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Framework to easily test your Alexa skills functionally by creating a conversation with your skill.

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Alexa Conversation: Tests for your Alexa skills

Framework to easily test your Alexa skills functionally by creating a conversation with your skill. This framework makes it easy to test your Alexa skill's outputs for a given user input (intent) in different ways. This library is build on top of mocha, so you will need mocha installed in order to run the tests written with this framework,

Install

Install alexa-conversation

npm install --save-dev alexa-conversation

Install mocha (if you don't have it already)

npm install -g mocha (you can install it locally too, up to you)

How to use

In your functional test files, include the alexa-conversation package

const conversation = require('alexa-conversation');
const app = require('../../index.js'); // your Alexa skill's main file.

const opts = { // those will be used to generate the requests to your skill
  name: 'Test Conversation',
  appId: 'your-app-id',
  // Either provide your app (app.handler must exist)...
  app: app,
  // ...or pass the handler in directly (for example, if you have a custom handler name)
  handler: app.customHandlerName
  // Other optional parameters. See readme.md
};

// initialize the conversation
conversation(opts)
  .userSays('LaunchIntent') // trigger the first Intent
    .plainResponse // this gives you access to the non-ssml response
	    // asserts that response and reprompt are equal to the given text
      .shouldEqual('Welcome back', 'This is the reprompt')
	    // assert not Equals
      .shouldNotEqual('Wrong answer', 'Wrong reprompt')
 	    // assert that repsonse contains the text
      .shouldContain('Welcome')
  	  // assert that the response matches the given Regular Expression
      .shouldMatch(/Welcome(.*)back/)
	    // fuzzy match, not recommended for production use. See readme.md for more details
      .shouldApproximate('This is an approximate match')
  .userSays('IntentWhichRequiresSlots', {slotOne: 'slotValue'}) // next interaction, this time with a slot.
    .ssmlResponse // access the SSML response
      .shouldMatch(/<say>(Hello|Bye)</say>/)
      .shouldNotMatch(/<say>Wrong answer</say>/)
  .userSays('IntentWhichRequiresSlots', {slotOne: {value: 'slotValue', resolutions: {}}}) // you can  also pass a object as a slotValue.
  .end(); // this will actually run the conversation defined above

Again, this module requires mocha as a peerDependency (make sure you have it installed either globally or locally: run npm install mocha -g). After that just run:

mocha {path/to/your/test.js}

API

conversation(opts: Object)

Initializes a new conversation and returns itself.

Non-optional parameters:

  • name String: The name you want this conversation to have (useful for the test reports)
  • app Object: Your Alexa skill main app object (normally what is returned from your index.js file). It either needs to expose app.handler, or you can pass in a handler instead (see below)
  • handler Function: If your app doesn't expose a handler method or you want to use a custom handler, you can pass the handler in directly - this will take precedence over app.handler
  • appId String: Your Alexa Skill Id in order to build requests that will be accepted by your skill.

Optional parameters:

  • sessionId String: Will default to SessionId.ee2e2123-75dc-4b32-bf87-8633ba72c294 if not provided.
  • fixSpaces Boolean: Defaults to false. If set to true, it will remove any unnecessary spaces form the actual responses before performing any assertions against them. Example: double spaces, spaces before comma or other punctuation marks, etc. This can be useful depending on how you build your reponses.
  • userId String: Will default to amzn1.ask.account.AHEYQEFEHVSPRHPZS4ZKSLDADKC62MMFTEC7MVZ636U56XIFWCFUAJ2Q2RJE47PNDHDBEEMMDTEQXWFSK3OPALF4G2D2QAJW4SDMEI5DCULK5G4R32T76G5SZIWDMJ2ZZQ37UYH2BIXBQ3GIGEBIRW4M4YV5QOQG3JXHB73CTH6AAPYZBOIQE5N3IKUETT54HMTRUX2EILTFGWQ if not provided.
  • accessToken String: Will default to 0b42d14150e71fb356f2abc42f5bc261dd18573a86a84aa5d7a74592b505a0b7 if not provided.
  • requestId String: Will default to EdwRequestId.33ac9138-640f-4e6e-ab71-b9619b2c2210 if not provided.
  • locale String: Will default to en-US if not provided.

userSays(intentName: String, slots: Object)

Specifies what intent to trigger and the optional slots that it needs. The slots object takes key-value pairs as parameters. The value of pair accepts String or Slot Object.

ssmlResponse

Use this member to add checks to the last SSML response and reprompt.

The response is taken form the JSON field: response.outputSpeech.ssml and the reprompt form the response.reprompt.outputSpeech.ssml

plainResponse

Use this member to add checks to the last plain text response and reprompt. Plain text is the same as the ssmlResponse without the markup tags.

shouldMatch(expectedSpeechRegex: Regex, expectedRepromptRegex: Regex)

Will assert that expectedSpeechRegex and expectedRepromptRegex Strings match (String.match()) the responses from plainResponse or ssmlResponse.

This is useful for implementing powerful checks like cases where several responses are valid (i.e. dates, locations, or dynamic conditions like weather, etc.)

shouldNotMatch(expectedSpeechRegex: Regex, expectedRepromptRegex: Regex)

Will assert that expectedSpeechRegex and expectedRepromptRegex Strings do not match (!String.match()) the responses from plainResponse or ssmlResponse.

This is useful for implementing powerful checks like cases where several responses are valid (i.e. dates, locations, or dynamic conditions like weather, etc.)

shouldApproximate(expectedSpeech: String, expectedReprompt: String, minFuzzyScore: float)

Will assert that expectedSpeech and expectedReprompt Strings are approximately the same as the ones in ssmlResponse or plainResponse using fuzzy string matching. The default minimum fuzzy score to pass the test is 0.85, you can override it by passing a new value to the call as the 3rd parameter (accepts values from [0...1]).

This check is useful if you want to assert actual and expected are the same but discarding small differences like spaces or punctuation marks like full stops or question marks.

Learn more about the fuzzy matcher used: fuzzyset.js

shouldNotApproximate(expectedSpeech: String, expectedReprompt: String, minFuzzyScore: float)

Will assert that expectedSpeech and expectedReprompt Strings are approximately NOT the same as the ones in ssmlResponse or plainResponse using fuzzy string matching. The default minimum fuzzy score to pass the test is 0.85, you can override it by passing a new value to the call as the 3rd parameter (accepts values from [0...1]).

This check is useful if you want to assert actual and expected are the same but discarding small differences like spaces or punctuation marks like full stops or question marks.

Learn more about the fuzzy matcher used: fuzzyset.js

shouldEqual(expectedSpeech: String, expectedReprompt: String)

Will assert that expectedSpeech and expectedReprompt Strings equal the ones in ssmlResponse or plainResponse.

shouldContain(expectedSpeech: String, expectedReprompt: String)

Will assert that expectedSpeech and expectedReprompt Strings are contained the ones in ssmlResponse or plainResponse.

shouldNotEqual(expectedSpeech: String, expectedReprompt: String)

Will assert that expectedSpeech and expectedReprompt Strings are not equal to the ones in ssmlResponse or plainResponse.

shouldNotContain(expectedSpeech: String, expectedReprompt: String)

Will assert that expectedSpeech and expectedReprompt Strings are not contained the ones in ssmlResponse or plainResponse.

Debugging & Troubleshooting

To start mocha in debug mode:

./node_modules/.bin/mocha debug {path/to/test/file}