Operators, Sensors & Hooks

This page is the full reference for the Arize AX Airflow Provider. It lists every operator, sensor, and hook in the package, grouped by the resource each one acts on. For setup, connection configuration, and patterns, start with the provider overview.

Import paths

Every class lives under the airflow.providers.arize_ax namespace:

# Operators: one module per resource domain
from airflow.providers.arize_ax.operators.datasets       import ...
from airflow.providers.arize_ax.operators.experiments    import ...
from airflow.providers.arize_ax.operators.projects       import ...
from airflow.providers.arize_ax.operators.spans          import ...
from airflow.providers.arize_ax.operators.ml             import ...
from airflow.providers.arize_ax.operators.evaluators     import ...
from airflow.providers.arize_ax.operators.tasks          import ...
from airflow.providers.arize_ax.operators.prompts        import ...
from airflow.providers.arize_ax.operators.spaces         import ...
from airflow.providers.arize_ax.operators.annotations    import ...
from airflow.providers.arize_ax.operators.api_keys       import ...
from airflow.providers.arize_ax.operators.ai_integrations import ...

# Sensors: a single module
from airflow.providers.arize_ax.sensors.arize_ax import ...

# Hook: used by every operator under the hood
from airflow.providers.arize_ax.hooks.arize_ax import ArizeAxHook

Common params. Every operator accepts arize_ax_conn_id (default arize_ax_default). Most accept space_id, which the provider resolves in this order: the operator argument, then the connection’s extra.default_space, then the Airflow Variable arize_ax_space_id. Create* operators accept if_exists="skip" for idempotent re-runs. Delete* and Get* operators accept ignore_if_missing=True. See design patterns.

Hook

ArizeAxHook is the only hook class. Every operator instantiates it in execute() to get a cached ArizeClient. You only use the hook directly when no operator covers your pattern.

from airflow.providers.arize_ax.hooks.arize_ax import ArizeAxHook

hook = ArizeAxHook(arize_ax_conn_id="arize_ax_default")
client = hook.get_conn()  # cached ArizeClient
datasets = hook.list_datasets(space_id="...", limit=50)

The hook exposes typed wrappers for every resource the operators cover (list_datasets, create_experiment, export_spans_to_df, trigger_task_run, log_spans, list_evaluators, and so on). It also handles pagination, retries transient Flight errors on span exports, and re-raises SDK 404s and backend errors as AirflowException with clear messages.

Datasets

Module: airflow.providers.arize_ax.operators.datasets

Operator	Purpose	Key params
`ArizeAxListDatasetsOperator`	List datasets in a space.	`space_id`, `limit`, `cursor`
`ArizeAxCreateDatasetOperator`	Create a dataset, optionally with starter examples.	`space_id`, `name`, `examples` or `examples_path`, `if_exists`
`ArizeAxGetDatasetOperator`	Fetch a dataset by ID.	`dataset_id`
`ArizeAxDeleteDatasetOperator`	Delete a dataset.	`dataset_id`, `ignore_if_missing`
`ArizeAxListDatasetExamplesOperator`	List examples in a dataset (or a specific version).	`dataset_id`, `dataset_version_id`, `limit`, `all`
`ArizeAxAppendDatasetExamplesOperator`	Append examples from memory, CSV, or JSON.	`dataset_id`, `examples` or `examples_path`
`ArizeAxExportDatasetExamplesToFileOperator`	Export all examples to JSON (paginated via SDK Flight).	`dataset_id`, `path`, `dataset_version_id`
`ArizeAxEvalDatasetHealthOperator`	Score a dataset on freshness, diversity, and coverage vs production.	`dataset_id`, `project_id`, `start_time`, `end_time`
`ArizeAxSmartDatasetRefreshOperator`	Evolve a dataset with diverse, high-value production examples.	`dataset_id`, `project_id`, `start_time`, `end_time`, `diversity_strategy`

Experiments

Module: airflow.providers.arize_ax.operators.experiments

Operator	Purpose	Key params
`ArizeAxListExperimentsOperator`	List experiments for a dataset.	`dataset_id`, `limit`, `cursor`
`ArizeAxCreateExperimentOperator`	Create experiment with pre-computed runs.	`name`, `dataset_id`, `experiment_runs`, `task_fields`, `evaluator_columns`, `if_exists`
`ArizeAxGetExperimentOperator`	Fetch an experiment by ID.	`experiment_id`
`ArizeAxDeleteExperimentOperator`	Delete an experiment.	`experiment_id`, `ignore_if_missing`
`ArizeAxRunExperimentOperator`	Run a task + evaluators end-to-end against a dataset.	`name`, `dataset_id`, `task`, `evaluators`, `concurrency`, `dry_run`
`ArizeAxListExperimentRunsOperator`	List runs for an experiment.	`experiment_id`, `limit`, `cursor`
`ArizeAxExportExperimentRunsToFileOperator`	Export all runs to a JSON file.	`experiment_id`, `path`
`ArizeAxGetExperimentScoreOperator`	Aggregate eval scores; gates on `min_score`.	`experiment_id`, `metric_names`, `aggregation`, `min_score`
`ArizeAxCompareExperimentsOperator`	Compare candidate vs baseline; gates on regression.	`candidate_experiment_id`, `baseline_experiment_id`, `pass_threshold`, `fail_on_regression`
`ArizeAxDetectEvalDriftOperator`	Detect metric drift between experiments; gates on drift.	`experiment_id`, `baseline_id`, `drift_threshold`, `fail_on_drift`
`ArizeAxEvaluatorCalibrationOperator`	Measure LLM-judge correlation vs human labels; gates on calibration.	`experiment_id`, `human_label_column`, `calibration_threshold`, `fail_on_poor_calibration`
`ArizeAxBehavioralRegressionOperator`	Compare behavioral distributions; gates on regression.	`candidate_id`, `baseline_id`, `metrics`, `fail_on_regression`
`ArizeAxEvalBudgetAllocatorOperator`	Distribute evaluation budget across projects.	`projects`, `total_budget`, `allocation_strategy`

Projects

Module: airflow.providers.arize_ax.operators.projects

Operator	Purpose	Key params
`ArizeAxListProjectsOperator`	List projects in a space.	`space_id`, `limit`, `cursor`
`ArizeAxCreateProjectOperator`	Create a project.	`space_id`, `name`, `if_exists`
`ArizeAxGetProjectOperator`	Fetch a project by ID.	`project_id`
`ArizeAxDeleteProjectOperator`	Delete a project.	`project_id`, `ignore_if_missing`

Spans

Module: airflow.providers.arize_ax.operators.spans

Operator	Purpose	Key params
`ArizeAxListSpansOperator`	List spans from a project (alpha).	`project_id`, `space_id`, `filter`, `start_time`, `end_time`
`ArizeAxSpansLogOperator`	Bulk-log spans from DataFrame, CSV, or JSON.	`space_id`, `project_name`, `dataframe` or `dataframe_path`, `evals_dataframe`
`ArizeAxSpansUpdateEvaluationsOperator`	Update span evaluations from a DataFrame.	`space_id`, `project_name`, `dataframe` or `dataframe_path`
`ArizeAxSpansUpdateAnnotationsOperator`	Update span annotations from a DataFrame.	`space_id`, `project_name`, `dataframe` or `dataframe_path`
`ArizeAxSpansUpdateMetadataOperator`	Update span metadata from a DataFrame.	`space_id`, `project_name`, `dataframe` or `dataframe_path`
`ArizeAxSpansExportToDataframeOperator`	Export filtered spans to a DataFrame.	`space_id`, `project_name`, `start_time`, `end_time`, `where`, `columns`
`ArizeAxSpansExportToParquetOperator`	Export filtered spans to a Parquet file.	`space_id`, `project_name`, `start_time`, `end_time`, `path`, `where`
`ArizeAxExportSpansToFineTuningOperator`	Export spans as OpenAI fine-tuning JSONL.	`space_id`, `project_name`, `start_time`, `end_time`, `path`
`ArizeAxGetSpanMetricsOperator`	Aggregate latency, cost, and token metrics.	`space_id`, `project_name`, `start_time`, `end_time`
`ArizeAxCurateSpansToDatasetOperator`	Curate filtered spans into a dataset.	`space_id`, `project_name`, `dataset_id`, `where`
`ArizeAxExportAnnotatedSpansOperator`	Export annotated spans to Parquet or JSON.	`space_id`, `project_name`, `start_time`, `end_time`, `path`, `format`
`ArizeAxAdaptiveSamplingOperator`	Pick priority spans for evaluation via uncertainty/novelty/anomaly.	`space_id`, `project_name`, `sample_size`, `strategy`

ML

Module: airflow.providers.arize_ax.operators.ml

Operator	Purpose	Key params
`ArizeAxMLLogBatchOperator`	Batch-log ML predictions from DataFrame or CSV.	`space_id`, `model_name`, `model_type`, `environment`, `dataframe`, `schema`
`ArizeAxMLLogStreamOperator`	Stream a single ML prediction.	`space_id`, `model_name`, `model_type`, `environment`, `log_params`
`ArizeAxMLExportToDataframeOperator`	Export ML data to a DataFrame.	`space_id`, `model_name`, `environment`, `start_time`, `end_time`, `where`
`ArizeAxMLExportToParquetOperator`	Export ML data to a Parquet file.	`space_id`, `model_name`, `environment`, `start_time`, `end_time`, `path`

Evaluators

Module: airflow.providers.arize_ax.operators.evaluators (alpha)

Operator	Purpose	Key params
`ArizeAxListEvaluatorsOperator`	List LLM-template evaluators in Eval Hub.	`space_id`, `limit`, `cursor`, `name_search`
`ArizeAxCreateEvaluatorOperator`	Create an LLM-template evaluator.	`space_id`, `name`, `evaluator_type`, `commit_message`, `template_config`, `if_exists`
`ArizeAxGetEvaluatorOperator`	Fetch an evaluator by ID.	`evaluator_id`
`ArizeAxUpdateEvaluatorOperator`	Update evaluator metadata (name, description).	`evaluator_id`, `name`, `description`
`ArizeAxDeleteEvaluatorOperator`	Delete an evaluator.	`evaluator_id`, `ignore_if_missing`
`ArizeAxAddEvaluatorVersionOperator`	Add a new template version.	`evaluator_id`, `commit_message`, `template_config`
`ArizeAxListEvaluatorVersionsOperator`	List versions of an evaluator.	`evaluator_id`, `limit`, `cursor`
`ArizeAxGetEvaluatorVersionOperator`	Fetch a specific version.	`evaluator_id`, `version_id`

Tasks

Module: airflow.providers.arize_ax.operators.tasks (alpha) Evaluation tasks attach evaluators to a project or dataset and execute on demand or on a schedule.

Operator	Purpose	Key params
`ArizeAxListTasksOperator`	List evaluation tasks (filter by space/project/dataset/type).	`space_id`, `project_id`, `dataset_id`, `eval_task_type`
`ArizeAxGetTaskOperator`	Fetch a task by ID.	`task_id_param`
`ArizeAxCreateTaskOperator`	Create a task that attaches evaluators to a project or dataset.	`name`, `eval_task_type`, `evaluators`, `project_id` or `dataset_id`, `sampling_rate`, `is_continuous`
`ArizeAxListTaskRunsOperator`	List runs for a task.	`task_id_param`, `limit`, `cursor`
`ArizeAxGetTaskRunOperator`	Fetch a task run by ID.	`run_id`
`ArizeAxTriggerTaskRunOperator`	Trigger an on-demand run; `override_evaluations=True` re-scores existing spans.	`task_id_param`, `data_start_time`, `data_end_time`, `max_spans`, `override_evaluations`
`ArizeAxCancelTaskRunOperator`	Cancel a pending or running task run.	`run_id`

Prompts

Module: airflow.providers.arize_ax.operators.prompts

Operator	Purpose	Key params
`ArizeAxListPromptsOperator`	List prompts in Prompt Hub.	`space_id`, `limit`, `cursor`
`ArizeAxGetPromptOperator`	Fetch a prompt by ID, version ID, or label.	`prompt_id`, `version_id`, `version_label`
`ArizeAxCreatePromptOperator`	Create a prompt with an initial version.	`space_id`, `name`, `messages` or `messages_task_id`, `provider`, `model`, `if_exists`
`ArizeAxDeletePromptOperator`	Delete a prompt.	`prompt_id`, `ignore_if_missing`
`ArizeAxPromotePromptOperator`	Apply a label to a prompt version (e.g. `production`).	`prompt_id`, `version_id`, `label`
`ArizeAxComparePromptsOperator`	Compare two prompt versions by experiment scores.	`prompt_id_1`, `prompt_id_2`, `experiment_id`

Spaces

Module: airflow.providers.arize_ax.operators.spaces

Operator	Purpose	Key params
`ArizeAxListSpacesOperator`	List spaces accessible to the authenticated user.	`limit`, `cursor`
`ArizeAxGetSpaceOperator`	Fetch a space by ID.	`space_id`
`ArizeAxCreateSpaceOperator`	Create a space in an organization.	`name`, `organization_id`, `description`
`ArizeAxUpdateSpaceOperator`	Update space name or description.	`space_id`, `name`, `description`
`ArizeAxDeleteSpaceOperator`	Delete a space (alpha).	`space_id`, `ignore_if_missing`

Annotation configs & queues

Module: airflow.providers.arize_ax.operators.annotations (alpha) For configuring HITL annotation flows. Pair with ArizeAxAnnotationQueueSensor to gate downstream tasks until a minimum number of annotation configs exist in the space.

Operator	Purpose	Key params
`ArizeAxListAnnotationConfigsOperator`	List annotation configurations.	`space_id`, `limit`, `cursor`
`ArizeAxCreateAnnotationConfigOperator`	Create a config (freeform, category, or numeric).	`space_id`, `name`, `config_type`, `minimum_score`, `maximum_score`
`ArizeAxDeleteAnnotationConfigOperator`	Delete a config.	`annotation_config`, `space_id`
`ArizeAxListAnnotationQueuesOperator`	List queues.	`space_id`, `limit`, `cursor`
`ArizeAxGetAnnotationQueueOperator`	Fetch a queue by ID or name.	`queue_id` or `queue_name`, `space_id`
`ArizeAxCreateAnnotationQueueOperator`	Create a queue with annotators and configs.	`space_id`, `name`, `description`, `annotators`, `configs`
`ArizeAxUpdateAnnotationQueueOperator`	Update queue metadata, annotators, or configs.	`queue_id`, `name`, `instructions`, `configs`, `annotators`
`ArizeAxDeleteAnnotationQueueOperator`	Delete a queue.	`queue_id`, `ignore_if_missing`
`ArizeAxListAnnotationQueueRecordsOperator`	List pending records (max 500/page).	`queue_id`, `limit`, `cursor`
`ArizeAxAddAnnotationQueueRecordsOperator`	Add record sources to a queue (max 2 sources).	`queue_id`, `sources`, `num_records`
`ArizeAxAnnotateQueueRecordOperator`	Submit annotations on a record.	`queue_id`, `record_id`, `annotations`
`ArizeAxAssignQueueRecordOperator`	Assign a record to one or more annotators.	`queue_id`, `record_id`, `annotators`

API keys

Module: airflow.providers.arize_ax.operators.api_keys

Operator	Purpose	Key params
`ArizeAxListAPIKeysOperator`	List API keys (user or service).	`limit`, `cursor`
`ArizeAxCreateAPIKeyOperator`	Create an API key.	`key_type`, `description`, `organization_id`
`ArizeAxDeleteAPIKeyOperator`	Delete an API key.	`api_key_id`, `ignore_if_missing`
`ArizeAxRefreshAPIKeyOperator`	Rotate (refresh) an API key.	`api_key_id`

AI integrations

Module: airflow.providers.arize_ax.operators.ai_integrations (alpha) Register external agent platforms (LangGraph, OpenAI Agents, Autogen) so Arize evaluators can run against them.

Operator	Purpose	Key params
`ArizeAxListAIIntegrationsOperator`	List AI integrations.	`space_id`, `limit`, `cursor`
`ArizeAxGetAIIntegrationOperator`	Fetch an integration by ID.	`integration_id`
`ArizeAxCreateAIIntegrationOperator`	Create an integration.	`name`, `provider`, `space_id`, `api_key`, `base_url`, `model_names`, `if_exists`
`ArizeAxUpdateAIIntegrationOperator`	Update an integration.	`integration_id`, `name`, `provider`, `api_key`
`ArizeAxDeleteAIIntegrationOperator`	Delete an integration.	`integration_id`, `ignore_if_missing`

Sensors

Module: airflow.providers.arize_ax.sensors.arize_ax All sensors accept the standard Airflow poke_interval, timeout, mode, and soft_fail.

Sensor	Waits until…	Key params
`ArizeAxExperimentCompleteSensor`	Experiment reaches a terminal state.	`experiment_id`, `min_runs`
`ArizeAxExperimentRunCountSensor`	Experiment has at least N completed runs.	`experiment_id`, `min_runs`
`ArizeAxEvaluationScoreSensor`	Experiment metric mean ≥ threshold.	`experiment_id`, `metric_name`, `min_score`
`ArizeAxDatasetReadySensor`	Dataset has ≥ N examples.	`dataset_id`, `min_examples`, `dataset_version_id`
`ArizeAxSpanCountSensor`	Project has ≥ N spans in the window.	`project_id`, `min_count`, `start_time`, `end_time`, `filter`
`ArizeAxSpanIngestionSensor`	Span count stops growing rapidly (ingestion stable).	`project_id`, `stable_window_seconds`
`ArizeAxAnnotationQueueSensor`	At least N annotation configs exist in the space.	`space_id`, `min_count`
`ArizeAxTaskRunSensor`	Evaluation task run reaches a terminal state.	`run_id`

Resources

Provider overview

Install, connection setup, design patterns, and example DAG walkthroughs.

Example DAGs

Runnable DAGs covering CI/CD gating, prompt lifecycle, dataset curation, and more.

Python SDK v8

The underlying ArizeClient API the provider wraps.

OpenTelemetry

LLM Providers

Python Agent Frameworks

TS/JS Agent Frameworks

Java Agent Frameworks

Coding Agents

Platforms

Orchestration Integrations

Evaluation Integrations

Operators, Sensors & Hooks

Import paths

Hook

Datasets

Experiments

Projects

Spans

ML

Evaluators

Tasks

Prompts

Spaces

Annotation configs & queues

API keys

AI integrations

Sensors

Resources

Provider overview

Example DAGs

Python SDK v8

OpenTelemetry

LLM Providers

Python Agent Frameworks

TS/JS Agent Frameworks

Java Agent Frameworks

Coding Agents

Platforms

Orchestration Integrations

Evaluation Integrations

Documentation Index

​Import paths

​Hook

​Datasets

​Experiments

​Projects

​Spans

​ML

​Evaluators

​Tasks

​Prompts

​Spaces

​Annotation configs & queues

​API keys

​AI integrations

​Sensors

​Resources

Provider overview

Example DAGs

Python SDK v8

Import paths

Hook

Datasets

Experiments

Projects

Spans

ML

Evaluators

Tasks

Prompts

Spaces

Annotation configs & queues

API keys

AI integrations

Sensors

Resources