In this repo you'll find the resources to continue the learning and implementation of Alexa Skill you learned in the session by ASI.
- STEP BY STEP Points to get you started Cake Walk skill.
- Hello World Skill code (python + Js)
- Barnacle Skill Code (certified and published)
To get started, log into the Alexa developer console with your Amazon Developer account. If you do not have an account, click here to create one.
a. Click Create Skill on the right-hand side of the console. A new page displays.
b. In the Skill name field, enter Cake Walk.
c. Leave the Default language set to English (US).
d. You are building a custom skill. Under Choose a model to add to your skill, select Custom.
Skills have a front end and backend. The front end is where you map utterances (what the user says) into an intent (the desired action). You must decide how to handle the user’s intent in the backend. Host the skill yourself using an function or HTTPS endpoint, or choose Alexa to host the skill for you. There are limits to the AWS Free Tier, so if your skill goes viral, you may want to move to the self-hosted option. For this course, choose Alexa-Hosted (Python).
e. Under Choose a method to host your skill’s backend resources, select Alexa-Hosted (Python).
f. At the top of the page, click Create skill.
It takes a few moments for AWS to provision resources for your skill. When this process completes, move to the next section.
Note: When you exit and return to the Alexa developer console, find your skill on the Skills tab, in the Alexa Skills list. Click Edit to continue working on your skill.
The first thing a user will want to do with the skill is open it. The intent of opening the skill is built into the experience, so you don’t need to define this intent in your front end.
However, you need to respond to the intent in your backend. In this step, you will update your backend code to greet the user when they open the skill.
a. Open the Cake Walk skill in the Alexa developer console. Click the Code tab. The code editor opens the lambda_function.py file.
To define how your skill responds to a JSON request, you will define a handler for each intent.
There are two pieces to a handler:
- can_handle() function
- handle() function The can_handle() function is where you define what requests the handler responds to. The handle() function returns a response to the user. If your skill receives a request, the can_handle() function within each handler determines whether or not that handler can service the request. In this case, the user wants to launch the skill, which is a LaunchRequest. Therefore, the can_handle() function within the LaunchRequestHandler will let the SDK know it can fulfill the request. In computer terms, the can_handle returns true to confirm it can do the work.
Tip: In the code editor, search for text by pressing CTRL+F (Command+F on a Mac). A search window opens. This is helpful for searching for pieces of code within the editor.
What should happen when a user launches the Cake Walk skill? In this case, you want the skill to simply confirm that the user opened it by saying, "Hello! Welcome to Cake Walk. That was a piece of cake! Bye!" Within the LaunchRequestHandler object, find the handle() function. This function uses the responseBuilder function to compose and return the response to the user.
Within the handle() function, find the line that begins speak_output =. This variable contains the string of words the skill should say back to the user when they launch the skill. Let’s change what it says to make sense for this skill.
b. Within the LaunchRequestHandler object, find the handle() function, and the line that begins speak_output =. Replace that line with the following:
speak_output = "Hello! Welcome to cake walk. That was a piece of cake! Bye!"If you are not familiar with programming, a string is encapsulated in single or double quotation marks. To change a string’s text, replace the text within the quotation marks.
When you replace existing text or add new text to the code, blank lines may be introduced just before or after the text. Blank lines will not impact the code, but you may remove them.
You may also notice your lines of code are not indented the same as code snippets in this course. This will also not impact the code, but you can use the TAB key to indent code if you would like.
Within the LaunchRequestHandler, on the line under the speech text you just replaced, look for handlerInput.responseBuilder. This piece of the SDK will help build the response to the user.
On the next line, look for .speak(speak_output). Note the speak_output variable, which you defined earlier. Calling the .speak() function tells responseBuilder to speak the value of speak_output to the user.
Next, look for the .ask() function within responseBuilder. (Be sure you are looking in the LaunchRequestHandler, within the handle() function.) If the skill was supposed to listen for the user’s response, you would use this. In this case, you want the skill to speak and then exit. Therefore, let’s omit this line of code for now.
c. Within the LaunchRequestHandler, in the handle() function, find the line that begins .ask(). Add a # at the beginning of the line. This turns the line into a comment, meaning the line is ignored when the code runs.
d. Next, look for the .response() function just below the line you commented out in the LaunchRequestHandler. This converts the responseBuilder’s work into the response that the skill will return. Remember the line that started with return? Think of it like hitting the Send button—it sends the response.
Your LaunchRequestHandler should now look like:
class LaunchRequestHandler(AbstractRequestHandler):
"""Handler for Skill Launch."""
def can_handle(self, handler_input):
# type: (HandlerInput) -> bool
return ask_utils.is_request_type("LaunchRequest")(handler_input)
def handle(self, handler_input):
# type: (HandlerInput) -> Response
speak_output = "Hello! Welcome to cake walk. That was a piece of cake! Bye!"
return (
handler_input.response_builder
.speak(speak_output)
#.ask(speak_output)
.response
)You have built the code that will handle a LaunchRequest for this skill. Before doing anything else, save your changes and deploy the code.
e. Click Save.
f. Click Deploy.
Now it is time to test the skill. Start by activating the test simulator.
a. Click the Test tab. The test simulator opens.
An alert may appear requesting to use your computer’s microphone. Click Allow to enable testing the skill with your voice, just like if you were talking to an Alexa-enabled device.
b. From the drop-down menu at the top left of the page, select Development.
There are two ways to test your skill in the console. With the first method, type what the user would say into the box at the top left. Be precise—spelling matters! Alternately, speak to the skill by clicking and holding the microphone icon and speaking.
So far, the skill has one intent: LaunchRequest. This function responds to the user when they ask Alexa to open or launch the skill. The user will say, “Alexa, open Cake Walk.” Cake Walk is the name of your skill and was automatically set as the invocation name for the skill. You can change the invocation name, but let’s leave it as is for this exercise.
c. Test the skill. Type open Cake Walk (not case sensitive) into the box at the top left and press ENTER, or click and hold the microphone icon and say, “Open Cake Walk.”
When testing your skill in the Alexa developer console, you don’t need to provide the wake word (usually “Alexa”). Typing or saying, “Open Cake Walk” is fine. When testing on an Alexa-enabled device, you need the wake word: “Alexa, open Cake Walk.”
When you open the skill, does it say, "Hello! Welcome to Cake Walk. That was a piece of cake! Bye!"? If so, congratulations! You have laid the groundwork for the skill. You will be building new skills with compelling conversational voice experiences in no time.
If your skill isn’t working or you’re getting some kind of syntax error, download the code sample in Cake Walk Folder. Then, go to the Code tab in the Alexa developer console and copy and paste the code into the lambda_function.py file. Be sure to save and deploy the code before testing it.