DataPipelinesPostNodesInner

pydantic model openapi_client.models.data_pipelines_post_nodes_inner.DataPipelinesPostNodesInner

DataPipelinesPostNodesInner

Fields:

• agent_type (str | None)

• arguments (Dict[str, Any] | None)

• batch_pages (int | None)

• checkpoint_interval (int | None)

• columns_to_visualise (List[str] | None)

• concurrency_factor (float | int | None)

• conditional_prompts (List[openapi_client.models.data_pipelines_post_nodes_inner_conditional_prompts_inner.DataPipelinesPostNodesInnerConditionalPromptsInner] | None)

• conditions (List[openapi_client.models.data_pipeline_nodes_inner_conditions_inner.DataPipelineNodesInnerConditionsInner] | None)

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

• dataset_domain (str | None)

• dataset_processing_mode (str | None)

• document_description (str | None)

• email_body_execution_property_key (str | None)

• email_subject_execution_property_key (str | None)

• email_to_execution_property_key (str | None)

• execution_mode (str | None)

• extraction_rules (str | None)

• fail_on_error (bool | None)

• features (List[str] | None)

• file_names_list (List[str] | None)

• file_processing_mode (str | None)

• from_time (str | None)

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

• ingestion_type (str | None)

• inner_document_end (str | None)

• inner_document_start (str | None)

• inputs (List[openapi_client.models.data_pipeline_nodes_inner_inputs_inner.DataPipelineNodesInnerInputsInner] | None)

• list_of_input_datasets (List[str] | None)

• max_file_workers (int | None)

• max_page_workers (int | None)

• model_id (str | None)

• model_ids (List[str] | None)

• module_type (str)

• node_instance (str | None)

• node_name (str)

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

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

• outputs (List[openapi_client.models.data_pipeline_nodes_inner_outputs_inner.DataPipelineNodesInnerOutputsInner] | None)

• parallel_workers (int | None)

• per_record_prompt (str | None)

• prompt (str | None)

• resource (openapi_client.models.data_pipeline_nodes_inner_resource.DataPipelineNodesInnerResource | None)

• resource_identifier (str | None)

• skip_previously_enriched_records (bool | None)

• source_dataset_id (str | None)

• source_language_id (str | None)

• sync_all_datasets (bool | None)

• target_dataset_id (str | None)

• target_language_id (str | None)

• timeout (int | None)

• to_time (str | None)

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

Constraints:

• strict = True

field source_dataset_id: Optional[StrictStr] = None (alias 'SourceDatasetId')

field source_language_id: Optional[StrictStr] = None (alias 'SourceLanguageId')

field target_language_id: Optional[StrictStr] = None (alias 'TargetLanguageId')

field target_dataset_id: Optional[StrictStr] = None (alias 'TargetDatasetId')

field file_processing_mode: Optional[StrictStr] = None (alias 'FileProcessingMode')

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

Constraints:

• strict = True

field resource: Optional[DataPipelineNodesInnerResource] = None (alias 'Resource')

field concurrency_factor: Optional[Union[StrictFloat, StrictInt]] = None (alias 'ConcurrencyFactor')

field dataset_domain: Optional[StrictStr] = None (alias 'DatasetDomain')

field sync_all_datasets: Optional[StrictBool] = None (alias 'SyncAllDatasets')

field list_of_input_datasets: Optional[List[StrictStr]] = None (alias 'ListOfInputDatasets')

field arguments: Optional[Dict[str, Any]] = None (alias 'Arguments')

field features: Optional[List[StrictStr]] = None (alias 'Features')

field email_body_execution_property_key: Optional[StrictStr] = None (alias 'EmailBodyExecutionPropertyKey')

field email_subject_execution_property_key: Optional[StrictStr] = None (alias 'EmailSubjectExecutionPropertyKey')

field email_to_execution_property_key: Optional[StrictStr] = None (alias 'EmailToExecutionPropertyKey')

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

field agent_type: Optional[StrictStr] = None (alias 'AgentType')

field model_id: Optional[StrictStr] = None (alias 'ModelId')

ID of the Bedrock model to be used by the Agent or LLM node.

field model_ids: Optional[List[StrictStr]] = None (alias 'ModelIds')

List of Bedrock model identifiers used by LLM Extraction node to fan out extraction across multiple models.

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

Optional user-supplied extraction rules / prompt appended to the extraction prompt for the LLM Extraction node.

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

Specifies the number of files to be processed in parallel.

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

Specifies the number of pages to be processed in parallel per file.

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

Optional guard rails for the LLM Extraction node. The first entry is used at runtime. When no guardrails are provided, the SYSTEM-PromptGuard (prompt guard rail) is applied by default.

field dataset_processing_mode: Optional[StrictStr] = None (alias 'DatasetProcessingMode')

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

field columns_to_visualise: Optional[List[StrictStr]] = None (alias 'ColumnsToVisualise')

field prompt: Optional[StrictStr] = None (alias 'Prompt')

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 conditional_prompts: Optional[List[DataPipelinesPostNodesInnerConditionalPromptsInner]] = None (alias 'ConditionalPrompts')

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

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

Number of records after which enriched output is flushed to S3 and the dedup manifest is checkpointed. Lower values reduce data at risk on failure; higher values reduce S3 write overhead. Valid range is between 20–1000. Default is 100.

field inner_document_start: Optional[StrictStr] = None (alias 'InnerDocumentStart')

Marker or criteria describing the first page of each inner document for split_doc_node.

field inner_document_end: Optional[StrictStr] = None (alias 'InnerDocumentEnd')

Marker or criteria describing the last page of each inner document for split_doc_node.

field document_description: Optional[StrictStr] = None (alias 'DocumentDescription')

Description of the inner documents to extract from the source PDF for split_doc_node.

field batch_pages: Optional[StrictInt] = None (alias 'BatchPages')

Number of pages sent to the vision model per batch for split_doc_node (1-20, default 5).

field parallel_workers: Optional[StrictInt] = None (alias 'ParallelWorkers')

Number of parallel threads extracting pages and querying the vision model for split_doc_node (1-20, default 5).

field ingestion_type: Optional[StrictStr] = None (alias 'IngestionType')

field node_instance: Optional[StrictStr] = None (alias 'NodeInstance')

field from_time: Optional[StrictStr] = None (alias 'FromTime')

field to_time: Optional[StrictStr] = None (alias 'ToTime')

field configuration: Optional[Dict[str, Any]] = None (alias 'Configuration')

field resource_identifier: Optional[StrictStr] = None (alias 'ResourceIdentifier')

Resource identifier for nodes that require external resources (e.g., KnowledgeBase)

field inputs: Optional[List[DataPipelineNodesInnerInputsInner]] = None (alias 'Inputs')

Input configurations for AI Flow nodes. Each input has Name and Type.

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

List of notification configurations for data pipeline events.

field outputs: Optional[List[DataPipelineNodesInnerOutputsInner]] = None (alias 'Outputs')

Output configurations for AI Flow nodes. Each output has Name and Type.

field conditions: Optional[List[DataPipelineNodesInnerConditionsInner]] = None (alias 'Conditions')

Condition configurations for Condition nodes. Each condition has Name and optional Expression (default condition doesn’t require Expression).

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 DataPipelinesPostNodesInner 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.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of DataPipelinesPostNodesInner from a dict

Return type:

Optional[Self]