Skip to content

vodlogic/alexa-voiceops

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

VoiceOps with Alexa - Start/Stop EC2 Instances on AWS

Introduction

This sample project demonstrates how to use Amazon Alexa to do various tasks on your AWS Account using your Amazon Echo (dot).

This example and code is brought to you by msales - convert everything

Lambda Function

The python-based Lambda function is organized into intent handler which represent the different functions. These handlers are called using some boilerplate code. The first part of the template will route the incoming request based on its type. The type will either be LaunchRequest, IntentRequest, or SessionEndedRequest and this function will be triggered whenever we interact with Alexa. The event parameter will have all the information we need about the given request.

AWS Lambda Python Boiler Plate for Custom Alexa Skills

The following code shows a minimal boilerplate to create your lambda-based Alexa skill:

def lambda_handler(event, context):
    """
    Route the incoming request based on type (LaunchRequest, IntentRequest,
    etc.) The JSON body of the request is provided in the event parameter.
    
    :param event: 
    :param context: 
    :return: 
    """
	
    if event['session']['new']:
        on_session_started({'requestId': event['request']['requestId']}, event['session'])

    if event['request']['type'] == "LaunchRequest":
        return on_launch(event['request'], event['session'])

    elif event['request']['type'] == "IntentRequest":
        return on_intent(event['request'], event['session'])

    elif event['request']['type'] == "SessionEndedRequest":
        return on_session_ended(event['request'], event['session'])
	
	
def on_session_started(session_started_request, session):
    """
    Called when the session starts
    
    :param session_started_request: 
    :param session: 
    :return: 
    """

    print("on_session_started requestId=" + session_started_request['requestId']
          + ", sessionId=" + session['sessionId'])
		  

def on_launch(launch_request, session):
    """
    Called when the user launches the skill without specifying what they want
    
    :param launch_request: 
    :param session: 
    :return: 
    """
	
	...
	
	
def on_intent(intent_request, session):
    """
    Called when the user specifies an intent for this skill 
    
    :param intent_request: 
    :param session: 
    :return: 
    """

    print("on_intent requestId=" + intent_request['requestId'] +
          ", sessionId=" + session['sessionId'])

    intent = intent_request['intent']
    intent_name = intent_request['intent']['name']

    # Dispatch to your skill's intent handlers
    if intent_name == "StopTaggedInstances":
        return function_for_handling_the_intent(intent, session)
		
    elif intent_name == "AMAZON.HelpIntent":
        return intent_help_function(intent, session)
		
	elif intent_name == "AMAZON.StopIntent":
		return intent_stop_function(intent, session)
	
    else:
        raise ValueError("Invalid intent")

def on_session_ended(session_ended_request, session):
    """
    Called when the user ends the session.
    Is not called when the skill returns should_end_session=true
    
    :param session_ended_request: 
    :param session: 
    :return: 
    """
    print("on_session_ended requestId=" + session_ended_request['requestId'] +
          ", sessionId=" + session['sessionId'])

	  
def build_speechlet_response(title, output, reprompt_text, should_end_session):
    """
    Build Speechlet Response
    
    :param title: 
    :param output: 
    :param reprompt_text: 
    :param should_end_session: 
    :return: 
    """
    return {
        'outputSpeech': {
            'type': 'PlainText',
            'text': output
        },
        'card': {
            'type': 'Simple',
            'title': 'SessionSpeechlet - ' + title,
            'content': 'SessionSpeechlet - ' + output
        },
        'reprompt': {
            'outputSpeech': {
                'type': 'PlainText',
                'text': reprompt_text
            }
        },
        'shouldEndSession': should_end_session
    }


def build_response(session_attributes, speechlet_response):
    """
    Build the Response
    
    :param session_attributes: 
    :param speechlet_response: 
    :return: 
    """
    return {
        'version': '1.0',
        'sessionAttributes': session_attributes,
        'response': speechlet_response
    }

As you can see every intent will be mapped to a python function call. The response at the end is simply a dictionary that tells Alexa with which text to response and if the session should be ended.

Our Lambda function

The code of the Lambda function for the skill can be found in src/aws_alexa_handler.py. The single function will be explained briefly in the following.

The function contains two constants that are used within the intents:

  • ALEXA_AWS_DEFAULT_TAG: The tag of the EC2 Instances that should be filtered.
  • AWS_DEFAULT_REGION: The default AWS Region which is used within the skill.

StartTaggedInstances

Starts all stopped EC2 instances in the current region containing the tag ALEXA_AWS_DEFAULT_TAG with the value True.

StopTaggedInstances

Stops all started EC2 instances in the current region containing the tag ALEXA_AWS_DEFAULT_TAG with the value True.

GetRunningTaggedInstances

Returns the number of running instances in the current region containing the tag ALEXA_AWS_DEFAULT_TAG with the value True.

SetCurrentRegion

Sets the AWS region of the current session to interact with.

GetCurrentRegion

Returns the current AWS region of the session.

AMAZON.HelpIntent

Returns some help for the VoiceOps Skill.

GetSomeFun

Just a fun output function which simply returns speech only without any further functionality.

How-to setup the Lambda function to be used as an Alexa Skill

Intent Schema

Alexa needs to know what intents your skill should contain. This done by providing a JSON document that describes your intents. Further you are able to define so called slots. Slots are variables with a list of values that can be referenced in the interaction with the user. In our cases we define the AWS_REGION_LIST slot which contains a lit of all supported AWS regions within this skill. Our intent schema can be found in src/intent.json.

Custom Slot Types

As already mentioned slots represent variables with pre-defined values the user can choose to interact with your intents. The values for our slot AWS_REGION_LIST can be found in src/AWS_REGION_LIST.txt.

Sample Utterances

Sample utterances provide Alexa some examples to find the right intent when a user is using your skill. You can use the defined slots within these utterances. In our case we use {Region} to reference a value of our slot AWS_REGION_LIST. Our utterances can be found in src/sample_utterances.txt

So what? Let us tell you how you can test te skill

Since you already have an AWS account ;) you should get an Amazon Developer Account too to be able to create your skill. Please click after the loging on "Get Started" at the Alexa Skills Kit.

Alexa Skill Welcome Page

On the Alexa Skills Kit overview just click "Add a New Skill" to get started. On the following screenshot we already filled all necessary things for our "VoiceOps" Skill. Please an appropriate invocation name which will be used to activate your skill later. The form offers you a link to some help how to choose your right invocation name. We tried "AWS" at the beginning which does not work maybe because it's a brand or reserved name. That is the reason why we have chosen "cloud" as our invocation name.

Skill information

Next you have to configure the interaction model of your skill. As mentioned before a skill contains a JSON-based intent definition, optionally some custom slots with values and some sample utterances.

Interaction model

The next step contains the configuration of your skill. You can setup here some endpoints or the Amazon Resource Names (ARNs) in order to call your lambda function. The ARN of your Lambda function can be found at the right side of the detail overview of your function.

Lambda ARN Location

Just copy the ARN and select the nearest location of your audience - or just you ;). One note to the Lambda function, currently the Alexa Tools Kit Gateway is only supported in the following regions:

  • us-east-1 US East (N. Virginia)
  • eu-west-1 EU (Ireland)

Skill Configuration

Having the skill configured you need to provide Amazon some publishing information - in case you wanna make your skill public available. In our case we filled everything but at the end we just test the skill using the beta test feature.

Publishing Information

Before your gonna be able to test your skill on your Echo using the beta test feature, you have provide some privacy information too. In our case we set everything to "no" since we are not going to collect some data or address people below the age of 13 years.

Privacy and Compliance

Now you will be able to activate the "Beta Test" in order to test your skill on your Echo. Just choose the email of your Account that is setup with your Echo. Your will get an email or simply call the Skill Url directly to add it into your account.

Privacy and Compliance

The skill will then appear in your Skill overview.

Skill Overview

Now lets have some fun with saying "Alexa, start cloud" ;). Feel free to ask Robert Hoppe [email protected] of msales if you have any questions.

Licence / Copyright

The code of this Alexa Skill / AWS Lambda function is brought to you by msales / Robert Hoppe and released und the MIT Licence.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%