NLP Pipelines

Enterprises can use the services of Webex Bot Builder intelligence rather than building a complete chatbot. An NLP pipeline bot is built using intelligence modules and is exposed as a service.

Webex Bot Builder platform enables developers to leverage pre-built Intelligence Modules (third-party or Webex Bot Builder libraries). These libraries help to "understand" the user's natural language input. A developer can choose the libraries they wish to include and also determine the order in which they are invoked. This selection, arrangement, and configuring of Intelligence Modules can be done through the Pipeline tab. Whenever an input is received from a user, it is parsed and passed through this pipeline. All the modules in the pipeline execute on this input text in sequential order.

For example, performing a spell check, date and time recognition from an application form, or converting audio into text.

Building an NLP pipeline bot

Follow these steps to build an NLP pipeline based bot (Bot intelligence as a service):

1. Click +New NLP Pipeline.

The Bot Profile screen appears.

2. Specify this information and click Done to create a new pipeline bot.

3. After the bot creation, from the categorized Intelligence libraries based on the media type on the NLP tab of the Input Recognition screen, click add to add the module to the Bot Intelligence Pipeline on the left-hand side. These modules are invoked in the order they are arranged.

Note: Modules related to text, image, video, and audio are grouped on each tab. Bot developers can now quickly access the text modules, image modules, video modules, and audio modules by navigating to the Text, Image, Video, and Audio tabs separately.

For more information, see the Intelligence module.

Note: You can remove the modules that are added to the bot intelligence pipeline, using the remove icon corresponding to the module.

6. To reorder the modules manually, drag the module and drop it at the required place.
7. Click Update Pipeline.

When the bot building is successful, the bot is displayed on the NLP Pipelines tab of the Dashboard.

NLP pipeline testing

Pipeline bot testing can be performed either by providing the text or URL on the Test pipeline bot screen. Based on the bot intelligence modules configured in the NLP, consumer inputs are processed through this sequence of modules to segregate the input parameters accordingly for analyzing the sentiment of the text, performing the spell check, expanding the contracted consumer text, and so on.

Follow these steps to test a pipeline based bot:

1. Select a specific pipeline bot on the NLP pipelines tab of the dashboard.
2. Click the Test tab. The Test NLP pipeline screen appears.

3. Select the Message type input. Possible values:

• Text
• URL

4. Enter the message in the provided Message box, in case if you set the Message type input to Text
   Note: Provide the URL, if you set the Message type Input to URL. You also have to add URL-related modules in the bot intelligence pipeline (such as OCR).
5. Click Test pipeline to classify the input parameters in the consumer message based on the configured bot intelligence modules.

Testing in other apps

Getting bot access token

To integrate the bot with other systems, an access code is required. Follow these steps to get the access code of the bot:

1. Navigate to the NLP pipelines tab on the dashboard.

2. Click the required bot.
3. Click the ellipses icon corresponding to a specific bot and click Copy Access Token.

Testing in Postman

Follow these steps to access your pipeline bot and test it through postman.

• Open a new postman tab by clicking on + set request type as 'Post' from the dropdown

• Enter the request URL: https://imibot.ai/api/v1/webhook/intelligent/
• Select the Headers section to provide these values:

• Navigate to Body section, select type as ‘raw’, and enter your request in this format:

{
   "msg": "your test text goes here",
"msg_type": "text"}

Transaction history in NLP pipelines

NLP pipelines contain a ‘Transactions’ tab similar to ‘Sessions’ in Q&A and Task bots. This allows developers to track usage of their pipelines and view the results of individual NLP transactions, providing granular insights into the performance of individual modules for each transaction. NLP node in Webex connect is powered by a system created NLP pipeline in each tenant. With the addition of this feature, developers stand to gain a better understanding of their conversational automation performance and can adjust their flows accordingly.

Users can search for transactions they’re interested in using a transaction ID or the date range when the transaction took place.
Clicking on any transaction in the table will display transaction details. User message along with information about all the modules used with their outputs is available on the left. The right side contains the raw response of the NLP pipeline.

Intelligence modules

Intelligence modules are pre-built libraries available to the developers. These include various third-party libraries as well as libraries built by Webex Bot Builder and can be leveraged by developers while designing and building their bot. These modules can be used by including them in the Pipeline.
The following table contains the list of all available intelligence modules, a brief explanation of their purpose, and details on different implementations available on IMIbot.ai. Scroll right for columns that aren't visible.