IDP Library

This IDP Library (flows_sdk.implementations) includes the latest performant blocks and functions for building intelligent document processing (IDP).

The IDP Library contains:

Processing Blocks, which are provided as convenient Python subclasses for plug-and-play use.
Trigger and Output Blocks, which require use of base classes.
Helper functions for ease of development.

Note

Most solutions will also require use of base classes, such as Flow or CodeBlock, found in the Source Documentation.

V41

Processing Blocks (v41)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v41 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v41.idp_blocks.IDPCoreBlock(idp_wf_config, reference_name='__idp_core__', title='Start Document Processing Subflow', description='Calls the Document Processing Subflow with the specified settings.', compatibility_spec=CompatibilitySpec(filter_roles=['idp_core'], filter_schema=None, label=None), identifier='IDP_CORE_V41', additional_inputs=None)

Bases: Block

IDP core block includes the steps to process the passed documents into machine-readable output.

Mandatory parameters:

Parameters:: idp_wf_config (IdpWorkflowConfig) – IdpWorkflowConfig object with all flow-level configuration settings for IDP

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique reference name within a flow, a unique one will be generated when not provided
compatibility_spec (Optional[CompatibilitySpec]) – defines a filter for flows that could be selected in the UI in place of “IDP Core” for the block. Defaults to flows with the role ‘idp_core’. The user will be able to pick any flow that matches the compatibility_spec. This serves to make upgrading to a new compatible version of “IDP Core” (e.g. IDP_CORE_V39) easier in future releases.
identifier (str) – The identifier of the flow. Defaults to the IDP_CORE_VXX identifier of the out-of-the-box flow that comes with the system.
additional_inputs (Optional[Dict[str, Any]]) – Dictionary containing key-value pairs that will be added to the inputs of the block. If a key is contained in the default inputs, its value will be overwritten by the value provided here. You generally do not need to provide additional_inputs, unless you are creating a custom derivative of the IDP_CODE_Vxx flow and are modifying or extending the list of inputs it accepts.

Example usage:

idp_core = IDPCoreBlock(idp_wf_config=idp_wf_config)

REFERENCE_NAME = '__idp_core__'

class flows_sdk.implementations.idp_v41.idp_blocks.SubmissionBootstrapBlock(reference_name=None, trigger='${workflow.input.$trigger}', layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${workflow.input.submission_bootstrap_s3_config}', s3_endpoint_url='${workflow.input.submission_bootstrap_s3_endpoint_url}', ocs_config='${workflow.input.submission_bootstrap_ocs_config}', http_config='${workflow.input.submission_bootstrap_http_config}', abs_auth_type='${workflow.input.submission_bootstrap_abs_auth_type}', abs_account_url='${workflow.input.submission_bootstrap_abs_account_url}', abs_tenant_id='${workflow.input.submission_bootstrap_abs_tenant_id}', abs_client_id='${workflow.input.submission_bootstrap_abs_client_id}', abs_client_secret='${workflow.input.submission_bootstrap_abs_client_secret}', abs_authority_host='${workflow.input.submission_bootstrap_abs_authority_host}', abs_account_name='${workflow.input.submission_bootstrap_abs_account_name}', abs_account_key='${workflow.input.submission_bootstrap_abs_account_key}', notification_workflow='${workflow.input.notification_workflow_initialization}', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}', submission='${workflow.input.submission}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
trigger (str) – the trigger input from a connector - if not set explicitly, it will default to the workflow input trigger (which is where this value is normally found)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to workflow_input(Settings.SubmissionBootstrapS3Config)
s3_endpoint_url (str) – Endpoint URL for S3 submission retrieval store, defaults to workflow_input(Settings.SubmissionBootstrapS3EndpointUrl)
ocs_config (str) – OCS Configuration for downloading submission data, defaults to workflow_input(Settings.SubmissionBootstrapOCSConfig)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to workflow_input(Settings.SubmissionBootstrapHTTPConfig)
notification_workflow (Optional[str]) – Notification flow name to run when the submission is initialized, defaults to workflow_input(Settings.SubmissionBootstrapNotificationWorkflow)
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)
submission (Any) – Submission object

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v41.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files='${workflow.input.machine_collation_dedupe_files}', refresh_retention_period='${workflow.input.machine_collation_refresh_retention_period}', remove_from_cases='${workflow.input.machine_collation_remove_from_cases}', retention_period='${workflow.input.machine_collation_retention_period}', reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (Union[bool, str]) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases. Defaults to workflow_input(Settings.CollationDedupeFiles)
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case, defaults to workflow_input(Settings.CollationRemoveFromCases)

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Union[int, str, None]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. Defaults to workflow_input(Settings.CollationRetentionPeriod)
refresh_retention_period (Union[bool, str]) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. Defaults to workflow_input(Settings.CollationRefreshRetentionPeriod)

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v41.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled='${workflow.input.machine_classification_rotation_correction_enabled}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', file_transcription_enabled='${workflow.input.machine_classification_file_transcription_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}', layout_id_dealbreaker='${workflow.input.layout_id_dealbreaker}', layout_id_dealbreaker_bypass='${workflow.input.layout_id_dealbreaker_bypass}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (Union[bool, str]) – Identifies and corrects the orientation of semi-structured images, defaults to workflow_input(Settings.RotationCorrectionEnabled)
mobile_processing_enabled (Union[bool, str]) – Improves the machine readability of photo captured documents, defaults to workflow_input(Settings.MobileProcessingEnabled)
file_transcription_enabled (Union[bool, str]) – Improves the transcription speed of pdf files. Make sure that the “Image Correction” option is disabled and the pdfs you submit do not contain any rotated images defaults to workflow_input(Settings.FileTranscriptionEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_7'

class flows_sdk.implementations.idp_v41.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions='${workflow.input.manual_classification_task_restrictions}', notification_workflow='${workflow.input.notification_workflow_classification}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualClassificationTaskRestrictions)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to workflow_input(Settings.ManualClassificationNotificationWorkflow)
nlc_enabled – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy – Classification Target Accuracy, defaults to workflow_input(Settings.SemiTargetAccuracy)
mobile_processing_enabled – Improves the machine readability of photo captured document, defaults to workflow_input(Settings.MobileProcessingEnabled)
vpc_registration_threshold (Optional[str]) – Structured pages above this threshold will be automatically matched to a layout variation when performing light vpc registration in the doc-org task, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_5'

class flows_sdk.implementations.idp_v41.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', force_required_missing_entries_to_sv='${workflow.input.force_required_entries_to_sv}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}', id_target_accuracies='${workflow.input.identification_target_accuracies}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (Any) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
force_required_missing_entries_to_sv (str) – defaults to workflow_input( Settings.ForceRequiredEntriesToSV )
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)
id_target_accuracies (str) – defaults to workflow_input( Settings.IdentificationTargetAccuracies )

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_8'

class flows_sdk.implementations.idp_v41.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions='${workflow.input.manual_identification_task_restrictions}', manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_identification}')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualFieldIdTaskRestrictions)
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to workflow_inputSettings.ManualFieldIdNotificationWorkflow

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v41.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', force_normalization_errors_to_sv='${workflow.input.force_normalization_errors_to_sv}', force_required_blank_entries_to_sv='${workflow.input.force_required_entries_to_sv}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}', field_target_accuracies='${workflow.input.field_transcription_target_accuracies}', column_target_accuracies='${workflow.input.column_transcription_target_accuracies}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
force_normalization_errors_to_sv (str) – defaults to workflow_input( Settings.ForceNormalizationErrorsToSV )
force_required_blank_entries_to_sv (str) – defaults to workflow_input( Settings.ForceRequiredEntriesToSV )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )
field_target_accuracies (str) – defaults to workflow_input( Settings.FieldTargetAccuracies )
column_target_accuracies (str) – Deprecated since R40.1 and will be removed in R43 defaults to workflow_input( Settings.ColumnTargetAccuracies )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_9'

class flows_sdk.implementations.idp_v41.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.manual_transcription_supervision_transcription_masking}', table_output_manual_review='${workflow.input.manual_transcription_table_output_manual_review}', always_supervise_blank_cells='${workflow.input.manual_transcription_always_supervise_blank_cells}', task_restrictions='${workflow.input.manual_transcription_task_restrictions}', manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='${workflow.input.notification_workflow_transcription}', title='Manual Transcription', description='Manually transcribe fields that could not be automatically transcribed')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str]) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to workflow_input(Settings.ManualTranscriptionSupervisionTranscriptionMasking)
table_output_manual_review (Union[bool, str]) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to workflow_input(Settings.ManualTranscriptionTableOutputManualReview)
always_supervise_blank_cells (Union[bool, str]) – If enabled, always send blank cells in transcribed tables to be supervised manually, regardless of confidence defaults to workflow_input(Settings.ManualTranscriptionAlwaysSuperviseBlankCells)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to workflow_input(Settings.ManualTranscriptionTaskRestrictions)
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to workflow_input(Settings.ManualTranscriptionNotificationWorkflow)

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_5'

class flows_sdk.implementations.idp_v41.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.flexible_extraction_supervision_transcription_masking}', task_restrictions='${workflow.input.flexible_extraction_task_restrictions}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_flexible_extraction}')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str, None]) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to workflow_input(Settings.FlexibleExtractionSupervisionTranscriptionMasking)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults workflow_input(Settings.FlexibleExtractionTaskRestrictions)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to workflow_input(Settings.FlexibleExtractionNotificationWorkflow)

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_4'

class flows_sdk.implementations.idp_v41.idp_blocks.ReprocessingBlock(reference_name, submission, parent_flow='${workflow.definition.identifier}', idp_wf_config='${workflow.input}', trigger='${workflow.input.$trigger}')

Bases: Block

Reprocessing block enables a second extraction attempt if documents were initially confidently mis-classified by the machine. When an end-user specifies that a document layout is incorrect during Manual Identification, Manual Transcription, or Flexible Extraction, the flow will reach the Reprocessing block which will mark correctly classified documents as “complete” status, and misclassified documents with “reprocess” status will be processed in a second execution of the flow. This block should be placed before the SubmissionCompleteBlock to enable reprocessing.

How the Reprocessing block works

The Reprocessing block examines whether any documents within the submission have been marked with an incorrect layout, and if so, redirects the submission to the classification step for proper classification. It does this by recursively calling the same flow or subflow with the same inputs and documents, but with the addition of a status key for each document to denote which were marked with an incorrect layout during supervision.

Note

The Reprocessing block works in tandem with the “Mark Incorrect Layout” option presented to users during Manual Identification, Manual Transcription, and Flexible Extraction supervision interfaces introduced in R38. Include the Reprocessing block in all custom flows in order to take advantage of this feature. The feature will remain selectable in supervision interfaces even if the Reprocessing block is not included in the flow.

The initial flow run will pause execution at the Reprocessing block until the recursive flow has completed, at which point the initial flow will resume to finish its execution. If an error occurs during the execution of the recursive flow, that error will be raised to the Reprocessing block of the initial flow.

Note

The recursive flow run is linked with the same correlation_id as the initial flow run and the submission. Users can click the “View related flow runs” link on the left sidebar of the initial flow run to view any recursive flow runs.

As expected, recursively calling the same flow may cause some blocks to run again, resulting in unnecessary work being performed, or work which doesn’t gracefully handle duplications (non-idempotent blocks). To mitigate this, certain Hyperscience-provided blocks - including Submission Initialization, Machine Collation, and Machine Classification - detect when the submission object already contains the output from its block to avoid re-execution. It’s a best practice to build custom blocks such that they are idempotent and reentrant; if that’s not feasible, you can add similar logic to custom blocks which do not depend on the layout for the documents being processed. Common methods for handling this include:

Iterating through each status key within the submission.document[] collection to see if any documents are set to “reprocess”.
Inspecting if the submission object already contains a key or value explicitly defined by the custom code block.

Recommended Placement for the Reprocessing Block

The Reprocessing block should not be placed before any supervision blocks which allow users to mark a document with an incorrect layout. These supervision blocks include Manual Identification, Manual Transcription and Flexible Extraction.
The Reprocessing block should always be placed before the SubmissionCompete Block.
The Reprocessing block can be used with flows which include multiple branches and conditionals; however, it’s recommended to ensure the Reprocessing block is executed to honor user’s selection of marking layouts incorrectly when supervising documents.
In general, any custom logic that is to be performed after data has been extracted from documents should be placed after the Reprocessing block. To avoid duplicate executions of this custom logic, it is recommended to separate the document processing blocks - inclusive of the Reprocessing block - from the custom logic. This can be handled in different ways:
- Split the flow into separate subflows, where the Reprocessing block is in a subflow that does not contain the custom logic.
- Add a decision to bypass the custom logic if the Reprocessing block was triggered. With this method, the recursive flow run will execute the custom logic, and the initial flow run will bypass the logic.

Mandatory parameters:

Parameters:: submission (Any) – Submission object

IDENTIFIER = 'REPROCESSING_2'

class flows_sdk.implementations.idp_v41.idp_blocks.SubmissionCompleteBlock(submission, is_reprocessing=False, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v41.idp_blocks.SetTransformedOutputBlock(submission, transformed_output, reference_name=None)

Bases: Block

Set Transformed Output block sets the transformed output for the provided submission. This can later be used to send the transformed data downstream using output blocks. For more information see https://docs.hyperscience.com/#retrieving-transformed-submissions.

Mandatory parameters:

Parameters:

submission (str) – Submission object
transformed_output (str) – Object that will be set as the transformed output for this submission

IDENTIFIER = 'SET_TRANSFORMED_OUTPUT'

class flows_sdk.implementations.idp_v41.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, data=None, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

data (Optional[Dict[str, Any]]) – Optional JSON structure that extends the data used to populate the supervision_template. This is intended to append to the data already gathered by the IDP wrapper. If there are any conflicting keys, the keys in this input will take precedent.
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[str, bool]) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Union[str, List[Any], None]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Union[str, List[int], None]) – This is an optional parameter. If left empty, the IDP wrapper will, by default, pull in all pages in the submission. Adding a list of page IDs will override the default list of pages. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            }
        ]
    }
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v41.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None, language_family=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families for your Hyperscience version in the Supported Languages section of the documentation https://help.hyperscience.com/docs/search?searchtext=”Supported%20Languages”&selectedTab=2

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION_2'

class flows_sdk.implementations.idp_v41.idp_blocks.DocumentRendererBlock(submission, is_reprocessing=False, title='Document Renderer', description='Renders a document into a PDF', reference_name=None, document_rendering_enabled='${workflow.input.document_rendering_enabled}', document_rendering_mime_type='${workflow.input.document_rendering_mime_type}', document_rendering_unit='${workflow.input.document_rendering_unit}', document_rendering_height='${workflow.input.document_rendering_height}', document_rendering_width='${workflow.input.document_rendering_width}', document_rendering_quality='${workflow.input.document_rendering_quality}')

Bases: Block

Document File Generator Block renders a document into a PDF and stores it in the Blob storage.

This block should be placed ALWAYS after a Reprocessing block (if there is any) so that it is not possible to have more changes in the documents’ organisation.

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be rendered.

Optional parameters:

Parameters:

document_rendering_enabled (Union[bool, str]) – a boolean that enables or disables the document rendering. Default is False.
document_rendering_mime_type (str) – the mime type of the document to be generated. Default is ‘application/pdf’
document_rendering_unit (str) – the unit of the document to be generated. Default is ‘inches’
document_rendering_height (Union[str, float]) – the height of the document to be generated. Default is 11
document_rendering_width (Union[str, float]) – the width of the document to be generated. Default is 8.5
document_rendering_quality (Union[str, int]) – Quality of pages (images) appended to the resulting document as a percentage (recommended 50%). Higher quality results in a larger file size for the generated PDF.
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

# Use the output of the reprocessing block.
reprocessing = ReprocessingBlock(reference_name='reprocessing')

document_renderer_block = DocumentRendererBlock(
    reference_name='document_renderer',
    submission=reprocessing.output(submission),
    document_rendering_enabled=True,
    document_rendering_unit='in',
    document_rendering_width=8.5,
    document_rendering_height=11,
    document_rendering_quality=50
    is_reprocessing=reprocessing.output('is_reprocessing')
)

output_ref = document_renderer_block.output()

Example content of output_ref:

{
    'document_files': {
        [
            {
                'document_id': "1",
                'blob_uuid': 'f42fc9af-b551-4403-aba6-d0eba2c41973',
                'mime_type': 'application/pdf',
                'height_in_mm': 279.4,
                'width_in_mm': 215.9,
                'quality': 50,
            }
        ]
    },
    'submission': {
        ...
    }
}

IDENTIFIER = 'DOCUMENT_RENDERER'

class flows_sdk.implementations.idp_v41.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, language_family=None, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of images. Enabled by default.
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents. Disabled by default.
language_family (Optional[str]) – language family to use when performing image correction. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families for your Hyperscience version in the Supported Languages section of the documentation https://help.hyperscience.com/docs/search?searchtext=”Supported%20Languages”&selectedTab=2
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

Additional Blocks (v41)

class flows_sdk.implementations.idp_v41.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v41.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, language_family=None, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of images. Enabled by default.
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents. Disabled by default.
language_family (Optional[str]) – language family to use when performing image correction. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families for your Hyperscience version in the Supported Languages section of the documentation https://help.hyperscience.com/docs/search?searchtext=”Supported%20Languages”&selectedTab=2
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v41.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', language_family=None, app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families for your Hyperscience version in the Supported Languages section of the documentation https://help.hyperscience.com/docs/search?searchtext=”Supported%20Languages”&selectedTab=2
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES_2'

class flows_sdk.implementations.idp_v41.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY', title='Custom Supervision', description='Custom Supervision')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populate the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 15,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': False,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurrence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,
                'image_url': '/image/2ed3d989-b64a-44bd-a9fb-6e0dcc5ccdb8',
                'form_id': 2,
                'submission_id': 1,
                'external_case_ids': [],
                'read_only': False,
                'filename': '1 page.pdf',
                'form_page_id': 1
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v41.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, use_wsdl=False, wsdl_uri='', wsdl_service_name='', wsdl_port_name='', title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v41.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, timeout=600, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
timeout (Optional[int]) – How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely (not recommended).
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v41.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, timeout=600, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make Http requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request. Mandatory parameters:

Parameters:

method (str) – HTTP method to use
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hypersciecne platform. For reference on the available endpoints, check out https://docs.hyperscience.com/

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
timeout (Optional[int]) – How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely (not recommended).

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v41.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

class flows_sdk.implementations.idp_v41.additional_blocks.LLMInstallBlock(model_name='Mistral', cloudsmith_key='', user_consent=False, reference_name=None, title='Install LLM/VLM', description='Sets up the necessary LLM or VLM in the HS instance.')

Bases: Block

The LLM Install Block sets up the necessary LLM or VLM in the HS instance. It begins by verifying whether the model is already present and, if not, retrieves it from S3 for SaaS instances or Cloudsmith for on-premises instances.

Mandatory parameters:

Parameters:

model_name (str) – Name of the LLM model to install (Choose from the available models)
cloudsmith_key (str) – Cloudsmith API key (Only when running on on-premise instance)
user_consent (bool) – User consent (The block will fail if set to False)

The block outputs the detailed model name and model UUID of the chosen LLM.

Example usage:

llm_install = LLMInstallBlock(
    model_name='Mistral',
    cloudsmith_key='cloudsmith_key',
    user_consent=True
)

Example output:

{
    "model": "mistral-7b-instruct-v0.2.Q5_K_M",
    "model_uuid": "3f04eae3-932a-4e18-827a-8ff120838c39"
}

IDENTIFIER = 'LLM_INSTALL'

class flows_sdk.implementations.idp_v41.additional_blocks.LlamaBlock(model_id, prompt, reference_name=None, consent=False, tokenize_only=False, predict_extra_kwargs=None, title='Llama Text Generation', description='Text generation using the Llama 2 model')

Bases: Block

Text generation using the Llama 2 model by Meta.

This block utilizes Llama 2 by Meta. Llama 2 is licensed under the LLAMA 2 Community License (https://ai.meta.com/llama/license/). By using the Llama Block, you acknowledge that you have received a copy of the LLAMA 2 Community License.

Note: This block is still experimental and not ready for production use.

Mandatory parameters:

Parameters:

model_id (str) – UUID, identifier of the asset with the ML model. Model assets are not part of the Hypersicence bundle and must first be downloaded and imported into the system before they can be used. Please contact your Hyperscience representative to discuss the usecase and the appropriate model and to get instructions on downloading the models. Once downloaded, here are the available model asset UUIDs: b3da05c7-061c-4a58-af6d-4c905d2e618f - Llama 2, 13B, 8-bit quantized
prompt (str) – The prompt to generate text from. Use a CodeBlock ahead of the LlamaBlock in order to build the prompt. The context window of the model is limited to 4096 tokens. If the prompt has more tokens, the block would return an error. The total input and output length also cannot exceed 4096 tokens, which means that if the input is too long, the output may be truncated. Also see tokenize_only for a more detailed explanation of how to handle longer texts.

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
consent (Optional[bool]) – Has the business user read and acknowledged the Llama 2 legal notice. Unless the flow would be used in CI automation, this should be set to False so that a business user can read and acknowledge the notice in the Hyperscience UI. Setting this to True in the Python definition of the flow is also treated as acknowledgement of the notice on behalf of the entity that will be using the flow.
tokenize_only (Optional[bool]) – In the context of LLMs, tokens correspond roughly to words, partial words and punctuation. A rough way to compute the number of tokens in a text is number_of_tokens = 1.25 * number_of_words. The Llama block works with a context window of 4096 tokens. If a longer prompt is passed in, it would return an error. Also, if the prompt is shorter, but still close to 4096, the output may be truncated. Since the length of the prompt in tokens cannot be known ahead of time, sometimes the flow may need to make dynamic decisions whether to pass the text to the Llama block, or to split it into multiple chunks, or to use some alternative method for processing it (e.g. a custom supervision manual task). The tokenize_only option enables flows to take such dynamic decisions based on the length of the prompt in tokens. The default is false - it instructs the block to run the ML model inference over the prompt, i.e. to generate a text response. When true is passed, the model will simply tokenize the prompt without running inference and return the list of tokens - this will work regardless of the length of the prompt. A subsequent Decision task can then route longer prompts to an alternative path in the flow, while routing shorter prompts to the LlamaBlock for actual text generation.
predict_extra_kwargs (Optional[Dict[Any, Any]]) – Extra keyword arguments used for model inference. (Used to fine-tune the model prediction. Not recommended to change this unless you know what you are doing)

Example usage:

llama = LlamaBlock(
    reference_name='llama',
    model_id='b3da05c7-061c-4a58-af6d-4c905d2e618f',
    prompt='${previous_block.output.llama_prompt}',
)

IDENTIFIER = 'LLAMA'

class flows_sdk.implementations.idp_v41.additional_blocks.EntityRecognitionBlock(pages, regex_map=None, keyword_map=None, enhanced_output=False, ner_enabled=True, ced_enabled=True, signature_enabled=True, reference_name=None, title='Entity Recognition', description='Recognizes entities of different types in documents')

Bases: Block

Entity Recognition Block detects entities of different types within the documents contained in a submission

This block requires the output of the Full Page Transcription Block as input data.

Mandatory parameters:

Parameters:

pages (str) – list of pages that includes the raw documents with the transcribed information from the FPT block
regex_map (Optional[Dict[str, str]]) – a map that specifies different regex patterns that the block should look for, a default one is present
keyword_map (Optional[Dict[str, List[str]]]) – a map that specifies different keyword patterns that the block should look for, a default one is present

Optional Parameters:

Parameters:

enhanced_output (bool) – a boolean flag that enables toggling between simple and enhanced output formats. Default value is False.
ner_enabled (bool) – a boolean flag that enables or disables Named Entity Recognition. Default value is True.
ced_enabled (bool) – a boolean flag that enables or disables Custom Entity Detection. Default value is True.
signature_enabled (bool) – a boolean flag that enables or disables Signature Detection. Default value is True.
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

# EntityRecognitionBlock detects entities within the documents contained in the submission
entity_recognition_block = EntityRecognitionBlock(
    reference_name='entity_recognition',
    pages=submission_bootstrap.output(submission.unassigned_pages),
    regex_map=DEFAULT_PII_REGEX_MAP,
    keyword_map=DEFAULT_PII_KEYWORD_MAP,
    enhanced_output=False,
)

# reference to the output of EntityRecognitionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = entity_recognition_block.output()

Example content of output_ref:

{
    "documents": [
        {
            "file_uuid": "da2c6117-43c4-4b30-84c4-cdc59cc3fa4f",
            "entities": [
                {
                    "text": "John Smith",
                    "type": "Person Name",
                    "positions": [
                        [0.5, 0.1, 0.55, 0.13],
                        [0.6, 0.2, 0.65, 0.23],
                        [0.7, 0.3, 0.75, 0.33],
                    ],
                    "page_ids": [0, 0, 1],
                    "origin": "NER",
                },
                {
                    "text": "<SIGNED>",
                    "type": "signature",
                    "positions": [[0.701171875, 0.732421875, 0.92578125, 0.8681640625]],
                    "page_ids": [0],
                    "origin": "Signature",
                },
            ]
        },
        {
            "file_uuid": "4aa38f84-e5af-4cdc-ba5c-edd60f0a6b89",
            "entities": [
                ...
            ]
        }
    ],
    "redaction_annotations": {
        "ner": [ ... ],
        "ced": [ ... ],
    }
}

IDENTIFIER = 'ENTITY_RECOGNITION'

class flows_sdk.implementations.idp_v41.additional_blocks.FileFilterBlock(trigger='${workflow.input.$trigger}', filter_type='${workflow.input.file_filter_filter_type}', minimum_image_width='${workflow.input.file_filter_minimum_image_width}', minimum_image_height='${workflow.input.file_filter_minimum_image_height}', minimum_file_size_kb='${workflow.input.file_filter_minimum_file_size_kb}', file_extensions_action='${workflow.input.file_filter_file_extensions_action}', file_extensions='${workflow.input.file_filter_file_extensions}', file_extensions_other='${workflow.input.file_filter_file_extensions_other}', reference_name=None, title='File Filter', description='Filters out unwanted files from the input of a flow')

Bases: Block

Available from V40.2

File Filter Block filters out unwanted files from the input of a flow

This block is meant to be placed at the start of the flow/subflow - BEFORE the SubmissionBootstrapBlock, not after it. It requires the output of a connector (e.g. Email Listener) or an API submission as input data, and its output is meant to be consumed by a SubmissionBootstrapBlock.

Mandatory parameters:

This block has no strictly required parameters - all of its filters are optional.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
trigger (str) – the trigger input from a connector - if not set explicitly, it will default to the workflow input trigger (which is where this value is normally found)
filter_type (str) – a discrete value, either “ALL_FILES” or “IMAGES_ONLY”. Determines what kind of files the filters will be applied to. Default value is “ALL_FILES”. If set to “IMAGES_ONLY”, all filtering options will be applied only to images, other files will pass through.
minimum_image_width (Optional[str]) – image width in pixels - half of the image dimension filter. Any image with less width than configured here will be filtered out. Defaults to None (will do nothing).
minimum_image_height (Optional[str]) – image height in pixels - second half of the image dimension filter. Any image with less height than configured here will be filtered out. Defaults to None (will do nothing).
minimum_file_size_kb (Optional[str]) – represents the file size filter. Any file whose disk size is less than this number (in KB) will be filtered out. May be fractional. Defaults to None (will do nothing).
file_extensions_action (str) – a discrete value, either “ALLOW”, “DENY” or “NONE”. Represents the function of the file extension filter. “ALLOW” means we only allow the configured file extensions. “DENY” means we only deny the configured file extensions. “NONE” means no file extension filtering takes place. Defaults to “NONE”
file_extensions (Optional[str]) – a list of strings, representing the file extensions used for file extension filtering. Expected if file_extensions_action is not “NONE”. Otherwise, defaults to None (will do nothing).
file_extensions_other (Optional[str]) – a comma separated list of file extensions used for file extension filtering. Meant for adding extra extensions that are not available in the pre-defined list. Optional, defaults to None (will do nothing). However, it is expected in case the file_extensions parameter contains “other”.

Example usage:

# File Filter Block filters out unwanted files from the input of a flow
file_filter_block = FileFilterBlock(
    # trigger: str = workflow_input(Inputs.Trigger),  # usually not necessary to set this
    reference_name='file_filter',
    filter_type='ALL_FILES',
    minimum_image_width=500,
    minimum_image_height=500,
    minimum_file_size_kb=2.5,
    file_extensions_action='ALLOW',
    file_extensions=['pdf', 'png'],
    file_extensions_other='jpg,svg,txt',
)

# reference to the output of FileFilterBlock which can be passed as input to the
# next block (a SubmissionBootstrapBlock)
output_ref = file_filter_block.output('result.filtered_trigger')
submission_bootstrap = SubmissionBootstrapBlock(trigger=output_ref)

Example content of output_ref:

{
    "payload": {
        "blob_storage_files": [
            {
                "uuid": "db58606e-32f9-42c9-a0bc-ed9848ff247a",
            }
        ],
        "filtered_files": [
            {
                "uuid": "db58606e-32f9-42c9-a0bc-ed9848ff246e",
                "filtered_by": [
                    "file_size_filter"
                ]
            },
        ]
    }
}

IDENTIFIER = 'FILE_FILTER'

Trigger Blocks (v41)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v41)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

S3 Listener (v41)

Identifier: S3_TRIGGER Parameters:

Name	Type	Default Value	Title	Description
bucket_uri	string	N/A	S3 source URI	S3 URI, where the files will be uploaded (e.g. s3://hs_bucket/prefix1/)
archive_bucket_uri	string	N/A	S3 archive URI	S3 URI to move the processed files to (e.g. s3://hs_bucket/prefix1/)
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission s3 prefixes. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or s3 prefixes (e.g., XXX.jpg.json for XXX.jpg)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used
poll_interval	integer	10	Polling interval (in seconds)	How often the S3 Listener will check the S3 bucket for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the S3 Listener will wait to process the document after it was first detected
api_params	object	{}	API Parameters	N/A

s3_listener = IOBlock(
    identifier='S3_TRIGGER',
    reference_name='s3_trigger',
    title='S3 Listener',
    enabled=True,
    input={
        'bucket_uri': 's3://hs_bucket/prefix1/',
        'archive_bucket_uri': 's3://hs_bucket/prefix2/',
        'file_extensions': ['png', 'pdf', 'jpg'],
        'aws_access_key_id': 'admin',
        'aws_secret_access_key': system_secret('s3_secret_access_key'),
        'use_ec2_instance_credentials': False,
    },
)
triggers = IDPTriggers(blocks=[s3_listener])

Email Listener (v41)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	The frequency at which the connection will monitor the email folder for submissions
folder	Path	N/A	Folder to scan for emails	The email folder to retrieve submissions from (e.g., “inbox”)
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v41)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	string	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	string	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': '24',
        'target_folder_id': '42',
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v41)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v41)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v41)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	No auth credentials required	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	MQCSP authentication mode	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v41)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Kafka Listener (v41)

Identifier: KAFKA_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
bootstrap_servers	string	N/A	Bootstrap Servers	A Comma separated list of host:port pairs to use for establishing the initial connection to the cluster
group_id	string	N/A	Group Id	A unique string that identifies the consumer group this consumer belongs to. BLOCK_THREADS_KAFKA_TRIGGER should be used to scale up or down the number of consumers (default: number of available cores)
topics	string	N/A	Topics	Comma separated list of topic names that the block will subscribe to
consumer_config_json	json	N/A	Consumer Config	JSON formatted string containing key-value pairs of Kafka consumer configurations described in the official Kafka documentation
api_params	object	{}	API Parameters	N/A
consume_timeout	integer	-1	Consume Timeout	Maximum time, in seconds, that the consumer will wait for new messages. If messages are received within the specified time, they are processed immediately. However, if no messages are received within that specified time, consumption cycle will be restarted internally to continue fetching messages. This ensures continuous message consumption (default: infinite)
consume_num_messages	integer	1	Consume Num Messages	Sets the maximum number of messages the consumer fetches in a single consumption cycle.If the number of available messages is less than the specified, and timeout is reached, messages will be processed. Consumption cycle will be restarted after the current finishes

kafka_listener = IOBlock(
    identifier='KAFKA_TRIGGER',
    reference_name='kafka_trigger',
    title='Kafka Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
         'bootstrap_servers': 'example.com',
         'group_id': 'test_group',
         'topics': 'test_topic1, test_topic2',
         'consumer_config_json': {},
         'number_of_workers': 1,
         'consume_timeout': 5,
         'consume_num_messages': 10
    }
)

triggers = IDPTriggers(blocks=[kafka_listener])

Output Blocks (v41)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v41.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v41)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [2]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [3]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A
additional_notification_http_headers	json	null	Additional Notification Request Headers	Key value pairs in json format which will be sent via the request as http headers

[1] one of:

"v5"
"transformed"

[2] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[3] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v41)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A

[1] one of:

"v5"
"transformed"

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v41)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

[1] one of:

"v5"
"transformed"

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v41)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
auth_method [2]	string	“basic_auth”	Authentication method	N/A
url	string	N/A	URL	Base URL of the uipath instance
app_id	string	N/A	App ID	App ID provided by UiPath
app_secret	Password	N/A	App Secret	App Secret provided by UiPath
oauth_token_endpoint	string	N/A	OAuth token endpoint	Endpoint to retrieve the token. Using https://cloud.uipath.com/identity_/connect/token by default
organization_unit_id	string	N/A	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

[1] one of:

"v5"
"transformed"

[2] one of:

"basic_auth"
"oauth"

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v41)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

[1] one of:

"v5"
"transformed"

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

S3 Notifier Output (v41)

With the S3 Notifier Block, you can configure your flow to send extracted information to an S3 bucket.

Identifier: COB_S3_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bucket_uri	string	N/A	S3 URI	S3 URI, where the data should be stored (e.g. s3://hs_bucket/prefix1/prefix2/)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used

[1] one of:

"v5"
"transformed"

cob_s3_notifier = IOBlock(
    identifier='COB_S3_NOTIFIER',
    reference_name='cob_s3_notifier',
    title='S3 Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bucket_uri': 's3://hs_bucket/prefix1/prefix2/',
        'aws_access_key_id': 'aws_access',
        'aws_secret_access_key': system_secret('aws_secret_access_key'),
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_s3_notifier],
)

Kafka Notifier Output (v41)

With the Kafka Notifier Block, you can configure your flow to send extracted information to a kafka topic.

Identifier: COB_KAFKA_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bootstrap_servers	string	N/A	Bootstrap Servers	A list of Kafka brokers to connect to. For example: “kafka1:9092,kafka2:9092”
topic	string	N/A	Topic	The Kafka topic where your data will be sent
client_id	string	N/A	SECRET ACCESS KEY	An identifier for your application when connecting to Kafka, typically used for tracking and logging purposes
producer_config_json	json	true	Producer Config (JSON)	Configuration settings for the Kafka producer in JSON format. See https://kafka.apache.org/documentation/#producerconfigs for more information
synchronous_publish	boolean	true	Sync Publish	If true, the publish call will block until the message is sent successfully or an error is raised. If false, the publish call will return immediately after enqueueing the message
message_key	string	null	Message Key	The key associated with the message to be sent. This is used to determine which partition the message is sent to. If null, the message will be sent to a random partition

[1] one of:

"v5"
"transformed"

cob_kafka_notifier = IOBlock(
    identifier='COB_KAFKA_NOTIFIER',
    reference_name='cob_kafka_notifier',
    title='Kafka Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bootstrap_servers': 'kafka1:9092,kafka2:9092',
        'topic': 'topic',
        'client_id': 'client_id',
        'producer_config_json': {},
        'synchronous_publish': True,
        'message_key': 'key'
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_kafka_notifier],
)

Helper Classes and Functions (v41)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v41.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v41.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v41.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config, document_rendering, file_filter, notification_workflow_initialization=None, notification_workflow_classification=None, notification_workflow_identification=None, notification_workflow_transcription=None, notification_workflow_flexible_extraction=None, field_transcription_target_accuracies=None, identification_target_accuracies=None): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v41.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v41.idp_values.IDPWrapperManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP wrapper flows. In particular, provides defaults for some fields (e.g. roles) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPWrapperManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

class flows_sdk.implementations.idp_v41.idp_values.IDPCoreManifest(flow_identifier, roles=None)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP Core flows. In particular, provides defaults for some fields (e.g. roles, output) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:

flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow
roles (Optional[List[str]]) – ‘read_only’, ‘supporting’ and ‘idp_core’ are the default roles of every subflow that can replace the default IDP_CORE subflow inside the top-level IDP flows. ‘supporting’ and ‘idp_core’ are mandatory roles that are necessary for all IDP Core flows. ‘supporting’ ensures that the subflow will be auto-deployed together with the top-level IDP flow. ‘idp_core’ ensures that this subflow can be selected in the UI in dropdowns which allow picking an alternative subflow to the default IDP_CORE subflow. If you are implementing a subflow that is not supposed to be a drop-in replacement for IDP_CORE, you will have to subclass or implement your own version of IDPCoreManifest class in order to remove the idp_core role.

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPCoreManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V40

Processing Blocks (v40)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v40 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v40.idp_blocks.IDPCoreBlock(idp_wf_config, reference_name='__idp_core__', title='Start Document Processing Subflow', description='Calls the Document Processing Subflow with the specified settings.', compatibility_spec=CompatibilitySpec(filter_roles=['idp_core'], filter_schema=None, label=None), identifier='IDP_CORE_V40', additional_inputs=None)

Bases: Block

IDP core block includes the steps to process the passed documents into machine-readable output.

Mandatory parameters:

Parameters:: idp_wf_config (IdpWorkflowConfig) – IdpWorkflowConfig object with all flow-level configuration settings for IDP

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique reference name within a flow, a unique one will be generated when not provided
compatibility_spec (Optional[CompatibilitySpec]) – defines a filter for flows that could be selected in the UI in place of “IDP Core” for the block. Defaults to flows with the role ‘idp_core’. The user will be able to pick any flow that matches the compatibility_spec. This serves to make upgrading to a new compatible version of “IDP Core” (e.g. IDP_CORE_V39) easier in future releases.
identifier (str) – The identifier of the flow. Defaults to the IDP_CORE_VXX identifier of the out-of-the-box flow that comes with the system.
additional_inputs (Optional[Dict[str, Any]]) – Dictionary containing key-value pairs that will be added to the inputs of the block. If a key is contained in the default inputs, its value will be overwritten by the value provided here. You generally do not need to provide additional_inputs, unless you are creating a custom derivative of the IDP_CODE_Vxx flow and are modifying or extending the list of inputs it accepts.

Example usage:

idp_core = IDPCoreBlock(idp_wf_config=idp_wf_config)

REFERENCE_NAME = '__idp_core__'

class flows_sdk.implementations.idp_v40.idp_blocks.SubmissionBootstrapBlock(reference_name=None, trigger='${workflow.input.$trigger}', layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${workflow.input.submission_bootstrap_s3_config}', s3_endpoint_url='${workflow.input.submission_bootstrap_s3_endpoint_url}', ocs_config='${workflow.input.submission_bootstrap_ocs_config}', http_config='${workflow.input.submission_bootstrap_http_config}', abs_auth_type='${workflow.input.submission_bootstrap_abs_auth_type}', abs_account_url='${workflow.input.submission_bootstrap_abs_account_url}', abs_tenant_id='${workflow.input.submission_bootstrap_abs_tenant_id}', abs_client_id='${workflow.input.submission_bootstrap_abs_client_id}', abs_client_secret='${workflow.input.submission_bootstrap_abs_client_secret}', abs_authority_host='${workflow.input.submission_bootstrap_abs_authority_host}', abs_account_name='${workflow.input.submission_bootstrap_abs_account_name}', abs_account_key='${workflow.input.submission_bootstrap_abs_account_key}', notification_workflow='${workflow.input.notification_workflow_initialization}', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}', submission='${workflow.input.submission}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
trigger (str) – the trigger input from a connector - if not set explicitly, it will default to the workflow input trigger (which is where this value is normally found)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to workflow_input(Settings.SubmissionBootstrapS3Config)
s3_endpoint_url (str) – Endpoint URL for S3 submission retrieval store, defaults to workflow_input(Settings.SubmissionBootstrapS3EndpointUrl)
ocs_config (str) – OCS Configuration for downloading submission data, defaults to workflow_input(Settings.SubmissionBootstrapOCSConfig)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to workflow_input(Settings.SubmissionBootstrapHTTPConfig)
notification_workflow (Optional[str]) – Notification flow name to run when the submission is initialized, defaults to workflow_input(Settings.SubmissionBootstrapNotificationWorkflow)
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)
submission (Any) – Submission object

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v40.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files='${workflow.input.machine_collation_dedupe_files}', refresh_retention_period='${workflow.input.machine_collation_refresh_retention_period}', remove_from_cases='${workflow.input.machine_collation_remove_from_cases}', retention_period='${workflow.input.machine_collation_retention_period}', reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (Union[bool, str]) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases. Defaults to workflow_input(Settings.CollationDedupeFiles)
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case, defaults to workflow_input(Settings.CollationRemoveFromCases)

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Union[int, str, None]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. Defaults to workflow_input(Settings.CollationRetentionPeriod)
refresh_retention_period (Union[bool, str]) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. Defaults to workflow_input(Settings.CollationRefreshRetentionPeriod)

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v40.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled='${workflow.input.machine_classification_rotation_correction_enabled}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', file_transcription_enabled='${workflow.input.machine_classification_file_transcription_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}', layout_id_dealbreaker='${workflow.input.layout_id_dealbreaker}', layout_id_dealbreaker_bypass='${workflow.input.layout_id_dealbreaker_bypass}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (Union[bool, str]) – Identifies and corrects the orientation of semi-structured images, defaults to workflow_input(Settings.RotationCorrectionEnabled)
mobile_processing_enabled (Union[bool, str]) – Improves the machine readability of photo captured documents, defaults to workflow_input(Settings.MobileProcessingEnabled)
file_transcription_enabled (Union[bool, str]) – Improves the transcription speed of pdf files. Make sure that the “Image Correction” option is disabled and the pdfs you submit do not contain any rotated images defaults to workflow_input(Settings.FileTranscriptionEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_7'

class flows_sdk.implementations.idp_v40.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions='${workflow.input.manual_classification_task_restrictions}', notification_workflow='${workflow.input.notification_workflow_classification}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualClassificationTaskRestrictions)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to workflow_input(Settings.ManualClassificationNotificationWorkflow)
nlc_enabled – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy – Classification Target Accuracy, defaults to workflow_input(Settings.SemiTargetAccuracy)
mobile_processing_enabled – Improves the machine readability of photo captured document, defaults to workflow_input(Settings.MobileProcessingEnabled)
vpc_registration_threshold (Optional[str]) – Structured pages above this threshold will be automatically matched to a layout variation when performing light vpc registration in the doc-org task, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_4'

class flows_sdk.implementations.idp_v40.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (Any) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_7'

class flows_sdk.implementations.idp_v40.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions='${workflow.input.manual_identification_task_restrictions}', manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_identification}')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualFieldIdTaskRestrictions)
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to workflow_inputSettings.ManualFieldIdNotificationWorkflow

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v40.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}', field_target_accuracies='${workflow.input.field_transcription_target_accuracies}', column_target_accuracies='${workflow.input.column_transcription_target_accuracies}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )
field_target_accuracies (str) – defaults to workflow_input( Settings.FieldTargetAccuracies )
column_target_accuracies (str) – defaults to workflow_input( Settings.ColumnTargetAccuracies )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_9'

class flows_sdk.implementations.idp_v40.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.manual_transcription_supervision_transcription_masking}', table_output_manual_review='${workflow.input.manual_transcription_table_output_manual_review}', always_supervise_blank_cells='${workflow.input.manual_transcription_always_supervise_blank_cells}', task_restrictions='${workflow.input.manual_transcription_task_restrictions}', manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='${workflow.input.notification_workflow_transcription}', title='Manual Transcription', description='Manually transcribe fields that could not be automatically transcribed')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str]) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to workflow_input(Settings.ManualTranscriptionSupervisionTranscriptionMasking)
table_output_manual_review (Union[bool, str]) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to workflow_input(Settings.ManualTranscriptionTableOutputManualReview)
always_supervise_blank_cells (Union[bool, str]) – If enabled, always send blank cells in transcribed tables to be supervised manually, regardless of confidence defaults to workflow_input(Settings.ManualTranscriptionAlwaysSuperviseBlankCells)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to workflow_input(Settings.ManualTranscriptionTaskRestrictions)
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to workflow_input(Settings.ManualTranscriptionNotificationWorkflow)

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_5'

class flows_sdk.implementations.idp_v40.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.flexible_extraction_supervision_transcription_masking}', task_restrictions='${workflow.input.flexible_extraction_task_restrictions}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_flexible_extraction}')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str, None]) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to workflow_input(Settings.FlexibleExtractionSupervisionTranscriptionMasking)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults workflow_input(Settings.FlexibleExtractionTaskRestrictions)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to workflow_input(Settings.FlexibleExtractionNotificationWorkflow)

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_4'

class flows_sdk.implementations.idp_v40.idp_blocks.ReprocessingBlock(reference_name, submission, parent_flow='${workflow.definition.identifier}', idp_wf_config='${workflow.input}', trigger='${workflow.input.$trigger}')

Bases: Block

Reprocessing block enables a second extraction attempt if documents were initially confidently mis-classified by the machine. When an end-user specifies that a document layout is incorrect during Manual Identification, Manual Transcription, or Flexible Extraction, the flow will reach the Reprocessing block which will mark correctly classified documents as “complete” status, and misclassified documents with “reprocess” status will be processed in a second execution of the flow. This block should be placed before the SubmissionCompleteBlock to enable reprocessing.

How the Reprocessing block works

The Reprocessing block examines whether any documents within the submission have been marked with an incorrect layout, and if so, redirects the submission to the classification step for proper classification. It does this by recursively calling the same flow or subflow with the same inputs and documents, but with the addition of a status key for each document to denote which were marked with an incorrect layout during supervision.

Note

The Reprocessing block works in tandem with the “Mark Incorrect Layout” option presented to users during Manual Identification, Manual Transcription, and Flexible Extraction supervision interfaces introduced in R38. Include the Reprocessing block in all custom flows in order to take advantage of this feature. The feature will remain selectable in supervision interfaces even if the Reprocessing block is not included in the flow.

The initial flow run will pause execution at the Reprocessing block until the recursive flow has completed, at which point the initial flow will resume to finish its execution. If an error occurs during the execution of the recursive flow, that error will be raised to the Reprocessing block of the initial flow.

Note

The recursive flow run is linked with the same correlation_id as the initial flow run and the submission. Users can click the “View related flow runs” link on the left sidebar of the initial flow run to view any recursive flow runs.

As expected, recursively calling the same flow may cause some blocks to run again, resulting in unnecessary work being performed, or work which doesn’t gracefully handle duplications (non-idempotent blocks). To mitigate this, certain Hyperscience-provided blocks - including Submission Initialization, Machine Collation, and Machine Classification - detect when the submission object already contains the output from its block to avoid re-execution. It’s a best practice to build custom blocks such that they are idempotent and reentrant; if that’s not feasible, you can add similar logic to custom blocks which do not depend on the layout for the documents being processed. Common methods for handling this include:

Iterating through each status key within the submission.document[] collection to see if any documents are set to “reprocess”.
Inspecting if the submission object already contains a key or value explicitly defined by the custom code block.

Recommended Placement for the Reprocessing Block

The Reprocessing block should not be placed before any supervision blocks which allow users to mark a document with an incorrect layout. These supervision blocks include Manual Identification, Manual Transcription and Flexible Extraction.
The Reprocessing block should always be placed before the SubmissionCompete Block.
The Reprocessing block can be used with flows which include multiple branches and conditionals; however, it’s recommended to ensure the Reprocessing block is executed to honor user’s selection of marking layouts incorrectly when supervising documents.
In general, any custom logic that is to be performed after data has been extracted from documents should be placed after the Reprocessing block. To avoid duplicate executions of this custom logic, it is recommended to separate the document processing blocks - inclusive of the Reprocessing block - from the custom logic. This can be handled in different ways:
- Split the flow into separate subflows, where the Reprocessing block is in a subflow that does not contain the custom logic.
- Add a decision to bypass the custom logic if the Reprocessing block was triggered. With this method, the recursive flow run will execute the custom logic, and the initial flow run will bypass the logic.

Mandatory parameters:

Parameters:: submission (Any) – Submission object

IDENTIFIER = 'REPROCESSING_2'

class flows_sdk.implementations.idp_v40.idp_blocks.SubmissionCompleteBlock(submission, is_reprocessing=False, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v40.idp_blocks.SetTransformedOutputBlock(submission, transformed_output, reference_name=None)

Bases: Block

Set Transformed Output block sets the transformed output for the provided submission. This can later be used to send the transformed data downstream using output blocks. For more information see https://docs.hyperscience.com/#retrieving-transformed-submissions.

Mandatory parameters:

Parameters:

submission (str) – Submission object
transformed_output (str) – Object that will be set as the transformed output for this submission

IDENTIFIER = 'SET_TRANSFORMED_OUTPUT'

class flows_sdk.implementations.idp_v40.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[str, bool]) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Union[str, List[Any], None]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Union[str, List[int], None]) – This is an optional parameter. If left empty, the IDP wrapper will, by default, pull in all pages in the submission. Adding a list of page IDs will override the default list of pages. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v40.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None, language_family=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v40/docs/supported-languages

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION_2'

class flows_sdk.implementations.idp_v40.idp_blocks.DocumentRendererBlock(submission, is_reprocessing=False, title='Document Renderer', description='Renders a document into a PDF', reference_name=None, document_rendering_enabled='${workflow.input.document_rendering_enabled}', document_rendering_mime_type='${workflow.input.document_rendering_mime_type}', document_rendering_unit='${workflow.input.document_rendering_unit}', document_rendering_height='${workflow.input.document_rendering_height}', document_rendering_width='${workflow.input.document_rendering_width}', document_rendering_quality='${workflow.input.document_rendering_quality}')

Bases: Block

Document File Generator Block renders a document into a PDF and stores it in the Blob storage.

This block should be placed ALWAYS after a Reprocessing block (if there is any) so that it is not possible to have more changes in the documents’ organisation.

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be rendered.

Optional parameters:

Parameters:

document_rendering_enabled (Union[bool, str]) – a boolean that enables or disables the document rendering. Default is False.
document_rendering_mime_type (str) – the mime type of the document to be generated. Default is ‘application/pdf’
document_rendering_unit (str) – the unit of the document to be generated. Default is ‘inches’
document_rendering_height (Union[str, float]) – the height of the document to be generated. Default is 11
document_rendering_width (Union[str, float]) – the width of the document to be generated. Default is 8.5
document_rendering_quality (Union[str, int]) – Quality of pages (images) appended to the resulting document as a percentage (recommended 50%). Higher quality results in a larger file size for the generated PDF.
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

# Use the output of the reprocessing block.
reprocessing = ReprocessingBlock(reference_name='reprocessing')

document_renderer_block = DocumentRendererBlock(
    reference_name='document_renderer',
    submission=reprocessing.output(submission),
    document_rendering_enabled=True,
    document_rendering_unit='in',
    document_rendering_width=8.5,
    document_rendering_height=11,
    document_rendering_quality=50
    is_reprocessing=reprocessing.output('is_reprocessing')
)

output_ref = document_renderer_block.output()

Example content of output_ref:

{
    'document_files': {
        [
            {
                'document_id': "1",
                'blob_uuid': 'f42fc9af-b551-4403-aba6-d0eba2c41973',
                'mime_type': 'application/pdf',
                'height_in_mm': 279.4,
                'width_in_mm': 215.9,
                'quality': 50,
            }
        ]
    },
    'submission': {
        ...
    }
}

IDENTIFIER = 'DOCUMENT_RENDERER'

class flows_sdk.implementations.idp_v40.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, language_family=None, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of images. Enabled by default.
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents. Disabled by default.
language_family (Optional[str]) – language family to use when performing image correction. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v40/docs/supported-languages
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

Additional Blocks (v40)

class flows_sdk.implementations.idp_v40.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v40.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, language_family=None, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of images. Enabled by default.
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents. Disabled by default.
language_family (Optional[str]) – language family to use when performing image correction. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v40/docs/supported-languages
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v40.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', language_family=None, app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v40/docs/supported-languages
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES_2'

class flows_sdk.implementations.idp_v40.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY', title='Custom Supervision', description='Custom Supervision')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 15,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': False,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurrence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,
                'image_url': '/image/2ed3d989-b64a-44bd-a9fb-6e0dcc5ccdb8',
                'form_id': 2,
                'submission_id': 1,
                'external_case_ids': [],
                'read_only': False,
                'filename': '1 page.pdf',
                'form_page_id': 1
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v40.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, use_wsdl=False, wsdl_uri='', wsdl_service_name='', wsdl_port_name='', title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v40.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v40.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v40.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

class flows_sdk.implementations.idp_v40.additional_blocks.LlamaBlock(model_id, prompt, reference_name=None, consent=False, tokenize_only=False, predict_extra_kwargs=None, title='Llama Text Generation', description='Text generation using the Llama 2 model')

Bases: Block

Text generation using the Llama 2 model by Meta.

This block utilizes Llama 2 by Meta. Llama 2 is licensed under the LLAMA 2 Community License (https://ai.meta.com/llama/license/). By using the Llama Block, you acknowledge that you have received a copy of the LLAMA 2 Community License.

Note: This block is still experimental and not ready for production use.

Mandatory parameters:

Parameters:

model_id (str) – UUID, identifier of the asset with the ML model. Model assets are not part of the Hypersicence bundle and must first be downloaded and imported into the system before they can be used. Please contact your Hyperscience representative to discuss the usecase and the appropriate model and to get instructions on downloading the models. Once downloaded, here are the available model asset UUIDs: b3da05c7-061c-4a58-af6d-4c905d2e618f - Llama 2, 13B, 8-bit quantized
prompt (str) – The prompt to generate text from. Use a CodeBlock ahead of the LlamaBlock in order to build the prompt. The context window of the model is limited to 4096 tokens. If the prompt has more tokens, the block would return an error. The total input and output length also cannot exceed 4096 tokens, which means that if the input is too long, the output may be truncated. Also see tokenize_only for a more detailed explanation of how to handle longer texts.

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
consent (Optional[bool]) – Has the business user read and acknowledged the Llama 2 legal notice. Unless the flow would be used in CI automation, this should be set to False so that a business user can read and acknowledge the notice in the Hyperscience UI. Setting this to True in the Python definition of the flow is also treated as acknowledgement of the notice on behalf of the entity that will be using the flow.
tokenize_only (Optional[bool]) – In the context of LLMs, tokens correspond roughly to words, partial words and punctuation. A rough way to compute the number of tokens in a text is number_of_tokens = 1.25 * number_of_words. The Llama block works with a context window of 4096 tokens. If a longer prompt is passed in, it would return an error. Also, if the prompt is shorter, but still close to 4096, the output may be truncated. Since the length of the prompt in tokens cannot be known ahead of time, sometimes the flow may need to make dynamic decisions whether to pass the text to the Llama block, or to split it into multiple chunks, or to use some alternative method for processing it (e.g. a custom supervision manual task). The tokenize_only option enables flows to take such dynamic decisions based on the length of the prompt in tokens. The default is false - it instructs the block to run the ML model inference over the prompt, i.e. to generate a text response. When true is passed, the model will simply tokenize the prompt without running inference and return the list of tokens - this will work regardless of the length of the prompt. A subsequent Decision task can then route longer prompts to an alternative path in the flow, while routing shorter prompts to the LlamaBlock for actual text generation.
predict_extra_kwargs (Optional[Dict[Any, Any]]) – Extra keyword arguments used for model inference. (Used to fine-tune the model prediction. Not recommended to change this unless you know what you are doing)

Example usage:

llama = LlamaBlock(
    reference_name='llama',
    model_id='b3da05c7-061c-4a58-af6d-4c905d2e618f',
    prompt='${previous_block.output.llama_prompt}',
)

IDENTIFIER = 'LLAMA'

class flows_sdk.implementations.idp_v40.additional_blocks.EntityRecognitionBlock(pages, regex_map=None, keyword_map=None, enhanced_output=False, ner_enabled=True, ced_enabled=True, signature_enabled=True, reference_name=None, title='Entity Recognition', description='Recognizes entities of different types in documents')

Bases: Block

Entity Recognition Block detects entities of different types within the documents contained in a submission

This block requires the output of the Full Page Transcription Block as input data.

Mandatory parameters:

Parameters:

pages (str) – list of pages that includes the raw documents with the transcribed information from the FPT block
regex_map (Optional[Dict[str, str]]) – a map that specifies different regex patterns that the block should look for, a default one is present
keyword_map (Optional[Dict[str, List[str]]]) – a map that specifies different keyword patterns that the block should look for, a default one is present

Optional Parameters:

Parameters:

enhanced_output (bool) – a boolean flag that enables toggling between simple and enhanced output formats. Default value is False.
ner_enabled (bool) – a boolean flag that enables or disables Named Entity Recognition. Default value is True.
ced_enabled (bool) – a boolean flag that enables or disables Custom Entity Detection. Default value is True.
signature_enabled (bool) – a boolean flag that enables or disables Signature Detection. Default value is True.
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

# EntityRecognitionBlock detects entities within the documents contained in the submission
entity_recognition_block = EntityRecognitionBlock(
    reference_name='entity_recognition',
    pages=submission_bootstrap.output(submission.unassigned_pages),
    regex_map=DEFAULT_PII_REGEX_MAP,
    keyword_map=DEFAULT_PII_KEYWORD_MAP,
    enhanced_output=False,
)

# reference to the output of EntityRecognitionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = entity_recognition_block.output()

Example content of output_ref:

{
    "documents": [
        {
            "file_uuid": "da2c6117-43c4-4b30-84c4-cdc59cc3fa4f",
            "entities": [
                {
                    "text": "John Smith",
                    "type": "Person Name",
                    "positions": [
                        [0.5, 0.1, 0.55, 0.13],
                        [0.6, 0.2, 0.65, 0.23],
                        [0.7, 0.3, 0.75, 0.33],
                    ],
                    "page_ids": [0, 0, 1],
                    "origin": "NER",
                },
                {
                    "text": "<SIGNED>",
                    "type": "signature",
                    "positions": [[0.701171875, 0.732421875, 0.92578125, 0.8681640625]],
                    "page_ids": [0],
                    "origin": "Signature",
                },
            ]
        },
        {
            "file_uuid": "4aa38f84-e5af-4cdc-ba5c-edd60f0a6b89",
            "entities": [
                ...
            ]
        }
    ],
    "redaction_annotations": {
        "ner": [ ... ],
        "ced": [ ... ],
    }
}

IDENTIFIER = 'ENTITY_RECOGNITION'

class flows_sdk.implementations.idp_v40.additional_blocks.FileFilterBlock(trigger='${workflow.input.$trigger}', filter_type='ALL_FILES', minimum_image_width=None, minimum_image_height=None, minimum_file_size_kb=None, file_extensions_action='NONE', file_extensions=None, file_extensions_other=None, reference_name=None, title='File Filter', description='Filters out unwanted files from the input of a flow')

Bases: Block

Available from V40.2

File Filter Block filters out unwanted files from the input of a flow

This block is meant to be placed at the start of the flow/subflow - BEFORE the SubmissionBootstrapBlock, not after it. It requires the output of a connector (e.g. Email Listener) or an API submission as input data, and its output is meant to be consumed by a SubmissionBootstrapBlock.

Mandatory parameters:

This block has no strictly required parameters - all of its filters are optional.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
trigger (str) – the trigger input from a connector - if not set explicitly, it will default to the workflow input trigger (which is where this value is normally found)
filter_type (Literal['ALL_FILES', 'IMAGES_ONLY']) – a discrete value, either “ALL_FILES” or “IMAGES_ONLY”. Determines what kind of files the filters will be applied to. Default value is “ALL_FILES”. If set to “IMAGES_ONLY”, all filtering options will be applied only to images, other files will pass through.
minimum_image_width (Optional[int]) – image width in pixels - half of the image dimension filter. Any image with less width than configured here will be filtered out. Defaults to None (will do nothing).
minimum_image_height (Optional[int]) – image height in pixels - second half of the image dimension filter. Any image with less height than configured here will be filtered out. Defaults to None (will do nothing).
minimum_file_size_kb (Optional[float]) – represents the file size filter. Any file whose disk size is less than this number (in KB) will be filtered out. May be fractional. Defaults to None (will do nothing).
file_extensions_action (Literal['NONE', 'ALLOW', 'DENY']) – a discrete value, either “ALLOW”, “DENY” or “NONE”. Represents the function of the file extension filter. “ALLOW” means we only allow the configured file extensions. “DENY” means we only deny the configured file extensions. “NONE” means no file extension filtering takes place. Defaults to “NONE”
file_extensions (Optional[list]) – a list of strings, representing the file extensions used for file extension filtering. Expected if file_extensions_action is not “NONE”. Otherwise, defaults to None (will do nothing).
file_extensions_other (Optional[str]) – a comma separated list of file extensions used for file extension filtering. Meant for adding extra extensions that are not available in the pre-defined list. Optional, defaults to None (will do nothing). However, it is expected in case the file_extensions parameter contains “other”.

Example usage:

# File Filter Block filters out unwanted files from the input of a flow
file_filter_block = FileFilterBlock(
    # trigger: str = workflow_input(Inputs.Trigger),  # usually not necessary to set this
    reference_name='file_filter',
    filter_type='ALL_FILES',
    minimum_image_width=500,
    minimum_image_height=500,
    minimum_file_size_kb=2.5,
    file_extensions_action='ALLOW',
    file_extensions=['pdf', 'png'],
    file_extensions_other='jpg,svg,txt',
)

# reference to the output of FileFilterBlock which can be passed as input to the
# next block (a SubmissionBootstrapBlock)
output_ref = file_filter_block.output('result.filtered_trigger')
submission_bootstrap = SubmissionBootstrapBlock(trigger=output_ref)

Example content of output_ref:

{
    "payload": {
        "blob_storage_files": [
            {
                "uuid": "db58606e-32f9-42c9-a0bc-ed9848ff247a",
            }
        ],
        "filtered_files": [
            {
                "uuid": "db58606e-32f9-42c9-a0bc-ed9848ff246e",
                "filtered_by": [
                    "file_size_filter"
                ]
            },
        ]
    }
}

IDENTIFIER = 'FILE_FILTER'

Trigger Blocks (v40)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v40)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

S3 Listener (v40)

Identifier: S3_TRIGGER Parameters:

Name	Type	Default Value	Title	Description
bucket_uri	string	N/A	S3 source URI	S3 URI, where the files will be uploaded (e.g. s3://hs_bucket/prefix1/)
archive_bucket_uri	string	N/A	S3 archive URI	S3 URI to move the processed files to (e.g. s3://hs_bucket/prefix1/)
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission s3 prefixes. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or s3 prefixes (e.g., XXX.jpg.json for XXX.jpg)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used
poll_interval	integer	10	Polling interval (in seconds)	How often the S3 Listener will check the S3 bucket for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the S3 Listener will wait to process the document after it was first detected
api_params	object	{}	API Parameters	N/A

s3_listener = IOBlock(
    identifier='S3_TRIGGER',
    reference_name='s3_trigger',
    title='S3 Listener',
    enabled=True,
    input={
        'bucket_uri': 's3://hs_bucket/prefix1/',
        'archive_bucket_uri': 's3://hs_bucket/prefix2/',
        'file_extensions': ['png', 'pdf', 'jpg'],
        'aws_access_key_id': 'admin',
        'aws_secret_access_key': system_secret('s3_secret_access_key'),
        'use_ec2_instance_credentials': False,
    },
)
triggers = IDPTriggers(blocks=[s3_listener])

Email Listener (v40)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	The frequency at which the connection will monitor the email folder for submissions
folder	Path	N/A	Folder to scan for emails	The email folder to retrieve submissions from (e.g., “inbox”)
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v40)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	string	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	string	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': '24',
        'target_folder_id': '42',
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v40)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v40)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v40)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	No auth credentials required	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	MQCSP authentication mode	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v40)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Kafka Listener (v40)

Identifier: KAFKA_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
bootstrap_servers	string	N/A	Bootstrap Servers	A Comma separated list of host:port pairs to use for establishing the initial connection to the cluster
group_id	string	N/A	Group Id	A unique string that identifies the consumer group this consumer belongs to. BLOCK_THREADS_KAFKA_TRIGGER should be used to scale up or down the number of consumers (default: number of available cores)
topics	string	N/A	Topics	Comma separated list of topic names that the block will subscribe to
consumer_config_json	json	N/A	Consumer Config	JSON formatted string containing key-value pairs of Kafka consumer configurations described in the official Kafka documentation
api_params	object	{}	API Parameters	N/A
consume_timeout	integer	-1	Consume Timeout	Maximum time, in seconds, that the consumer will wait for new messages. If messages are received within the specified time, they are processed immediately. However, if no messages are received within that specified time, consumption cycle will be restarted internally to continue fetching messages. This ensures continuous message consumption (default: infinite)
consume_num_messages	integer	1	Consume Num Messages	Sets the maximum number of messages the consumer fetches in a single consumption cycle.If the number of available messages is less than the specified, and timeout is reached, messages will be processed. Consumption cycle will be restarted after the current finishes

kafka_listener = IOBlock(
    identifier='KAFKA_TRIGGER',
    reference_name='kafka_trigger',
    title='Kafka Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
         'bootstrap_servers': 'example.com',
         'group_id': 'test_group',
         'topics': 'test_topic1, test_topic2',
         'consumer_config_json': {},
         'number_of_workers': 1,
         'consume_timeout': 5,
         'consume_num_messages': 10
    }
)

triggers = IDPTriggers(blocks=[kafka_listener])

Output Blocks (v40)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v40.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v40)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [2]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [3]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A
additional_notification_http_headers	json	null	Additional Notification Request Headers	Key value pairs in json format which will be sent via the request as http headers

[1] one of:

"v5"
"transformed"

[2] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[3] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v40)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A

[1] one of:

"v5"
"transformed"

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v40)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

[1] one of:

"v5"
"transformed"

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v40)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
auth_method [2]	string	“basic_auth”	Authentication method	N/A
url	string	N/A	URL	Base URL of the uipath instance
app_id	string	N/A	App ID	App ID provided by UiPath
app_secret	Password	N/A	App Secret	App Secret provided by UiPath
oauth_token_endpoint	string	N/A	OAuth token endpoint	Endpoint to retrieve the token. Using https://cloud.uipath.com/identity_/connect/token by default
organization_unit_id	string	N/A	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

[1] one of:

"v5"
"transformed"

[2] one of:

"basic_auth"
"oauth"

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v40)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

[1] one of:

"v5"
"transformed"

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

S3 Notifier Output (v40)

With the S3 Notifier Block, you can configure your flow to send extracted information to an S3 bucket.

Identifier: COB_S3_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bucket_uri	string	N/A	S3 URI	S3 URI, where the data should be stored (e.g. s3://hs_bucket/prefix1/prefix2/)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used

[1] one of:

"v5"
"transformed"

cob_s3_notifier = IOBlock(
    identifier='COB_S3_NOTIFIER',
    reference_name='cob_s3_notifier',
    title='S3 Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bucket_uri': 's3://hs_bucket/prefix1/prefix2/',
        'aws_access_key_id': 'aws_access',
        'aws_secret_access_key': system_secret('aws_secret_access_key'),
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_s3_notifier],
)

Kafka Notifier Output (v40)

With the Kafka Notifier Block, you can configure your flow to send extracted information to a kafka topic.

Identifier: COB_KAFKA_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bootstrap_servers	string	N/A	Bootstrap Servers	A list of Kafka brokers to connect to. For example: “kafka1:9092,kafka2:9092”
topic	string	N/A	Topic	The Kafka topic where your data will be sent
client_id	string	N/A	SECRET ACCESS KEY	An identifier for your application when connecting to Kafka, typically used for tracking and logging purposes
producer_config_json	json	true	Producer Config (JSON)	Configuration settings for the Kafka producer in JSON format. See https://kafka.apache.org/documentation/#producerconfigs for more information
synchronous_publish	boolean	true	Sync Publish	If true, the publish call will block until the message is sent successfully or an error is raised. If false, the publish call will return immediately after enqueueing the message
message_key	string	null	Message Key	The key associated with the message to be sent. This is used to determine which partition the message is sent to. If null, the message will be sent to a random partition

[1] one of:

"v5"
"transformed"

cob_kafka_notifier = IOBlock(
    identifier='COB_KAFKA_NOTIFIER',
    reference_name='cob_kafka_notifier',
    title='Kafka Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bootstrap_servers': 'kafka1:9092,kafka2:9092',
        'topic': 'topic',
        'client_id': 'client_id',
        'producer_config_json': {},
        'synchronous_publish': True,
        'message_key': 'key'
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_kafka_notifier],
)

Helper Classes and Functions (v40)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v40.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v40.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v40.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config, document_rendering, notification_workflow_initialization=None, notification_workflow_classification=None, notification_workflow_identification=None, notification_workflow_transcription=None, notification_workflow_flexible_extraction=None, field_transcription_target_accuracies=None, column_transcription_target_accuracies=None): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v40.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v40.idp_values.IDPWrapperManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP wrapper flows. In particular, provides defaults for some fields (e.g. roles) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPWrapperManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

class flows_sdk.implementations.idp_v40.idp_values.IDPCoreManifest(flow_identifier, roles=None)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP Core flows. In particular, provides defaults for some fields (e.g. roles, output) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:

flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow
roles (Optional[List[str]]) – ‘read_only’, ‘supporting’ and ‘idp_core’ are the default roles of every subflow that can replace the default IDP_CORE subflow inside the top-level IDP flows. ‘supporting’ and ‘idp_core’ are mandatory roles that are necessary for all IDP Core flows. ‘supporting’ ensures that the subflow will be auto-deployed together with the top-level IDP flow. ‘idp_core’ ensures that this subflow can be selected in the UI in dropdowns which allow picking an alternative subflow to the default IDP_CORE subflow. If you are implementing a subflow that is not supposed to be a drop-in replacement for IDP_CORE, you will have to subclass or implement your own version of IDPCoreManifest class in order to remove the idp_core role.

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPCoreManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V39.1

Processing Blocks (v39.1)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v39_1 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v39_1.idp_blocks.IDPCoreBlock(idp_wf_config, reference_name='__idp_core__', title='Start Document Processing Subflow', description='Calls the Document Processing Subflow with the specified settings.', compatibility_spec=CompatibilitySpec(filter_roles=['idp_core'], filter_schema=None, label=None), identifier='IDP_CORE_V39_1', additional_inputs=None)

Bases: Block

IDP core block includes the steps to process the passed documents into machine-readable output.

Mandatory parameters:

Parameters:: idp_wf_config (IdpWorkflowConfig) – IdpWorkflowConfig object with all flow-level configuration settings for IDP

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique reference name within a flow, a unique one will be generated when not provided
compatibility_spec (Optional[CompatibilitySpec]) – defines a filter for flows that could be selected in the UI in place of “IDP Core” for the block. Defaults to flows with the role ‘idp_core’. The user will be able to pick any flow that matches the compatibility_spec. This serves to make upgrading to a new compatible version of “IDP Core” (e.g. IDP_CORE_V39) easier in future releases.
identifier (str) – The identifier of the flow. Defaults to the IDP_CORE_VXX identifier of the out-of-the-box flow that comes with the system.
additional_inputs (Optional[Dict[str, Any]]) – Dictionary containing key-value pairs that will be added to the inputs of the block. If a key is contained in the default inputs, its value will be overwritten by the value provided here. You generally do not need to provide additional_inputs, unless you are creating a custom derivative of the IDP_CODE_Vxx flow and are modifying or extending the list of inputs it accepts.

Example usage:

idp_core = IDPCoreBlock(idp_wf_config=idp_wf_config)

REFERENCE_NAME = '__idp_core__'

class flows_sdk.implementations.idp_v39_1.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${workflow.input.submission_bootstrap_s3_config}', s3_endpoint_url='${workflow.input.submission_bootstrap_s3_endpoint_url}', ocs_config='${workflow.input.submission_bootstrap_ocs_config}', http_config='${workflow.input.submission_bootstrap_http_config}', notification_workflow='${workflow.input.notification_workflow_initialization}', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}', submission='${workflow.input.submission}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to workflow_input(Settings.SubmissionBootstrapS3Config)
s3_endpoint_url (str) – Endpoint URL for S3 submission retrieval store, defaults to workflow_input(Settings.SubmissionBootstrapS3EndpointUrl)
ocs_config (str) – OCS Configuration for downloading submission data, defaults to workflow_input(Settings.SubmissionBootstrapOCSConfig)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to workflow_input(Settings.SubmissionBootstrapHTTPConfig)
notification_workflow (Optional[str]) – Notification flow name to run when the submission is initialized, defaults to workflow_input(Settings.SubmissionBootstrapNotificationWorkflow)
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)
submission (Any) – Submission object

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v39_1.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files='${workflow.input.machine_collation_dedupe_files}', refresh_retention_period='${workflow.input.machine_collation_refresh_retention_period}', remove_from_cases='${workflow.input.machine_collation_remove_from_cases}', retention_period='${workflow.input.machine_collation_retention_period}', reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (Union[bool, str]) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases. Defaults to workflow_input(Settings.CollationDedupeFiles)
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case, defaults to workflow_input(Settings.CollationRemoveFromCases)

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Union[int, str, None]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. Defaults to workflow_input(Settings.CollationRetentionPeriod)
refresh_retention_period (Union[bool, str]) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. Defaults to workflow_input(Settings.CollationRefreshRetentionPeriod)

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v39_1.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled='${workflow.input.machine_classification_rotation_correction_enabled}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', file_transcription_enabled='${workflow.input.machine_classification_file_transcription_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (Union[bool, str]) – Identifies and corrects the orientation of semi-structured images, defaults to workflow_input(Settings.RotationCorrectionEnabled)
mobile_processing_enabled (Union[bool, str]) – Improves the machine readability of photo captured documents, defaults to workflow_input(Settings.MobileProcessingEnabled)
file_transcription_enabled (Union[bool, str]) – Improves the transcription speed of pdf files. Make sure that the “Image Correction” option is disabled and the pdfs you submit do not contain any rotated images defaults to workflow_input(Settings.FileTranscriptionEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_6'

class flows_sdk.implementations.idp_v39_1.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions='${workflow.input.manual_classification_task_restrictions}', notification_workflow='${workflow.input.notification_workflow_classification}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualClassificationTaskRestrictions)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to workflow_input(Settings.ManualClassificationNotificationWorkflow)
nlc_enabled (Union[bool, str, None]) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (Union[float, str, None]) – Classification Target Accuracy, defaults to workflow_input(Settings.SemiTargetAccuracy)
mobile_processing_enabled (Union[bool, str, None]) – Improves the machine readability of photo captured document, defaults to workflow_input(Settings.MobileProcessingEnabled)
vpc_registration_threshold (Optional[str]) – Structured pages above this threshold will be automatically matched to a layout variation when performing light vpc registration in the doc-org task, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_3'

class flows_sdk.implementations.idp_v39_1.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (Any) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_7'

class flows_sdk.implementations.idp_v39_1.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions='${workflow.input.manual_identification_task_restrictions}', manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_identification}')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualFieldIdTaskRestrictions)
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to workflow_inputSettings.ManualFieldIdNotificationWorkflow

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v39_1.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_9'

class flows_sdk.implementations.idp_v39_1.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.manual_transcription_supervision_transcription_masking}', table_output_manual_review='${workflow.input.manual_transcription_table_output_manual_review}', always_supervise_blank_cells='${workflow.input.manual_transcription_always_supervise_blank_cells}', task_restrictions='${workflow.input.manual_transcription_task_restrictions}', manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='${workflow.input.notification_workflow_transcription}', title='Manual Transcription', description='Manually transcribe fields that could not be automatically transcribed')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str]) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to workflow_input(Settings.ManualTranscriptionSupervisionTranscriptionMasking)
table_output_manual_review (Union[bool, str]) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to workflow_input(Settings.ManualTranscriptionTableOutputManualReview)
always_supervise_blank_cells (Union[bool, str]) – If enabled, always send blank cells in transcribed tables to be supervised manually, regardless of confidence defaults to workflow_input(Settings.ManualTranscriptionAlwaysSuperviseBlankCells)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to workflow_input(Settings.ManualTranscriptionTaskRestrictions)
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to workflow_input(Settings.ManualTranscriptionNotificationWorkflow)

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_5'

class flows_sdk.implementations.idp_v39_1.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.flexible_extraction_supervision_transcription_masking}', task_restrictions='${workflow.input.flexible_extraction_task_restrictions}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_flexible_extraction}')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str, None]) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to workflow_input(Settings.FlexibleExtractionSupervisionTranscriptionMasking)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults workflow_input(Settings.FlexibleExtractionTaskRestrictions)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to workflow_input(Settings.FlexibleExtractionNotificationWorkflow)

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_4'

class flows_sdk.implementations.idp_v39_1.idp_blocks.ReprocessingBlock(reference_name, submission, parent_flow='${workflow.definition.identifier}', idp_wf_config='${workflow.input}', trigger='${workflow.input.$trigger}')

Bases: Block

Reprocessing block enables a second extraction attempt if documents were initially confidently mis-classified by the machine. When an end-user specifies that a document layout is incorrect during Manual Identification, Manual Transcription, or Flexible Extraction, the flow will reach the Reprocessing block which will mark correctly classified documents as “complete” status, and misclassified documents with “reprocess” status will be processed in a second execution of the flow. This block should be placed before the SubmissionCompleteBlock to enable reprocessing.

Mandatory parameters:

Parameters:: submission (Any) – Submission object

IDENTIFIER = 'REPROCESSING'

class flows_sdk.implementations.idp_v39_1.idp_blocks.SubmissionCompleteBlock(submission, is_reprocessing=False, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v39_1.idp_blocks.SetTransformedOutputBlock(submission, transformed_output, reference_name=None)

Bases: Block

Set Transformed Output block sets the transformed output for the provided submission. This can later be used to send the transformed data downstream using output blocks. For more information see https://docs.hyperscience.com/#retrieving-transformed-submissions.

Mandatory parameters:

Parameters:

submission (str) – Submission object
transformed_output (str) – Object that will be set as the transformed output for this submission

IDENTIFIER = 'SET_TRANSFORMED_OUTPUT'

class flows_sdk.implementations.idp_v39_1.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V39_1', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[str, bool]) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Union[str, List[Any], None]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Union[str, List[int], None]) – This is an optional parameter. If left empty, the IDP wrapper will, by default, pull in all pages in the submission. Adding a list of page IDs will override the default list of pages. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v39_1.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION_2'

class flows_sdk.implementations.idp_v39_1.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

Additional Blocks (v39.1)

class flows_sdk.implementations.idp_v39_1.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v39_1.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v39_1.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES_2'

class flows_sdk.implementations.idp_v39_1.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V39_1', title='Custom Supervision', description='Custom Supervision')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 15,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': False,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurrence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,
                'image_url': '/image/2ed3d989-b64a-44bd-a9fb-6e0dcc5ccdb8',
                'form_id': 2,
                'submission_id': 1,
                'external_case_ids': [],
                'read_only': False,
                'filename': '1 page.pdf',
                'form_page_id': 1
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v39_1.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, use_wsdl=False, wsdl_uri='', wsdl_service_name='', wsdl_port_name='', title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v39_1.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v39_1.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v39_1.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

class flows_sdk.implementations.idp_v39_1.additional_blocks.LlamaBlock(model_id, prompt, reference_name=None, consent=False, tokenize_only=False, predict_extra_kwargs=None, title='Llama Text Generation', description='Text generation using the Llama 2 model')

Bases: Block

Text generation using the Llama 2 model by Meta.

This block utilizes Llama 2 by Meta. Llama 2 is licensed under the LLAMA 2 Community License (https://ai.meta.com/llama/license/). By using the Llama Block, you acknowledge that you have received a copy of the LLAMA 2 Community License.

Note: This block is still experimental and not ready for production use.

Mandatory parameters:

Parameters:

model_id (str) – UUID, identifier of the asset with the ML model. Model assets are not part of the Hypersicence bundle and must first be downloaded and imported into the system before they can be used. Please contact your Hyperscience representative to discuss the usecase and the appropriate model and to get instructions on downloading the models. Once downloaded, here are the available model asset UUIDs: b3da05c7-061c-4a58-af6d-4c905d2e618f - Llama 2, 13B, 8-bit quantized
prompt (str) – The prompt to generate text from. Use a CodeBlock ahead of the LlamaBlock in order to build the prompt. The context window of the model is limited to 4096 tokens. If the prompt has more tokens, the block would return an error. The total input and output length also cannot exceed 4096 tokens, which means that if the input is too long, the output may be truncated. Also see tokenize_only for a more detailed explanation of how to handle longer texts.

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
consent (Optional[bool]) – Has the business user read and acknowledged the Llama 2 legal notice. Unless the flow would be used in CI automation, this should be set to False so that a business user can read and acknowledge the notice in the Hyperscience UI. Setting this to True in the Python definition of the flow is also treated as acknowledgement of the notice on behalf of the entity that will be using the flow.
tokenize_only (Optional[bool]) – In the context of LLMs, tokens correspond roughly to words, partial words and punctuation. A rough way to compute the number of tokens in a text is number_of_tokens = 1.25 * number_of_words. The Llama block works with a context window of 4096 tokens. If a longer prompt is passed in, it would return an error. Also, if the prompt is shorter, but still close to 4096, the output may be truncated. Since the length of the prompt in tokens cannot be known ahead of time, sometimes the flow may need to make dynamic decisions whether to pass the text to the Llama block, or to split it into multiple chunks, or to use some alternative method for processing it (e.g. a custom supervision manual task). The tokenize_only option enables flows to take such dynamic decisions based on the length of the prompt in tokens. The default is false - it instructs the block to run the ML model inference over the prompt, i.e. to generate a text response. When true is passed, the model will simply tokenize the prompt without running inference and return the list of tokens - this will work regardless of the length of the prompt. A subsequent Decision task can then route longer prompts to an alternative path in the flow, while routing shorter prompts to the LlamaBlock for actual text generation.
predict_extra_kwargs (Optional[Dict[Any, Any]]) – Extra keyword arguments used for model inference. (Used to fine-tune the model prediction. Not recommended to change this unless you know what you are doing)

Example usage:

llama = LlamaBlock(
    reference_name='llama',
    model_id='b3da05c7-061c-4a58-af6d-4c905d2e618f',
    prompt='${previous_block.output.llama_prompt}',
)

IDENTIFIER = 'LLAMA'

class flows_sdk.implementations.idp_v39_1.additional_blocks.EntityRecognitionBlock(pages, regex_map=None, keyword_map=None, enhanced_output=False, reference_name=None, title='Entity Recognition', description='Recognizes entities of different types in documents')

Bases: Block

Entity Recognition Block detects entities of different types within the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

regex_map (Optional[Dict[str, str]]) – a map that specifies different regex patterns that the block should look for, a default one is present
keyword_map (Optional[Dict[str, List[str]]]) – a map that specifies different keyword patterns that the block should look for, a default one is present
enhanced_output (bool) – a boolean flag that enables toggling between simple and enhanced output formats. Default value is False.
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

# EntityRecognitionBlock detects entities within the documents contained in the submission
entity_recognition_block = EntityRecognitionBlock(
    reference_name='entity_recognition',
    pages=submission_bootstrap.output(submission.unassigned_pages),
    regex_map=DEFAULT_PII_REGEX_MAP,
    keyword_map=DEFAULT_PII_KEYWORD_MAP,
    enhanced_output=False,
)

# reference to the output of EntityRecognitionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = entity_recognition_block.output()

Example content of output_ref:

{
    "documents": [
        {
            "file_uuid": "da2c6117-43c4-4b30-84c4-cdc59cc3fa4f",
            "entities": [
                {
                    "text": "John Smith",
                    "type": "Person Name",
                    "positions": [
                        [0.5, 0.1, 0.55, 0.13],
                        [0.6, 0.2, 0.65, 0.23],
                        [0.7, 0.3, 0.75, 0.33],
                    ],
                    "page_ids": [0, 0, 1],
                    "origin": "NER",
                },
                {
                    "text": "<SIGNED>",
                    "type": "signature",
                    "positions": [[0.701171875, 0.732421875, 0.92578125, 0.8681640625]],
                    "page_ids": [0],
                    "origin": "Signature",
                },
            ]
        },
        {
            "file_uuid": "4aa38f84-e5af-4cdc-ba5c-edd60f0a6b89",
            "entities": [
                ...
            ]
        }
    ],
    "redaction_annotations": {
        "ner": [ ... ],
        "ced": [ ... ],
    }
}

IDENTIFIER = 'ENTITY_RECOGNITION'

Trigger Blocks (v39.1)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v39.1)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

S3 Listener (v39.1)

Identifier: S3_TRIGGER Parameters:

Name	Type	Default Value	Title	Description
bucket_uri	string	N/A	S3 source URI	S3 URI, where the files will be uploaded (e.g. s3://hs_bucket/prefix1/)
archive_bucket_uri	string	N/A	S3 archive URI	S3 URI to move the processed files to (e.g. s3://hs_bucket/prefix1/)
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission s3 prefixes. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or s3 prefixes (e.g., XXX.jpg.json for XXX.jpg)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used
poll_interval	integer	10	Polling interval (in seconds)	How often the S3 Listener will check the S3 bucket for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the S3 Listener will wait to process the document after it was first detected
api_params	object	{}	API Parameters	N/A

s3_listener = IOBlock(
    identifier='S3_TRIGGER',
    reference_name='s3_trigger',
    title='S3 Listener',
    enabled=True,
    input={
        'bucket_uri': 's3://hs_bucket/prefix1/',
        'archive_bucket_uri': 's3://hs_bucket/prefix2/',
        'file_extensions': ['png', 'pdf', 'jpg'],
        'aws_access_key_id': 'admin',
        'aws_secret_access_key': system_secret('s3_secret_access_key'),
        'use_ec2_instance_credentials': False,
    },
)
triggers = IDPTriggers(blocks=[s3_listener])

Email Listener (v39.1)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	The frequency at which the connection will monitor the email folder for submissions
folder	Path	N/A	Folder to scan for emails	The email folder to retrieve submissions from (e.g., “inbox”)
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v39.1)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	string	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	string	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': '24',
        'target_folder_id': '42',
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v39.1)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v39.1)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v39.1)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	No auth credentials required	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	MQCSP authentication mode	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v39.1)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Kafka Listener (v39.1)

Identifier: KAFKA_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
bootstrap_servers	string	N/A	Bootstrap Servers	A Comma separated list of host:port pairs to use for establishing the initial connection to the cluster
group_id	string	N/A	Group Id	A unique string that identifies the consumer group this consumer belongs to. BLOCK_THREADS_KAFKA_TRIGGER should be used to scale up or down the number of consumers (default: number of available cores)
topics	string	N/A	Topics	Comma separated list of topic names that the block will subscribe to
consumer_config_json	json	N/A	Consumer Config	JSON formatted string containing key-value pairs of Kafka consumer configurations described in the official Kafka documentation
api_params	object	{}	API Parameters	N/A
consume_timeout	integer	-1	Consume Timeout	Maximum time, in seconds, that the consumer will wait for new messages. If messages are received within the specified time, they are processed immediately. However, if no messages are received within that specified time, consumption cycle will be restarted internally to continue fetching messages. This ensures continuous message consumption (default: infinite)
consume_num_messages	integer	1	Consume Num Messages	Sets the maximum number of messages the consumer fetches in a single consumption cycle.If the number of available messages is less than the specified, and timeout is reached, messages will be processed. Consumption cycle will be restarted after the current finishes

kafka_listener = IOBlock(
    identifier='KAFKA_TRIGGER',
    reference_name='kafka_trigger',
    title='Kafka Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
         'bootstrap_servers': 'example.com',
         'group_id': 'test_group',
         'topics': 'test_topic1, test_topic2',
         'consumer_config_json': {},
         'number_of_workers': 1,
         'consume_timeout': 5,
         'consume_num_messages': 10
    }
)

triggers = IDPTriggers(blocks=[kafka_listener])

Output Blocks (v39.1)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v39_1.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v39.1)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [2]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [3]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A
additional_notification_http_headers	json	null	Additional Notification Request Headers	Key value pairs in json format which will be sent via the request as http headers

[1] one of:

"v5"
"transformed"

[2] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[3] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v39.1)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A

[1] one of:

"v5"
"transformed"

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v39.1)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

[1] one of:

"v5"
"transformed"

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v39.1)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
auth_method [2]	string	“basic_auth”	Authentication method	N/A
url	string	N/A	URL	Base URL of the uipath instance
app_id	string	N/A	App ID	App ID provided by UiPath
app_secret	Password	N/A	App Secret	App Secret provided by UiPath
oauth_token_endpoint	string	N/A	OAuth token endpoint	Endpoint to retrieve the token. Using https://cloud.uipath.com/identity_/connect/token by default
organization_unit_id	string	N/A	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

[1] one of:

"v5"
"transformed"

[2] one of:

"basic_auth"
"oauth"

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v39.1)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

[1] one of:

"v5"
"transformed"

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

S3 Notifier Output (v39.1)

With the S3 Notifier Block, you can configure your flow to send extracted information to an S3 bucket.

Identifier: COB_S3_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bucket_uri	string	N/A	S3 URI	S3 URI, where the data should be stored (e.g. s3://hs_bucket/prefix1/prefix2/)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used

[1] one of:

"v5"
"transformed"

cob_s3_notifier = IOBlock(
    identifier='COB_S3_NOTIFIER',
    reference_name='cob_s3_notifier',
    title='S3 Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bucket_uri': 's3://hs_bucket/prefix1/prefix2/',
        'aws_access_key_id': 'aws_access',
        'aws_secret_access_key': system_secret('aws_secret_access_key'),
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_s3_notifier],
)

Kafka Notifier Output (v39.1)

With the Kafka Notifier Block, you can configure your flow to send extracted information to a kafka topic.

Identifier: COB_KAFKA_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bootstrap_servers	string	N/A	Bootstrap Servers	A list of Kafka brokers to connect to. For example: “kafka1:9092,kafka2:9092”
topic	string	N/A	Topic	The Kafka topic where your data will be sent
client_id	string	N/A	SECRET ACCESS KEY	An identifier for your application when connecting to Kafka, typically used for tracking and logging purposes
producer_config_json	json	true	Producer Config (JSON)	Configuration settings for the Kafka producer in JSON format. See https://kafka.apache.org/documentation/#producerconfigs for more information
synchronous_publish	boolean	true	Sync Publish	If true, the publish call will block until the message is sent successfully or an error is raised. If false, the publish call will return immediately after enqueueing the message
message_key	string	null	Message Key	The key associated with the message to be sent. This is used to determine which partition the message is sent to. If null, the message will be sent to a random partition

[1] one of:

"v5"
"transformed"

cob_kafka_notifier = IOBlock(
    identifier='COB_KAFKA_NOTIFIER',
    reference_name='cob_kafka_notifier',
    title='Kafka Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bootstrap_servers': 'kafka1:9092,kafka2:9092',
        'topic': 'topic',
        'client_id': 'client_id',
        'producer_config_json': {},
        'synchronous_publish': True,
        'message_key': 'key'
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_kafka_notifier],
)

Helper Classes and Functions (v39.1)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v39_1.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v39_1.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v39_1.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config, notification_workflow_initialization=None, notification_workflow_classification=None, notification_workflow_identification=None, notification_workflow_transcription=None, notification_workflow_flexible_extraction=None): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v39_1.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v39_1.idp_values.IDPWrapperManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP wrapper flows. In particular, provides defaults for some fields (e.g. roles) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPWrapperManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

class flows_sdk.implementations.idp_v39_1.idp_values.IDPCoreManifest(flow_identifier, roles=None)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP Core flows. In particular, provides defaults for some fields (e.g. roles, output) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:

flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow
roles (Optional[List[str]]) – ‘read_only’, ‘supporting’ and ‘idp_core’ are the default roles of every subflow that can replace the default IDP_CORE subflow inside the top-level IDP flows. ‘supporting’ and ‘idp_core’ are mandatory roles that are necessary for all IDP Core flows. ‘supporting’ ensures that the subflow will be auto-deployed together with the top-level IDP flow. ‘idp_core’ ensures that this subflow can be selected in the UI in dropdowns which allow picking an alternative subflow to the default IDP_CORE subflow. If you are implementing a subflow that is not supposed to be a drop-in replacement for IDP_CORE, you will have to subclass or implement your own version of IDPCoreManifest class in order to remove the idp_core role.

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPCoreManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V39

Processing Blocks (v39)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v39 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v39.idp_blocks.IDPCoreBlock(idp_wf_config, reference_name='__idp_core__', title='Start Document Processing Subflow', description='Calls the Document Processing Subflow with the specified settings.', compatibility_spec=CompatibilitySpec(filter_roles=['idp_core'], filter_schema=None, label=None), identifier='IDP_CORE_V39', additional_inputs=None)

Bases: Block

IDP core block includes the steps to process the passed documents into machine-readable output.

Mandatory parameters:

Parameters:: idp_wf_config (IdpWorkflowConfig) – IdpWorkflowConfig object with all flow-level configuration settings for IDP

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique reference name within a flow, a unique one will be generated when not provided
compatibility_spec (Optional[CompatibilitySpec]) – defines a filter for flows that could be selected in the UI in place of “IDP Core” for the block. Defaults to flows with the role ‘idp_core’. The user will be able to pick any flow that matches the compatibility_spec. This serves to make upgrading to a new compatible version of “IDP Core” (e.g. IDP_CORE_V39) easier in future releases.
identifier (str) – The identifier of the flow. Defaults to the IDP_CORE_VXX identifier of the out-of-the-box flow that comes with the system.
additional_inputs (Optional[Dict[str, Any]]) – Dictionary containing key-value pairs that will be added to the inputs of the block. If a key is contained in the default inputs, its value will be overwritten by the value provided here. You generally do not need to provide additional_inputs, unless you are creating a custom derivative of the IDP_CODE_Vxx flow and are modifying or extending the list of inputs it accepts.

Example usage:

idp_core = IDPCoreBlock(idp_wf_config=idp_wf_config)

REFERENCE_NAME = '__idp_core__'

class flows_sdk.implementations.idp_v39.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${workflow.input.submission_bootstrap_s3_config}', s3_endpoint_url='${workflow.input.submission_bootstrap_s3_endpoint_url}', ocs_config='${workflow.input.submission_bootstrap_ocs_config}', http_config='${workflow.input.submission_bootstrap_http_config}', notification_workflow='${workflow.input.notification_workflow_initialization}', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}', submission='${workflow.input.submission}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to workflow_input(Settings.SubmissionBootstrapS3Config)
s3_endpoint_url (str) – Endpoint URL for S3 submission retrieval store, defaults to workflow_input(Settings.SubmissionBootstrapS3EndpointUrl)
ocs_config (str) – OCS Configuration for downloading submission data, defaults to workflow_input(Settings.SubmissionBootstrapOCSConfig)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to workflow_input(Settings.SubmissionBootstrapHTTPConfig)
notification_workflow (Optional[str]) – Notification flow name to run when the submission is initialized, defaults to workflow_input(Settings.SubmissionBootstrapNotificationWorkflow)
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)
submission (Any) – Submission object

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v39.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files='${workflow.input.machine_collation_dedupe_files}', refresh_retention_period='${workflow.input.machine_collation_refresh_retention_period}', remove_from_cases='${workflow.input.machine_collation_remove_from_cases}', retention_period='${workflow.input.machine_collation_retention_period}', reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (Union[bool, str]) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases. Defaults to workflow_input(Settings.CollationDedupeFiles)
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case, defaults to workflow_input(Settings.CollationRemoveFromCases)

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Union[int, str, None]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. Defaults to workflow_input(Settings.CollationRetentionPeriod)
refresh_retention_period (Union[bool, str]) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. Defaults to workflow_input(Settings.CollationRefreshRetentionPeriod)

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v39.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled='${workflow.input.machine_classification_rotation_correction_enabled}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', file_transcription_enabled='${workflow.input.machine_classification_file_transcription_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (Union[bool, str]) – Identifies and corrects the orientation of semi-structured images, defaults to workflow_input(Settings.RotationCorrectionEnabled)
mobile_processing_enabled (Union[bool, str]) – Improves the machine readability of photo captured documents, defaults to workflow_input(Settings.MobileProcessingEnabled)
file_transcription_enabled (Union[bool, str]) – Improves the transcription speed of pdf files. Make sure that the “Image Correction” option is disabled and the pdfs you submit do not contain any rotated images defaults to workflow_input(Settings.FileTranscriptionEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_6'

class flows_sdk.implementations.idp_v39.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions='${workflow.input.manual_classification_task_restrictions}', notification_workflow='${workflow.input.notification_workflow_classification}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualClassificationTaskRestrictions)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to workflow_input(Settings.ManualClassificationNotificationWorkflow)
nlc_enabled (Union[bool, str, None]) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (Union[float, str, None]) – Classification Target Accuracy, defaults to workflow_input(Settings.SemiTargetAccuracy)
mobile_processing_enabled (Union[bool, str, None]) – Improves the machine readability of photo captured document, defaults to workflow_input(Settings.MobileProcessingEnabled)
vpc_registration_threshold (Optional[str]) – Structured pages above this threshold will be automatically matched to a layout variation when performing light vpc registration in the doc-org task, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_3'

class flows_sdk.implementations.idp_v39.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (Any) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_7'

class flows_sdk.implementations.idp_v39.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions='${workflow.input.manual_identification_task_restrictions}', manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_identification}')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to workflow_input(Settings.ManualFieldIdTaskRestrictions)
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to workflow_inputSettings.ManualFieldIdNotificationWorkflow

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v39.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_9'

class flows_sdk.implementations.idp_v39.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.manual_transcription_supervision_transcription_masking}', table_output_manual_review='${workflow.input.manual_transcription_table_output_manual_review}', always_supervise_blank_cells='${workflow.input.manual_transcription_always_supervise_blank_cells}', task_restrictions='${workflow.input.manual_transcription_task_restrictions}', manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='${workflow.input.notification_workflow_transcription}', title='Manual Transcription', description='Manually transcribe fields that could not be automatically transcribed')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str]) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to workflow_input(Settings.ManualTranscriptionSupervisionTranscriptionMasking)
table_output_manual_review (Union[bool, str]) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to workflow_input(Settings.ManualTranscriptionTableOutputManualReview)
always_supervise_blank_cells (Union[bool, str]) – If enabled, always send blank cells in transcribed tables to be supervised manually, regardless of confidence defaults to workflow_input(Settings.ManualTranscriptionAlwaysSuperviseBlankCells)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to workflow_input(Settings.ManualTranscriptionTaskRestrictions)
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to workflow_input(Settings.ManualTranscriptionNotificationWorkflow)

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_5'

class flows_sdk.implementations.idp_v39.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.flexible_extraction_supervision_transcription_masking}', task_restrictions='${workflow.input.flexible_extraction_task_restrictions}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_flexible_extraction}')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str, None]) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to workflow_input(Settings.FlexibleExtractionSupervisionTranscriptionMasking)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults workflow_input(Settings.FlexibleExtractionTaskRestrictions)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to workflow_input(Settings.FlexibleExtractionNotificationWorkflow)

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_4'

class flows_sdk.implementations.idp_v39.idp_blocks.ReprocessingBlock(reference_name, submission, parent_flow='${workflow.definition.identifier}', idp_wf_config='${workflow.input}', trigger='${workflow.input.$trigger}')

Bases: Block

Reprocessing block enables a second extraction attempt if documents were initially confidently mis-classified by the machine. When an end-user specifies that a document layout is incorrect during Manual Identification, Manual Transcription, or Flexible Extraction, the flow will reach the Reprocessing block which will mark correctly classified documents as “complete” status, and misclassified documents with “reprocess” status will be processed in a second execution of the flow. This block should be placed before the SubmissionCompleteBlock to enable reprocessing.

Mandatory parameters:

Parameters:: submission (Any) – Submission object

IDENTIFIER = 'REPROCESSING'

class flows_sdk.implementations.idp_v39.idp_blocks.SubmissionCompleteBlock(submission, is_reprocessing=False, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v39.idp_blocks.SetTransformedOutputBlock(submission, transformed_output, reference_name=None)

Bases: Block

Set Transformed Output block sets the transformed output for the provided submission. This can later be used to send the transformed data downstream using output blocks. For more information see https://docs.hyperscience.com/#retrieving-transformed-submissions.

Mandatory parameters:

Parameters:

submission (str) – Submission object
transformed_output (str) – Object that will be set as the transformed output for this submission

IDENTIFIER = 'SET_TRANSFORMED_OUTPUT'

class flows_sdk.implementations.idp_v39.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V39', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[str, bool]) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Union[str, List[Any], None]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Union[str, List[int], None]) – This is an optional parameter. If left empty, the IDP wrapper will, by default, pull in all pages in the submission. Adding a list of page IDs will override the default list of pages. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v39.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None, language_family=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v39/docs/supported-languages Note: This field was included in v39.0.9

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION_2'

class flows_sdk.implementations.idp_v39.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

Additional Blocks (v39)

class flows_sdk.implementations.idp_v39.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v39.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v39.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', language_family=None, app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
language_family (Optional[str]) – language family to use when instantiating the underlying transcription model. If not provided, the system will default to latin. Language families are single word lowercase strings, e.g., latin, arabic, korean, chinese. You can read more about language families in the Supported Languages section of the documentation https://help.hyperscience.com/v39/docs/supported-languages Note: This field was included in v39.0.9
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES_2'

class flows_sdk.implementations.idp_v39.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V39', title='Custom Supervision', description='Custom Supervision')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 15,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': False,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurrence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,
                'image_url': '/image/2ed3d989-b64a-44bd-a9fb-6e0dcc5ccdb8',
                'form_id': 2,
                'submission_id': 1,
                'external_case_ids': [],
                'read_only': False,
                'filename': '1 page.pdf',
                'form_page_id': 1
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v39.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, use_wsdl=False, wsdl_uri='', wsdl_service_name='', wsdl_port_name='', title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v39.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v39.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v39.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

class flows_sdk.implementations.idp_v39.additional_blocks.LlamaBlock(model_id, prompt, reference_name=None, consent=False, tokenize_only=False, predict_extra_kwargs=None, title='Llama Text Generation', description='Text generation using the Llama 2 model')

Bases: Block

Text generation using the Llama 2 model by Meta.

This block utilizes Llama 2 by Meta. Llama 2 is licensed under the LLAMA 2 Community License (https://ai.meta.com/llama/license/). By using the Llama Block, you acknowledge that you have received a copy of the LLAMA 2 Community License.

Note: This block is still experimental and not ready for production use.

Mandatory parameters:

Parameters:

model_id (str) – UUID, identifier of the asset with the ML model. Model assets are not part of the Hypersicence bundle and must first be downloaded and imported into the system before they can be used. Please contact your Hyperscience representative to discuss the usecase and the appropriate model and to get instructions on downloading the models. Once downloaded, here are the available model asset UUIDs: b3da05c7-061c-4a58-af6d-4c905d2e618f - Llama 2, 13B, 8-bit quantized
prompt (str) – The prompt to generate text from. Use a CodeBlock ahead of the LlamaBlock in order to build the prompt. The context window of the model is limited to 4096 tokens. If the prompt has more tokens, the block would return an error. The total input and output length also cannot exceed 4096 tokens, which means that if the input is too long, the output may be truncated. Also see tokenize_only for a more detailed explanation of how to handle longer texts.

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
consent (Optional[bool]) – Has the business user read and acknowledged the Llama 2 legal notice. Unless the flow would be used in CI automation, this should be set to False so that a business user can read and acknowledge the notice in the Hyperscience UI. Setting this to True in the Python definition of the flow is also treated as acknowledgement of the notice on behalf of the entity that will be using the flow.
tokenize_only (Optional[bool]) – In the context of LLMs, tokens correspond roughly to words, partial words and punctuation. A rough way to compute the number of tokens in a text is number_of_tokens = 1.25 * number_of_words. The Llama block works with a context window of 4096 tokens. If a longer prompt is passed in, it would return an error. Also, if the prompt is shorter, but still close to 4096, the output may be truncated. Since the length of the prompt in tokens cannot be known ahead of time, sometimes the flow may need to make dynamic decisions whether to pass the text to the Llama block, or to split it into multiple chunks, or to use some alternative method for processing it (e.g. a custom supervision manual task). The tokenize_only option enables flows to take such dynamic decisions based on the length of the prompt in tokens. The default is false - it instructs the block to run the ML model inference over the prompt, i.e. to generate a text response. When true is passed, the model will simply tokenize the prompt without running inference and return the list of tokens - this will work regardless of the length of the prompt. A subsequent Decision task can then route longer prompts to an alternative path in the flow, while routing shorter prompts to the LlamaBlock for actual text generation.
predict_extra_kwargs (Optional[Dict[Any, Any]]) – Extra keyword arguments used for model inference. (Used to fine-tune the model prediction. Not recommended to change this unless you know what you are doing)

Example usage:

llama = LlamaBlock(
    reference_name='llama',
    model_id='b3da05c7-061c-4a58-af6d-4c905d2e618f',
    prompt='${previous_block.output.llama_prompt}',
)

IDENTIFIER = 'LLAMA'

class flows_sdk.implementations.idp_v39.additional_blocks.EntityRecognitionBlock(pages, regex_map=None, keyword_map=None, reference_name=None, title='Entity Recognition', description='Recognizes entities of different types in documents')

Bases: Block

Entity Recognition Block detects entities of different types within the documents contained in a submission

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

regex_map (Optional[Dict[str, str]]) – a map that specifies different regex patterns that the block should look for, a default one is present
keyword_map (Optional[Dict[str, List[str]]]) – a map that specifies different keyword patterns that the block should look for, a default one is present
reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

# EntityRecognitionBlock detects entities within the documents contained in the submission
entity_recognition_block = EntityRecognitionBlock(
    reference_name='entity_recognition',
    pages=submission_bootstrap.output(submission.unassigned_pages),
    regex_map=DEFAULT_PII_REGEX_MAP,
    keyword_map=DEFAULT_PII_KEYWORD_MAP,
)

# reference to the output of EntityRecognitionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = entity_recognition_block.output()

Example content of output_ref:

{
    "documents": [
        {
            "file_uuid": "da2c6117-43c4-4b30-84c4-cdc59cc3fa4f",
            "entities": [
                {
                    "text": "John Smith",
                    "type": "Person Name",
                    "positions": [
                        [0.5, 0.1, 0.55, 0.13],
                        [0.6, 0.2, 0.65, 0.23],
                        [0.7, 0.3, 0.75, 0.33],
                    ],
                    "page_ids": [0, 0, 1],
                    "origin": "NER",
                },
                {
                    "text": "<SIGNED>",
                    "type": "signature",
                    "positions": [[0.701171875, 0.732421875, 0.92578125, 0.8681640625]],
                    "page_ids": [0],
                    "origin": "Signature",
                },
            ]
        },
        {
            "file_uuid": "4aa38f84-e5af-4cdc-ba5c-edd60f0a6b89",
            "entities": [
                ...
            ]
        }
    ]
}

IDENTIFIER = 'ENTITY_RECOGNITION'

Trigger Blocks (v39)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v39)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

S3 Listener (v39)

Identifier: S3_TRIGGER Parameters:

Name	Type	Default Value	Title	Description
bucket_uri	string	N/A	S3 source URI	S3 URI, where the files will be uploaded (e.g. s3://hs_bucket/prefix1/)
archive_bucket_uri	string	N/A	S3 archive URI	S3 URI to move the processed files to (e.g. s3://hs_bucket/prefix1/)
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission s3 prefixes. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or s3 prefixes (e.g., XXX.jpg.json for XXX.jpg)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used
poll_interval	integer	10	Polling interval (in seconds)	How often the S3 Listener will check the S3 bucket for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the S3 Listener will wait to process the document after it was first detected
api_params	object	{}	API Parameters	N/A

s3_listener = IOBlock(
    identifier='S3_TRIGGER',
    reference_name='s3_trigger',
    title='S3 Listener',
    enabled=True,
    input={
        'bucket_uri': 's3://hs_bucket/prefix1/',
        'archive_bucket_uri': 's3://hs_bucket/prefix2/',
        'file_extensions': ['png', 'pdf', 'jpg'],
        'aws_access_key_id': 'admin',
        'aws_secret_access_key': system_secret('s3_secret_access_key'),
        'use_ec2_instance_credentials': False,
    },
)
triggers = IDPTriggers(blocks=[s3_listener])

Email Listener (v39)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	The frequency at which the connection will monitor the email folder for submissions
folder	Path	N/A	Folder to scan for emails	The email folder to retrieve submissions from (e.g., “inbox”)
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v39)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	string	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	string	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': '24',
        'target_folder_id': '42',
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v39)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v39)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v39)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	No auth credentials required	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	MQCSP authentication mode	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v39)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Kafka Listener (v39)

Identifier: KAFKA_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
bootstrap_servers	string	N/A	Bootstrap Servers	A Comma separated list of host:port pairs to use for establishing the initial connection to the cluster
group_id	string	N/A	Group Id	A unique string that identifies the consumer group this consumer belongs to. BLOCK_THREADS_KAFKA_TRIGGER should be used to scale up or down the number of consumers (default: number of available cores)
topics	string	N/A	Topics	Comma separated list of topic names that the block will subscribe to
consumer_config_json	json	N/A	Consumer Config	JSON formatted string containing key-value pairs of Kafka consumer configurations described in the official Kafka documentation
api_params	object	{}	API Parameters	N/A
consume_timeout	integer	-1	Consume Timeout	Maximum time, in seconds, that the consumer will wait for new messages. If messages are received within the specified time, they are processed immediately. However, if no messages are received within that specified time, consumption cycle will be restarted internally to continue fetching messages. This ensures continuous message consumption (default: infinite)
consume_num_messages	integer	1	Consume Num Messages	Sets the maximum number of messages the consumer fetches in a single consumption cycle.If the number of available messages is less than the specified, and timeout is reached, messages will be processed. Consumption cycle will be restarted after the current finishes

kafka_listener = IOBlock(
    identifier='KAFKA_TRIGGER',
    reference_name='kafka_trigger',
    title='Kafka Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
         'bootstrap_servers': 'example.com',
         'group_id': 'test_group',
         'topics': 'test_topic1, test_topic2',
         'consumer_config_json': {},
         'number_of_workers': 1,
         'consume_timeout': 5,
         'consume_num_messages': 10
    }
)

triggers = IDPTriggers(blocks=[kafka_listener])

Output Blocks (v39)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v39.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v39)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [2]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [3]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A
additional_notification_http_headers	json	null	Additional Notification Request Headers	Key value pairs in json format which will be sent via the request as http headers

[1] one of:

"v5"
"transformed"

[2] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[3] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v39)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A

[1] one of:

"v5"
"transformed"

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v39)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

[1] one of:

"v5"
"transformed"

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v39)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
auth_method [2]	string	“basic_auth”	Authentication method	N/A
url	string	N/A	URL	Base URL of the uipath instance
app_id	string	N/A	App ID	App ID provided by UiPath
app_secret	Password	N/A	App Secret	App Secret provided by UiPath
oauth_token_endpoint	string	N/A	OAuth token endpoint	Endpoint to retrieve the token. Using https://cloud.uipath.com/identity_/connect/token by default
organization_unit_id	string	N/A	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

[1] one of:

"v5"
"transformed"

[2] one of:

"basic_auth"
"oauth"

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v39)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

[1] one of:

"v5"
"transformed"

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

S3 Notifier Output (v39)

With the S3 Notifier Block, you can configure your flow to send extracted information to an S3 bucket.

Identifier: COB_S3_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bucket_uri	string	N/A	S3 URI	S3 URI, where the data should be stored (e.g. s3://hs_bucket/prefix1/prefix2/)
aws_access_key_id	string	N/A	AWS ACCESS KEY ID	Access Key used for authentication
aws_secret_access_key	password	N/A	SECRET ACCESS KEY	Secret Key used for authentication
use_ec2_instance_credentials	boolean	true	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used

[1] one of:

"v5"
"transformed"

cob_s3_notifier = IOBlock(
    identifier='COB_S3_NOTIFIER',
    reference_name='cob_s3_notifier',
    title='S3 Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bucket_uri': 's3://hs_bucket/prefix1/prefix2/',
        'aws_access_key_id': 'aws_access',
        'aws_secret_access_key': system_secret('aws_secret_access_key'),
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_s3_notifier],
)

Kafka Notifier Output (v39)

With the Kafka Notifier Block, you can configure your flow to send extracted information to a kafka topic.

Identifier: COB_KAFKA_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
bootstrap_servers	string	N/A	Bootstrap Servers	A list of Kafka brokers to connect to. For example: “kafka1:9092,kafka2:9092”
topic	string	N/A	Topic	The Kafka topic where your data will be sent
client_id	string	N/A	SECRET ACCESS KEY	An identifier for your application when connecting to Kafka, typically used for tracking and logging purposes
producer_config_json	json	true	Producer Config (JSON)	Configuration settings for the Kafka producer in JSON format. See https://kafka.apache.org/documentation/#producerconfigs for more information
synchronous_publish	boolean	true	Sync Publish	If true, the publish call will block until the message is sent successfully or an error is raised. If false, the publish call will return immediately after enqueueing the message
message_key	string	null	Message Key	The key associated with the message to be sent. This is used to determine which partition the message is sent to. If null, the message will be sent to a random partition

[1] one of:

"v5"
"transformed"

cob_kafka_notifier = IOBlock(
    identifier='COB_KAFKA_NOTIFIER',
    reference_name='cob_kafka_notifier',
    title='Kafka Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'bootstrap_servers': 'kafka1:9092,kafka2:9092',
        'topic': 'topic',
        'client_id': 'client_id',
        'producer_config_json': {},
        'synchronous_publish': True,
        'message_key': 'key'
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_kafka_notifier],
)

Helper Classes and Functions (v39)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v39.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v39.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v39.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config, notification_workflow_initialization=None, notification_workflow_classification=None, notification_workflow_identification=None, notification_workflow_transcription=None, notification_workflow_flexible_extraction=None): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v39.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v39.idp_values.IDPWrapperManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP wrapper flows. In particular, provides defaults for some fields (e.g. roles) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPWrapperManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

class flows_sdk.implementations.idp_v39.idp_values.IDPCoreManifest(flow_identifier, roles=None)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP Core flows. In particular, provides defaults for some fields (e.g. roles, output) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:

flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow
roles (Optional[List[str]]) – ‘read_only’, ‘supporting’ and ‘idp_core’ are the default roles of every subflow that can replace the default IDP_CORE subflow inside the top-level IDP flows. ‘supporting’ and ‘idp_core’ are mandatory roles that are necessary for all IDP Core flows. ‘supporting’ ensures that the subflow will be auto-deployed together with the top-level IDP flow. ‘idp_core’ ensures that this subflow can be selected in the UI in dropdowns which allow picking an alternative subflow to the default IDP_CORE subflow. If you are implementing a subflow that is not supposed to be a drop-in replacement for IDP_CORE, you will have to subclass or implement your own version of IDPCoreManifest class in order to remove the idp_core role.

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPCoreManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V38

Processing Blocks (v38)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v38 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v38.idp_blocks.IDPCoreBlock(idp_wf_config, reference_name='__idp_core__', title='Start Document Processing Subflow', description='Calls the Document Processing Subflow with the specified settings.', compatibility_spec=CompatibilitySpec(filter_roles=['idp_core'], filter_schema=None, label=None), identifier='IDP_CORE_V38', additional_inputs=None)

Bases: Block

IDP core block includes the steps to process the passed documents into machine-readable output.

Mandatory parameters:

Parameters:: idp_wf_config (IdpWorkflowConfig) – IdpWorkflowConfig object with all flow-level configuration settings for IDP

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
compatibility_spec (Optional[CompatibilitySpec]) – defines a filter for flows that could be selected in the UI in place of “IDP Core” for the block. Defaults to flows with the role ‘idp_core’. The user will be able to pick any flow that matches the compatibility_spec. This serves to make upgrading to a new compatible version of “IDP Core” (e.g. IDP_CORE_V39) easier in future releases.
identifier (str) – The identifier of the flow. Defaults to the IDP_CORE_VXX identifier of the out-of-the-box flow that comes with the system.
additional_inputs (Optional[Dict[str, Any]]) – Dictionary containing key-value pairs that will be added to the inputs of the block. If a key is contained in the default inputs, its value will be overwritten by the value provided here. You generally do not need to provide additional_inputs, unless you are creating a custom derivative of the IDP_CODE_Vxx flow and are modifying or extending the list of inputs it accepts.

Example usage:

idp_core = IDPCoreBlock(idp_wf_config=idp_wf_config)

REFERENCE_NAME = '__idp_core__'

class flows_sdk.implementations.idp_v38.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${workflow.input.submission_bootstrap_s3_config}', s3_endpoint_url='${workflow.input.submission_bootstrap_s3_endpoint_url}', ocs_config='${workflow.input.submission_bootstrap_ocs_config}', http_config='${workflow.input.submission_bootstrap_http_config}', notification_workflow='${workflow.input.notification_workflow_initialization}', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}', submission='${workflow.input.submission}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (str) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v38.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files='${workflow.input.machine_collation_dedupe_files}', refresh_retention_period='${workflow.input.machine_collation_refresh_retention_period}', remove_from_cases='${workflow.input.machine_collation_remove_from_cases}', retention_period='${workflow.input.machine_collation_retention_period}', reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (Union[bool, str]) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Union[int, str, None]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. By default, this value is None
refresh_retention_period (Union[bool, str]) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. By default, this value is True

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v38.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled='${workflow.input.machine_classification_rotation_correction_enabled}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}', file_transcription_enabled='${workflow.input.machine_classification_file_transcription_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (Union[bool, str]) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (Union[bool, str]) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_5'

class flows_sdk.implementations.idp_v38.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions='${workflow.input.manual_classification_task_restrictions}', notification_workflow='${workflow.input.notification_workflow_classification}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', mobile_processing_enabled='${workflow.input.machine_classification_mobile_processing_enabled}')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_2'

class flows_sdk.implementations.idp_v38.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_6'

class flows_sdk.implementations.idp_v38.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions='${workflow.input.manual_identification_task_restrictions}', manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_identification}')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to DEFAULT_IDP_SUBMISSION_NOTIFY_IDENTIFIER

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v38.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_9'

class flows_sdk.implementations.idp_v38.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.manual_transcription_supervision_transcription_masking}', table_output_manual_review='${workflow.input.manual_transcription_table_output_manual_review}', always_supervise_blank_cells='${workflow.input.manual_transcription_always_supervise_blank_cells}', task_restrictions='${workflow.input.manual_transcription_task_restrictions}', manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='${workflow.input.notification_workflow_transcription}', title='Manual Transcription', description='Manually transcribe fields that could not be automatically transcribed')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str]) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (Union[bool, str]) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to DEFAULT_IDP_SUBMISSION_NOTIFY_IDENTIFIER

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_5'

class flows_sdk.implementations.idp_v38.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking='${workflow.input.flexible_extraction_supervision_transcription_masking}', task_restrictions='${workflow.input.flexible_extraction_task_restrictions}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='${workflow.input.notification_workflow_flexible_extraction}')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (Union[bool, str, None]) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Union[List[Any], str, None]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to DEFAULT_IDP_SUBMISSION_NOTIFY_IDENTIFIER

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_4'

class flows_sdk.implementations.idp_v38.idp_blocks.ReprocessingBlock(reference_name, submission, parent_flow='${workflow.definition.identifier}', idp_wf_config=None, trigger='${workflow.input.$trigger}')

Bases: Block

Reprocessing block enables a second extraction attempt if documents were initially confidently mis-classified by the machine. When an end-user specifies that a document layout is incorrect during Manual Identification, Manual Transcription, or Flexible Extraction, the flow will reach the Reprocessing block which will mark correctly classified documents as “complete” status, and misclassified documents with “reprocess” status will be processed in a second execution of the flow. This block should be placed before the SubmissionCompleteBlock to enable reprocessing.

Mandatory parameters:

Parameters:: submission (Any) – Submission object

IDENTIFIER = 'REPROCESSING'

class flows_sdk.implementations.idp_v38.idp_blocks.SubmissionCompleteBlock(submission, is_reprocessing=False, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)
is_reprocessing (Union[str, bool]) – boolean to handle execution when reprocessing defaults to False

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v38.idp_blocks.SetTransformedOutputBlock(submission, transformed_output, reference_name=None)

Bases: Block

Set Transformed Output block sets the transformed output for the provided submission. This can later be used to send the transformed data downstream using output blocks. For more information see https://docs.hyperscience.com/#retrieving-transformed-submissions.

Mandatory parameters:

Parameters:

submission (str) – Submission object
transformed_output (str) – Object that will be set as the transformed output for this submission

IDENTIFIER = 'SET_TRANSFORMED_OUTPUT'

class flows_sdk.implementations.idp_v38.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V38', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – This is an optional parameter. If left empty, the IDP wrapper will, by default, pull in all pages in the submission. Adding a list of page IDs will override the default list of pages. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to DEFAULT_IDP_SUBMISSION_NOTIFY_IDENTIFIER
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v38.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION'

class flows_sdk.implementations.idp_v38.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

Additional Blocks (v38)

class flows_sdk.implementations.idp_v38.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v38.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v38.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the document pages passed to it Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES'

class flows_sdk.implementations.idp_v38.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V38')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (Optional[str]) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 15,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': False,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurrence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,
                'image_url': '/image/2ed3d989-b64a-44bd-a9fb-6e0dcc5ccdb8',
                'form_id': 2,
                'submission_id': 1,
                'external_case_ids': [],
                'read_only': False,
                'filename': '1 page.pdf',
                'form_page_id': 1
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': False,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v38.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v38.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v38.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v38.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

class flows_sdk.implementations.idp_v38.additional_blocks.LlamaBlock(model_id, prompt, reference_name=None, consent=False, tokenize_only=False, predict_extra_kwargs=None, title='Llama Text Generation', description='Text generation using the Llama 2 model')

Bases: Block

Text generation using the Llama 2 model by Meta.

This block utilizes Llama 2 by Meta. Llama 2 is licensed under the LLAMA 2 Community License (https://ai.meta.com/llama/license/). By using the Llama Block, you acknowledge that you have received a copy of the LLAMA 2 Community License.

Note: This block is still experimental and not ready for production use.

Mandatory parameters:

Parameters:

model_id (str) – UUID, identifier of the asset with the ML model. Model assets are not part of the Hypersicence bundle and must first be downloaded and imported into the system before they can be used. Please contact your Hyperscience representative to discuss the usecase and the appropriate model and to get instructions on downloading the models. Once downloaded, here are the available model asset UUIDs: b3da05c7-061c-4a58-af6d-4c905d2e618f - Llama 2, 13B, 8-bit quantized
prompt (str) – The prompt to generate text from. Use a CodeBlock ahead of the LlamaBlock in order to build the prompt. The context window of the model is limited to 4096 tokens. If the prompt has more tokens, the block would return an error. The total input and output length also cannot exceed 4096 tokens, which means that if the input is too long, the output may be truncated. Also see tokenize_only for a more detailed explanation of how to handle longer texts.

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
consent (Optional[bool]) – Has the business user read and acknowledged the Llama 2 legal notice. Unless the flow would be used in CI automation, this should be set to False so that a business user can read and acknowledge the notice in the Hyperscience UI. Setting this to True in the Python definition of the flow is also treated as acknowledgement of the notice on behalf of the entity that will be using the flow.
tokenize_only (Optional[bool]) – In the context of LLMs, tokens correspond roughly to words, partial words and punctuation. A rough way to compute the number of tokens in a text is number_of_tokens = 1.25 * number_of_words. The Llama block works with a context window of 4096 tokens. If a longer prompt is passed in, it would return an error. Also, if the prompt is shorter, but still close to 4096, the output may be truncated. Since the length of the prompt in tokens cannot be known ahead of time, sometimes the flow may need to make dynamic decisions whether to pass the text to the Llama block, or to split it into multiple chunks, or to use some alternative method for processing it (e.g. a custom supervision manual task). The tokenize_only option enables flows to take such dynamic decisions based on the length of the prompt in tokens. The default is false - it instructs the block to run the ML model inference over the prompt, i.e. to generate a text response. When true is passed, the model will simply tokenize the prompt without running inference and return the list of tokens - this will work regardless of the length of the prompt. A subsequent Decision task can then route longer prompts to an alternative path in the flow, while routing shorter prompts to the LlamaBlock for actual text generation.
predict_extra_kwargs (Optional[Dict[Any, Any]]) – Extra keyword arguments used for model inference. (Used to fine-tune the model prediction. Not recommended to change this unless you know what you are doing)

Example usage:

llama = LlamaBlock(
    reference_name='llama',
    model_id='b3da05c7-061c-4a58-af6d-4c905d2e618f',
    prompt='${previous_block.output.llama_prompt}',
)

IDENTIFIER = 'LLAMA'

Trigger Blocks (v38)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v38)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Email Listener (v38)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	The frequency at which the connection will monitor the email folder for submissions
folder	Path	N/A	Folder to scan for emails	The email folder to retrieve submissions from (e.g., “inbox”)
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v38)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	string	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	string	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': '24',
        'target_folder_id': '42',
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v38)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v38)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v38)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	No auth credentials required	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	MQCSP authentication mode	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v38)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Kafka Listener (v38)

Identifier: KAFKA_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
bootstrap_servers	string	N/A	Bootstrap Servers	A Comma separated list of host:port pairs to use for establishing the initial connection to the cluster
group_id	string	N/A	Group Id	A unique string that identifies the consumer group this consumer belongs to. BLOCK_THREADS_KAFKA_TRIGGER should be used to scale up or down the number of consumers (default: number of available cores)
topics	string	N/A	Topics	Comma separated list of topic names that the block will subscribe to
consumer_config_json	json	N/A	Consumer Config	JSON formatted string containing key-value pairs of Kafka consumer configurations described in the official Kafka documentation
api_params	object	{}	API Parameters	N/A
consume_timeout	integer	-1	Consume Timeout	Maximum time, in seconds, that the consumer will wait for new messages. If messages are received within the specified time, they are processed immediately. However, if no messages are received within that specified time, consumption cycle will be restarted internally to continue fetching messages. This ensures continuous message consumption (default: infinite)
consume_num_messages	integer	1	Consume Num Messages	Sets the maximum number of messages the consumer fetches in a single consumption cycle.If the number of available messages is less than the specified, and timeout is reached, messages will be processed. Consumption cycle will be restarted after the current finishes

kafka_listener = IOBlock(
    identifier='KAFKA_TRIGGER',
    reference_name='kafka_trigger',
    title='Kafka Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
         'bootstrap_servers': 'example.com',
         'group_id': 'test_group',
         'topics': 'test_topic1, test_topic2',
         'consumer_config_json': {},
         'number_of_workers': 1,
         'consume_timeout': 5,
         'consume_num_messages': 10
    }
)

triggers = IDPTriggers(blocks=[kafka_listener])

Output Blocks (v38)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v38.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v38)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [2]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [3]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A
additional_notification_http_headers	json	null	Additional Notification Request Headers	Key value pairs in json format which will be sent via the request as http headers

[1] one of:

"v5"
"transformed"

[2] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[3] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v38)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	5672 when “RABBIT_MQ”, 1414 when “IBM_MQ”, otherwise null	Port Number	N/A

[1] one of:

"v5"
"transformed"

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v38)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

[1] one of:

"v5"
"transformed"

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v38)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
auth_method [2]	string	“basic_auth”	Authentication method	N/A
url	string	N/A	URL	Base URL of the uipath instance
app_id	string	N/A	App ID	App ID provided by UiPath
app_secret	Password	N/A	App Secret	App Secret provided by UiPath
oauth_token_endpoint	string	N/A	OAuth token endpoint	Endpoint to retrieve the token. Using https://cloud.uipath.com/identity_/connect/token by default
organization_unit_id	string	N/A	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

[1] one of:

"v5"
"transformed"

[2] one of:

"basic_auth"
"oauth"

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v38)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version [1]	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

[1] one of:

"v5"
"transformed"

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v38)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v38.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v38.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v38.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config, notification_workflow_initialization=None, notification_workflow_classification=None, notification_workflow_identification=None, notification_workflow_transcription=None, notification_workflow_flexible_extraction=None): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v38.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v38.idp_values.IDPWrapperManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP wrapper flows. In particular, provides defaults for some fields (e.g. roles) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPWrapperManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

class flows_sdk.implementations.idp_v38.idp_values.IDPCoreManifest(flow_identifier, roles=None)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP Core flows. In particular, provides defaults for some fields (e.g. roles, output) but more importantly, defines all flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:

flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow
roles (Optional[List[str]]) – ‘read_only’, ‘supporting’ and ‘idp_core’ are the default roles of every subflow that can replace the default IDP_CORE subflow inside the top-level IDP flows. ‘supporting’ and ‘idp_core’ are mandatory roles that are necessary for all IDP Core flows. ‘supporting’ ensures that the subflow will be auto-deployed together with the top-level IDP flow. ‘idp_core’ ensures that this subflow can be selected in the UI in dropdowns which allow picking an alternative subflow to the default IDP_CORE subflow. If you are implementing a subflow that is not supposed to be a drop-in replacement for IDP_CORE, you will have to subclass or implement your own version of IDPCoreManifest class in order to remove the idp_core role.

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPCoreManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V37

Processing Blocks (v37)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v37 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v37.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', http_config=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V37', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed. This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned. For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v37.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files=False, refresh_retention_period=True, remove_from_cases=None, retention_period=None, reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Optional[int]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. By default, this value is None
refresh_retention_period (bool) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. By default, this value is True

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v37.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_4'

class flows_sdk.implementations.idp_v37.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V37')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_2'

class flows_sdk.implementations.idp_v37.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_5'

class flows_sdk.implementations.idp_v37.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V37')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_4'

class flows_sdk.implementations.idp_v37.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_8'

class flows_sdk.implementations.idp_v37.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', always_supervise_blank_cells=True, notification_workflow='IDP_SUBMISSION_NOTIFY_V37')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
always_supervise_blank_cells (bool) – Generates a table transcription task even if all cells are high confidence but at least one of them is a blank cell. Defaults to True.
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_4'

class flows_sdk.implementations.idp_v37.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V37')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_3'

class flows_sdk.implementations.idp_v37.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v37.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V37', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v37.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION'

class flows_sdk.implementations.idp_v37.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

class flows_sdk.implementations.idp_v37.additional_blocks.JSONOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send JSON data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = JSONOutputBlock(
    inputs={'result': }
)

class flows_sdk.implementations.idp_v37.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v37.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES'

class flows_sdk.implementations.idp_v37.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V37')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v37.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v37.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v37.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v37.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

Trigger Blocks (v37)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v37)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Email Listener (v37)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed. It will be included only if `post_process_action` is set to “move”.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v37)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v37)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v37)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v37)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Universal Folder Listener (v37)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Enter the path relative to the base folder. Leave blank to monitor the base folder
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
other_file_extensions	string	N/A	Other file extensions	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
has_meta	boolean	false	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Polling interval (in seconds)	How often the Folder Listener will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the Folder Listener will wait to process the document after it was last modified
folder_cleanup_delay	number	24	Empty folder cleanup delay (in hours)	How often the Folder Listener will remove empty folders from the base folder
api_params	object	{}	API Parameters	N/A

universal_folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder Listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    }
)

triggers = IDPTriggers(blocks=[universal_folder_listener])

Output Blocks (v37)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v37.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v37)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [1]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [2]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A

[1] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[2] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v37)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v37)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v37)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v37)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v37)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v37.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys. :type idp_wf_config: IdpWorkflowConfig :param idp_wf_config: with static values to be filled. :rtype: Dict[str, Any] :return: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::
flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v37.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings. :rtype: IdpWorkflowConfig :return: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v37.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v37.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v37.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V36

Processing Blocks (v36)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v36 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v36.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', http_config=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V36', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed.

This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

IDENTIFIER = 'SUBMISSION_BOOTSTRAP_2'

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned.

For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v36.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files=False, refresh_retention_period=True, remove_from_cases=None, retention_period=None, reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Optional[int]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. By default, this value is None
refresh_retention_period (bool) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. By default, this value is True

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

IDENTIFIER = 'MACHINE_COLLATION_2'

class flows_sdk.implementations.idp_v36.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

IDENTIFIER = 'MACHINE_CLASSIFICATION_3'

class flows_sdk.implementations.idp_v36.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V36')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MANUAL_CLASSIFICATION_2'

class flows_sdk.implementations.idp_v36.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_IDENTIFICATION_4'

class flows_sdk.implementations.idp_v36.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V36')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_IDENTIFICATION_4'

class flows_sdk.implementations.idp_v36.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

IDENTIFIER = 'MACHINE_TRANSCRIPTION_7'

class flows_sdk.implementations.idp_v36.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='IDP_SUBMISSION_NOTIFY_V36')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

IDENTIFIER = 'MANUAL_TRANSCRIPTION_4'

class flows_sdk.implementations.idp_v36.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V36')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

IDENTIFIER = 'FLEXIBLE_EXTRACTION_3'

class flows_sdk.implementations.idp_v36.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_structured_entry_qa_sample_rate='${workflow.input.structured_entry_qa_sample_rate}', transcription_structured_signature_qa_sample_rate='${workflow.input.structured_signature_qa_sample_rate}', transcription_structured_checkbox_qa_sample_rate='${workflow.input.structured_checkbox_qa_sample_rate}', transcription_semi_structured_qa_sample_rate='${workflow.input.semi_structured_qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', exclude_auto_transcribe_fields_from_qa='${workflow.input.exclude_auto_transcribe_fields_from_qa}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v36 library.

The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)
exclude_auto_transcribe_fields_from_qa (Union[str, bool]) – Defines fields that are marked as auto-transcribe in layout should be excluded from QA or not. defaults to workflow_input(Settings.ExcludeAutoTranscribeFieldsFromQA)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

IDENTIFIER = 'SUBMISSION_COMPLETE_4'

class flows_sdk.implementations.idp_v36.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V36', title='IDP Custom Supervision', description='IDP Custom Supervision')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME
title (Optional[str]) – UI-visible title of the block. Defaults to ‘IDP Custom Supervision’
description (Optional[str]) – Description of the block. Both useful for documentation purpose and visible to users in the Flow studio. Defaults to ‘IDP Custom Supervision’

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

IDENTIFIER = 'IDP_CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v36.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_SUBMISSION'

class flows_sdk.implementations.idp_v36.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_SUBMISSION'

class flows_sdk.implementations.idp_v36.additional_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

IDENTIFIER = 'IMAGE_CORRECTION_PAGES'

class flows_sdk.implementations.idp_v36.additional_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

IDENTIFIER = 'FULL_PAGE_TRANSCRIPTION_PAGES'

class flows_sdk.implementations.idp_v36.additional_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V36')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

IDENTIFIER = 'CUSTOM_SUPERVISION_2'

class flows_sdk.implementations.idp_v36.additional_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

IDENTIFIER = 'SOAP_REQ'

class flows_sdk.implementations.idp_v36.additional_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, title='HTTP REST Block', description='HTTP REST block', auth_params=None)

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v36.additional_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v36.additional_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

IDENTIFIER = 'DB_ACCESS'

Trigger Blocks (v36)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To enable trigger definition via the Flow Studio UI, you need to instantiate the IDPTriggers() convenience class and pass it to the triggers property of the Flow

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v36)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Kofax Folder Listener (v36)

Identifier: KOFAX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
poll_interval	integer	10	Poll interval in seconds	N/A
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

kofax_folder_listener = IOBlock(
    identifier='KOFAX_FOLDER_TRIGGER',
    reference_name='kofax_folder_listener',
    title='Kofax Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/kofax/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[kofax_folder_listener])

Email Listener (v36)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v36)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v36)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v36)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v36)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Output Blocks (v36)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v36.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v36)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [1]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [2]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A

[1] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[2] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v36)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A
MQ_MQCSP_AUTHENTICATION_MODE	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v36)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v36)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v36)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v36)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v36.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::
flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v36.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v36.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v36.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v36.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V35

Processing Blocks (v35)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v35 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v35.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', http_config=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V35', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed.

This block should be called at the START of every flow that uses blocks included in the library.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned.

For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v35.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files=False, refresh_retention_period=True, remove_from_cases=None, retention_period=None, reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```
retention_period (Optional[int]) – The number of days to retain cases after they are updated by this block. If passed None, no changes to the deletion date will be made. By default, this value is None
refresh_retention_period (bool) – If True, (re)applies Retention Period parameter to all cases passed into the block. If False, only updates those without a pre-existing deletion date. By default, this value is True

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
    retention_period=90,
    refresh_retention_period=True
)

class flows_sdk.implementations.idp_v35.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

class flows_sdk.implementations.idp_v35.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v35.idp_blocks.MachineIdentificationBlock(submission, api_params, layout_release_uuid='${workflow.input.layout_release_uuid}', reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v35.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

class flows_sdk.implementations.idp_v35.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_model='${workflow.input.transcription_model}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v35.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

class flows_sdk.implementations.idp_v35.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

class flows_sdk.implementations.idp_v35.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_qa_sampling_ratio='${workflow.input.qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', auto_qa_sampling_rate_enabled='${workflow.input.auto_qa_sampling_rate_enabled}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data. This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v35 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio (Union[str, int]) – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

class flows_sdk.implementations.idp_v35.idp_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)
# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)
# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()
# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

class flows_sdk.implementations.idp_v35.idp_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)
# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v35.idp_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v35.idp_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)
# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

class flows_sdk.implementations.idp_v35.idp_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v35.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V35')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v35.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

class flows_sdk.implementations.idp_v35.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

class flows_sdk.implementations.idp_v35.idp_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:: pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

class flows_sdk.implementations.idp_v35.idp_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:: pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow, a unique one will be generated when not provided
app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

Trigger Blocks (v35)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To define your triggers in the Flow Studio, simply use the IDPTriggers() convenience class:

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v35)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Kofax Folder Listener (v35)

Identifier: KOFAX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
poll_interval	integer	10	Poll interval in seconds	N/A
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

kofax_folder_listener = IOBlock(
    identifier='KOFAX_FOLDER_TRIGGER',
    reference_name='kofax_folder_listener',
    title='Kofax Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/kofax/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[kofax_folder_listener])

Email Listener (v35)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v35)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v35)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *',
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Salesforce Listener (v35)

Identifier: SALESFORCE_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce.
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App.
consumer_key	Password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	Password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
api_params	object	{}	API Parameters	N/A

Message Queue Listener (v35)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ',
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Output Blocks (v35)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v35.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v35)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
endpoint_secrets	string	N/A	Endpoint URL secrets	Endpoint URL Secrets, format: (one per line) secret_key_name=secret_value
timeout	int	600	Timeout (seconds)	How long (in seconds) to keep the connection open if no bytes are received from the endpoint. Set to 0 to wait indefinitely.
authorization_type [1]	string	“none”	Authorization type	Type of authorization
authorization_header_name	string	null	Authorization header name	Authorization header name to be set in the notification request
authorization_header	Password	null	Authorization header value	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
scope	string	null	Scope	Scope to request to oauth server
audience	string	null	Audience	Resource service URL where token will be valid
additional_oauth_parameters	json	{}	Additional Oauth Request Parameters	Additional parameters to send when requesting token
ssl_cert_source [2]	string	null	Source	N/A
ssl_cert_path	string	null	Trusted Certificate(s) path	Enter the path relative to the base folder
ssl_cert_value	MultilineText	null	Trusted Certificate(s)	N/A

[1] one of:

"none"
"http_header"
"oauth_2_client_credentials"

[2] one of:

"env_var"
"ca_bundle_path"
"certificate_value"

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v35)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v35)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v35)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v35)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v35)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v35.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::
flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v35.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v35.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v35.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows.

In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v35.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V34

Processing Blocks (v34)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v34 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v34.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', http_config=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V34', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed.

This block should be called at the START of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library.

Mandatory parameters:

Parameters:: reference_name (Optional[str]) – unique identifier within a flow

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned.

For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v34.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files=False, remove_from_cases=None, reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

class flows_sdk.implementations.idp_v34.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

class flows_sdk.implementations.idp_v34.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v34.idp_blocks.MachineIdentificationBlock(submission, api_params, reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v34.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

class flows_sdk.implementations.idp_v34.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_automation_training='${workflow.input.transcription_automation_training}', transcription_model='${workflow.input.transcription_model}', flex_confidence_boosting_enabled='${workflow.input.semi_transcription_conf_boost}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', transcription_overrides='${workflow.input.transcription_overrides}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_automation_training (str) – defaults to workflow_input( Settings.TranscriptionAutomationTraining )
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
flex_confidence_boosting_enabled (str) – Boosts semi-structured transcription confidence for repeated values., defaults to workflow_input(Settings.SemiTranscriptionConfBoost)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
transcription_overrides (str) – defaults to workflow_input( Settings.TranscriptionOverrides )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v34.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

class flows_sdk.implementations.idp_v34.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

class flows_sdk.implementations.idp_v34.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_qa_sampling_ratio='${workflow.input.qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data.

This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v34 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow.
submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio (Union[str, int]) – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

class flows_sdk.implementations.idp_v34.idp_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)

# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)

# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()

# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

class flows_sdk.implementations.idp_v34.idp_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)

http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)

# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v34.idp_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v34.idp_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)

soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)

# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

class flows_sdk.implementations.idp_v34.idp_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v34.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V34')

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []
notification_workflow (str) – Notification flow name to run when the submission enters Custom Supervision (which is called within the IDP Custom Supervision block), defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'data_identifier': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v34.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

class flows_sdk.implementations.idp_v34.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

class flows_sdk.implementations.idp_v34.idp_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

class flows_sdk.implementations.idp_v34.idp_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

Trigger Blocks (v34)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To define your triggers in the Flow Studio, simply use the IDPTriggers() convenience class:

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v34)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Universal Folder Listener (v34)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Path relative to the base folder. Leave blank to monitor the base folder
file_extensions	string	N/A	File extensions	List of file extensions to monitor for
other_file_extensions	string	N/A	Other file extensions	Comma separated other file extensions to monitor for
has_meta	boolean	False	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	24	Folder cleanup delay	How often the Folder Listener will remove empty folders from the base folder (in hours)
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder listener',
    enabled=True,
    input={
        'folder': 'folder',
        'file_extensions': ['png', 'pdf', 'jpg', 'other'],
        'other_file_extensions': 'msg, csv'
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Salesforce Listener (v34)

Identifier: SALESFORCE_TRIGGER

With the Salesforce Listener Block, you can configure your flow to ingest files attached to Salesforce Objects for processing within the Hyperscience application. The Salesforce Listener Block is available in both SaaS and on-premise versions of the Hyperscience application.

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued
private_key	password	false	Sandbox Environment	Private key used for authentication with Salesforce
sandbox_environment	boolean	15	Warm-up interval	Enable if the Salesforce environment is a sandbox
api_params	object	{}	API Parameters	N/A

salesforce_listener = IOBlock(
    identifier='SALESFORCE_TRIGGER',
    reference_name='salesforce_trigger',
    title='Salesforce Listener',
    enabled=True,
    input={
        'channel_name': '/u/saleforce_streaming_channel',
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key'
    },
)

triggers = IDPTriggers(blocks=[salesforce_listener])

Email Listener (v34)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
provider [1]	string	imap	Email Provider	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested. Available options are “process” and “ignore”.
post_process_action	string	“move”	Post process action	What to do with the email after it is processed. Available options are “move” and “delete”.
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed.
api_params	object	{}	API Parameters	N/A
render_headers [2]	array	[]	Headers to include	Headers to render at the top of the email body. Headers will be included only if `email_body_treatment` is set to “process”.

[1] one of:

imap
graph

[2] any of:

To
From
Subject
Date

Additional inputs when "imap" is the selected provider:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A

Additional inputs when "graph" is the selected provider:

Name	Type	Default Value	Title	Description
client_id	string	N/A	Client id	Application (client) ID for the corresponding application registered with the Microsoft identity platform.
tenant_id	string	N/A	Tenant id	Also called directory ID. Unique identifier of the tenant in which the corresponding application is registered with.
graph_cloud_endpoint [1]	string	Global	Microsoft Graph Cloud Endpoint	Determines base URL used for accessing cloud services through Microsoft Graph.
azure_ad_endpoint [2]	string	AZURE_PUBLIC_CLOUD	Azure AD Endpoint	Determines base URL for the Azure Active Directory (Azure AD) endpoint to acquire token for each national cloud.
client_secret	Password	N/A	Client secret	Client secret for the corresponding application registered with the Microsoft identity platform.

[1] one of:

Global
US_GOV
US_DoD
Germany
China

[2] one of:

AZURE_PUBLIC_CLOUD
AZURE_CHINA
AZURE_GERMANY
AZURE_GOVERNMENT

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v34)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v34)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *', 
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Message Queue Listener (v34)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ', 
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Output Blocks (v34)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v34.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v34)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
authorization_type	string	“none”	Authorization type	Type of authorization
authorization_header	Password	null	Authorization header	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
audience	string	null	Audience	Resource service URL where token will be valid

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v34)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v34)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v34)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v34)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v34)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v34.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v34.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v34.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v34.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v34.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V33

Processing Blocks (v33)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v33 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v33.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', http_config=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V33', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed.

This block should be called at the START of every flow that uses blocks included in the flows_sdk.implementations.idp_v33 library.

Mandatory parameters:

Parameters:: reference_name (Optional[str]) – unique identifier within a flow

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
http_config (Optional[str]) – An optional system secret field expressing the HTTP Configuration for downloading submission data. The content is expected to be a json formatted as: {"username": "X", "password": "Y", "ssl_cert": "CA bundle filename"}, defaults to None
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned.

For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v33.idp_blocks.MachineCollationBlock(submission, cases, dedupe_files=False, remove_from_cases=None, reference_name=None)

Bases: Block

Machine collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
cases (Any) –
This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

This parameter follows the given format:
```
{
    'cases': [
        'external_case_id': 'HS-1',
        'filename': 'file1.pdf',
        'documents': [42],
        'pages': [43]
    ]
}
```

Parameters with defaults:

Parameters:

dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases
remove_from_cases (Optional[Any]) –
This parameter accepts an array of JSON objects that contains information on how documents or pages should be removed from a pre-existing case. Currently, the only way to de-collate from a case is by the ids of the Documents or Pages within a given case

This parameter follows the given format:
```
{
    'remove_from_cases': [
        'external_case_id': 'HS-1',
        'documents': [42],
        'pages': [43]
    ]
}
```

Example usage:

machine_collation = MachineCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
    dedupe_files=True,
    remove_from_cases=custom_supervision.output('remove_from_cases')
)

class flows_sdk.implementations.idp_v33.idp_blocks.MachineClassificationBlock(submission, api_params, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

class flows_sdk.implementations.idp_v33.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V33')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v33.idp_blocks.MachineIdentificationBlock(submission, api_params, reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v33.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V33')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

class flows_sdk.implementations.idp_v33.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_automation_training='${workflow.input.transcription_automation_training}', transcription_model='${workflow.input.transcription_model}', flex_confidence_boosting_enabled='${workflow.input.semi_transcription_conf_boost}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', semi_structured_table_target_accuracy='${workflow.input.semi_structured_table_target_accuracy}', semi_structured_table_confidence_threshold='${workflow.input.semi_structured_table_threshold}', semi_structured_table_acceptable_confidence='${workflow.input.semi_structured_table_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_automation_training (str) – defaults to workflow_input( Settings.TranscriptionAutomationTraining )
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
flex_confidence_boosting_enabled (str) – Boosts semi-structured transcription confidence for repeated values., defaults to workflow_input(Settings.SemiTranscriptionConfBoost)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v33.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='IDP_SUBMISSION_NOTIFY_V33')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

class flows_sdk.implementations.idp_v33.idp_blocks.FlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V33')

Bases: Block

Flexible extraction manually transcribes fields marked for review

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

class flows_sdk.implementations.idp_v33.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_qa_sampling_ratio='${workflow.input.qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data.

This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v33 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow.
submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio (Union[str, int]) – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

class flows_sdk.implementations.idp_v33.idp_blocks.DatabaseAccessBlock(reference_name=None, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)

# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)

# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()

# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

class flows_sdk.implementations.idp_v33.idp_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)

http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)

# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v33.idp_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v33.idp_blocks.SoapRequestBlock(method, reference_name=None, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)

soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)

# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

class flows_sdk.implementations.idp_v33.idp_blocks.CustomSupervisionBlock(submission, task_purpose, data, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None)

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v33.idp_blocks.IdpCustomSupervisionBlock(submission, task_purpose, supervision_template, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, page_ids=None)

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v33.idp_blocks.IDPFullPageTranscriptionBlock(submission, reference_name=None, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

This block is available on 33.0.1 or later

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

class flows_sdk.implementations.idp_v33.idp_blocks.IDPImageCorrectionBlock(submission, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

This block is available on 33.0.1 or later

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

class flows_sdk.implementations.idp_v33.idp_blocks.FullPageTranscriptionBlock(pages, reference_name=None, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

This block is available on 33.0.1 or later

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

class flows_sdk.implementations.idp_v33.idp_blocks.ImageCorrectionBlock(pages, reference_name=None, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

This block is available on 33.0.1 or later

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

Trigger Blocks (v33)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To define your triggers in the Flow Studio, simply use the IDPTriggers() convenience class:

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Salesforce Listener (v33)

Identifier: SALESFORCE_TRIGGER

With the Salesforce Listener Block, you can configure your flow to ingest files attached to Salesforce Objects for processing within the Hyperscience application. The Salesforce Listener Block is available in both SaaS and on-premise versions of the Hyperscience application.

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued
private_key	password	false	Sandbox Environment	Private key used for authentication with Salesforce
sandbox_environment	boolean	15	Warm-up interval	Enable if the Salesforce environment is a sandbox
api_params	object	{}	API Parameters	N/A

salesforce_listener = IOBlock(
    identifier='SALESFORCE_TRIGGER',
    reference_name='salesforce_trigger',
    title='Salesforce Listener',
    enabled=True,
    input={
        'channel_name': '/u/saleforce_streaming_channel',
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key'
    },
)

triggers = IDPTriggers(blocks=[salesforce_listener])

Folder Listener (v33)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Universal Folder Listener (v33)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Path relative to the base folder. Leave blank to monitor the base folder
file_extensions	string	N/A	File extensions	List of file extensions to monitor for
other_file_extensions	string	N/A	Other file extensions	Comma separated other file extensions to monitor for
has_meta	boolean	False	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	24	Folder cleanup delay	How often the Folder Listener will remove empty folders from the base folder (in hours)
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder listener',
    enabled=True,
    input={
        'folder': 'folder',
        'file_extensions': ['png', 'pdf', 'jpg', 'other'],
        'other_file_extensions': 'msg, csv'
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Salesforce Listener (v33)

Identifier: SALESFORCE_TRIGGER

With the Salesforce Listener Block, you can configure your flow to ingest files attached to Salesforce Objects for processing within the Hyperscience application. The Salesforce Listener Block is available in both SaaS and on-premise versions of the Hyperscience application.

Parameters:

Name	Type	Default Value	Title	Description
channel_name	string	N/A	Channel Name	Configured in the Hyperscience app in Salesforce
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued
private_key	password	false	Sandbox Environment	Private key used for authentication with Salesforce
sandbox_environment	boolean	15	Warm-up interval	Enable if the Salesforce environment is a sandbox
api_params	object	{}	API Parameters	N/A

salesforce_listener = IOBlock(
    identifier='SALESFORCE_TRIGGER',
    reference_name='salesforce_trigger',
    title='Salesforce Listener',
    enabled=True,
    input={
        'channel_name': '/u/saleforce_streaming_channel',
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key'
    },
)

triggers = IDPTriggers(blocks=[salesforce_listener])

Email Listener (IMAP)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested
post_process_action	string	“move”	Post process action	What to do with the email after it is processed
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed
api_params	object	{}	API Parameters	N/A

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v33)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v33)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *', 
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Message Queue Listener (v33)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ', 
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Output Blocks (v33)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v33.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v33)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
authorization_type	string	“none”	Authorization type	Type of authorization
authorization_header	Password	null	Authorization header	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
audience	string	null	Audience	Resource service URL where token will be valid

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v33)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to. It applies only to “ACTIVE_MQ”, “IBM_MQ” and “RABBIT_MQ” `MQ_TYPE`s.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A

Additional inputs when "AMAZON_SQS" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	N/A
MQ_MESSAGE_METADATA	string	null	Additional SQS Metadata	Input additional metadata key value pairs in the format of { “key”: {“TYPE”: “String”, “VALUE”: “”}, “key2”: {“TYPE”: “Number”, “VALUE”: “12345”}

NOTE: MQ_USERNAME can be used to provide Access Key ID and MQ_PASSWORD to provide Secret Access Key.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A
MQ_NO_AUTH_REQUIRED	boolean	false	Channel	N/A

NOTE: MQ_NO_AUTH_REQUIRED is True, MQ_USERNAME and MQ_PASSWORD are optional.

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	“”	Routing key	N/A
MQ_CONNECTION_TYPE	string	“TCP”	Connection Type	“TCP or SSL”

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v33)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v33)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Salesforce Notifier Output (v33)

With the Salesforce Notifier Block, you can configure your flow to send extracted information to Salesforce. The Salesforce Notifier Block can use extracted information to look up, and then update any number of fields on a Salesforce object. The Salesforce Notifier Block is available in both SaaS and on-premise versions of the Hyperscience application.

Identifier: COB_SALESFORCE_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
username	string	N/A	Associated Username	Username associated with the Salesforce Connected App
consumer_key	password	N/A	Consumer Key	Consumer key used for authentication with Salesforce. Paired with the Salesforce instance from which it was issued.
private_key	password	N/A	Private Key	Private key used for authentication with Salesforce.
sandbox_environment	boolean	false	Private Key	Enable if the Salesforce environment is a sandbox.
object_api_name	string	N/A	Object API Name	API name of the object in Salesforce to lookup and update.
new_record_on_lookup_failure	boolean	false	Create new record on lookup failure	When enabled, it will create a new record if the lookup fails to find a record using the lookup parameters. When disabled, lookup will fail if it does not find a record using the lookup parameters.
object_lookup_mapping	json	N/A	Lookup Field Mapping	Specify which Salesforce fields (using their API name) to be queried with which extracted values from the document for the lookup using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.
document_fields_mapping	json	N/A	Document Field Mappings	Specify which Salesforce fields (using their API name) you want to update with which extracted data from Hyperscience using key-value format. For example: “DOCUMENT_FIELD_NAME”: “OBJECT_FIELD_API_NAME”.”
overwrite_existing_field_data	boolean	false	Overwrite existing field data	If this is checked and a selected field has data in it, Hyperscience will overwrite that data. If this is unchecked, existing data will not be overwritten and the operation will fail.

cob_salesforce_notifier = IOBlock(
    identifier='COB_SALESFORCE_NOTIFIER',
    reference_name='cob_salesforce_notifier',
    title='Salesforce Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'username': 'salesforce_user',
        'consumer_key': 'salesforce_consumer_key',
        'private_key': 'salesforce_private_key',
        'object_api_name': 'salesforce_object_api_name',
        'object_lookup_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_1": "SF_FIELD_API_NAME_1", "LAYOUT_VARIATION_XYZ_FIELD_NAME_2": "SF_FIELD_API_NAME_2"},
        'document_fields_mapping': {"LAYOUT_VARIATION_XYZ_FIELD_NAME_3": "SF_FIELD_API_NAME_3", "LAYOUT_VARIATION_XYZ_FIELD_NAME_4": "SF_FIELD_API_NAME_4"}
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_salesforce_notifier],
)

Helper Classes and Functions (v33)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v33.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v33.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v33.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, semi_structured_table, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v33.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v33.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)

V32

Processing Blocks (v32)

Core Blocks are powerful processing blocks necessary to build intelligent document processing solutions on Hyperscience. They include both manual and machine processing blocks.

Note

Classes in the idp_v32 implementation have parameters with ambiguous typing. For example, a field of type integer could also be represented as a string reference (e.g. that integer gets provided at runtime). The types introduced in the example are therefore incomplete and are likely to be revisioned in a future version.

class flows_sdk.implementations.idp_v32.idp_blocks.SubmissionBootstrapBlock(reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', s3_config='${system.secrets.s3_downloader}', s3_endpoint_url=None, ocs_config='${system.secrets.ocs_downloader}', notification_workflow='IDP_SUBMISSION_NOTIFY_V32', workflow_uuid='${workflow.input.workflow_uuid}', workflow_name='${workflow.input.workflow_name}', workflow_version='${workflow.input.workflow_version}')

Bases: Block

Submission bootstrap block initializes the submission object and prepares external images or other submission data if needed.

This block should be called at the START of every flow that uses blocks included in the flows_sdk.implementations.idp_v32 library.

Mandatory parameters:

Parameters:: reference_name (Optional[str]) – unique identifier within a flow

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
s3_config (str) – Specify Amazon S3 credentials for submission retrieval store. Expects a json expression: {"aws_access_key_id": "X", "aws_secret_access_key": "Y"}, defaults to system_secret(S3_SECRET_KEY)
s3_endpoint_url (Optional[str]) – Endpoint URL for S3 submission retrieval store, defaults to None
ocs_config (str) – OCS Configuration for downloading submission data, defaults to system_secret(OCS_SECRET_KEY)
notification_workflow (str) – Notification flow name to run when the submission is initialized, defaults to IDP_SUBMISSION_NOTIFY_NAME
workflow_uuid (str) – UUID of the triggered workflow version, defaults to workflow_input(Inputs.WorkflowUuid)
workflow_name (str) – Name of the triggered workflow, defaults to workflow_input(Inputs.WorkflowName)
workflow_version (str) – Version of the triggered workflow, defaults to workflow_input(Inputs.WorkflowVersion)

Example usage:

submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')

output(key=None)

Submission bootstrap ends with a CodeBlock, which nests the actual outputs under the ‘result’ key. This method overrides the default output in the same manner that flows_sdk.blocks.Routing.CodeBlock does for convenience.

Parameters:

key (Optional[str]) –

Optionally provide a key to directly get a nested property. When not provided, the entire ‘result’ will be returned.

For example, we have:

{
    "result": {
        "a": {
            "b": 42
        }
    }
}

skipping the key output()` will return ``{"a": {"b": 42}}
calling with output("a") will result in {"b": 42}
calling with output("a.b") will return 42

Return type:

str

Returns:

the value under the provided key

class flows_sdk.implementations.idp_v32.idp_blocks.CaseCollationBlock(submission, cases, dedupe_files=False, reference_name=None)

Bases: Block

Case collation block groups files, documents and pages (from the submission) into cases

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
cases (Any) – This parameter accepts an array of JSON objects that contain information on how Cases should be created. There are two ways to collate a case: by the filenames specified in the current Submission, or by the ids of the Documents or Pages submitted in previous submissions.

Parameters with defaults:

Parameters:: dedupe_files (bool) – Enabling this setting will replace case data from repeated file names within the same case. Cases will retain data from the most recently submitted version of a particular file. Note that this setting does not delete the old data, it just removes it from the case. Keep in mind this option is only relevant when adding to cases

Example usage:

case_collation = CaseCollationBlock(
    reference_name='machine_collation',
    submission=submission_bootstrap.output('result.submission'),
    cases=submission_bootstrap.output('result.api_params.cases'),
)

class flows_sdk.implementations.idp_v32.idp_blocks.MachineClassificationBlock(submission, api_params, rotation_correction_enabled=True, mobile_processing_enabled=False, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', vpc_registration_threshold='${workflow.input.structured_layout_match_threshold}', nlc_enabled='${workflow.input.semi_structured_classification}', nlc_target_accuracy='${workflow.input.semi_target_accuracy}', nlc_doc_grouping_logic='${workflow.input.semi_doc_grouping_logic}')

Bases: Block

Machine classification block automatically matches documents to structured, semi-structured or additional layouts

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

rotation_correction_enabled (bool) – Identifies and corrects the orientation of semi-structured images, defaults to True
mobile_processing_enabled (bool) – Improves the machine readability of photo captured documents, defaults to False
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
vpc_registration_threshold (str) – Structured pages above this threshold will be automatically matched to a layout variation, defaults to workflow_input(Settings.StructuredLayoutMatchThreshold)
nlc_enabled (str) – Enables workflow to manage a model for automated classification of semi-structured and additional layout variations, defaults to workflow_input(Settings.SemiStructuredClassification)
nlc_target_accuracy (str) – defaults to workflow_input(Settings.SemiTargetAccuracy)
nlc_doc_grouping_logic (str) – Logic to handle multiple pages matched to the same layout variationin a given submission, defaults to workflow_input(Settings.SemiDocGroupingLogic)

Example usage:

machine_classification = MachineClassificationBlock(
    reference_name='machine_classification',
    submission=case_collation.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    rotation_correction_enabled=idp_wf_config.rotation_correction_enabled,
)

class flows_sdk.implementations.idp_v32.idp_blocks.ManualClassificationBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', manual_nlc_enabled='${workflow.input.manual_nlc_enabled}', task_restrictions=None, notification_workflow='IDP_SUBMISSION_NOTIFY_V32')

Bases: Block

Manual classification block allows keyers to manually match submissions to their layouts. Keyers may perform manual classification if machine classification cannot automatically match a submission to a layout with high confidence

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
manual_nlc_enabled (str) – Enables manual classification when applicable, defaults to workflow_input(Settings.ManualNlcEnabled)
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to None
notification_workflow (str) – Notification flow name to run when the submission enters Manual Classification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_classification = ManualClassificationBlock(
    reference_name='manual_classification',
    submission=machine_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v32.idp_blocks.MachineIdentificationBlock(submission, api_params, reference_name=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', field_id_target_accuracy='${workflow.input.field_id_target_accuracy}', table_id_target_accuracy='${workflow.input.table_id_target_accuracy}')

Bases: Block

Machine identification automatically identify fields and tables in the submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
field_id_target_accuracy (str) – Field ID Target Accuracy, defaults to workflow_input(Settings.FieldIdTargetAccuracy)
table_id_target_accuracy (str) – Table ID Target Accuracy, defaults to workflow_input(Settings.TableIdTargetAccuracy)

Example usage:

machine_identification = MachineIdentificationBlock(
    reference_name='machine_identification',
    submission=manual_classification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v32.idp_blocks.ManualIdentificationBlock(submission, api_params, reference_name=None, task_restrictions=None, manual_field_id_enabled='${workflow.input.manual_field_id_enabled}', layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V32')

Bases: Block

Manual identification allows keyers to complete field identification or table identification tasks, where they draw bounding boxes around the contents of certain fields, table columns or table rows. This identification process ensures that the system will be able to transcribe the correct content in the upcoming transcription process

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
manual_field_id_enabled (str) – Enables manual identification when applicable, defaults to workflow_input(Settings.ManualFieldIdEnabled)
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Identification, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_identification = ManualIdentificationBlock(
    reference_name='manual_identification',
    submission=machine_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    task_restrictions=idp_wf_config.manual_identification_config.task_restrictions,
)

class flows_sdk.implementations.idp_v32.idp_blocks.MachineTranscriptionBlock(submission, api_params, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', transcription_automation_training='${workflow.input.transcription_automation_training}', transcription_model='${workflow.input.transcription_model}', flex_confidence_boosting_enabled='${workflow.input.semi_transcription_conf_boost}', finetuning_only_trained_layouts='${workflow.input.finetuning_only_trained_layouts}', structured_text_target_accuracy='${workflow.input.structured_text_target_accuracy}', structured_text_confidence_threshold='${workflow.input.structured_text_threshold}', structured_text_acceptable_confidence='${workflow.input.structured_min_leg_threshold}', semi_structured_text_target_accuracy='${workflow.input.semi_structured_text_target_accuracy}', semi_structured_text_confidence_threshold='${workflow.input.semi_structured_text_threshold}', semi_structured_text_acceptable_confidence='${workflow.input.semi_structured_min_leg_threshold}', structured_checkbox_target_accuracy='${workflow.input.structured_checkbox_target_accuracy}', structured_checkbox_confidence_threshold='${workflow.input.structured_checkbox_threshold}', structured_checkbox_acceptable_confidence='${workflow.input.checkbox_min_leg_threshold}', structured_signature_target_accuracy='${workflow.input.structured_signature_target_accuracy}', structured_signature_confidence_threshold='${workflow.input.structured_signature_threshold}', structured_signature_acceptable_confidence='${workflow.input.signature_min_leg_threshold}', semi_structured_checkbox_target_accuracy='${workflow.input.semi_structured_checkbox_target_accuracy}', semi_structured_checkbox_confidence_threshold='${workflow.input.semi_structured_checkbox_threshold}', semi_structured_checkbox_acceptable_confidence='${workflow.input.semi_structured_checkbox_min_leg_threshold}')

Bases: Block

Machine transcription automatically transcribes the content of your submission

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
transcription_automation_training (str) – defaults to workflow_input( Settings.TranscriptionAutomationTraining )
transcription_model (str) – The transcription model that will be used for this flow, defaults to workflow_input(Settings.TranscriptionModel)
flex_confidence_boosting_enabled (str) – Boosts semi-structured transcription confidence for repeated values., defaults to workflow_input(Settings.SemiTranscriptionConfBoost)
finetuning_only_trained_layouts (str) – defaults to workflow_input( Settings.FinetuningOnlyTrainedLayouts )
structured_text_target_accuracy (str) – defaults to workflow_input( Settings.StructuredTextTargetAccuracy )
structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredTextThreshold )
structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredTextMinLegThreshold )
semi_structured_text_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredTextTargetAccuracy )
semi_structured_text_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredTextThreshold )
semi_structured_text_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredTextMinLegThreshold )
structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.StructuredCheckboxTargetAccuracy )
structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredCheckboxThreshold )
structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredCheckboxMinLegThreshold )
structured_signature_target_accuracy (str) – defaults to workflow_input( Settings.StructuredSignatureTargetAccuracy )
structured_signature_confidence_threshold (str) – defaults to workflow_input( Settings.StructuredSignatureThreshold )
structured_signature_acceptable_confidence (str) – defaults to workflow_input( Settings.StructuredSignatureMinLegThreshold )
semi_structured_checkbox_target_accuracy (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxTargetAccuracy )
semi_structured_checkbox_confidence_threshold (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxThreshold )
semi_structured_checkbox_acceptable_confidence (str) – defaults to workflow_input( Settings.SemiStructuredCheckboxMinLegThreshold )

Example usage:

machine_transcription = MachineTranscriptionBlock(
    reference_name='machine_transcription',
    submission=manual_identification.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
)

class flows_sdk.implementations.idp_v32.idp_blocks.ManualTranscriptionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, table_output_manual_review=False, task_restrictions=None, manual_transcription_enabled='${workflow.input.manual_transcription_enabled}', notification_workflow='IDP_SUBMISSION_NOTIFY_V32')

Bases: Block

Manual transcription lets your keyers manually enter the text found in fields or tables that could not be automatically transcribed

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during Supervision Transcription tasks, defaults to True
table_output_manual_review (bool) – Always generates a table transcription task if the layout contains a table. If disabled, a table transcription task will only be generated if one or more cells have transcribed values below the defined thresholds, defaults to False
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks for submission from a particular source or submissions matching a specific layout, defaults to []
manual_transcription_enabled (str) – Enables manual transcription when applicable, defaults to workflow_input(Settings.ManualTranscriptionEnabled)
notification_workflow (str) – Notification flow name to run when the submission enters Manual Transcription, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

manual_transcription = ManualTranscriptionBlock(
    reference_name='manual_transcription',
    submission=machine_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.manual_transcription_config.supervision_transcription_masking
    ),
    table_output_manual_review=(
        idp_wf_config.manual_transcription_config.table_output_manual_review
    ),
    task_restrictions=idp_wf_config.manual_transcription_config.task_restrictions,
)

class flows_sdk.implementations.idp_v32.idp_blocks.FlexibleExtractionBlock(submission, api_params, supervision_transcription_masking=True, task_restrictions=None, reference_name=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V32')

Bases: Block

Flexible extraction manually transcribes fields marked for review

This block ships with HS platform versions 32.0.9 and up

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

class flows_sdk.implementations.idp_v32.idp_blocks.LegacyFlexibleExtractionBlock(submission, api_params, reference_name=None, supervision_transcription_masking=True, task_restrictions=None, layout_release_uuid='${workflow.input.layout_release_uuid}', notification_workflow='IDP_SUBMISSION_NOTIFY_V32')

Bases: Block

Flexible extraction manually transcribes fields marked for review

DEPRECATED This block ships with HS platform versions up to and including 32.0.8

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
submission (Any) – Submission object
api_params (Any) –

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Flexible Extraction task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
layout_release_uuid (str) – Layout Release UUID at submission creation time, defaults to workflow_input(Settings.LayoutReleaseUuid)
notification_workflow (str) – Notification flow name to run when the submission enters Flexible Extraction, defaults to IDP_SUBMISSION_NOTIFY_NAME

Example usage:

flexible_extraction = FlexibleExtractionBlock(
    reference_name='flexible_extraction',
    submission=manual_transcription.output('submission'),
    api_params=submission_bootstrap.output('result.api_params'),
    supervision_transcription_masking=(
        idp_wf_config.flexible_extraction_config.supervision_transcription_masking
    ),
    task_restrictions=idp_wf_config.flexible_extraction_config.task_restrictions,
)

class flows_sdk.implementations.idp_v32.idp_blocks.SubmissionCompleteBlock(submission, reference_name=None, nlc_qa_sampling_ratio='${workflow.input.semi_qa_sample_rate}', field_id_qa_enabled='${workflow.input.field_id_qa_enabled}', field_id_qa_sampling_ratio='${workflow.input.field_id_qa_sample_rate}', table_id_qa_enabled='${workflow.input.table_id_qa_enabled}', table_id_qa_sampling_ratio='${workflow.input.table_id_qa_sample_rate}', transcription_qa_enabled='${workflow.input.qa}', transcription_qa_sampling_ratio='${workflow.input.qa_sample_rate}', table_cell_transcription_qa_enabled='${workflow.input.table_cell_transcription_qa_enabled}', table_cell_transcription_qa_sample_rate='${workflow.input.table_cell_transcription_qa_sample_rate}', payload=None)

Bases: Block

Submission complete block finalizes submission processing and updates reporting data.

This block should be called at the END of every flow that uses blocks included in the flows_sdk.implementations.idp_v32 library. The block requires both the submission object and a payload to be passed in.

Mandatory parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow.
submission (str) – Submission object
payload (Optional[Any]) – Object to pass to downstream systems

Parameters with defaults:

Parameters:

nlc_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Classification QA, defaults to workflow_input(Settings.SemiQaSampleRate)
field_id_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.FieldIdQaEnabled)
field_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of documents sampled for Identification QA, defaults to workflow_input(Settings.FieldIdQaSampleRate)
table_id_qa_enabled (Union[str, bool]) – Allows users to verify the location of table cells, defaults to workflow_input(Settings.TableIdQaEnabled)
table_id_qa_sampling_ratio (Union[str, int]) – Defines the percentage of tables the system samples for QA, defaults to workflow_input(Settings.TableIdQaSampleRate)
transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TranscriptionQaEnabled)
transcription_qa_sampling_ratio (Union[str, int]) – Defines the percentage of fields sampled for Transcription QA, defaults to workflow_input(Settings.TranscriptionQaSampleRate)
table_cell_transcription_qa_enabled (Union[str, bool]) – defaults to workflow_input(Settings.TableCellTranscriptionQaEnabled)
table_cell_transcription_qa_sample_rate (Union[str, int]) – Defines the percentage of cells the system samples for QA. This value is likely to be lower than “Transcription QA Sample Rate” since there are more table cells than fields on any given page, defaults to workflow_input(Settings.TableCellTranscriptionQaSampleRate)

Example usage:

submission_complete = SubmissionCompleteBlock(
    reference_name='complete_submission',
    submission=flexible_extraction.output('submission')
)

class flows_sdk.implementations.idp_v32.idp_blocks.DatabaseAccessBlock(reference_name, db_type='', database='', host='', username='', password='', query='', port=None, options=None, timeout=None, query_params=None, title='DB Block', description='DB access block')

Bases: Block

Database Block allows user to access and perform queries on the specified database

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
db_type (str) – database type (mssql, oracle, postgres)
host (str) – URL/IP address of the server database is hosted on
database (str) – database name
username (str) – database username
password (str) – database password
query (str) – parameterized query

Optional parameters:

Parameters:

port (Optional[int]) – database port number
options (Optional[Dict[Any, Any]]) – dictionary of additional connection string options
query_params (Optional[Dict[Any, Any]]) – dictionary of values for query placeholders
timeout (Optional[int]) – timeout in seconds (mssql and postgres only)

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
)

# note that storing password in plain text form is not recommended
# password can later be entered in the UI or defined as a flow secret.
db_lookup = DatabaseAccessBlock(
    reference_name='db_lookup',
    title='Database Lookup',
    description='Perform database lookup',
    db_type='mssql',
    database='cars',
    host='example.com',
    username='user',
    # we recommend skipping the password field or defining it as a system secret
    # e.g. system_secret('{your_secret_identifier}') (both allow for secret input via. UI)
    password='pw'
    port=1433,
    timeout=200,
    query='SELECT * from CAR',
)

# reference to the output of DBAccessBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = db_lookup.output()

# content of output_ref:
{
    "result": [
        {
            "id": 1,
            "brand": "Aston Martin",
            "model": "Vanquish"
        },
        {
            "id": 2,
            "brand": "Jaguar",
            "model": "XE 2018"
        }
    ]
}

Database output for the same query (SELECT * FROM CAR)

class flows_sdk.implementations.idp_v32.idp_blocks.HttpRestBlock(method, endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, authorization_type=None, handled_error_codes=None, auth_params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: BaseHttpRestBlock

Http Rest Block allows user to perform HTTP requests

Mandatory parameters:

Parameters:

method (str) – HTTP method to use
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
authorization_type (Optional[str]) – authorization type (none, http_header, oauth_2_client_credentials)
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]
auth_params (Union[HttpHeaderAuthorizationParams, OAuth2AuthorizationParams, None]) – authorization parameters to be passed when the authorization_type is set to “http_header” or “oauth_2_client_credentials”

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
)

http_rest_block = HttpRestBlock(
    reference_name='http_request',
    title='Http Request',
    description='Perform http request',
    method='GET',
    endpoint='https://sheets.googleapis.com/v4/spreadsheets/example',
)

# reference to the output of HttpRestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = http_rest_block.output()

class flows_sdk.implementations.idp_v32.idp_blocks.HyperscienceRestApiBlock(method, app_endpoint, reference_name=None, headers=None, params=None, payload=None, json=None, handled_error_codes=None, title='Hyperscience HTTP REST Block', description='Hyperscience HTTP REST block')

Bases: BaseHttpRestBlock

Make HTTP requests to the Hyperscience platform APIs. This block will automatically take care of prepending the base url and will include the appropriate authentication headers with the request.

Mandatory parameters:

Parameters:

method (str) – HTTP method to use, e.g. ‘GET’, ‘POST’, etc.
app_endpoint (str) – relative url, beginning with a forward slash, to an HTTP endpoint served by the Hyperscience platform. For reference on the available endpoints, check out https://docs.hyperscience.com/. Absolute URLs that include a hostname are allowed only if the flow has received them as part of the response of a previous API request that the flow has made. Do not hardcode the hostname of the Hyperscience instance in your flow definitions as they will not work when you run the flows on another instance, or if the hostname changes. For making requests to external systems, use the HttpRestBlock or a library like “requests”.

Optional Parameters:

Parameters:

reference_name (Optional[str]) – unique identifier within a flow
headers (Optional[Dict[str, str]]) – HTTP headers to use
params (Optional[Dict[str, Any]]) – key-value pair used as query parameters in the request
payload (Optional[Dict[str, str]]) – key-value pair to be used as x-www-form-urlencoded data. Mutually exclusive with json
json (Optional[Dict[str, Any]]) – key-value pair to be used as json data. Mutually exclusive with payload
handled_error_codes (Optional[List[Union[int, str]]]) – specify HTTP error codes that will not fail the task, allowing for wildcards with the ‘x’ char. Example: [400, “5xx”]

Example usage:

hs_rest_block = HyperscienceRestApiBlock(
    reference_name='http_request',
    app_endpoint='/api/healthcheck',
    method='GET',
)

class flows_sdk.implementations.idp_v32.idp_blocks.SoapRequestBlock(reference_name, method, endpoint='', body_namespace=None, headers_namespace=None, headers=None, params=None, title='HTTP REST Block', description='HTTP REST block')

Bases: Block

Soap Block allows user to perform SOAP requests

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
method (str) – SOAP method to invoke
endpoint (str) – absolute url including schema to HTTP endpoint for this request

Optional Parameters:

Parameters:

body_namespace (Optional[str]) – SOAP request body namespace url
headers_namespace (Optional[str]) – SOAP request headers namespace url
headers (Optional[Dict[Any, Any]]) – SOAP headers to use
params (Optional[Dict[Any, Any]]) – key-value pair used as query parameters in the request to be inserted as SOAP body

Example usage:

# minimum viable instantiation, the rest of the fields can later be added in the UI
soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
)

soap_block = SoapRequestBlock(
    reference_name='soap_request',
    title='Soap Request',
    description='Perform soap request',
    method='ExampleMethod',
    endpoint='http://example.org/abc.wso',
    body_namespace='http://www.example.org/abc.countryinfo',
    params={'example': 'stuff'},
    headers={}
)

# reference to the output of SoapRequestBlock which can be passed as input to the next block
# for more information on output() and output references, please take a look at class Block
# and its output() method
output_ref = soap_block.output()

class flows_sdk.implementations.idp_v32.idp_blocks.CustomSupervisionBlock(reference_name, submission, task_purpose, data, supervision_template, supervision_transcription_masking=True, task_restrictions=None)

Bases: Block

The CustomSupervisionBlock uses a JSON schema as a form builder to create customer-driven UIs for Supervision tasks.

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
data (Any) – JSON structure that supplies the data used to populated the supervision_template
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []

Example usage:

custom_supervision = CustomSupervisionBlock(
    reference_name='custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    data={
        'fields': [
            {
                'id': 967,
                'uuid': 'fe8d4e7a-a82c-448c-85a1-0a3cbbe53b61',
                'value': '111-22-3333',
                'page_id': 1,
                'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'validation_overridden': false,
                'bounding_box': [
                    0.09360783305186686,
                    0.25792617589433436,
                    0.6358913805295097,
                    0.28862414740388187,
                ],
                'occurence_index': 1,
            },
        ],
        'template_fields': [
            {
                'uuid': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                'notes': '',
                'type': 'entry',
                'data_type_uuid': 'b600a4e4-758f-4c4b-a2f4-cbb5dd870a0c',
                'name': 'SSN',
                'n_occurences': 1,
            },
        ],
        'pages': [
            {
                'id': 15,
                'file_page_number': 1,
                'document_page_number': 1,  // Optional
                'image_url': '/image/6e55fa86-a36b-4178-8db1-3a514621d4c1',
                'form_id': 2,
                'submission_id': 3,
                'external_case_ids': [
                    'HS-27',
                ],
                'read_only': False,
                'filename': 'filename.pdf',
            },
        ],
        'documents': [
            {
                'id': 2,
                'layout_uuid': 'e31c3cbf-dcea-44fd-a052-902463c6040f',
                'layout_name': 'layout_name',
                'page_count': 2,
                'read_only': false,
            },
        ],
        'cases': [],
        'selected_choices': [],
    },
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v32.idp_blocks.IdpCustomSupervisionBlock(reference_name, submission, task_purpose, supervision_template, supervision_transcription_masking=True, task_restrictions=None, page_ids=None)

Bases: Block

An IDP wrapper for the Custom Supervision block. It has the same functionality, but handles reading/writing data from the IDP database.

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
submission (Any) – Submission object
task_purpose (str) – the custom task name that’s given to all supervision tasks that run through a particular instance of a custom supervision block. This can be used to filter tasks in the task queue.
supervision_template (Any) – JSON used for configuration of the Custom Supervision Task.

Parameters with defaults:

Parameters:

supervision_transcription_masking (bool) – Prevents users from inputting invalid characters during the Custom Supervision task, defaults to True
task_restrictions (Optional[List[Any]]) – Defines what users can access Supervision tasks created by this block, defaults to []
page_ids (Optional[List[int]]) – A list of page ids to include. This should not be used. The IDP wrapper should handle pulling in all pages in the submission. defaults to []

Example usage:

idp_custom_supervision = IdpCustomSupervisionBlock(
    reference_name='idp_custom_supervision',
    submission=manual_transcription.output('submission'),
    task_purpose='make_custom_decision',
    supervision_template=[
        {
            'name': 'three_column_template',
            'version': '1.0',
            'thumbnail': {
                'group_by_document': True,
                'group_by_case': True,
            },
            'action': [
                {
                    'name': 'my_tab',
                    'display': 'SSN Info',
                    'input': [
                        {
                            'name': 'ssn_field',
                            'type': 'transcription',
                            'layout_field_id': '2afd7a67-ddee-484f-ab6b-2d292752e5ee',
                            'title': 'SSN',
                        },
                    ],
                    'ui': {
                        'groups': [
                            {
                                'title': 'My Group',
                                'fields': ['ssn_field'],
                            },
                        ],
                    },
                },
            ],
        },
    ],
    supervision_transcription_masking=False,
)

class flows_sdk.implementations.idp_v32.idp_blocks.IDPFullPageTranscriptionBlock(reference_name, submission, title='Full Page Transcription (Submission)', description='Transcribes the documents included in a submission', app_metadata=None)

Bases: Block

This block is available on 32.0.9 or later

IDP Full Page Transcription Block machine-transcribes the unassigned pages in a submission

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SUbmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPFullPageTranscriptionBlock transcribes the documents contained in the submission object
idp_fpt_block = IDPFullPageTranscriptionBlock(
    reference_name='idp_fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPFullPageTranscriptionBlock which can be passed as input to
# the next block. For more information on output() and output references, please take a
# look at class Block and its output() method
output_ref = idp_fpt_block.output()

class flows_sdk.implementations.idp_v32.idp_blocks.IDPImageCorrectionBlock(reference_name, submission, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Submission)', description='Rotate and de-skew documents included in a submission', app_metadata=None)

Bases: Block

This block is available on 32.0.9 or later

IDP Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
submission (str) – submission object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# IDPImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
idp_image_correct_block = IDPImageCorrectionBlock(
    reference_name='idp_image_correct',
    submission=submission_bootstrap.output(),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = idp_image_correct_block.output()

class flows_sdk.implementations.idp_v32.idp_blocks.FullPageTranscriptionBlock(reference_name, pages, title='Full Page Transcription (Pages)', description='Transcribes documents', app_metadata=None)

Bases: Block

This block is available on 32.0.9 or later

Full Page Transcription Block machine-transcribes the document pages passed to it

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
pages (str) – list of pages that includes the raw documents that need to be transcribed

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# FullPageTranscriptionBlock transcribes the documents contained in the submission object
fpt_block = FullPageTranscriptionBlock(
    reference_name='fpt',
    submission=submission_bootstrap.output(),
)
# reference to the output of FullPageTranscriptionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look at
# class Block and its output() method
output_ref = fpt_block.output()

class flows_sdk.implementations.idp_v32.idp_blocks.ImageCorrectionBlock(reference_name, pages, rotation_correction_enabled=True, mobile_processing_enabled=False, title='Image Correction (Pages)', description='Rotate and de-skew documents', app_metadata=None)

Bases: Block

This block is available on 32.0.9 or later

Image Correction Block rotates and de-skews tilted/skewed images so that they are more transcription-friendly

Mandatory parameters:

Parameters:

reference_name (str) – unique identifier within a flow
pages (str) – list of page object that includes the raw documents that need to be image-corrected

Optional Parameters:

Parameters:: app_metadata (Optional[List[str]]) – used for capturing information about the flow

Example usage:

# This is one way to obtain the submission object (using SubmissionBootstrapBlock)
submission_bootstrap = SubmissionBootstrapBlock(reference_name='submission_bootstrap')
# ImageCorrectionBlock takes in the submission object and outputs in the same format with
# its images
image_correct_block = ImageCorrectionBlock(
    reference_name='image_correct',
    pages=submission_bootstrap.output(submission.unassigned_pages),
)
# reference to the output of IDPImageCorrectionBlock which can be passed as input to the
# next block. For more information on output() and output references, please take a look
# at class Block and its output() method
output_ref = image_correct_block.output()

Trigger Blocks (v32)

Note

“Triggers” are referred to as “Input Blocks” in our non-technical documentation.

Warning

Flows are built to allow full definition of triggers either in code or manually in the Flow Studio. We recommend defining triggers manually in the Flow Studio. Instructions on how to do so are in our non-technical documentation.

To define your triggers in the Flow Studio, simply use the IDPTriggers() convenience class:

return Flow(
   ...
   triggers=IDPTriggers()
)

If instead you wish to define specific triggers in Python, use the trigger definitions below.

Folder Listener (v32)

Identifier: FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	Path	N/A	Folder to scan for submissions	N/A
file_extensions	string	N/A	File extensions	List of file extensions to monitor for (e.g.: ‘png, jpg, pdf’)
has_meta	boolean	False	Enable metadata	Select this if a metadata file is to be expected along with document files (in XXX_index.txt file)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	86400	Folder cleanup delay	Seconds to wait before cleaning up subfolders
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='FOLDER_TRIGGER',
    reference_name='folder_trigger',
    title='Folder listener',
    enabled=True,
    input={
        'folder': '/var/www/forms/forms/folder/',
        'file_extensions': 'png, pdf, jpg',
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Universal Folder Listener (v32)

Identifier: UNIVERSAL_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
folder	string	N/A	Folder to scan for submissions	Path relative to the base folder. Leave blank to monitor the base folder
file_extensions	string	N/A	File extensions	List of file extensions to monitor for
other_file_extensions	string	N/A	Other file extensions	Comma separated other file extensions to monitor for
has_meta	boolean	False	Include submission level parameters	Select this to ingest JSON files along with document files and submission folders. These JSON files can contain information such as metadata, cases and external_id. These JSON file names should match the related files or folders (e.g., XXX.jpg.json for XXX.jpg)
poll_interval	integer	10	Poll interval	Poll interval in seconds
warmup_interval	integer	15	Warm-up interval	Seconds to wait past document last modified time before processing it
folder_cleanup_delay	integer	24	Folder cleanup delay	How often the Folder Listener will remove empty folders from the base folder (in hours)
api_params	object	{}	API Parameters	N/A

folder_listener = IOBlock(
    identifier='UNIVERSAL_FOLDER_TRIGGER',
    reference_name='universal_folder_trigger',
    title='Universal Folder listener',
    enabled=True,
    input={
        'folder': 'folder',
        'file_extensions': ['png', 'pdf', 'jpg', 'other'],
        'other_file_extensions': 'msg, csv'
    },
)

triggers = IDPTriggers(blocks=[folder_listener])

Email Listener (IMAP) (v32)

Identifier: IMAP_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
host	string	N/A	IMAP server address	N/A
port	integer	993	Port Number	N/A
ssl	boolean	True	Use SSL connection	N/A
username	string	N/A	Username	N/A
password	Password	N/A	Password	N/A
poll_interval	integer	60	Polling interval in seconds	N/A
folder	Path	N/A	Folder to scan for emails	N/A
email_body_treatment	string	“ignore”	Email body treatment	What to do with the body of an email that is ingested
post_process_action	string	“move”	Post process action	What to do with the email after it is processed
post_process_move_folder	string	“”	Post process archive folder	Folder to move emails to once they are processed
api_params	object	{}	API Parameters	N/A

imap_trigger = IOBlock(
    identifier='IMAP_TRIGGER',
    reference_name='imap_trigger',
    title='IMAP trigger',
    enabled=True,
    input={
        'host': 'example@mail.com',
        'folder': '/var/www/forms/forms/imap/',
        'username': 'admin',
        'password': 'pass',
    }
)

triggers = IDPTriggers(blocks=[imap_trigger])

Box Folder Listener (v32)

Identifier: BOX_FOLDER_TRIGGER

Parameters:

Name	Type	Default Value	Title	Description
source_folder_id	integer	N/A	Folder to scan for submissions	Use the Box Folder ID found in the URL
target_folder_id	integer	N/A	Folder to move completed files	Use the Box Folder ID found in the URL
file_extensions	array	[]	File extensions	Types of file extensions for which to monitor
custom_file_extensions	string	N/A	Other file extension types	Comma separated list of file extensions for which to monitor (e.g. ‘png, jpg, pdf’)
poll_interval	integer	10	Polling interval (in seconds)	How often the connector will check the base folder for submissions
warmup_interval	integer	15	Warm-up interval (in seconds)	How long the connector will wait to process the document after it was last modified
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
api_params	object	{}	API Parameters	N/A

box_folder_trigger = IOBlock(
    identifier='BOX_FOLDER_TRIGGER',
    reference_name='box_folder_trigger',
    title='Box folder',
    enabled=True,
    input={
        'file_extensions': ['png', 'pdf', 'jpg'],
        'source_folder_id': 24,
        'target_folder_id': 42,
        'public_key_id': 'admin',
        'private_key': 'secret',
        'passphrase': 'password',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
    }
)

triggers = IDPTriggers(blocks=[box_folder_trigger])

Cron Listener (v32)

Identifier: CRON_TRIGGER

Inputs:

Name	Type	Default Value	Title	Description
cron_spec	string	`"/5 * * *"`	Cron specification	N/A
time_zone	string	“US/Eastern”	Time Zone	N/A
api_params	object	{}	API Parameters	N/A

cron_trigger = IOBlock(
    identifier='CRON_TRIGGER',
    reference_name='cron_trigger',
    title='Cron Trigger',
    enabled=True,
    input={
        'cron_spec': '0 10 * * *', 
        'time_zone': 'Europe/Sofia',
    }
)

triggers = IDPTriggers(blocks=[cron_trigger])

Message Queue Listener (v32)

Identifier: MQ_LISTENER

Inputs:

Name	Type	Default Value	Title	Description
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	Type of the message queue to connect with. Valid values are “ACTIVE_MQ”, “AMAZON_SQS”, “IBM_MQ” and “RABBIT_MQ”
MQ_USERNAME	string	null	Username/Access Key ID	N/A
MQ_PASSWORD	Password	null	Password/Secret Access Key	N/A
MQ_QUEUE_NAME	string	null	Queue Name	Name of the queue (topic) to connect to.
MQ_HOST	string	null	Host Name	N/A
MQ_PORT	integer	1415	Port Number	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	null	Routing key	N/A
api_params	object	{}	API Parameters	N/A

Additional inputs when "ACTIVE_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.

Additional inputs when "IBM_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_QUEUE_MANAGER	string	null	Queue Manager (IBM MQ)	N/A
MQ_SSL_CIPHER_SUITE [1]	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used.
MQ_CHANNEL	string	null	Channel	N/A

[1] one of:

"NULL_MD5"
"NULL_SHA"
"RC4_MD5_EXPORT"
"RC4_MD5_US"
"RC4_SHA_US"
"RC2_MD5_EXPORT"
"DES_SHA_EXPORT"
"RC4_56_SHA_EXPORT1024"
"DES_SHA_EXPORT1024"
"TRIPLE_DES_SHA_US"
"TLS_RSA_WITH_NULL_SHA256"
"TLS_RSA_WITH_AES_128_CBC_SHA"
"TLS_RSA_WITH_AES_128_CBC_SHA256"
"TLS_RSA_WITH_AES_256_CBC_SHA"
"TLS_RSA_WITH_AES_256_CBC_SHA256"
"AES_SHA_US"
"TLS_RSA_WITH_DES_CBC_SHA"
"TLS_RSA_WITH_3DES_EDE_CBC_SHA"
"TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256"
"FIPS_WITH_DES_CBC_SHA"
"FIPS_WITH_3DES_EDE_CBC_SHA"

Additional inputs when "RABBIT_MQ" is the selected MQ_TYPE:

Name	Type	Default Value	Title	Description
MQ_VIRTUAL_HOST	string	null	Virtual Host (RABBIT MQ)	N/A

rabbit_mq_listener = IOBlock(
    identifier='MQ_LISTENER',
    reference_name='mq_listener',
    title='RabbitMQ Listener',
    enabled=True,
    input={
        'MQ_TYPE': 'RABBIT_MQ', 
        'MQ_QUEUE_NAME': 'some_queue_name',
        'MQ_HOST': 'somehost.com',
        'MQ_USERNAME': 'foo',
        'MQ_PASSWORD': system_secret('rabbit_mq_1_password'),
    }
)

triggers = IDPTriggers(blocks=[rabbit_mq_listener])

Output Blocks (v32)

Warning

Flows pass information to downstream systems using the IDPOutputsBlock. This block is specially built to allow full definition either in code or manually in the Flow Studio. We recommend defining outputs manually in the Flow Studio.

Instructions on how to do so are in our non-technical documentation. Simply include an IDPOutputsBlock in your Python flow definition wherever you wish to send information to downstream systems.

class flows_sdk.implementations.idp_v32.idp_blocks.IDPOutputsBlock(inputs, blocks=None)

Bases: Outputs

Output block allows users to send data extracted by an IDP flow to other systems for downstream processing

Mandatory parameters:

Parameters:: inputs (Dict[str, Any]) – Used by the UI to automatically pre-populate the input of newly added blocks. Extended in this class to include 'enabled': True to visualize an enabled/disabled trigger that is controllable via Flow Studio.

Usage when parameters are to be defined in Flow Studio:

outputs = IDPOutputBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')}
)

If instead you wish to define specific outputs in Python, use the outputs definitions below.

HTTP Notifier Output (v32)

The HTTP Notifier (REST) output connection will POST results from the system to a specified HTTP endpoint.

Identifier: COB_HTTP_EXPORT

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
endpoint	string	N/A	Endpoint URL	URL that output notifications will be posted to
authorization_type	string	“none”	Authorization type	Type of authorization
authorization_header	Password	null	Authorization header	Authorization header to be set in the notification request
auth_url	string	null	OAuth2 authorization URL	The endpoint for the authorization server
client_id	string	null	Client ID	The client identifier issued to the client during the application registration process
client_secret	Password	null	Client Secret	The client secret issued to the client during the application registration process
audience	string	null	Audience	Resource service URL where token will be valid

cob_http_export = IOBlock(
    identifier='COB_HTTP_EXPORT',
    reference_name='cob_http_export',
    title='HTTP Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'endpoint': 'example.com',
        'authorization_type': 'none',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_http_export],
)

Message Queue Notifier Output (v32)

The Message Queue Notifier Output can configure connections to ActiveMQ, Amazon SQS, IBM MQ, and RabbitMQ message queues.

Identifier: COB_MQ_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
MQ_TYPE	string	“ACTIVE_MQ”	Message Queue type	N/A
MQ_NO_AUTH_REQUIRED	boolean	False	No auth credentials required	N/A
MQ_USERNAME	string	null	Username	N/A
MQ_PASSWORD	Password	null	Password	N/A
MQ_QUEUE_NAME	string	null	Queue Name	N/A
MQ_HOST	string	null	Host Name	N/A
MQ_REGION	string	null	AWS Region	N/A
MQ_QUEUE_URL	string	null	Queue URL	N/A
MQ_MESSAGE_GROUP_ID	string	null	Group ID for FIFO queues	Group ID for FIFO queues
MQ_USE_EC2_INSTANCE_CREDENTIALS	boolean	True	Use AWS EC2 Instance IAM Role Credentials	If selected, credentials are obtained from the EC2 instance directly, and the AWS Access Key ID and Secret Key are not used.
MQ_PORT	integer	1415	Port Number	N/A
MQ_QUEUE_MANAGER	string	null	Queue Manager	N/A
MQ_CHANNEL	string	null	Channel	N/A
MQ_SSL_CIPHER_SUITE	string	null	SSL cipher suite	SSL cipher suite to use if SSL connection is used
MQ_VIRTUAL_HOST	string	null	Virtual Host	N/A
MQ_EXCHANGE	string	“”	Exchange	N/A
MQ_ROUTING_KEY	string	null	Routing key	N/A

mq_notifier = IOBlock(
    identifier='COB_MQ_NOTIFIER',
    reference_name='mq_notifier',
    title='MQ Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'SUBMISSION',
        'MQ_USERNAME': 'admin',
        'MQ_PASSWORD': 'pass',
        'MQ_QUEUE_NAME': 'queue',
        'MQ_HOST': 'host',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[mq_notifier],
)

Box Notifier Output (v32)

Provides an out-of-the-box integration into Box systems.

Identifier: COB_BOX_NOTIFIER

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
public_key_id	string	N/A	Public-Key ID	ID of the Public-key used for authentication with Box
private_key	Password	N/A	Private-Key	Private key used for authentication with Box
passphrase	Password	N/A	Passphrase	Passphrase used for authentication with Box
client_id	string	N/A	Client ID	Client Id used for authentication with Box
client_secret	Password	N/A	Client Secret	Client Secret used for authentication with Box
enterprise_id	string	N/A	Enterprise ID	Enterprise Id used for authentication with Box
template_key	string	“”	Box Metadata Template Key	Enter the key of the Box Metadata template that you would like to map the Hyperscience metadata to.
static_output_fields_to_map	array	[]	Static Metadata Fields	Specify the Hyperscience fields you want to store in Box metadata.
submission_id	string	“”	Key for Mapping Submission ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_id	string	“”	Key for Mapping Document ID	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_state	string	“”	Key for Mapping Submission State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_state	string	“”	Key for Mapping Document State	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
submission_exceptions	string	“”	Key for Mapping Submission Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_exceptions	string	“”	Key for Mapping Document Exceptions	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_uuid	string	“”	Key for Mapping Document Layout Uuid	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_layout_name	string	“”	Key for Mapping Document Layout Name	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
start_time	string	“”	Key for Mapping Start Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
complete_time	string	“”	Key for Mapping Complete Time	Specify a Box metadata field key from your chosen Box template. The Hyperscience field will be stored in this specified field.
document_fields_template_mappings	json	{}	JSON for Additional Metadata Fields	Specify additional metadata fields using their key value. Please consult Box Integration setup manual for JSON template and instructions.

box_notifier = IOBlock(
    identifier='COB_BOX_NOTIFIER',
    reference_name='box_notifier',
    title='Box Notifier Output Block',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'private_key': 'password',
        'passphrase': 'password',
        'public_key_id': 'admin',
        'client_id': 'admin',
        'client_secret': 'secret',
        'enterprise_id': 'admin',
        'template_key': 'key',
    },
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[box_notifier],
)

UiPath Notifier Output (v32)

Provides an out-of-the-box integration into UiPath systems.

Identifier: COB_EXPORT_UIPATH

Parameters:

Name	Type	Default Value	Title	Description
submission	Submission	N/A	Submission Object	N/A
enabled	boolean	True	Enabled	Enable or disable this output block
api_version	string	N/A	API Version	API version to be used for rendering payload
export_type	string	N/A	Export Type	Payload rendering choice. If “Flat” is chosen, a simplified version of the payload will be sent, as described in the “flat” parameter for submission retrieval API
export_routing_filter	string	null	Routing Filter	By default, status change notifications are sent for each submission processed by the system. You can filter what notifications are received through this connection by specifying an expression like has_layout_tag(‘some_layout_tag’) or has_source_routing_tag(‘some_source_routing_tag’)
url	string	N/A	URL	Base URL of the uipath instance
organization_unit_id	string	null	Organization unit id	Organization unit id
tenant	string	N/A	Tenant	Tenant
username	string	N/A	Username	Username
password	Password	N/A	Password	Password
queue	string	N/A	Queue	Queue

cob_export_uipath = IOBlock(
    identifier='COB_EXPORT_UIPATH',
    reference_name='cob_export_uipath',
    title='CCB Export UiPath',
    enabled=True,
    input={
        'submission': submission_bootstrap.output('result.submission'),
        'enabled': True,
        'api_version': 'v5',
        'export_type': 'FLAT_SUBMISSION',
        'url': 'example.com',
        'tenant': 'tenant',
        'username': 'admin',
        'password': 'pass',
        'queue': 'queue',
    }
)

outputs = IDPOutputsBlock(
    inputs={'submission': submission_bootstrap.output('result.submission')},
    blocks=[cob_export_uipath],
)

Helper Classes and Functions (v32)

The following classes are used to easily instantiate and manage a flow’s settings.

flows_sdk.implementations.idp_v32.idp_values.get_idp_wf_inputs(idp_wf_config)

A helper function that maps the values provided by an IdpWorkflowConfig to their corresponding IDP keys.

Parameters:: idp_wf_config (IdpWorkflowConfig) – with static values to be filled.
Return type:: Dict[str, Any]
Returns:: a dictionary with filled static values, compatible with IDP flows.

Example usage with default values:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

Example usage:

Example usage when instantiating an IDP flow with custom parameters::

flow = Flow(
    input=get_idp_wf_inputs({an instance of IdpWorkflowConfig}),
    ...
)

flows_sdk.implementations.idp_v32.idp_values.get_idp_wf_config()

A helper function that instantiates an IdpWorkflowConfig pre-filled with default values. IdpWorkflowConfig is the container class for defining flow-level settings.

Return type:: IdpWorkflowConfig
Returns:: a valid, fully constructed IdpWorkflowConfig instance

Example usage when instantiating an IDP flow:

flow = Flow(
    input=get_idp_wf_inputs(get_idp_wf_config()),
    ...
)

class flows_sdk.implementations.idp_v32.idp_values.IdpWorkflowConfig(rotation_correction_enabled, document_grouping_logic, qa_config, manual_document_organization_enabled, transcription_automation_training, transcription_training_legibility_period, transcription_model, manual_transcription_enabled, finetuning_only_trained_layouts, flex_confidence_boosting_enabled, improved_transcription_threshold_accuracy, structured_text, semi_structured_text, structured_checkbox, structured_signature, semi_structured_checkbox, field_id_target_accuracy, table_id_target_accuracy, manual_field_id_enabled, machine_classification_config, manual_transcription_config, manual_identification_config, flexible_extraction_config): Convenience dataclass outlining all flow-level config values for IDP.

class flows_sdk.implementations.idp_v32.idp_values.IDPTriggers(blocks=None)

An adapter class making it easier to instantiate flows_sdk.flows.Triggers for IDP flows. In particular, provides defaults for some fields (e.g. title, description, reference_name) and defines api_params_manifest with IDP specific parameters.

Parameters:: blocks (Optional[Sequence[IOBlock]]) – flows_sdk.blocks.IOBlock s to be included as triggers for an IDP Flow. Optional, defaults to an empty list.

Example usage when instantiating an IDP flow:

folder_listener = IOBlock(...)
flow = Flow(
    triggers=IDPTriggers([folder_listener]),
    ...
)

class flows_sdk.implementations.idp_v32.idp_values.IDPManifest(flow_identifier)

An adapter class making it easier to instantiate flows_sdk.flows.Manifest for IDP flows. In particular, provides defaults for some fields (e.g. roles, identifier) but more importantly, defines all py:class:flows_sdk.flows.Parameter that construct the Flow inputs and their UI representation (left-hand side menu in Flow studio).

Parameters:: flow_identifier (str) – A system-wide unique identifier for flows_sdk.flows.Flow

Example usage when instantiating an IDP flow:

flow = Flow(
    manifest=IDPManifest(flow_identifier='FLOW_IDENTIFIER'),
    ...
)