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

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations

import abc
from typing import TYPE_CHECKING, Any, Sequence

from airflow.configuration import conf
from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.providers.amazon.aws.hooks.bedrock import BedrockHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.bedrock import (
    BedrockCustomizeModelCompletedTrigger,
    BedrockProvisionModelThroughputCompletedTrigger,
)
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class BedrockBaseSensor(AwsBaseSensor[BedrockHook]): """ 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 = BedrockHook
[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) -> bool: state = self.get_state() if state in self.FAILURE_STATES: # TODO: remove this if block when min_airflow_version is set to higher than 2.7.1 if self.soft_fail: raise AirflowSkipException(self.FAILURE_MESSAGE) 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): """ 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] 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): """ 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] 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)

Was this entry helpful?