Skip to main content

Machine learning based dialogue engine for conversational software.

Project description

Rasa Core

Join the chat on Gitter Build Status Coverage Status PyPI version

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:

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
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 2018 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
fbmessenger Apache Licence 2.0
tqdm MIT
ConfigArgParse MIT

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rasa-core-0.9.0a2.tar.gz (80.3 kB view details)

Uploaded Source

Built Distribution

rasa_core-0.9.0a2-py2.py3-none-any.whl (108.4 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file rasa-core-0.9.0a2.tar.gz.

File metadata

  • Download URL: rasa-core-0.9.0a2.tar.gz
  • Upload date:
  • Size: 80.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for rasa-core-0.9.0a2.tar.gz
Algorithm Hash digest
SHA256 eba9788bb991072f645cb771ccb7102baf400c419f83f472fa129caf75016c29
MD5 80805cd4e1863bc09771daf8acacbfa4
BLAKE2b-256 e46467a3a3b69c542d30a3b8b9917144805224727b6b620f01467ffb6b178556

See more details on using hashes here.

File details

Details for the file rasa_core-0.9.0a2-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for rasa_core-0.9.0a2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 d6e9905e9ca88eeb68609d06df6c353349f9c3dbb4a5c542822e439733f26690
MD5 05d466ed9b39bfc0a0ec0073ba6dc95b
BLAKE2b-256 a6cb8b0ff9bd6d571515fc11f5088f4afae769e63c4c8b786c96b609b7a09d86

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page