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, AirflowSkipException
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:
            # 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[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)