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sample work queue research assistant for IBM Supply Chain Intelligence Suite

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supply-chain-assistant-work-queue-research

A sample work queue research assistant for IBM Supply Chain Intelligence Suite (SCIS).

Introduction

A team of supply chain analysts need to review and work on issues with their supply chain. Those issues are surfaced as work items in a given work queue, e.g. inventory above upper threshold.

This sample is designed to help users research their respective work items within SCIS by faciliating a set of bookmarked research questions which are relevant to the business use case surrounding a given work queue.

The project illustrates how to create a Watson Assistant skill, train it with example utterances, and have it return a set of bookmarks that will guide the user as they research how to best resolve their work items.

Documentation of how to design, build and deploy Watson Assistant skills for the Sterling AI assistant can be found in the Sterling Knowledge Center.

Uploading the skill to Watson Assistant

Before testing the skill you need to upload it to Watson Assistant.

Please do the following:

  • Create a Watson Assistant service resource in an IBM cloud account.

  • In the Watson Assistant tool, select Create assistant and create an assistant named Work Queue Research Sample, which will be necessary to host the skill.

  • Write down the assistant URL and API key for the Work Queue Research Sample assistant, found on that assistant's Settings page.

  • In the Watson Assistant tool, select Create skill, choose Dialog Skill, then select Upload skill to upload src/skill.json into the new skill.

  • Write down the Legacy v1 workspace URL for the Work Queue Research Sample skill, found on the skill's API details page.

  • Open the Work Queue Research Sample assistant again, select Add dialog skill to add the Work Queue Research Sample skill to the assistant.

Building the project

The project contains a set of Node.js sample test programs which can be used to test the skill.

To build the test programs, make sure you have Node.js and yarn installed, then run the following command:

yarn build

Testing the skill

The sample test programs illustrate how to test that the skill functions as expected, with good language recognition accuracy.

Configure the following environment variables related to Watson Assistant:

export ASSISTANT="the assistant URL for the Work Queue Research Sample assistant"
export KEY="the API key for the Work Queue Research Sample assistant"
export SKILL="the legacy v1 workspace URL for the Work Queue Research Sample skill"

The assistant URL and API key can be found on the Settings page of the Work Queue Research Sample assistant.

The skill's Legacy v1 workspace URL can be found on the API details page of the Work Queue Research Sample skill.

Since this sample uses the Named Entity Recognition API, you will need to authenticate using a JSON Web Token which can be obtained from the Saascore Authentication API.

Configure the following environment variables related to authentication:

export SCIS_ORGANIZATION="the ID for your SCIS organization"
export INFOHUB_TENANT="the Infohub tenant ID associated with your SCIS organization"
export SAASCORE_BASIC_USERNAME="the username (IBMID) of the authenticating user"
export SAASCORE_BASIC_PASSWORD="the corresponding password of the authenticating user"

Run the following command:

yarn test

Registering the skill with the Sterling Assistant

To register the sample skill with the Sterling AI Assistant, follow the steps described in Registering your skills with the Sterling Assistant.

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