yanfjz / rasa_core

machine learning based dialogue engine for conversational software

Rasa Core

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Introduction

Rasa Core is a framework for building conversational software, which includes:

• chatbots on Messenger
• Slack bots
• Alexa Skills
• Google Home Actions

etc.

Rasa Core's primary purpose is to help you build contextual, layered conversations with lots of back-and-forth. To have a real conversation, you need to have some memory and build on things that were said earlier. Rasa Core lets you do that in a scalable way.

There's a lot more background information in this blog post

Where to get help

There is extensive documentation:

• master  (if you install from github) or
• stable   (if you install from pypi)

Please use gitter for quick answers to questions.

README Contents:

• Setup
• How to contribute
• Development Internals
• License

Setup

There isn't a released pypi package yet. Hence, you need to clone and install the package from the github repository. For a more detailed description, please visit the Installation page of the docs.

If you want to install the latest master version from github, run:

git clone https://github.com/RasaHQ/rasa_core.git
cd rasa_core
pip install -r requirements.txt
pip install -e .

Development Internals

Running and changing the documentation

To build & edit the docs, first install all necessary dependencies:

brew install sphinx
pip install -r dev-requirements.txt

After the installation has finished, you can run and view the documentation locally using

make livedocs

Visit the local version of the docs at http://localhost:8000 in your browser. You can now change the docs locally and the web page will automatically reload and apply your changes.

License

Licensed under the Apache License, Version 2.0. Copyright 2017 Rasa Technologies GmbH. Copy of the license.

As a reference, the following contains a listing of the licenses of the different dependencies as of this writing. Licenses of the dependencies:

required package	License
apscheduler	MIT
fakeredis	BSD
graphviz	MIT
typing	PSF
future	MIT
six	MIT
h5py	BSD
jsonpickle	BSD
keras	MIT
numpy	BSD
pandoc	MIT
redis	MIT
tensorflow	Apache Licence 2.0
networkx	BSD
pymessenger	MIT
tqdm	MIT
ConfigArgParse	MIT