Machine learning based dialogue engine for conversational software.
Project description
Go To Docs
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:
Please use gitter for quick answers to questions.
README Contents:
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 |
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