Source code for airflow.providers.amazon.aws.sensors.bedrock

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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] INTERMEDIATE_STATES: tuple[str, ...] = ()
[docs] FAILURE_STATES: tuple[str, ...] = ()
[docs] SUCCESS_STATES: tuple[str, ...] = ()
[docs] FAILURE_MESSAGE = ""
[docs] aws_hook_class: type[_GenericBedrockHook]
[docs] ui_color = "#66c3ff"
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] INTERMEDIATE_STATES: tuple[str, ...] = ("InProgress",)
[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] INTERMEDIATE_STATES: tuple[str, ...] = ("Creating", "Updating")
[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] INTERMEDIATE_STATES: tuple[str, ...] = ("CREATING", "UPDATING")
[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] INTERMEDIATE_STATES: tuple[str, ...] = ("STARTING", "IN_PROGRESS")
[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)

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