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In this Code Pattern, we will use the Watson Assistant Slots feature to build a chatbot that takes a pizza order. The needed information such as size, type, and ingredient choices can all be entered within one Assistant Node, unlike with previous versions of Assistant.
When the reader has completed this Code Pattern, they will understand how to:
- Create a chatbot dialog with Watson Assistant
- Use the power of Assistant Slots to more efficiently populate data fields
- Use Assistant Slots to handle various inputs within one Node.
- User sends messages to the application (running locally or on IBM Cloud).
- The application sends the user message to IBM Watson Assistant service, and displays the ongoing chat in a web page.
- Watson Assistant uses the Slots feature to fill out the required fields for a pizza order, and sends requests for additional information back to the running application.
- IBM Watson Assistant: Build, test and deploy a bot or virtual agent across mobile devices, messaging platforms, or even on a physical robot.
- Node.js: An asynchronous event driven JavaScript runtime, designed to build scalable applications.
Click the Deploy to IBM Cloud
button and hit Create
and then jump to step 5.
OR
Run in a container on IBM Cloud, using these instructions.
OR
Perform steps 1-5:
- Clone the repo
- Create IBM Cloud services
- Configure Watson Assistant
- Get IBM Cloud credentials and add to .env
- Run the application
Clone watson-conversation-slots-intro
locally. In a terminal, run:
$ git clone https://github.com/ibm/watson-conversation-slots-intro
We’ll be using the file data/watson-pizzeria.json
to upload
the Assistant Intents, Entities, and Dialog Nodes.
Create the following service and name it wcsi-conversation-service
:
- Find the Assistant service in your IBM Cloud Dashboard.
- Click on the service and then click on
Launch tool
. - Go to the
Skills
tab. - Click
Create new
- Click the
Import skill
tab. - Click
Choose JSON file
, go to your cloned repo dir, andOpen
the workspace.json file indata/watson-pizzeria.json
. - Select
Everything
and clickImport
.
To find the WORKSPACE_ID
for Watson Assistant:
- Go back to the
Skills
tab. - Find the card for the workspace you would like to use. Look for
WatsonPizzeria
. - Click on the three dots in the upper right-hand corner of the card and select
View API Details
. - Copy the
Workspace ID
GUID.
- In the next step, you will put this
Workspace ID
into the `.env file asWORKSPACE_ID
.
-
Move the
watson-conversation-slots-intro/env.sample
file towatson-conversation-slots-intro/.env
. -
Use the
apikey
from your Watson Assistant service credentials in the.env
file. Note that older services might still use username/password, so comment those out and use instead, if applicable.
- Put the
Workspace ID
into the `.env file asWORKSPACE_ID
.
WORKSPACE_ID=<put workspace id here>
# Watson Assistant Authentication using IAM
CONVERSATION_IAM_APIKEY=<put assistant IAM apikey here>
CONVERSATION_URL=<put assistant url here>
# Deprecated: Watson Assistant authentication using username/password authentication
#CONVERSATION_USERNAME=<put assistant username here>
#CONVERSATION_PASSWORD=<put assistant password here>
If you used Deploy to IBM Cloud
, the setup is automatic.
npm install
npm start
The application will be available in your browser at http://localhost:3000
The power of Slots is in how it reduces the number of nodes required to implement logic in your Watson Assistant Dialog. Here's a partial conversation Dialog using the old method:
And here's a more complete Dialog using slots, which puts all the logic in the Pizza ordering
Node.
Open up the Dialog, and we'll have a look:
Each slot represents a field to be populated in the chatbot: pizza_size
, pizza_type
, and pizza_topings
.
If they are not present, the user will be prompted, starting at the top, until all are populated via
the associated variable ($pizza_size
, $pizza_type
, etc).
Click on the Configure to add more functionality:
Here, we can add a response for when this slot is filled (Found). Logic can be used for one ingredient:
or if there are greater than one ingredient added:
We've added logic to address yes or no answers to the question "Any extra toppings?":
Click on the 3 circles and choose
Open JSON editor
to edit the json directly:
Here, we've set an empty value for the context: {"pizza_topings"} field, so that we can exit the loop by filling this slot.
Finally, we add responses for once the slots are all filled:
We start with the case where we have "pizza_toppings", by detecting that the array has size>0. Here, we first handle the case where the optional "pizza_place" slot is filled, and then handle the case where it is not.
Finally, we add a handler for the case where the user's answers to a prompt is not found. We've added a handler for the intent "help".
We have a dialog node to handle the intent #reset
which will reset all fields to null
:
Let's look at an example conversation and the associated json. With your Watson Pizzeria running, start a dialog and begin with telling the Pizza Bot you want a large pizza:
The 'User Input' shows you the "input"{"text"} field, as well as come of the
"context" that is mostly used for Assistant to keep track of internal state.
Scroll Down to Watson Understands
and look at intents
:
Note that the intent for "order" is detected. The entity "pizza_size" is now a slot that is filled out. We still have 2 required slots, "pizza_type" and "pizza_toppings". The user will be prompted until these are filled out:
We can now see that all required slots are filled:
What if we wanted to tell the Watson Pizzeria that we wanted to eat the pizza there, in the restaurant? Too late! the slot for "pizza_place" is optional, so the user won't be prompted for it, and once the required slots are filled, we exit the "Pizza Ordering" dialog node. The user needs to fill out optional slots first. Type reset to start again and test this by adding the phrase "to eat there...":
- Deploy using Cloud Foundry
cf push
gives:
FAILED Could not find service <Watson_service> to bind to <IBM_Cloud_application>
If you name your service wcsi-conversation-service
, this should work.
When you use cf push
, it is trying to bind to the services listed in the manifest.yml
.
So, there are 2 ways you can get this to work:
- Change the names of your IBM Cloud services to match the names in the manifest.
- Change the names in the manifest to match the names of your IBM Cloud services.
NOTE: The
Deploy to IBM Cloud
button solves this issue by creating the services on the fly (with the correct names).
This code pattern is licensed under the Apache Software License, Version 2. Separate third party code objects invoked within this code pattern are licensed by their respective providers pursuant to their own separate licenses. Contributions are subject to the Developer Certificate of Origin, Version 1.1 (DCO) and the Apache Software License, Version 2.
Apache Software License (ASL) FAQ
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