Alexa Skill using OpenWhisk, IBM Watson Assistant and Weather Channel Data
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Create an Alexa skill using Watson Assistant and OpenWhisk

Watson Conversation is now Watson Assistant. Although some images in this code pattern may show the service as Watson Conversation, the steps and processes will still work.

In this Code Pattern, we will create an Alexa skill using Watson Assistant via the Apache OpenWhisk serverless framework. Alexa is the voice service behind products like the Amazon Echo. IBM Cloud Functions (based on Apache OpenWhisk) will be used to integrate Alexa with Watson Assistant. Credit goes to Niklas Heidloff for creating the original project.

An example conversation is included to demonstrate how to pass context between different intents. You can also use this Code Pattern to try out a conversation from the Bot Asset Exchange (BAE).

When the reader has completed this Code Pattern, they will understand how to:

  • Create an OpenWhisk action in the IBM Cloud Functions serverless platform
  • Use Redis to store a session's conversation context across events
  • Import a conversation from the Bot Asset Exchange (BAE) or a JSON file
  • Invoke a conversation with Watson using Node.js
  • Use the Weather Channel Data service to lookup locations and forecasts
  • Create an Alexa skill to reach tens of millions of customers


  1. User says "Alexa, ask Watson...".
  2. Alexa invokes IBM Cloud Functions with input text.
  3. The action gets the conversation context from Redis (if any).
  4. The action gets a response from Watson Assistant.
  5. The Weather Company Data service provides the forecast (when applicable).
  6. The response context is stored in Redis.
  7. The response text is sent back to Alexa.
  8. Alexa replies to the user.

Included components

  • Watson Assistant: Create a chatbot with a program that conducts a conversation via auditory or textual methods.
  • OpenWhisk: Execute code on demand in a highly scalable, serverless environment.
  • Redis: An open-source, in-memory data structure store, used as a database, cache and message broker.

Featured technologies

  • Serverless: An event-action platform that allows you to execute code in response to an event.
  • Databases: Repository for storing and managing collections of data.
  • Node.js: An open-source JavaScript run-time environment for executing server-side JavaScript code.

Watch the Video


Run locally

  1. Clone the repo
  2. Create a Watson Assistant workspace
  3. Create a Compose for Redis service
  4. Create a Weather Company Data service
  5. Configure credentials
  6. Create the OpenWhisk action
  7. Create an Alexa skill
  8. Talk to it

1. Clone the repo

Clone the alexa-skill-watson-conversation repo locally and cd to the local repo (for commands in later steps). In a terminal, run:

$ git clone
$ cd alexa-skill-watson-conversation

2. Create a Watson Assistant workspace

Sign up for IBM Cloud if you don't have an IBM Cloud account yet.

Use one or both of these options (with or without BAE) to setup a Assistant workspace.

Using Bot Asset Exchange (BAE)

If you are using BAE, click on a Deploy this bot button to automatically create your Assistant service and import your workspace. The service will be named Bot Asset Exchange Workspaces and can hold up to 5 selected workspaces.

Using the provided workspace.json file

Create the service by following this link and hitting Create:

Import the Assistant workspace.json:

  • Find the Assistant service in your IBM Cloud Dashboard.
  • Click on the service and then click on Launch tool.
  • Go to the Workspaces tab.
  • Click on the Import workspace icon.
  • Click Choose a file, go to your cloned repo dir, and Open the workspace.json file in data/conversation/workspaces/workspace.json.
  • Select Everything and click Import.

3. Create a Compose for Redis service

NOTE: The code currently requires you to disable TLS.

  1. Follow this link: Compose for Redis
  2. Use the TLS Enabled pull-down to select False
  3. Hit the Create button

4. Create a Weather Company Data service

If you are using the provided workspace.json, use Weather Company Data to provide weather responses.

Follow this link and hit Create:

5. Configure credentials

The default runtime parameters need to be set for the action. These can be set on the command-line or via the IBM Cloud UI. Here we've provided a params.sample file for you to copy and use with the -param-file .params option (which is used in the instructions below).

Copy the params.sample to .params.

$ cp params.sample .params

Edit the .params file and add the required settings.


  "CONVERSATION_USERNAME": "<add_assistant_username>",
  "CONVERSATION_PASSWORD": "<add_assistant_password>",
  "WORKSPACE_ID": "<add_assistant_workspace_id>",
  "REDIS_URI": "<add_redis_uri>",
  "WEATHER_URL": "<add_weather_url>"
  • If the service credentials from IBM Watson Assistant contains username/password based credentials as shown in the diagram below, populate the values for username, password and workspace_id and other fields and replace the content .params file with the populated JSON from below.

  "CONVERSATION_USERNAME": "<add_assistant_username>",
  "CONVERSATION_PASSWORD": "<add_assistant_password>",
  "WORKSPACE_ID": "<add_assistant_workspace_id>",
  "REDIS_URI": "<add_redis_uri>",
  "WEATHER_URL": "<add_weather_url>"
  • If the service credentials from IBM Watson Assistant are IAM based as shown in the diagram below, populate the values for IAM apikey, url, workspace_id and other fields and replace the content of .params file with the populated JSON from below.

  "CONVERSATION_IAM_APIKEY": "<add_assistant_apikey>",
  "CONVERSATION_IAM_URL": "<add_assistant_url>",
  "WORKSPACE_ID": "<add_assistant_workspace_id>",
  "REDIS_URI": "<add_redis_uri>",
  "WEATHER_URL": "<add_weather_url>"

How to find the credentials and workspace ID:

The credentials for IBM Cloud services (Assistant, Compose for Redis, and Weather Company Data), can be found in the IBM Cloud UI.

  • Go to your IBM Cloud Dashboard.
  • Find each service in the Cloud Foundry Services list.
  • Click on the service name.
  • Click on Service credentials in the sidebar.
  • If there are no credentials listed, click the New credential button (some services will create one by default).
  • Click on View credentials to see your credentials.
  • Collect the username, password, uri, and url as needed to fill out the .params file.

To find the WORKSPACE_ID for Watson Assistant:

  • Go to your IBM Cloud Dashboard.
  • Click on your Assistant service in the Cloud Foundry Services list.
  • Click on Manage in the sidebar.
  • Click on the Launch tool button.
  • Click on the Workspaces tab.
  • Find the card for the workspace you would like to use. Look for Alexa Sample, if you uploaded workspace.json. The name will vary if you used BAE.
  • Click on the three dots in the upper right-hand corner of the card and select View details.
  • Copy the Workspace ID GUID.

6. Create the OpenWhisk action

Run the following to install the OpenWhisk bindings for IBM Cloud:

bx plugin install Cloud-Functions -r Bluemix

Use bx login to initially login or to change your target:

bx login -a <API endpoint> -o <Organization> -s <Space>

Run the following command to update your OpenWhisk bindings if they are already installed:

bx wsk package refresh

Run the following to test OpenWhisk on IBM Cloud:

bx wsk action invoke /whisk.system/utils/echo -p message hello --result

Create the OpenWhisk action

Run these commands to gather Node.js requirements, zip the source files, and upload the zipped files to create a raw HTTP web action in OpenWhisk.

Note: You can use the same commands to update the action if you modify the code or the .params.

npm install
zip -r main.js package* node_modules
bx wsk action update alexa-watson --kind nodejs:6 --web raw --param-file .params

Determine your IBM Cloud endpoint:

To find this URL, navigate to IBM Cloud Functions - Actions, click on your alexa-watson action and use the sidebar to navigate to Endpoints. The Web Action URL ends with .json.

7. Create an Alexa skill

Sign up for an Amazon Developer Portal account here.

Go to and click the Create Skill button.

Provide a name and hit Next.

Use the Select button to create a Custom skill and hit the Create Skill button.

Provide an invocation name:

Add a custom slot type:

  • In the left sidebar menu, click on Slot Types (#) and hit + Add.

  • Use the name BAG_OF_WORDS and hit the Create custom slot type button.

  • Now BAG_OF_WORDS needs a slot value. Just enter Hello World and hit the plus sign so that it has a slot value.

Add a custom intent type:

  • In the left sidebar menu, click on Intents (#) and hit + Add.

  • Use the name EveryThingIntent and hit the Create custom intent button.
  • Add {EveryThingSlot} under Sample Utterances. Use the plus sign to create the EveryThingSlot.

  • Scroll down to Intent Slots (#)
  • Use the Select a slot type pulldown to give EveryThingSlot the slot type BAG_OF_WORDS.

Click on Save Model and then Build Model.

Configure the endpoint:

  • Click on Endpoint in the sidebar.
  • Select HTTPS as the Service Endpoint Type.
  • For the Default Region enter the HTTPS service endpoint which is the URL of your OpenWhisk Web Action from step 6.
  • Use the pull-down to select My development endpoint is a sub-domain of a domain that has a wildcard certificate from a certificate authority.
  • Click the Save Endpoints button!

8. Talk to it

Use the Test tab in the Amazon developer console.

Use the slider to enable your skill for testing. You can type or talk and test the skill in the test UI.

Once enabled, you can run the sample via Alexa enabled devices, or the Echo simulator.

You can invite others to test it with the beta test feature. In order to be eligible for beta test, you must fill out most of the publishing information.

You probably shouldn't publish this example, but you are now ready to create and publish your own Alexa skill.

Sample output

Here is a sample conversation flow using the provided conversation workspace.json:

The sample has been implemented via the slots filling functionality in Watson Assistant. The screenshot shows how the entity (slot) 'location' is defined as mandatory and how the value is stored in a context variable.


The next screenshot shows how the location is automatically used in the next 'weather' intent.



Use the IBM Cloud UI to monitor logs, or use this command to show the latest activation log:

bx wsk activation list -l1 | tail -n1 | cut -d ' ' -f1 | xargs bx wsk activation logs
  • Invoke from command line

    Use these commands to invoke the action (named alexa-watson in the example) without any input, then check the latest logs. Expect an error ("Must be called from Alexa").

    bx wsk action invoke alexa-watson -bvd
    bx wsk activation list -l1 | tail -n1 | cut -d ' ' -f1 | xargs bx wsk activation logs


Learn more

  • Artificial Intelligence Code Patterns: Enjoyed this Code Pattern? Check out our other AI Code Patterns.
  • AI and Data Code Pattern Playlist: Bookmark our playlist with all of our Code Pattern videos
  • With Watson: Want to take your Watson app to the next level? Looking to utilize Watson Brand assets? Join the With Watson program to leverage exclusive brand, marketing, and tech resources to amplify and accelerate your Watson embedded commercial solution.


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