airflow.providers.amazon.aws.sensors.bedrock
¶
Module Contents¶
Classes¶
General sensor behavior for Amazon Bedrock. |
|
Poll the state of the model customization job until it reaches a terminal state; fails if the job fails. |
|
Poll the provisioned model throughput job until it reaches a terminal state; fails if the job fails. |
|
Poll the Knowledge Base status until it reaches a terminal state; fails if creation fails. |
|
Poll the ingestion job status until it reaches a terminal state; fails if creation fails. |
- class airflow.providers.amazon.aws.sensors.bedrock.BedrockBaseSensor(deferrable=conf.getboolean('operators', 'default_deferrable', fallback=False), **kwargs)[source]¶
Bases:
airflow.providers.amazon.aws.sensors.base_aws.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
- Parameters
deferrable (bool) – 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)
- class airflow.providers.amazon.aws.sensors.bedrock.BedrockCustomizeModelCompletedSensor(*, job_name, max_retries=75, poke_interval=120, **kwargs)[source]¶
Bases:
BedrockBaseSensor
[airflow.providers.amazon.aws.hooks.bedrock.BedrockHook
]Poll the state of the model customization job until it reaches a terminal state; fails if the job fails.
See also
For more information on how to use this sensor, take a look at the guide: Wait for an Amazon Bedrock customize model job
- Parameters
job_name (str) – The name of the Bedrock model customization job.
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)
poke_interval (int) – Polling period in seconds to check for the status of the job. (default: 120)
max_retries (int) – Number of times before returning the current state. (default: 75)
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).region_name – AWS region_name. If not specified then the default boto3 behaviour is used.
verify – Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
botocore_config – Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
- class airflow.providers.amazon.aws.sensors.bedrock.BedrockProvisionModelThroughputCompletedSensor(*, model_id, poke_interval=60, max_retries=20, **kwargs)[source]¶
Bases:
BedrockBaseSensor
[airflow.providers.amazon.aws.hooks.bedrock.BedrockHook
]Poll the provisioned model throughput job until it reaches a terminal state; fails if the job fails.
See also
For more information on how to use this sensor, take a look at the guide: Wait for an Amazon Bedrock provision model throughput job
- Parameters
model_id (str) – The ARN or name of the provisioned throughput.
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)
poke_interval (int) – Polling period in seconds to check for the status of the job. (default: 60)
max_retries (int) – Number of times before returning the current state (default: 20)
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).region_name – AWS region_name. If not specified then the default boto3 behaviour is used.
verify – Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
botocore_config – Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
- class airflow.providers.amazon.aws.sensors.bedrock.BedrockKnowledgeBaseActiveSensor(*, knowledge_base_id, poke_interval=5, max_retries=24, **kwargs)[source]¶
Bases:
BedrockBaseSensor
[airflow.providers.amazon.aws.hooks.bedrock.BedrockAgentHook
]Poll the Knowledge Base status until it reaches a terminal state; fails if creation fails.
See also
For more information on how to use this sensor, take a look at the guide: Wait for an Amazon Bedrock Knowledge Base
- Parameters
knowledge_base_id (str) – The unique identifier of the knowledge base for which to get information. (templated)
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)
poke_interval (int) – Polling period in seconds to check for the status of the job. (default: 5)
max_retries (int) – Number of times before returning the current state (default: 24)
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).region_name – AWS region_name. If not specified then the default boto3 behaviour is used.
verify – Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
botocore_config – Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
- class airflow.providers.amazon.aws.sensors.bedrock.BedrockIngestionJobSensor(*, knowledge_base_id, data_source_id, ingestion_job_id, poke_interval=60, max_retries=10, **kwargs)[source]¶
Bases:
BedrockBaseSensor
[airflow.providers.amazon.aws.hooks.bedrock.BedrockAgentHook
]Poll the ingestion job status until it reaches a terminal state; fails if creation fails.
See also
For more information on how to use this sensor, take a look at the guide: Wait for an Amazon Bedrock ingestion job to finish
- Parameters
knowledge_base_id (str) – The unique identifier of the knowledge base for which to get information. (templated)
data_source_id (str) – The unique identifier of the data source in the ingestion job. (templated)
ingestion_job_id (str) – The unique identifier of the ingestion job. (templated)
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)
poke_interval (int) – Polling period in seconds to check for the status of the job. (default: 60)
max_retries (int) – Number of times before returning the current state (default: 10)
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).region_name – AWS region_name. If not specified then the default boto3 behaviour is used.
verify – Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
botocore_config – Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html