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Build an enhanced IT help desk chatbot on IBM i with Watson Assistant

January 14, 2019
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Credit: IBM

Deploy a chatbot prototype that can understand and automatically solve
password-related issues on IBM i

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Comments

Watson Conversation is now Watson Assistant. Although some illustrations in this tutorial may show the service as Watson Conversation, the steps and processes will still work.

Did you know that as per recent studies, an average of 20% to 50% of all help desk
calls are password related? Mundane tasks can be a headache for help desk teams,
especially when higher priority jobs need attention. Virtual assistants (also known
as chatbot) for IT help desk can automatically process tickets that do not
need deep expertise such as managing access credentials and password-related issues,
allowing your staff to focus on critical issues and value-added tasks. For instance,
a chatbot can analyze the root cause and automatically solve password-related
issues.

In this article, you will implement a simple chatbot to illustrate this kind of
solution.

It can understand user profile-related issues, and, if possible, automatically solve
the problem. As the icing on the cake, it can also answer to
queries about system utilization, such as processor utilization or the percentage of
system auxiliary storage pool (ASP) used.

This chatbot links the IBM® Watson® Assistant service and IBM i (back
end) to Slack (front end), which is the messaging team collaboration tool. It will
be implemented in the prototyping mode with Node_RED, and will run on IBM i.

You are now going to instantiate and configure the required services, import the
Watson Assistant workspace (predefined dialog training) and Node-RED flow
(chatbot back-end program), and test it!

What you’ll
need

To implement this chatbot on your IBM i system, you need:

  • An IBM i 7.3 partition with Node-RED installed (if you need to install Node-RED
    on your IBM i, you can refer to my previous article Running Node-RED on IBM i: Installation and first flow,
    developerWorks, October 2017).
  • An IBM Cloud (earlier known as IBM Bluemix®) account to be able to
    provision Watson Assistant services.
    Register for your free trial
    account
    or log
    in to IBM Cloud
      if you already have an account.
  • A Twilio account (trial version available), and a Slack account (free version
    available).
Note:
If you do not want to create a Twilio account, you will still be able
to run the chatbot program. In this case, the user will not receive the
authentication code by text. The only way to retrieve the code will be
to look at the program trace, in the Node-RED user interface, on the
Debug tab.

Architecture
overview

To implement this IT help desk chatbot on IBM i, four components must be deployed and
configured. Figure 1 shows the components deployed to support the chatbot solution
implemented in this article.

Figure 1. Chatbot architecture overview diagram

The four components are:

  1. IBM Watson Assistant service providing natural language capabilities:
    intents/entities recognition and dialog management.
  2. Slack software used as the user interface, in which you will create a Slack bot,
    a component required to interface Slack with your own chatbot program (#3).
  3. Your chatbot back-end program, implemented with Node-RED on your IBM i system.
    It is the core of the solution, called application logic, linking all
    the components: Watson Assistant service (#1), user interface (#2), and IBM i
    system and database (#4).
  4. IBM i system and the IBM Db2® database for retrieving and updating IBM i
    user profile (*USRPRF) attributes.
    In this prototype, the Node-RED program
    can directly query the database or run the program (integrated in #3). But, in a
    multi-system configuration, this component must be independent and deployed on
    all systems. Then data and services are available through web services
    [Representational State Transfer (REST) APIs].

In this article, let us see how to set up these components.

IBM Cloud: Deploy and train Watson Assistant service

In this first part, you will instantiate, train, and test Watson Assistant, (the
Watson cognitive service in charge of dialog with a chatbot user).

The IBM Watson Assistant service combines machine learning, natural language
understanding, and integrated dialog tools to create conversation flows between your
applications and your users.

Perform the following steps to create your own Watson Assistant instance:

  1. Log in to IBM
    Cloud
    using your IBM Cloud account.
  2. Select the region and space you want to work in.
  3. Click Catalog, then click Watson in the left
    navigation panel. The catalog displays the available Watson services. Click
    Assistant to view the service configuration page.

    Figure 2. IBM Cloud platform, Watson services
    catalog

  4. Provide a unique service name (or use the default service name), and choose plan
    Lite (free). This plan allows 10,000 API calls per month,
    five workspaces, 25 intents and 25 entities. If you need more, you can subscribe
    to Standard or Premium plans. Click Create.

    Figure 3. Assistant instance creation

  5. In the new service dashboard that is displayed, click Launch
    tool
    to launch the web tooling interface where you can define
    intents, entities, and the dialog for conversation. A new page opens in your
    browser. Click Log with your IBMid.

Watson Assistant: Import a conversation

In this part, you will import a conversation flow to handle a dialog with a help desk
chatbot user. The JSON file containing the dialog flow
(iHelpdesk.json) is provided in the “Downloadable resources” section of this article.

The Watson Assistant tool page allows to create a new workspace or to import an exported
one. A workspace is a container for the artifacts that define the
conversation flow for an application.

Perform the following steps to import a conversation flow:

  1. Import the iHelpdesk.json workspace by clicking the
    Import icon (highlighted on Figure 4).

    Figure 4. Watson Assistant tool

  2. Click Choose a file, and select the iHelpdesk.json file,
    previously downloaded from “
    Downloadable
    resources
    “.
    Then, click Import.

    Figure 5. Importing a workspace

  3. A new workspace is created and opened. To view the conversation dialog, click
    the Dialog tab.

    Figure 6. Watson Assistant workspace

Note:
A dialog consists of the following three types of data:

  • Intentions (the verb)
    Intentions represent the purpose of a
    user’s input. You can think of intentions as the actions your
    users might want to perform in your application.Example: A user
    wants to know the value of a system resource
  • Entities (the name)
    An entity represents a term or an object
    in the user’s text that provides clarification or a specific
    context for a particular intent. By recognizing the entities
    that are mentioned in the user’s entry, the Watson Assistant service
    can choose the specific actions to perform to achieve a given
    intent.Example entity: System resource (such as processor, disk,
    memory, and so on)
  • The dialog itself
    The dialog defines the flow of your
    conversation as a logical tree. Each node of the tree has a
    condition that triggers it, depending on the input of the
    user.The purpose of the dialog is to lead to the answer to a
    question or the execution of an action or a command.

Watson Assistant: Understanding a conversation

You can have a look at the workspace content to get an idea of the questions you
could ask to the chatbot (in the Intents and
Entities
tabs) or understand the way the dialog flow has been created
(in the Dialog tab).

For example, you can try to understand the Reset Password flow
implementation in the Watson Assistant service. Figure 7 illustrates how the
#lost password intent dialog has been designed for this demo,
where:

  • Text within blue boxes are messages sent to a user
  • Text within green boxes are actions identified by the Watson Assistant service that
    the chatbot program will have to run
  • Orange squares are conditional statements
  • Green circle is dialog entry point for this intent
  • Red circles are dialog exit points for this intent
Figure 7. Reset password dialog flow

The chatbot program on IBM i requires the workspace ID and credentials to connect to
the Watson Assistant API. To retrieve these values, click the
Deploy icon and then click Credentials
(highlighted in Figure 8).
Copy the workspace ID, user name, and password.

Figure 8. Watson Assistant credentials

Your Watson Assistant workspace is now configured. Intends, entities, and dialogs
are ready to be used by your IBM i chatbot program.

If you want to learn more about Watson Assistant tool and interface, refer to the
Watson Assistant documentation website.

Now, let’s configure Slack, a software as a service (SaaS) collaborative solution
that will provide the user interface of this chatbot.

Slack

Slack is a cloud-based set of team collaboration tools and
services.

Slack works like an Internet RelayChat (IRC), organized in channels
corresponding to many topics of discussion. The platform also makes it possible to
keep track of all exchanges, allows file sharing within conversations, and
integrates external services (such as GitHub, Box, Skype and so on) or your
chatbot implemented with Watson Assistant. To integrate your chatbot, you need to
use Slack bot, an integration solution that allows to communicate with your chatbot
program which in turn communicates with Watson Assistant.

First create a Slack workspace or use an existing one if you have sufficient
authorization. If needed, refer to Slack’s how-to on creating a new workspace. During
this process, you must enter a name that will identify your Slack workspace and
define the workspace host name (by default, <WORKSPACE>.slack.com).

In this article, we will use ihelpdesk as the workspace name, and
ihelpdesk.slack.com as the host name (don’t forget to use your
own details).

Open a new browser page on this host name to get access to your Slack workspace.

Figure 9. Slack Workspace on ihelpdesk.slack.com

Perform the following steps to create a custom bot in your Slack workspace:

  1. Open a new page in your browser and navigate to the Slack Custom
    Integration-Bots creation page using the following URL:
    https://<WORKSPACE>.slack.com/services/new/bot (replace
    WORKSPACE by your own workspace name).

    Figure 10. Slack bot creation interface

  2. Name the bot (you could change name after, if needed) and click Add bot
    integration
    . In this article, we will use ibot as
    the bot name.
  3. A new page opens containing the API token (the bot’s secret token).
    Token
    is used to connect your chatbot application (running on Node-RED on IBM i) to
    Slack servers by using a custom TCP/IP network API called Slack Real Time
    Messaging (RTM) API. This allows all user interactions with the Slack bot to be
    sent to your connected chatbot application.

    Figure 11. API Token in Slack bot setting page

    Copy this token because you will need it to configure Slack nodes in the
    Node-RED flow.

  4. Switch back to the Slack workspace page.
    You can see a new app, the Slack
    bot (highlighted on Figure 12). It is currently not connected. It will appear as
    connected after creating the chatbot program with Node-RED (refer to the “Node-RED” section of this article).

    Figure 12. Slack new app available

    Your Slack
    workspace is configured. The Slack bot application (a virtual user) is now ready
    to be connected to the Node-RED application you will create.

Twilio

Twilio is a cloud
communications platform as a service (PaaS) that allows developers to
programmatically integrate voice, messaging, and VoIP into web and mobile apps.

You can access Twilio’s services using web service APIs and you will be billed based
on the usage.

In this article, we will use Twilio to implement a Two Factor Authentication (2FA)
process. In this process, the user is authenticated first by his Slack ID and then
by his phone number (a validation code is sent to the user’s mobile number).

If you don’t have an account yet, Twilio offers a trial version to all
customers who sign up, which includes a free balance for you to experiment
with. When your balance gets low, Twilio sends you an email with the
information required to upgrade your project.

Create a
trial account
(or connect to Twilio using your existing account) and obtain a SMS-capable
phone number.

Check the following references for detailed information about Twilio
configuration:

  1. Sign up for a Twilio account
  2. Get an SMS capable phone number used to send text
    messages.

After completing the configuration, retrieve and copy the following information that
will be required to configure the Node-RED Twilio node:

  1. Account security ID (SID) and authentication token from the Dashboard page.
    Figure 13. Twilio account SID and authentication
    token

  2. An SMS-capable phone number (see Figure 14). To access this, click All
    Products & Services
    on the home page, and then click #
    Phone Numbers
    .

    Figure 14. Twilio active numbers

    Note: If you
    want to send text messages to another phone number, you must declare it on
    the Verified Caller IDs page.

    Figure 15. Twilio callers

    Your Twilio service
    is configured and ready to be used for authentication (2FA).

As all cloud external services are ready (Watson Assistant, Slack, and Twilio),
you can now create the chatbot program with Node-RED on your IBM i system.

Node-RED

Node-RED is a flow-based
programming tool, originally developed by the IBM Emerging Technology Services
team (in early 2013) and now a part of JS Foundation.

Traditional development can be very technical, but Node-RED enables you to
concentrate on the logic of your workflow, allowing fast prototyping.

If you want to know more about Node-RED and how to get started on IBM i, refer to my
previous IBM developerWorks® article, “Running Node-RED on IBM i: Installation and first flow”.

Install additional nodes in Node-RED

To implement this chatbot, you need to connect your chatbot program to IBM Watson
Assistant (in the IBM Cloud platform), Twilio, Slack, and also locally to the IBM
Db2 for i database.

By default, Node-RED doesn’t install nodes for Watson software development kit (SDK),
Twilio, Slack, or Db2 for i. So, you must now install them.

There are two ways to do that: Using the shell command line or the Node-RED UI.

First, let us install Db2 for i and Watson SDK nodes using the shell command line,
then install Twilio and Slack nodes using the Node-RED UI.

  1. Install node-red-contrib-db2-for-i and node-red-node-watson
    packages

    The
    node-red-contrib-db2-for-i package provides a node allowing
    to read and write to a local Db2 for i database from Node-RED on IBM i.
    Description can be found here.

    The node-red-node-watson
    package provides a collection of nodes for IBM Watson services. Description
    of packages and nodes, provided for Watson services, can be found here. Of course, it includes Watson Assistant
    node, which is the service supporting our chatbot dialog.

    Using a node
    package manager (NPM), you can install Node-RED packages globally (thus
    making it available for all Node-RED users) or locally (making it available
    for a specific user environment only).
    As these packages can be useful
    for every project. You need to do a global installation using the
    npm shell command.

    Start a shell session. It can be
    Qshell or remote Secure Shell (SSH). I recommend using SSH. Read Jesse Gorzinski’s article, “Eight Reasons to Embrace SSH” on IBMSystemsMag.com
    to be convinced.

    To install the packages, run the following
    commands:

    $ npm install -g node-red-contrib-db2-for-i
    …
    $ npm install -g node-red-node-watson
    …

    You
    can now see the packages installed in the npm global root
    directory:

    $ ls /QOpenSys/QIBM/ProdData/OPS/Node6/lib/node_modules
    node-gyp                       node-red              node-red-node-watson  
    node-red-contrib-db2-for-i     npm                   websocket-stream

    Stop
    and start Node-RED to load new nodes.

    Open your browser enter the
    URLhttp://<YOUR_SERVER_IP_ADDRESS>:1880 to open a page on Node-RED
    user interface.

    In the palette (as shown in Figure 16), you can see
    the Db2 for i node and a new IBM Watson
    category.

    Figure 16. Db2 for i and Watson nodes

  2. Install Slack and Twilio
    packages

    Package
    node-red-contrib-slack provides a Node-RED node to receive
    from and post messages to Slack. Description can be found here.

    You can install it using the Node-RED
    UI. In this case, new nodes will be available only in the running Node-RED
    environment.

    In Node-RED:

    1. Click the menu icon at the upper-right corner and click Manage
      Palette
      .
    2. Click the Install tab and search for the word,
      “slack”.
      In the list that appears, search for
      node-red-contrib-slack and click
      install.

      Figure 17. Install Slack nodes

    3. Wait for the installation confirmation message.

    Next, let us install the Twilio node. The
    node-red-node-twilio package provides a Node-RED node to
    send SMS messages using the Twilio service. Install it the same way you did
    for node-red-contrib-slack :

    1. Click the menu icon at the upper-right corner and click Manage
      Palette
      .
    2. Click the Install tab and search for the word,
      “twilio”.
      In the list that appears, search for
      node-red-node-twilio and click
      install.
    3. Wait for the installation confirmation message.

    Let’s now restart Node-RED. When restarted, take a look at the palette.
    In the Social category, three Slack nodes are now
    available. In the Mobile category, one Twilio node is now
    available.

    Figure 18. Slack and Twilio nodes

Import
flow and configure nodes

You are now going to import the chatbot flow and configure it to use your own
services (Watson Assistant, Slack, and Twilio previously configured).

You need to get the (JSON) code, import it into Node-RED on IBM i, and deploy it.

Get the code.
To get the code, download the
Node-Red_chatbot_flow.v1.1.json file from the “
Downloadable
resources
” section of this article, and copy the entire file’s content into
clipboard.

Import the code.
Go back to the IBM i Node-RED editor in your
browser, click the menu at the upper-right corner and click Import
-> Clipboard. Then, paste
the contents of the Node-Red_chatbot_flow.v1.1.json
file content that you
copied. Click New flow, and then click Import.

Figure 19. Import chatbot flow

Click somewhere on the blank sheet to paste nodes.

Have a quick look at chatbot flow. Figure 20 highlights the main logic of the
flow.

Figure 20. Chatbot flow overview

The numbering in the figure corresponds to the numbering in the following procedure
that explains the flow.

  1. Get the text entered by the user on Slack.
  2. Send it to the Watson Assistant service. This service understands the intent,
    identifies entities, defines what to answer.
    It sends back an answer for the
    Slack user and initializes variables in the context part of the JSON object
    exchanged. The value of context.Action variable indicates whether
    an action has to be executed by the chatbot (and what action) or not.
  3. Depending on the Action variable value, the switch case node will
    route to perform one or two steps (from within step 4 to step 8).
  4. Answer directly to the Slack user.
  5. Retrieve resource usage value from IBM i (by querying Db2 for i services).
  6. Generate a temporary password and an authentication code, and send text.
    If
    you don’t want to use SMS to send code, you can configure the email
    node to send it by email.
  7. Change the user profile (*USRPRF) IBM i object. First test if password reset is
    allowed (password not *NONE), and then run the system CHGUSRPRF
    shell command.
  8. Retrieve the user profile parameters from IBM i (by querying Db2 for i services)
    and determine the possible cause of the connection issue.

After performing steps 5, 7 or 8, the result is sent to Watson Assistant to
transcript in a natural language sentence.

Link nodes (#a, #b) allow to make a connection back to the beginning of
the flows (from a to b), without overwriting the flow representation.
Link nodes allow to set up a mechanism like the symbolic links of
UNIX file systems.

Update the code.
You must now configure nodes corresponding to
cloud external services previously created. Figure 21 shows the nodes to be
configured.

Figure 21. nodes to be configured

  1. Watson Assistant
    Double-click the Conversation-Slack node
    (Figure 21, #1), and enter the user name,
    password and workspace ID (captured in the
    “Watson Assistant: Understanding a
    conversation
    ” section of this article.
  2. Slack
    Two Slack nodes must be configured: Slack bot in and
    Slack bot out, and they both have the same name:
    helpdeskbot.
    Double-click each node (Figure 21, #2), and
    enter the bot API token (captured in the “Slack”
    section of this article).
  3. Twilio
    To configure the Twilio node (refer Figure 21, #3a),
    double-click it, and select the External service value for the
    Service field.

    Figure 22. Twilio node configuration

    Then,
    click the Edit button (highlighted in Figure 22) to add a
    new Twilio API (twilio-api).

    Figure 23. Twilio node account configuration

    Enter
    the required values in the Account SID, From, Token and
    Name fields (see Figure 23). You should have captured
    those values in the “Twilio” section of this
    article.

    Then, configure the function node (Figure 21, #3b), named
    Build SMS.
    This node build message to be sent by text,
    and also defined the target phone number (this is only a simple demo, but
    think about dynamically retrieving this phone number from an enterprise user
    directory, for instance, Lightweight Directory Access Protocol (LDAP) or IBM
    Directory Server).

    Initialize the msg.topic
    variable with the phone number to which you want to send messages. Remember
    to replace xxxxxx with this phone number in the code (see Figure 24).

    Figure 24. Twilio function node

Note:
The two Db2 for i nodes are configured to use the *Local connection to
the IBM i database. User profiles used to launch Node-RED will be used
for Db2 authorizations.
Maybe, for security reasons, you will have
to reconfigure the Db2 for i nodes to declare the credentials of a
specific user profile to be used for Db2 connections.

Deploy the code.
Click Deploy to deploy and
make your application live.
A message, Successfully deployed,
appears at the top of the window.

You can now test the chatbot.

Test chatbot

Go back to the Slack window, and see that the virtual user is now connected (as shown
in Figure 25).

Figure 25. Slack bot connected

This chatbot was trained to answer the following four user intents:

These are just examples of resolving password-related issues. You can find many ways
to improve it by changing the Watson Assistant dialog flow or the Node-RED
flow.

Remember that the quality of chatbot is mainly related to the quality of the Watson
Assistant training. And, as you could see in the “Watson
Assistant: Import a conversation
” section, the current training (number
of sample sentences by intent) is not sufficient. You can add more sample sentences
to train Watson Assistant better.

So, now, it is your turn.

Switch back to the Slack interface.

Click the iBot app on the left pane, and enter your questions.

For exhaustive tests, don’t forget to change the parameters of test user profile
(*USRPRF on IBM i), for example, password *NONE or expired, user profile *DISABLED
due to too many wrong passwords entered, and so on.

Conclusion

In this article, you could see that it is quite easy to create a chatbot to
automatically support simple ticket resolution tasks.

This easiness is due to three main factors:

  • Watson Assistant in IBM Cloud, providing a powerful tool to design and
    support dialogs in a natural language
  • Node-RED on IBM i, a Node.js development application allowing quick and easy
    prototyping
  • Db2 for i services, simplifying access to many pieces of IBM i system
    information through a database interface rather than complex commands or
    APIs.

So, next, what will you request to your chatbot to do? Solve printer issues, the
second source of tickets in IT help desk organizations? Provide FAQ interface to
your IBM i users?

There are so many ideas and their implementations are now possible on your IBM i.
Let’s do it!

IBM Watson Assistant

Node-RED

DB2 for i services


Downloadable resources

Credit: IBM

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