Chat application
From start to finish, set up a chat-based application in minutes with NLX
Checklist
You'll complete the following to successfully launch your chat application:
Pre-setup: Integrations
Est. time to complete: ~5 minutes
A one-time integration of a Natural Language Processing (NLP) engine must be completed in your workspace:
Step 1: Create a flow
Est. time to complete: ~10 minutes
Begin by identifying the tasks your conversational AI application will automate and organize them into individual topics handled by a flow. Determine the sequence of steps and messaging that the conversational application follows to assist a user with the task. The conversation workflow is assembled in a flow's Canvas with a pattern of nodes similar to a flow diagram.
Each flow is invoked when your chosen AI model identifies customer intent from a user's query ("I want to order room service") and matches it to a flow you've created (OrderRoomService). This match is done based on the training data you provide for your AI model.
Enter a descriptive name (no spaces or special characters) > Select Save
Complete Flow setup by attaching training data and attaching slots
Add nodes by right-clicking on the Canvas & choosing New node (see available node types)
Connect first node to Start node > Connect sequential nodes via node edges or stacking
Add conversational AI messages to nodes by selecting + Add message on a node's side panel
Click Save
Repeat for any additional flows your application will help automate.
Step 2: Set up application
Est. time to complete: ~3 minutes
Now you'll create the conversational AI application users will interface with. This step involves attaching all intent flows you want your application to access, defining flows to handle certain behaviors, and setting up the channel your application supports.
Select Applications from workspace menu > Choose New application
Enter a descriptive name > Click Save
Click Flows tab of application > Select Attach flows > Attach one or more flows created to make available to your application > Click Attach selected then Save
Select Default behaviors tab of application > Assign any attached flows to the application's behaviors > Click Save
Select Channels tab of application > Expand API option > Click + Create channel
Click + Add domain under Whitelisted domains > Add your webpage's URL and https://developers.nlx.ai
Click Create channel
Step 3: Build & deploy
Est. time to complete: ~5 minutes
A build constructs the array of flows that make up your conversational AI application and updates any changes made to your flows, while deploying makes a successful build live:
Click Deployment tab of application > Select Create or Review & build
Wait for validation to complete > Select Create build*
When satisfied with a successful build, click Deploy
Step 4: Install SDK
Est. time to complete: ~5 minutes
To make your application available through your frontend and adjust the look, feel, and chat experience with theming and custom UI components, install the NLX chat SDK:
From Deployment tab of application, select Details next to the Deployed status
Expand the API section under Setup instructions in the pop-up modal
Expand the API section under Setup instructions in the pop-up > Select Open Touchpoint configurator
Make adjustments to the theming > Copy Setup snippet > Install on your site
Optional: Retrieve external data
To pull in and reference information from an external system, you may first set up a data request integration and invoke it in a flow using the Data request node.
Select Data requests under Resources of workspace menu > Choose New data request > Provide a name
Switch to External implementation under the Implementation tab > Choose the appropriate HTTPS method
Expand Production endpoint > Enter the URL and any applicable Header(s)*
Download the provided AWS CloudFormation template listed in the Instructions section
Select the Response model tab > Choose <> Auto-generate option > Enter a snippet of your schema
Optional: If you require sending a payload when the API call is made in a workflow, select the Request model tab > Click Create from example JSON > Enter a snippet of the payload schema
Click Save
Now that your integration is set up, trigger your API call during a flow using a Data request node
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