In this module, you will build the Alexa Skill in the Amazon Developer console and test the *intent* programmed. The skill, locally running on your laptop, will *publish* a message to CloudMQTT to turn on, or off, the light (LED).
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In this module, you will build the Alexa Skill in the Amazon Developer console and test the intent programmed. The skill, locally running on your laptop, will publish a message to CloudMQTT to turn on, or off, the light (LED).
Upon completion you will have created an Alexa skill and demonstrated that it can execute the application logic to publish messages to MQTT and control your MCU.
This module covers:
From a new browser, navigate to the Amazon Developer Console, sign-in if needed, then click on Alexa. From the top menu, mouse Your Alexa Consoles and click on Skills. This takes you to the main list of skills, if any exist.
From here, click on Create Skill and complete the following:
Smart Devicethen click on Create Skill. On the Choose a template page, make sure Start from scratch is selected and click Choose. This will take you to the main development page. You will complete the 2nd through 4th sections on the right, under Skill builder checklist. the first section is complete, so click on 2. Intents, Samples, and Slots. Under Create custom intent, enter
led_onto turn on the led to turn on the light to turn on the lamp lamp on light on turn on the lamp turn on the light turn on the led
These utterances help train the machine learning model for your skill. With these entered for the led_on intent, click the add button to the left to create a new intent for led_off.
Again, create a custom intent named
led_offto turn off the led to turn off the light to turn off the lamp lamp off light off turn off the lamp turn off the light turn off the led
💡 You can select all lines above, click on Bulk Edit and paste in to the text box instead of copy/pasting each line.
At this point, click on Save Model near the top center. Next the endpoint, where the Skill with communicate with to invoke application logic, needs to be configured and running. Leave the browser open here while you complete the other work.
The skill needs something execute when an intent is matched--that will be your local python code. In order for it to be accessible from the Internet, ngrok is used to broker an HTTPS connection from Amazon Alexa to your locally running code.
In VSCode, open the
~/tm_iot/workshop-ess-alexa-controlled-device/code/mod_4-alexa_skill/skill.py# Enter your CloudMQTT endpoint and credentials MQTT_HOST = 'FQDN' MQTT_WEBSOCKET_PORT = portnun MQTT_USERNAME = 'username' MQTT_PASSWORD = 'password'
Open a terminal window, change to the
mod_4-alexa_skillpython3 skill.py * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit) * Restarting with stat * Debugger is active! * Debugger PIN: 256-577-502
Next, open a second window (it doesn't need to be in any particular directory) to start ngrok and use the port number above (5000) as the parameter:
ngrok http 5000
This will start the ngrok server, clear the screen and display something similar. Note the last forwarding line (https) and copy everything through the ngrok.io portion.
With both ngrok acting as the reverse proxy and your skill running locally, go back to the Alexa Developer page and click on Endpoint from the left menu (you may need to scroll down to see it). Select the HTTPS option and complete the following:
Then click Save Endpoints from above. Then select Build (next to Test) and verify that the skill have green check marks for 1 through 4 on the right hand side. At this point, click on Test and toggle the Test is disabled for this skill. to enabled.
The moment of truth. At this point the skill is active and ready to receive inquiries. In the Alexa Simulator box, click into the Type or click and hold the mic and enter the following:
turn on led
If all is setup and working, you should see the following in the test console:
The left pane shows the command issues and the response. Also, monitoring CloudMQTT and looking at the MCU, it took should have turned on the LED. Now try turning off the LED. Play around with the test console and try different utterances.
In this module you: