Pipeline Assistant

model-pipeline-assistant

Supports the use of Models and Model Runtimes in a pipeline

This assistant can be configured to hold multiple models in a sequence of your choice. This allows several models to work one after the other to enable a combination of readily available models or even simple models of your choice.

You can list a component in the marketplace, and define if you want it to be a template.

✅ Available in Marketplace

✅ Can be used as a template to create a new component

What is an Assistant?

Assistants are the building blocks of the automation system. They are the components that decides the actual work of the automation system. They can be used to perform a wide variety of tasks, from sending notifications, building pipelines and organizing workflow.

Options

Below are the options for this assistant.

Option Name	Default	Required?	Type	Description
pipeline	None	False	pipeline	The pipeline to use
complete_label	MODEL-APPLIED	False	string	The label name to apply after processing
training_store	None	False	documentStore	The store to use for training models in this pipeline
taxonomies	None	False	list	Extraction Data Structure
data_store	None	False	tableStore	An instance of a table store that we will use
apply_labels_from_related	None	False	boolean	Using source metadata from the taxonomy store, apply labels to the extracted data
write_back_to_store	True	False	boolean	Write back the updated document to the data store

## Reactive

This assistant can be triggered by content based events on stores which it is monitoring.



## Custom Events

This assistant also supports custom events that you can use to trigger automations. These events are listed below.



    ### Test


        Run the pipeline against the current document

Option Name	Default	Required?	Type	Description
test_only	False	True	boolean	Skip training the model and just run the inference
model_options	None	True	pipelineModelOptions	The options for the models in the pipeline
enable_logging	False	True	boolean	Enable logging of the training process

    ### Train


        Use documents in the training store to train the models in the pipeline

Option Name	Default	Required?	Type	Description
training_name	{'helper': 'randomName'}	True	string	The name of the training to use
make_active	True	True	boolean	The name of the training to use
reprocess	True	True	boolean	Reprocess the operational stores after training
model_options	None	True	pipelineModelOptions	The options for the models in the pipeline