Stamplay makes it easy to chain services and deploy to messaging platforms with little to no code. See how Watson Conversation can be quickly integrated into chat platforms such as Facebook Messenger and Slack.

1. Giuliano Iacobelli, Co-founder /
CEO
g@stamplay.com
Easily Deploy your Chat Bot
to Multiple Channels with
Stamplay
Cooking time: 30 mins

2. Chat UX is more natural, dynamic and avoid any
friction opening new accounts
The ideal user engagement channel
Messaging platforms aim to change the way brands communicate with consumers
More than 900 million monthly active users only
on Facebook Messenger
In 2015 messaging apps have been the fastest
growing In the global Top 10 of most used apps 6 are
messaging apps
No need to download yet another app

3. Ingredients
The bot will be available on Cisco Spark and Facebook Messenger will use IBM Watson
Conversation to handle natural language and will be implemented using Stamplay.

5. Create an account on Stamplay
Go to https://editor.stamplay.com/signup and create your account for free

6. Create the project on Stamplay
Once inside, click on the green “+” button in the upper right corner and select Start from Scratch

7. Create the project on Stamplay
Type a name for your project

8. Grab your credentials from Watson Conversation
Enter your Bluemix account get the credentials for the Watson Conversation service

9. Connect IBM Watson Converstion on Stamplay
On Stamplay go to Dashboard > Integrations and search IBM Watson Conversation

10. Copy your Watson Conversation credentials
Copy Username and password and then click “Connect”

11. Copy your Watson Conversation credentials
Go to https://developer.ciscospark.com/apps.html and create a Bot

12. Fill basic info for your bot
Icon URL https://dl.dropboxusercontent.com/u/397182/logo_white_512x512.png

13. Save the Access Token
Once the bot is created you’ll see an Access token, copy it and save it somewhere

14. Connect Cisco Spark Bot on Stamplay
On Stamplay go to Dashboard > Integrations and search Cisco Spark bot

15. Copy your Spark bot token
Copy the Access Token you got before and then click “Connect”

17. Launch the Watson Conversation tool
From your Bluemix account enter the Conversation service and click Launch Tool

18. Import the dialogue model
Click the icon next to “Create” button and upload the dialogue model
https://app.box.com/s/x4j6fb8036lasosl45blyv9ir9s9gluo

19. Dialogue overview: Intents
A set of intents are used to return answers to known questions

20. Dialogue overview: Intents
#when_it_burns intent handles questions like “what night does the man burn?”

21. Dialogue overview: Intents
#when_it_is intent handles questions like “what are the dates for the event?”

22. Dialogue overview: Intents
#where_is_it intent handles questions like “where is the festival located”

23. Dialogue overview: Intents
#what_is_it intent handles questions like “what is the burning man?”

24. The Dialogue model
An Start node of the dialogue tree handles the initial conversation

25. The Dialogue model
Create a root node for each intent that can answer a question (e.g #what_is_it)

26. The Dialogue model
Create a root node for each intent that can answer a question (e.g #where_is_it)

28. Inizializing the integration Flow
Go to Flows and start by selecting the Cisco Spark bot app from the list

29. Configure the event that starts the flow
We’ll start this flow everytime the bot receives a New Direct Message

30. Select the event that starts the flow
Click on continue when you get to the Account tab, we’ve connected this before

31. Adding a steps to your flow
After each step of your workflow you can define the following action by moving your
mouse hover the + icon

32. Add a Contidion step to filter bot messages
Spark triggers this event also when is the bot itself writing so we filter out its messages
with a condition step that checks for the sender email address

33. Checking if the message is sent by the bot
Click on the first dropdown on the left and select personEmail, this will be the property we
use to recognize if is a bot writing (something@sparkbot.io)

34. If the condition is met stop the flow
To run a branch of our flow only when the condition is met let’s add a step that will be
executed IF TRUE.

35. Adding a Stop step
After clicking IF TRUE, select STOP to add a step that will terminate flow execution.

36. Saving the Stop step
Save the new step without any additional configuration and you’re good to go

37. Retrieve message content
The New Message trigger of Spark only pass an ID of the message received without
content. To read the actual message we add the Get Message action.

38. Passing data from step to step
To use a Message Id from a previous step. Click on the “{}” button to see the steps
available to fetch data from and select New Direct Message.

39. Passing data from step to step
Click on the id attribute of the message JSON representation sent by Spark

40. Passing data from step to step
Stamplay will add a parameter inside the input field and will automatically replace it with
the actual value of the id of the New Direct Message that will trigger this flow

41. Passing the message to Watson
Now that we have the message that has been type by the user we can pass it to Watson,
add a new Action and select IBM Watson Conversation

42. Passing the message to Watson
Select the only action available, Conversation

43. Passing the message to Watson
Fill the parameters by passing the Workspace ID and the text. Workspace Id is available
on the Watson Conversation tool home, text will be passed by the previous step.

44. Getting the Workspace Id
On your account of the Watson Conversation tool you can find the workspace Id
by entering the Workspace details

45. Passing the message to Watson
Select the text attribute from the JSON representation passed by the Get Message action

46. Passing the message to Watson
Stamplay will add a parameter inside the input field and will automatically replace it with
the actual value of the text of the Get Message action

47. Returning the answer to the User
The last step of our flow is to return the answer computed by IBM Watson Conversation.
Add one more action and select Cisco Spark Bot Post Message action

48. Returning the answer to the User
The Room dropdown shows us all the room where the bot is currently available. Click on
Type a custom value to be able to pass here a dynamic value

49. Returning the answer to the User
Once che cursor is blinking, click on the “{}” button to grab a valid Room Id from the New
Direct Message step of this flow

50. Returning the answer to the User
Select the roomId attribute from the JSON representation

51. Returning the answer to the User
Text field will be filled by passing the result returned by IBM Watson Conversation, once
again click the “{}” button to open the dropdown with the previous step of the flow

52. Returning the answer to the User
After selecting IBM Watson Conversation select the text attribute nested under output

53. You’re all set
The final flow should look like this, make sure it’s on by checking the switch

55. The Data Model

56. Connecting your Facebook Page

57. Connecting your Facebook Page

58. Creating the integration Flow

59. What starts the flow (trigger)

60. Configuring Webhook URL on Facebook

61. Configuring Webhook URL on Facebook

62. Configuring Webhook URL on Facebook

63. Lookup for existing conversations

64. If conversation not found..

65. ..get info about user profile..

66. ..process user message with Watson..

67. ..save new conversation record..

68. .. and reply to user on Facebook Messenger

69. Giuliano Iacobelli
g@stamplay.com
Thanks!