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from __future__ import annotations
import abc
from typing import TYPE_CHECKING, Any, Sequence, TypeVar
from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.bedrock import BedrockAgentHook, BedrockHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.bedrock import (
BedrockCustomizeModelCompletedTrigger,
BedrockIngestionJobTrigger,
BedrockKnowledgeBaseActiveTrigger,
BedrockProvisionModelThroughputCompletedTrigger,
)
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
if TYPE_CHECKING:
from airflow.utils.context import Context
_GenericBedrockHook = TypeVar("_GenericBedrockHook", BedrockAgentHook, BedrockHook)
[docs]class BedrockBaseSensor(AwsBaseSensor[_GenericBedrockHook]):
"""
General sensor behavior for Amazon Bedrock.
Subclasses must implement following methods:
- ``get_state()``
Subclasses must set the following fields:
- ``INTERMEDIATE_STATES``
- ``FAILURE_STATES``
- ``SUCCESS_STATES``
- ``FAILURE_MESSAGE``
:param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
"""
[docs] FAILURE_STATES: tuple[str, ...] = ()
[docs] SUCCESS_STATES: tuple[str, ...] = ()
[docs] aws_hook_class: type[_GenericBedrockHook]
def __init__(
self,
deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False),
**kwargs: Any,
):
super().__init__(**kwargs)
self.deferrable = deferrable
[docs] def poke(self, context: Context, **kwargs) -> bool:
state = self.get_state()
if state in self.FAILURE_STATES:
raise AirflowException(self.FAILURE_MESSAGE)
return state not in self.INTERMEDIATE_STATES
@abc.abstractmethod
[docs] def get_state(self) -> str:
"""Implement in subclasses."""
[docs]class BedrockCustomizeModelCompletedSensor(BedrockBaseSensor[BedrockHook]):
"""
Poll the state of the model customization job until it reaches a terminal state; fails if the job fails.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:BedrockCustomizeModelCompletedSensor`
:param job_name: The name of the Bedrock model customization job.
:param deferrable: If True, the sensor will operate in deferrable mode. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 120)
:param max_retries: Number of times before returning the current state. (default: 75)
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs] FAILURE_STATES: tuple[str, ...] = ("Failed", "Stopping", "Stopped")
[docs] SUCCESS_STATES: tuple[str, ...] = ("Completed",)
[docs] FAILURE_MESSAGE = "Bedrock model customization job sensor failed."
[docs] aws_hook_class = BedrockHook
[docs] template_fields: Sequence[str] = aws_template_fields("job_name")
def __init__(
self,
*,
job_name: str,
max_retries: int = 75,
poke_interval: int = 120,
**kwargs: Any,
) -> None:
super().__init__(**kwargs)
self.poke_interval = poke_interval
self.max_retries = max_retries
self.job_name = job_name
[docs] def execute(self, context: Context) -> Any:
if self.deferrable:
self.defer(
trigger=BedrockCustomizeModelCompletedTrigger(
job_name=self.job_name,
waiter_delay=int(self.poke_interval),
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="poke",
)
else:
super().execute(context=context)
[docs] def get_state(self) -> str:
return self.hook.conn.get_model_customization_job(jobIdentifier=self.job_name)["status"]
[docs]class BedrockProvisionModelThroughputCompletedSensor(BedrockBaseSensor[BedrockHook]):
"""
Poll the provisioned model throughput job until it reaches a terminal state; fails if the job fails.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:BedrockProvisionModelThroughputCompletedSensor`
:param model_id: The ARN or name of the provisioned throughput.
:param deferrable: If True, the sensor will operate in deferrable more. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 60)
:param max_retries: Number of times before returning the current state (default: 20)
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs] FAILURE_STATES: tuple[str, ...] = ("Failed",)
[docs] SUCCESS_STATES: tuple[str, ...] = ("InService",)
[docs] FAILURE_MESSAGE = "Bedrock provision model throughput sensor failed."
[docs] aws_hook_class = BedrockHook
[docs] template_fields: Sequence[str] = aws_template_fields("model_id")
def __init__(
self,
*,
model_id: str,
poke_interval: int = 60,
max_retries: int = 20,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.poke_interval = poke_interval
self.max_retries = max_retries
self.model_id = model_id
[docs] def get_state(self) -> str:
return self.hook.conn.get_provisioned_model_throughput(provisionedModelId=self.model_id)["status"]
[docs] def execute(self, context: Context) -> Any:
if self.deferrable:
self.defer(
trigger=BedrockProvisionModelThroughputCompletedTrigger(
provisioned_model_id=self.model_id,
waiter_delay=int(self.poke_interval),
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="poke",
)
else:
super().execute(context=context)
[docs]class BedrockKnowledgeBaseActiveSensor(BedrockBaseSensor[BedrockAgentHook]):
"""
Poll the Knowledge Base status until it reaches a terminal state; fails if creation fails.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:BedrockKnowledgeBaseActiveSensor`
:param knowledge_base_id: The unique identifier of the knowledge base for which to get information. (templated)
:param deferrable: If True, the sensor will operate in deferrable more. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 5)
:param max_retries: Number of times before returning the current state (default: 24)
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs] FAILURE_STATES: tuple[str, ...] = ("DELETING", "FAILED")
[docs] SUCCESS_STATES: tuple[str, ...] = ("ACTIVE",)
[docs] FAILURE_MESSAGE = "Bedrock Knowledge Base Active sensor failed."
[docs] aws_hook_class = BedrockAgentHook
[docs] template_fields: Sequence[str] = aws_template_fields("knowledge_base_id")
def __init__(
self,
*,
knowledge_base_id: str,
poke_interval: int = 5,
max_retries: int = 24,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.poke_interval = poke_interval
self.max_retries = max_retries
self.knowledge_base_id = knowledge_base_id
[docs] def get_state(self) -> str:
return self.hook.conn.get_knowledge_base(knowledgeBaseId=self.knowledge_base_id)["knowledgeBase"][
"status"
]
[docs] def execute(self, context: Context) -> Any:
if self.deferrable:
self.defer(
trigger=BedrockKnowledgeBaseActiveTrigger(
knowledge_base_id=self.knowledge_base_id,
waiter_delay=int(self.poke_interval),
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="poke",
)
else:
super().execute(context=context)
[docs]class BedrockIngestionJobSensor(BedrockBaseSensor[BedrockAgentHook]):
"""
Poll the ingestion job status until it reaches a terminal state; fails if creation fails.
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:BedrockIngestionJobSensor`
:param knowledge_base_id: The unique identifier of the knowledge base for which to get information. (templated)
:param data_source_id: The unique identifier of the data source in the ingestion job. (templated)
:param ingestion_job_id: The unique identifier of the ingestion job. (templated)
:param deferrable: If True, the sensor will operate in deferrable more. This mode requires aiobotocore
module to be installed.
(default: False, but can be overridden in config file by setting default_deferrable to True)
:param poke_interval: Polling period in seconds to check for the status of the job. (default: 60)
:param max_retries: Number of times before returning the current state (default: 10)
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs] FAILURE_STATES: tuple[str, ...] = ("FAILED",)
[docs] SUCCESS_STATES: tuple[str, ...] = ("COMPLETE",)
[docs] FAILURE_MESSAGE = "Bedrock ingestion job sensor failed."
[docs] aws_hook_class = BedrockAgentHook
[docs] template_fields: Sequence[str] = aws_template_fields(
"knowledge_base_id", "data_source_id", "ingestion_job_id"
)
def __init__(
self,
*,
knowledge_base_id: str,
data_source_id: str,
ingestion_job_id: str,
poke_interval: int = 60,
max_retries: int = 10,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.poke_interval = poke_interval
self.max_retries = max_retries
self.knowledge_base_id = knowledge_base_id
self.data_source_id = data_source_id
self.ingestion_job_id = ingestion_job_id
[docs] def get_state(self) -> str:
return self.hook.conn.get_ingestion_job(
knowledgeBaseId=self.knowledge_base_id,
ingestionJobId=self.ingestion_job_id,
dataSourceId=self.data_source_id,
)["ingestionJob"]["status"]
[docs] def execute(self, context: Context) -> Any:
if self.deferrable:
self.defer(
trigger=BedrockIngestionJobTrigger(
knowledge_base_id=self.knowledge_base_id,
ingestion_job_id=self.ingestion_job_id,
data_source_id=self.data_source_id,
waiter_delay=int(self.poke_interval),
waiter_max_attempts=self.max_retries,
aws_conn_id=self.aws_conn_id,
),
method_name="poke",
)
else:
super().execute(context=context)