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Machine learning based dialogue engine for conversational software.

Project description

Rasa Stack

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

  • Facebook Messenger
  • Slack
  • Microsoft Bot Framework
  • Rocket.Chat
  • Mattermost
  • Telegram
  • Twilio

But you can also build assistants using:

  • Alexa Skills
  • Google Home Actions

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 Rasa Community Forum for quick answers to questions.

README Contents:

How to contribute

We are very happy to receive and merge your contributions. There is some more information about the style of the code and docs in the documentation.

In general the process is rather simple:

  1. create an issue describing the feature you want to work on (or have a look at issues with the label help wanted)
  2. write your code, tests and documentation
  3. create a pull request describing your changes

You pull request will be reviewed by a maintainer, who might get back to you about any necessary changes or questions. You will also be asked to sign a Contributor License Agreement.

Development Internals

Running and changing the documentation

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

brew install sphinx
pip3 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 2019 Rasa Technologies GmbH. Copy of the license.

A list of the Licenses of the dependencies of the project can be found at the bottom of the Libraries Summary.

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