Built for streamlining development of Google Assistant Actions

Related tags

Third-party APIs Wrapperspythonserverlessgoogle-voicegoogle-cloud-functionsgoogle-actionsdialogflowdialogflow-action
Overview

rocket ship

Apprentice

Build Status PyPI version

Apprentice is a framework built for developing Google Actions via Dialogflow and Google Cloud (serverless) Functions.

Includes:

  • plug-and-play feel to get going quickly
  • basic Dialogflow API 2.0 response handling
  • local setup for quick iteration

Installation

pip install apprentice

Quickstart

We recommend you read the full tutorial here.

A Google Action project will consist of two things:

  1. Dialogflow Intent
  2. A webhook to satisfy your users intent

To generate a "Hello World" webhook, run:

$ apprentice init

This will create a file structure:

src/
    main.py
    requirements.txt

Run a local server with

$ apprentice run

and expose to localhost port via an https tunnel. Then add the url to the fulfillment webhook in Dialogflow.

For a more indepth example please see the tutorial I wrote here.

Deployment

Note

gcloud cli must be installed and authorized for the following command to work. If you wish to not have gcloud cli installed, you can copy the file contents via the gcloud function dashboard.

$ apprentice -f hello_world -s hello_world_agent -e hello_world

This will generate the command to execute a gcloud function deploy via the cli.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

GNU 3.0

Comments
  • Increase the usability of the Apprentice API

    Increase the usability of the Apprentice API

    This is what I could imagine the API for Apprentice looking like:

    
from apprentice import Apprentice

apr = Apprentice(__name__)

ENTITIES = {
    "name": "History",
    "entries": [
        {
            "value": "history",
            "synonyms": [
                "history",
                "past event",
                "the past",
                "past"
            ]
        }, {
            "value": "birth",
            "synonyms": [
                "birth",
                "births",
                "born"
            ]
        }
    ]
}


@apr.action(entities=['name'])
def cool_fact_generator(*args, **kwargs):
    reply = _fact_response(apr.entity)
    return apr.make_repsonse(reply)
    opened by andrewgy8 1
  • Add suggestions

    Add suggestions

    When creating a response a user should be able to configure the view of suggestions.

    The resulting payload would look like:

    'payload': {
                'google': {
                    'expect_user_response': False,
                    'is_ssml': True,
                    'permissions_request': None,
                    "richResponse": {
                        "items": [],
                        "suggestions": [],
                        "linkOutSuggestion": {}
                    }
                }
            }
    opened by andrewgy8 0
  • .env with the Flask App path

    .env with the Flask App path

    For the local server to work as plug-and-play, it would be nice to have .env file that is read as a default to the installed main.py flask app. That way a user could execute:

    1. apprentice init
    2. apprentice run

    And have the local server running immediately.

    opened by andrewgy8 0
  • Fix triplicate deployment issue

    Fix triplicate deployment issue

    It seems that travis is trying to deploy the package with every version of python declared. For instance, https://travis-ci.com/andrewgy8/apprentice/builds/93792889

    The build succeeds with 3.7, but with 3.6 and 3.5, it fails. It shouldn't be deploying with all the python versions, only one.

    opened by andrewgy8 0
  • Allow user to define init directory name and function name

    Allow user to define init directory name and function name

    Be able to handle and argument such as:

    apprentice init --name=foo_bar

    and the output should be a direct called /foo_bar with a main.py file containing a foo_bar function.

    enhancement 
    opened by andrewgy8 0
Releases(v0.4.4)
Owner
Andrew Graham-Yooll
Software engineer with background in molecular biology
Andrew Graham-Yooll
GitHub Repository
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