Get Prediction (Amazon SageMaker) activity

Display Name

Description:

Specifies the activity name that shows in your process.

Allowed Values:

One line of text (a string).

Accepted:

• Letters
• Numbers
• Spaces

Default Value:

None

Accepts Variables:

No

Example:

This is a common configuration field that is used in many examples. Refer to:

• Examples - Step-by-step use case examples, information about what types of examples are provided in the AgilePoint NX Product Documentation, and other resources where you can find more examples.

Description

Description:

Specifies an optional text description for your activity.

Allowed Values:

More than one line of text.

Default Value:

None

Accepts Variables:

No

Add Model

Function:

Creates a model with a name you specify.

In this activity, you can create more than one model to configure an Amazon SageMaker model to give predictions for an app. Each configuration is stored as a model with a name specified in this field.

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Clone

Function:

Creates a new model that is a copy of the selected model.

Edit

Function:

Changes the model name.

Delete

Function:

Deletes the selected model.

Amazon Web Services

Description:

Specifies the access token that connects to your Amazon Web Services.

Allowed Values:

A list of access tokens configured for your environment.

Default Value:

None

Accepts Variables:

No

Create

Opens this Screen:

Access Token for Amazon Web Services

Function of this Screen:

Configure an access token to connect to Amazon Web Services.

Endpoint

Description:

Specifies the Amazon SageMaker endpoint from which to retrieve the prediction.

Allowed Values:

An endpoint from the list.

When you select the access token in the Amazon Web Services field, this field shows the endpoints associated with the access token.

Default Value:

None

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Target Container Host Name

Description:

Specifies the host name of the target container from which to retrieve the prediction.

If you select a multi-container endpoint in the Endpoint field, you can specify the container host name to invoke.

Allowed Values:

One line of text (a string) that represents a target container host name from Amazon SageMaker.

Default Value:

None

Accepts Variables:

Yes

Example:

• AmazonSagemaker-02101989
• Also refer to:
  • (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Target Model

Description:

Specifies the name of the target model from the Amazon SageMaker endpoint from which to retrieve the prediction.

This field enables when you select a multi-model endpoint in the Endpoint field.

Allowed Values:

A target model from the list.

When you select the endpoint from the Endpoint field, this field shows the target model names associated with the endpoint.

Default Value:

None

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Save

Opens this Screen:

Saves the configuration for your model and does not close the configuration screen.

Activity

Description:

Specifies an activity on which to run the Amazon SageMaker model.

Allowed Values:

An activity from the list.

Default Value:

None

Accepts Variables:

No

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

On Event

Description:

Specifies the status for an activity instance where the change occurs.

Allowed Values:

• Assign Work Item - Amazon SageMaker runs when the specified task is ready to be Assigned to a participant.
• Complete Work Item - Amazon SageMaker runs when a task is Completed.
• Cancel Work Item - Amazon SageMaker runs when a task is Cancelled.
• Enter Activity Instance - Amazon SageMaker runs when the activity instance starts.
• Leave Activity Instance - Amazon SageMaker runs when the activity instance ends.
• Reassign Work Item - Amazon SageMaker runs when a task is Reassigned.
• Work Item Assigned - Amazon SageMaker runs after the specified task is Assigned to a participant.
• Work Item Overdue - Amazon SageMaker runs when a task is Overdue.

Default Value:

None

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Set Trigger Condition

Opens this Screen:

Get Prediction > Triggering Event tab > Set Trigger Condition

Function of this Screen:

Specifies the conditions that cause the Amazon SageMaker model to run.

Rule Type

Description:

Specifies a rule to execute.

Allowed Values:

• IF - Specifies a rule to execute if a specified condition is true.
• ELSE IF - Specifies a rule to execute if the previous condition is false.

  To open this field, click Add New Rule .

• ELSE - The rule executes if the all the specified conditions are false.

Default Value:

1. IF
2. ELSE

Condition

Description:

Specifies a name for a rule in your condition.

Allowed Values:

One line of text (a string).

Accepted:

• Letters
• Numbers
• Spaces

Default Value:

Rule Name 1

Edit

Opens this Screen:

Get Prediction Configuration > Triggering Event > Condition Builder screen

Function of this Screen:

Creates or changes logical rules. You can put one statement inside another statement to create complex logical expressions.

Delete

Function:

Deletes the selected row.

Condition Name

Description:

Shows the name for your rule.

Allowed Values:

Read only.

Default Value:

Rule Name 1

Preview

Function:

Shows the preview of your rule.

Validate

Function:

Makes sure the rule is correct.

Rule Variable

Description:

Specifies the value to analyze.

Allowed Values:

One line of text (a string).

Accepted:

• Letters
• Numbers
• Spaces

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

• (Example) Configure a Condition Activity (Check Leave Approval Status)
• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Operator

Description:

Lets you select the operators for a logical expression.

Allowed Values:

Data Type	Expression Operators
String	, ==, Starts with, Ends with, Contains, Does Not Contains, !=, Does Not Contain Data, Contains Data
Bool	==
Date Time	, ==, >, >= , <, <=, !=
Number	, ==, >, >=, <, <=, !=

Default Value:

None

Example:

Refer to:

• (Example) Configure a Condition Activity (Check Leave Approval Status)
• (Example) Configure a Condition Activity (Compare Leave Hours)
• (Example) Create Zoom Meeting

Rule Value

Description:

The value for the data variable.

Allowed Values:

One line of text (a string).

Accepted:

• Letters
• Numbers
• Spaces

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

• (Example) Configure a Condition Activity (Check Leave Approval Status)
• (Example) Create Zoom Meeting
• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Add Row

Function:

Creates a condition row.

Select Nest Type

Function:

Specifies the use of logical AND and OR operators to nest conditions to use for predictions.

You must set the condition first, before you specify the nest type.

Allowed Values:

• And - Specifies the logical AND operator.
• Or - Specifies the logical OR operator.

Default Value:

AND

Indent Right

Function:

Creates the statement that is a condition of a parent statement.

Delete

Function:

Deletes the selected row.

Back

Function:

Saves the rule and goes back to the Create Condition screen.

Content Type

Description:

Specifies the format to send the request.

Allowed Values:

• CSV
• JSON

Default Value:

None

Accepts Variables:

No

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Configure Request Mapping

Opens this Screen:

Get Prediction > Request tab > Configure Request Mapping

To Open this Field:

1. In the Content Type field, select one of these:
   • CSV
   • JSON

Function of this Screen:

Connects the request payload from Amazon SageMaker to the process schema.

Read Message From This Variable / Map Payload To App Schema / Map Payload To Grid

Description:

Specifies how to connect the request data from Amazon SageMaker to your AgilePoint process schema.

Allowed Values:

• Read Payload From This Variable - Specifies a variable that stores the payload. The value of the process data variable must be in a valid JSON format.
• Map Payload To App Schema - Specifies a payload to use to connect to the AgilePoint process schema.

  Click the Map Schema button to open the Schema Mapper.

  Use this screen to connect the payload values to the AgilePoint process schema.

• Map Payload To Grid - Sends a request in specified key-value pairs.

Default Value:

Read Payload From This Variable

Accepts Variables:

Yes

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Import

Description:

Specifies the column names to upload to Amazon SageMaker to send as the request.

To Open this Field:

1. On the Get Prediction > Request tab, in the Content Type field, select CSV.
2. On the Configure Request Mapping screen, select Map Payload To Grid.

Allowed Values:

One or more column names, separated by commas (,).

Default Value:

None

Column Name

Description:

Specifies the name of the column to use for predictions.

To Open this Field:

1. On the Configure Request Mapping screen, select Map Payload To Grid.

Allowed Values:

A column name from Amazon SageMaker.

Default Value:

None

Accepts Variables:

No

Example:

• Refer to:
  • (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Column Value

Description:

Specifies a value for the column in a key-value pair.

To Open this Field:

1. On the Configure Request Mapping screen, select Map Payload To Grid.

Allowed Values:

A number or a text string that can contain spaces.

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Create

Function:

Adds a row for the Column Name and Column Value.

To Open this Field:

1. On the Configure Request Mapping screen, select Map Payload To Grid.

Delete

Function:

Deletes the selected row.

To Open this Field:

1. On the Configure Request Mapping screen, select Map Payload To Grid.

Map Response To App Schema / Store Response In This Variable

Description:

Specifies where to store the response from Amazon SageMaker.

Allowed Values:

• Map Response To App Schema – Select this option if you want to map the information from the Amazon SageMaker data model to your process schema.

  Click the Schema Mapping button to open the Schema Mapper.

  Use this screen to connect the response to the data model for your process.

• Store Response In This Variable – Select this option if you want to store the information from Amazon SageMaker to a variable in the AgilePoint NX app.

  In the text field, specify a variable that accepts an alphanumeric string in JSON format.

Default Value:

Map Response To App Schema

Accepts Variables:

Yes

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Save Status In This Variable (Boolean)

Description:

Specifies a variable to store the status as a Boolean value.

The value is true if the prediction has no errors.

Allowed Values:

A variable.

Format:

• Boolean

Response Values

• true
• false

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Save Error Message In This Variable (String)

Description:

Specifies a variable to store the error message of the prediction.

Allowed Values:

A variable.

Format:

• String

Accepted:

• Letters
• Numbers
• Spaces
• Special characters

Default Value:

None

Accepts Variables:

Yes

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Limitations:

Some information about third-party integrations is outside the scope of the AgilePoint NX Product Documentation. It is the responsibility of the vendors who create and maintain these technologies to provide this information. This includes specific business use cases and examples; explanations for third-party concepts; details about the data models and input and output data formats for third-party technologies; and various types of IDs, URL patterns, connection string formats, or other technical information that is specific to the third-party technologies. For more information, refer to Where Can I Find Information and Examples for Third-Party Integrations?

Suspend Process Instance If Exception Occurs

Description:

Specifies whether to move the process forward when an error occurs in the AgilePoint NX app.

Allowed Values:

• Selected - Pauses the process when an error occurs, and shows an error in the log.
• Deselected - Shows an error in the log when an error occurs, but does not pause the process.

Default Value:

Selected

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making

Enable Debug

Description:

Specifies whether to store the debugging information for the AI Control Tower activity in the debug log folder on the AgilePoint Server machine.

Allowed Values:

• Selected - Stores the runtime debugging information for the AI Control Tower activity in a debug log file.

  A debug log file is created for each process instance.

  For more information, refer to Where Are the AgilePoint NX OnPremises Logs?

• Deselected - Does not store the debugging information for the AI Control Tower activity.

Default Value:

Selected

Example:

Refer to:

• (External) Supercharge Your end-to-end Orchestration with AI Control Tower: Real-Time Monitoring and Smart Decision Making