This documentation supports the 20.08 version of BMC Helix Platform. 
To view an earlier version, select 20.02 from the Product version menu.

Configuring cognitive service for a custom application by using BMC Native (Google) classification

BMC Helix Platform enables the administrators to make a choice between the classification service provider that they can use for auto-categorization and auto-assignment. Along with IBM Watson Assistant, BMC Helix Platform enables the administrator to use BMC Native (Google) classification service for their cognitive service. 

The BMC Native (Google) classification uses the Google Cloud Platform. BMC does not provide a Google Cloud Platform account, but provides the classification algorithm. To use BMC Native (Google) classification you must create your own Google Cloud Platform account and download a file that contains the service account credentials. 

If you want to use Google Cloud Translation Service as a provider for real-time translation for a chatbot or custom application, you can use the same Google Cloud Platform account. 

The following image illustrates the end-to-end process to configure BMC Native (Google) classification service in BMC Helix Platform. It describes the steps required and the UI tools used to configure BMC Native (Google) classification service.

TaskActionReference
1Set the Google Cloud Platform account to create your project, enable billing, and create service account credentials.Setting up the Google Cloud Platform account
2Define the value for the Classification-Service-Provider setting.Updating centralized tenant configuration settings
3Configure BMC Native (Google) classification and set the Service Account Credentials.

To use BMC Native (Google) classification for cognitive service

4Define the value for the Gcp-Project-Id setting based on the project id provided while setting up the Google Cloud Platform account.Updating centralized tenant configuration settings
5Define the value for the Gcp-Region setting based on the value of the region provided while setting up the Google Cloud Platform account.Updating centralized tenant configuration settings

Setting up the Google Cloud Platform account

You can set up the Google Cloud Platform accounts in one of the following ways:

To set up the Google Cloud Platform account manually

If you are using Google Cloud Translation Service for real-time translation, use this method to set up the Google Cloud Platform account.

  1. Log in to Google Cloud Platform Console.
  2.  Create a new Google Cloud Platform project.
    1. On the Dashboard, click Create.
    2. On the New Project page, enter the following details:
      1. In Project Name, provide a meaningful name for the project.
      2. In Location, provide a region where the data sets will be trained and deployed.

      Note

      Project ID is generated by Google Cloud Platform. Project ID is the globally unique identifier for your project. You cannot change the Project ID after the project is created. 

      Ensure that you note this Project ID generated by the Google Cloud Platform. You will need this Project ID while configuring Gcp-Project-Id setting on the Centralized Tenant Configuration UI in BMC Helix Platform.

  3.  Enable billing for this project.
    1. From the left navigation menu, select Billing.
    2. Click Link a billing account.

      Note

      If this is not your first billing account, ensure that you open the billing account list by clicking the name of your existing billing account near the top of the page, and then clicking Manage billing accounts.

    3. Enter the name of the billing account and your billing information. The options you see depend on the country of your billing address. 

      Note

      For United States accounts, you cannot change tax status after the account is created.

    4. Click Submit and enable billing.
  4.  Create a service account for your project.
    1. Select the project and click Service accounts
    2. On the Service accounts page, click CREATE SERVICE ACCOUNT.
    3. On the Create service account page, enter the following details:
      1. In Service account details, provide a meaningful name for the service account. For example, bmc-gcp-serviceaccount.
      2. In Service account ID, an Id is auto-generated by Google Cloud Platform.
      3. In Service account description, provide a meaningful description of what this account will do.
      4. Click CREATE.
    4. On the Grant this service account access to project tab, provide the following permissions to the service account.

      1. To add all the roles, click ADD ANOTHER ROLE and the select the following roles:

        PurposeRole CategoryName of the role
        Google classificationProjectOwner
        StorageStorage Admin
        Machine Learning EngineML EngineAdmin
        Real-time translationCloud TranslationCloud Translation API Admin
        Cloud TranslationCloud Translation API User
    5. Click Continue
    6. On the Grant users access to this service account tab, grant access to users and generate the Create Key.
      1. Click CREATE KEY.

        Important

        Store the file securely because this key cannot be recovered if lost.

      2. To select a download format for the key, select JSON, and click Create

      3. Rename the .json file  as <projectID>-key.json.
    7. Click Done.
  5.  Create a bucket.

    This step is required only for BMC Native (Google) Classification. You can skip this step for enabling Google Cloud Translation Service.

    1. On Dashboard, click Cloud Storage.

    2. Click Create bucket to open the bucket creation form, and enter the following details:
      1. In Name, provide a meaningful name for the bucket. 

        Note

        Ensure that the name of your bucket must be the same as your project ID.


      2. Select Regional for Storage class and for Location ensure that your Google Cloud Platform machine learning job is able to access it. For more information, see region values on  https://cloud.google.com/ml-engine/docs/tensorflow/regions .
      3. In Access control model, select Set object-level and bucket-level permissions.
      4. Click Create.

  6.  Create folders inside the bucket.

    This step is required only for BMC Native (Google) Classification. You can skip this step for enabling Google Cloud Translation Service.

    Click Create Folder to create the following metadata files: 

    FolderFolder content
    credentialContent from the service account credential .json file <projectID>-key.json created in step 4.
    dataempty folder
    model-codeUpload the sequential-tokenizer-0.1.tar.gz file.
    job-dirempty folder
    resultsempty folder
  7.  Enable the APIs and Service.
    1. From the Navigation menu, select APIs & Services.
    2. On the APIs & Services page, click ENABLE APIS AND SERVICES.
    3. Search for the following APIs and Services, and click Enable

      PurposeAPI name
      Google classification
      • Cloud Machine Learning Engine (ml.googleapis.com)
      • Google Cloud Storage JSON API (storage-api.googleapis.com)
      • Identity and Access Management (IAM) API (iam.googleapis.com)
      • Compute Engine API (compute.googleapis.com)
      • Cloud Resource Manager API (cloudresourcemanager.googleapis.com)
      Real-time translation
      • Cloud Translation API (translate.googleapis.com)


To set up the Google Cloud Platform account by using an onboarding script

  1. Log in to Google Cloud Platform Console.
  2. Install Google Cloud Platform SDK.
    For more details about Google Cloud Platform SDK and installing it, see https://cloud.google.com/sdk/ .
  3. Run the following commands to ensure that gcloud and gsutil are installed in the bash shell.

    gcloud --help
    gsutil --help
  4. Download a local copy of the following machine learning job code's compressed files:

  5. Change the execution mode for gcp_onboarding.sh by using the following command:

    chmod +x gcp_onboarding.sh
  6. (Windows only) Create bash functions so that gcp_onboarding.sh can use these functions. Use the following commands and add the functions with correct paths into the user's .bashrc file.

    gsutil() {
    /c/Program\ Files\ \(x86\)/Google/Cloud\ SDK/google-cloud-sdk/bin/gsutil.cmd $@
    }
    gcloud() {
    /c/Program\ Files\ \(x86\)/Google/Cloud\ SDK/google-cloud-sdk/bin/gcloud.cmd $@
    }
  7. Run the following script to create a new project:

    ./gcp_onboarding.sh -p <PROJECT-ID> -v -r <REGION-CODE>

    where

    <PROJECT-ID>A unique identifier for your Google Cloud Platform project.

    Note: Ensure that you provide the same projectID value in the Gcp-Project-Id setting in the Centralized Tenant Configuration UI.

    <REGION-CODE>A geographical location where you want to execute your Google Cloud Platform machine learning jobs.

    Note: Ensure that you provide the same region code value to the Gcp-Region setting in the Centralized Tenant Configuration UI.


    New <projectID>-key.json file is generated and saved in the execution folder along with the <privateID>-key.json file.

To use BMC Native (Google) classification for cognitive service

  1. Log in to BMC Helix Innovation Studio and navigate to the Administration tab.
  2. Select Configure My Server > Cognitive Service.
  3. From the Configure list, select Cognitive Service Connections.
  4. In the BMC Native for natural language classification section, in the Service Account Credentials field, add the content from the <projectID>-key.json file downloaded from Google Cloud Platform.
  5. To test the connection, click Test.
    If the connection fails, verify your service account credentials.
  6. After verifying the connection is successful, click Save.

Where to go from here

Training and testing the cognitive service for a custom application

Related topic

Enabling a real-time translation provider for chatbots

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