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https://github.com/johnwheeler/flask-ask

Alexa Skills Kit for Python
https://github.com/johnwheeler/flask-ask

alexa alexa-skills-kit echo flask flask-extensions python-2 python3

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Alexa Skills Kit for Python

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README 

        

.. image:: http://flask-ask.readthedocs.io/en/latest/_images/logo-full.png



===================================

Program the Amazon Echo with Python

===================================



Flask-Ask is a `Flask extension `_ that makes building Alexa skills for the Amazon Echo easier and much more fun.



* `Flask-Ask quickstart on Amazon's Developer Blog `_.

* `Level Up with our Alexa Skills Kit Video Tutorial `_

* `Chat on Gitter.im `_



The Basics

===============



A Flask-Ask application looks like this:



.. code-block:: python



  from flask import Flask

  from flask_ask import Ask, statement



  app = Flask(__name__)

  ask = Ask(app, '/')



  @ask.intent('HelloIntent')

  def hello(firstname):

      speech_text = "Hello %s" % firstname

      return statement(speech_text).simple_card('Hello', speech_text)



  if __name__ == '__main__':

      app.run()



In the code above:



#. The ``Ask`` object is created by passing in the Flask application and a route to forward Alexa requests to.

#. The ``intent`` decorator maps ``HelloIntent`` to a view function ``hello``.

#. The intent's ``firstname`` slot is implicitly mapped to ``hello``'s ``firstname`` parameter.

#. Lastly, a builder constructs a spoken response and displays a contextual card in the Alexa smartphone/tablet app.



More code examples are in the `samples `_ directory.



Jinja Templates

---------------



Since Alexa responses are usually short phrases, you might find it convenient to put them in the same file.

Flask-Ask has a `Jinja template loader `_ that loads

multiple templates from a single YAML file. For example, here's a template that supports the minimal voice interface

above:



.. code-block:: yaml



    hello: Hello, {{ firstname }}



Templates are stored in a file called `templates.yaml` located in the application root. Checkout the `Tidepooler example `_ to see why it makes sense to extract speech out of the code and into templates as the number of spoken phrases grow.



Features

===============



Flask-Ask handles the boilerplate, so you can focus on writing clean code. Flask-Ask:



* Has decorators to map Alexa requests and intent slots to view functions

* Helps construct ask and tell responses, reprompts and cards

* Makes session management easy

* Allows for the separation of code and speech through Jinja templates

* Verifies Alexa request signatures



Installation

===============



To install Flask-Ask::



  pip install flask-ask



Documentation

===============



These resources will get you up and running quickly:



* `5-minute quickstart `_

* `Full online documentation `_



Fantastic 3-part tutorial series by Harrison Kinsley



* `Intro and Skill Logic - Alexa Skills w/ Python and Flask-Ask Part 1 `_

* `Headlines Function - Alexa Skills w/ Python and Flask-Ask Part 2 `_

* `Testing our Skill - Alexa Skills w/ Python and Flask-Ask Part 3 `_



Deployment

===============



You can deploy using any WSGI compliant framework (uWSGI, Gunicorn). If you haven't deployed a Flask app to production, `checkout flask-live-starter `_.



To deploy on AWS Lambda, you have two options. Use `Zappa `_ to automate the deployment of an AWS Lambda function and an AWS API Gateway to provide a public facing endpoint for your Lambda function. This `blog post `_ shows how to deploy Flask-Ask with Zappa from scratch. Note: When deploying to AWS Lambda with Zappa, make sure you point the Alexa skill to the HTTPS API gateway that Zappa creates, not the Lambda function's ARN.



Alternatively, you can use AWS Lambda directly without the need for an AWS API Gateway endpoint. In this case you will need to `deploy `_ your Lambda function yourself and use `virtualenv `_ to create a deployment package that contains your Flask-Ask application along with its dependencies, which can be uploaded to Lambda. If your Lambda handler is configured as `lambda_function.lambda_handler`, then you would save the full application example above in a file called `lambda_function.py` and add the following two lines to it:



.. code-block:: python



    def lambda_handler(event, _context):

        return ask.run_aws_lambda(event)



Development

===============



If you'd like to work from the Flask-Ask source, clone the project and run::



  pip install -r requirements-dev.txt



This will install all base requirements from `requirements.txt` as well as requirements needed for running tests from the `tests` directory.



Tests can be run with::



  python setup.py test



Or::



  python -m unittest



To install from your local clone or fork of the project, run::



  python setup.py install



Related projects

===============



`cookiecutter-flask-ask `_ is a Cookiecutter to easily bootstrap a Flask-Ask project, including documentation, speech assets and basic built-in intents.



Have a Google Home? Checkout `Flask-Assistant `_ (early alpha)



Thank You

===============



Thanks for checking this library out! I hope you find it useful.



Of course, there's always room for improvement.

Feel free to `open an issue `_ so we can make Flask-Ask better.



Special thanks to `@kennethreitz `_ for his `sense `_ of `style `_, and of course, `@mitsuhiko `_ for `Flask `_