task Types: THUMBNAIL: Generating thumbnails MATERIALIZE: Materializing processed data

Usage: Task types are automatically assigned when tasks are created. You can filter tasks by type when listing or searching for specific operations.

Enumeration of task statuses for tracking asynchronous operations.

Task statuses indicate the current state of asynchronous operations like batch processing, object ingestion, clustering, and taxonomy execution.

Status Categories: Operation Statuses: Track progress of async operations Lifecycle Statuses: Track entity state (buckets, collections, namespaces)

Values: PENDING: Task is queued but has not started processing yet IN_PROGRESS: Task is currently being executed PROCESSING: Task is actively processing data (similar to IN_PROGRESS) COMPLETED: Task finished successfully with no errors COMPLETED_WITH_ERRORS: Task finished but some items failed (partial success) FAILED: Task encountered an error and could not complete CANCELED: Task was manually canceled by a user or system UNKNOWN: Task status could not be determined SKIPPED: Task was intentionally skipped DRAFT: Task is in draft state and not yet submitted

ACTIVE: Entity is active and operational (for buckets, collections, etc.)
ARCHIVED: Entity has been archived
SUSPENDED: Entity has been temporarily suspended

Terminal Statuses: COMPLETED, COMPLETED_WITH_ERRORS, FAILED, CANCELED are terminal statuses. Once a task reaches these states, it will not transition to another state.

Partial Success Handling: COMPLETED_WITH_ERRORS indicates that the operation completed but some documents/items failed. The task result includes: - List of successful items - List of failed items with error details - Success rate percentage This allows clients to handle partial success scenarios appropriately.

Polling Guidance: - Poll tasks in PENDING, QUEUED, IN_PROGRESS, or PROCESSING states - Stop polling when task reaches COMPLETED, COMPLETED_WITH_ERRORS, FAILED, or CANCELED - Use exponential backoff (1s → 30s) when polling

Flattened error message for convenient error handling. OPTIONAL. Automatically populated from additional_data['error'] when the task has FAILED status. This is a convenience field - the full error details are always available in additional_data['error']. Use this field for displaying errors to users or logging. Will be None if task has not failed or if no error details are available. Serialized as 'error' in API responses for backward compatibility.

1-based position in the Ray processing waitlist. None if the batch was dispatched immediately (no queue). Position 1 means this batch will be processed next.

Estimated minutes until this batch starts processing, based on queue position and average batch duration. None if the batch was dispatched immediately.