GlueLlmExtractionNode

pydantic model openapi_client.models.glue_llm_extraction_node.GlueLlmExtractionNode

Glue llm_extraction_node. ModelIds (plural) plus extraction fields.

Fields:

• additional_properties (Dict[str, Any])

• checkpoint_interval (int | None)

• compute_resource (Dict[str, Any] | None)

• dataset_processing_mode (str)

• execution_mode (str | None)

• extraction_rules (str | None)

• fail_on_error (bool | None)

• file_names_list (List[str] | None)

• guard_rails (List[openapi_client.models.guardrail.Guardrail] | None)

• max_file_workers (int | None)

• max_page_workers (int | None)

• model_ids (List[str])

• module_type (str)

• node_name (str)

• notification_configuration (List[openapi_client.models.data_pipelines_notification_configuration_inner.DataPipelinesNotificationConfigurationInner] | None)

• output_schema (Dict[str, Any] | None)

• per_record_prompt (str | None)

• skip_previously_enriched_records (bool | None)

• source_dataset_id (str)

• target_dataset_id (str)

• timeout (int | None)

field module_type: StrictStr [Required] (alias 'ModuleType')

Constraints:

• strict = True

field node_name: StrictStr [Required] (alias 'NodeName')

Constraints:

• strict = True

field model_ids: List[StrictStr] [Required] (alias 'ModelIds')

field extraction_rules: Optional[StrictStr] = None (alias 'ExtractionRules')

field source_dataset_id: StrictStr [Required] (alias 'SourceDatasetId')

Constraints:

• strict = True

field dataset_processing_mode: StrictStr [Required] (alias 'DatasetProcessingMode')

Constraints:

• strict = True

field target_dataset_id: StrictStr [Required] (alias 'TargetDatasetId')

Constraints:

• strict = True

field guard_rails: Optional[List[Guardrail]] = None (alias 'GuardRails')

field file_names_list: Optional[List[StrictStr]] = None (alias 'FileNamesList')

field max_file_workers: Optional[StrictInt] = None (alias 'MaxFileWorkers')

field max_page_workers: Optional[StrictInt] = None (alias 'MaxPageWorkers')

field execution_mode: Optional[StrictStr] = None (alias 'ExecutionMode')

field output_schema: Optional[Dict[str, Any]] = None (alias 'OutputSchema')

field per_record_prompt: Optional[StrictStr] = None (alias 'PerRecordPrompt')

field skip_previously_enriched_records: Optional[StrictBool] = None (alias 'SkipPreviouslyEnrichedRecords')

field fail_on_error: Optional[StrictBool] = None (alias 'FailOnError')

field checkpoint_interval: Optional[StrictInt] = None (alias 'CheckpointInterval')

field timeout: Optional[StrictInt] = None (alias 'Timeout')

Optional Glue job timeout in minutes when the node runs a job.

field notification_configuration: Optional[List[DataPipelinesNotificationConfigurationInner]] = None (alias 'NotificationConfiguration')

List of notification configurations for data pipeline events.

field compute_resource: Optional[Dict[str, Any]] = None (alias 'ComputeResource')

Optional Glue worker sizing when the node runs a job.

field additional_properties: Dict[str, Any] = {}

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of GlueLlmExtractionNode from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

• Fields in self.additional_properties are added to the output dict.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of GlueLlmExtractionNode from a dict

Return type:

Optional[Self]