
Speak the Command, Execute the Lambda
Discover how to trigger AWS Lambda with Amazon Alexa for seamless voice-controlled automation and smart solutions.
- Choose "Author from scratch."
- Enter a function name (e.g.,
WeatherCheckerLambda
). - Choose a runtime (e.g., Python 3.9 or Node.js 18.x).
- Set up an execution role with basic Lambda permissions. If your function needs to access other AWS services, ensure the role has the appropriate permissions.
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import json
def lambda_handler(event, context):
# Sample response to be returned by Alexa
return {
'version': '1.0',
'response': {
'outputSpeech': {
'type': 'PlainText',
'text': 'The weather today is sunny with a high of 25 degrees.',
},
'shouldEndSession': True
}
}
- Set up environment variables and resource limits according to your needs.
- Test the function using the AWS Lambda console's built-in test feature. This ensures that your function executes as expected before integrating with Alexa.
- Choose “Create Skill” and select the “Custom” skill type.
- Set your skill name (e.g.,
Weather Checker
). - Select
other
for theexperience
type. - Choose a template: Start from scratch or use the provided templates for a custom experience.
- Hit
Create Skill
- Set an invocation name for your skill (e.g.,
weather checker
). - This is what users will say to start the interaction (e.g., “Alexa, ask weather checker...”).
- Hit
Build Skill
- Intents represent actions users want to perform. For example, create an intent called
GetWeatherIntent
. - Under the
GetWeatherIntent
, add sample utterances like:- "What is the weather today?"
- "Tell me the weather."
- "Give me today's weather forecast."
- In the Alexa Developer Console, navigate to the Endpoint section.
- Select AWS Lambda ARN as the service endpoint type.
- Paste the ARN of the Lambda function you created earlier.
- Ensure your Lambda function’s IAM role has the necessary permissions to execute and return data.
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import json
def lambda_handler(event, context):
# Extracting intent name from Alexa's request
intent_name = event['request']['intent']['name']
if intent_name == "GetWeatherIntent":
# Build response
return {
'version': '1.0',
'response': {
'outputSpeech': {
'type': 'PlainText',
'text': 'The weather today is sunny with a high of 25 degrees.',
},
'shouldEndSession': True
}
}
else:
return {
'version': '1.0',
'response': {
'outputSpeech': {
'type': 'PlainText',
'text': 'I am not sure how to help with that.',
},
'shouldEndSession': True
}
}
- Use the AWS Lambda console to trigger the function manually with test events that simulate Alexa requests.
- Enable detailed logging in CloudWatch to troubleshoot any issues and ensure your function handles requests correctly.
- Go to the Alexa Developer Console and open your skill.
- Use the Test tab: Here, you can simulate voice commands using the Alexa Simulator. Type or speak phrases like “Alexa, ask weather checker what the weather is today.”
- Review responses: Ensure Alexa returns the expected responses, and debug if necessary.
- Enable your skill on an Alexa-enabled device, such as an Amazon Echo.
- Speak the invocation name and command: For example, say “Alexa, ask weather checker what the weather is today.”
- Refine based on feedback: Adjust your Lambda function and skill interaction model based on real-world testing.
- Publish your skill: Once satisfied with the functionality, you can submit your skill for certification through the Alexa Developer Console.
- Private or Public: Choose whether to keep the skill private for personal use or make it available to the public.
- Use AWS CloudWatch: Monitor logs to track Lambda execution, identify errors, and optimize performance.
- Skill Analytics: In the Alexa Developer Console, you can also access analytics to see how users interact with your skill.