@talkyjs/core v1.1.0

@talkyjs/core

Simply Alexa skill framework with ask-sdk.

Getting started

Install

$ npm i -S @talkyjs/core

Create lambda handler

import { SkillFactory } from '@talkyjs/core'

export const handler = SkillFactory.launch()
.addRequestHandlers({
    canHandle(input) {
        return input.requestEnvelope.request.type === 'LaunchRequest'
    },
    handle(input) {
        return input.responseBuilder.speak('Hello').getResponse()
    }
})
.createLambdaHandler()

Skill Configuration

We can easy to set up a several skill configuration.

import { SkillFactory, TalkyJSSkillConfig } from '@talkyjs/core'

const config: TalkyJSSkillConfig = {
    stage: 'production',                  // [Optional] Skill Stage
    logLevel: 'error',                    // [Optional] Log level
    database: {                           // [Optional] Database configuration
        type: 's3',                       // [Optional] Database type (none / s3 / dynamodb)
        tableName: 'example-bucket-name', // [Optional] Database table name
        s3PathPrefix: 'path-prefix'       // [Optional] [Only S3] S3 path prefix
    },
    apiClient: {                            // SMAPI and Alexa API Client configuration
        useDefault: true,                   // Use DefaultApiClient
        // client: new DefaultApiClient()   // If you have own ApiClient, put here
    },
    skillId: 'ask.your.skill.id',         // [Optional] Skill ID
    errorHandler: {                       // [Optional] error handler configurations
        usePreset: true,                  // [Optional] Use preset error handler
        sentry: {                         // [Optional] Error tracker configuration (sentry)
            dsn: process.env.SENTRY.DSN   // [Optional] Sentry dsn
        }
    }
}

export const handler = SkillFactory.launch(config)
.addRequestHandlers({
    canHandle(input) {
        return input.requestEnvelope.request.type === 'LaunchRequest'
    },
    handle(input) {
        return input.responseBuilder.speak('Hello').getResponse()
    }
})
.createLambdaHandler()

Feature

Fully Compatible to ask-sdk

@talkyjs has a various utility classes and function. But almost feature has a compatibility to ask-sdk.

Easy to setup, easty to customize.

Stage Handling

We can choose these stage to run the skill

Preset Handlers

Logging

Automatically log these props.

• Request
• Response

Optimizing the Database request

TalkyJS has a extended persistentAttributesManager.

import { PersistentAttributesManager, SkillFactory } from '@talkyjs/core';
SkillFactory.launch({
  database: {
    type: 's3', // or 'dynamodb'. When select 'none', it does not work!
    tableName: 'example-bucket'
  }
}).addRequestHandlers({
  canHandle(input) {
    return input.requestEnvelope.request.type === 'LaunchRequest'
  },
  async handle(input) {
    // Create manager
    const persistenceManager = new PersistentAttributesManager(input.attributesManager)

    // Get saved data with default value
    const { name } = await persistenceManager.getPersistentAttributes({
      name: 'sir'
    })

    // Update parameter with merging exists attributes
    await persistenceManager.updatePersistentAttributes({
      now: new Date().toISOString()
    })
    return input.responseBuilder.speak(`Hello ${name}`).getResponse()
  }
})

And all persistent attributes using the manager will saved at the ResponseInterceptor automatically. So, the database connection has been optimized.

Own attributes management

We can define attributes for your own Skill

type MySkillData = {
  name: string;
  favoritesCities: string[];
  preferedLevel: 'easy' | 'normal' | 'hard'
}
class MySkillPersistentAttributesManager extends PersistentAttributesManager<MySkillData> {
  protected readonly defaultAttributes = {
    name: '',
    favoritesCities: [],
    preferedLevel: 'normal' as const
  }
}

And use own class intead of default class.

SkillFactory.launch({
  database: {
    type: 's3',
    tableName: 'example-bucket'
  }
}).addRequestHandlers({
  canHandle(input) {
    return input.requestEnvelope.request.type === 'LaunchRequest'
  },
  async handle(input) {
    const persistenceAdapter = new MySkillPersistentAttributesManager(input.attributesManager)
    const { name } = await persistenceAdapter.getPersistentAttributes()
    await persistenceAdapter.updatePersistentAttributes({
      preferedLevel: 'hard'
    })
    await persistenceAdapter.save()
    return input.responseBuilder.speak(`Hello ${name}`).getResponse()
  }
})

Save immediately

We can save it to execute await persistenceAdapter.save() method. And the method is checking is the attributes updated.

// Update attributes
await persistenceManager.updatePersistentAttributes({
  now: new Date().toISOString()
})

// Save now!
await persistenceAdapter.save()

// Nothing to do (Because no attributes has been updated)
await persistenceAdapter.save()

// Update attributes second time
await persistenceManager.updatePersistentAttributes({
  now: new Date().toISOString()
})

// Save!
await persistenceAdapter.save()