Page Comparison

This article deals with the following topics:

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1. Click Create Tenant on the Tenant Management page.
   
   
2. On the Tenant details section, specify the following information:        
   
   1. Tenant name.
   2. The tenant which is used when logging into the Bot Builder.
   3. The tenant ID which must fall in the range from 1000 to 999999999. If you do not specify the tenant id, a unique id is auto-generated after the tenant is created.
   4. Specify the symbol. This symbol is used internally to identify the tenant in the database. The maximum number of characters is limited to 6. The allowed characters are A-Z, a-z, 0-9,_. Values must start with a letter and must not end with _(underscore).
3. Click on Next to add Default Bot & Domain Details. By default, the data is automatically populated based on the Tenant Details section. However, you can configure the bot and domain details, if required.
   
                                                     
   
   1. The bot name. This is used to identify the bot easily in the Bot Builder.
   2. Select the language that the bot can communicate with the user. Currently, the bot supports the following languages:
      • English
      • Chinese
      • Japanese
      • Spanish
      • Portuguese
   3. Build and Publish Service: The Service assigned to the Tenant is required to build and publish the training data to the bot. It could be AWS Sagemaker or RASA Adapter.
   4. The bot symbol. This symbol is used internally to identify the bot in the database. The maximum number of characters is limited to 6. The allowed characters are A-Z, a-z, 0-9,_. Values must start with a letter and must not end with _(underscore).
   5. The domain name. The skills and attributes are associated with a domain.

   6. The unique identifier for the domain.    

      Info
      title AWS Sagemaker
      RASA adapter runs the Build and Publish process on the Local infrastructure. Run time performance is better on AWS SageMaker. Customers must subscribe to AWS services and configure AWS SageMaker for On-Premise implementations.

      
      

4.  Click Next to navigate to Tenant Administrator Details to define the tenant administrator information:
                   
                 
   1. The username of the tenant administrator.
   2. The email id of the tenant administrator.
   3. The password using which the tenant administrator can log in to the Bot Builder.
   4. Select the language from English or Chinese. This is the language to be used across the Bot Builder UI.
   5. The first name of the tenant administrator.
   6. The last name of the tenant administrator.    
      
      
5. Click Next to navigate to Generative AI Configuration to enable Azure Open AI for the tenant. The configuration should be enabled if you want to enable Generative AI capabilities for your tenant.
   
   
   To enable Generative AI, follow the below steps:
   
   1. Enable Generative AI
   2. Add the following configurations:
      1. Azure Resource Name.
         
      2. Endpoint
      3. Deployment name for gpt-35-turbo
      4. Deployment name for gpt-35-turbo-16k
      5. API Key to connect to your Generative AI instance.
   3. Enable the features required for Luma Virtual Agent and Luma Knowledge.
      

      1. Under ‘Features available in Virtual Agent’ you can view the Generative AI Features used in Virtual Agent. The skill developer uses these features to integrate Generative AI into skill building and execution seamlessly.

         1. Auto Phrase Generation for Skills enables the Skill developer to automatically generate user phrases that the end-user can use to request the skill.

         2. AI Task in Skill Conversation Flow enables the skill developer to add an AI Task as a step in a skill. The conversation step, AI Task, can be added to the canvas or is executed only if the feature is available for your tenant.

      2. Under ‘Features available in Knowledge,’ you can view the functionalities available in Luma Knowledge. Using these capabilities, Luma can adeptly curate and oversee your Knowledge Articles. For more information, refer to Integrating Advanced Language Models.

         1. Keyword and Keypharses generation allows Luma to automatically extract relevant keywords from documents and data, making information retrieval faster and more effective.

         2. Automatic Summarization allows the automatic summary generation based on the artifact content.

         3. Question and Answer generation(FAQ) generates Questions and corresponding answers, which can be quickly presented to the user, reducing the time spent on answering customer inquiries.

         4. Suggest Content on Knowledge Gap Resolution enables the curator to use Generative AI to build Knowledge to resolve unanswered user queries.

         5. Precise Answering enables Luma Knowledge to interpret and understand the user’s request and generate answers specific to the question.

6. Click Next to navigate to Automation Integration, to enable automation for the tenant.
   
   
   To configure automation, follow the below steps:
   
   1. Enable Provision Automation.
   2. Select ‘Automation Version’ as V2
   3. Add Automation Tenant Identifier and Access Token retrieved from ITAS Tenant Provisioning API in ‘Tenant Secret Key’ fields in VSA.

   4. Click Save.

      Info
      The above information is generated through ITAS Tenant Provisioning API. Contact the Serviceaide support team to create your tenant in ITAS and obtain the details required to enable automation for your tenant in Luma VA.

      
      

7. Click Next to navigate to the Subscription tab.

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