Machine learning based dialogue engine for conversational software.
Project description
Rasa (Rasa Core + Rasa NLU)
Note This repository now contains the code for both Rasa NLU AND Rasa Core. Nothing has changed yet in terms of usage, but we are in the process of simplifying everything ahead of the next major release.
Rasa 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'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 lets you do that in a scalable way.
There's a lot more background information in this blog post.
-
What do Rasa Core & NLU do? 🤔 Read About Rasa
-
I'd like to read the detailed docs 🤓 Read The Docs
-
I'm ready to install Rasa! 🚀 Installation
-
I have a question ❓ Rasa Community Forum
-
I would like to contribute 🤗 How to contribute
Where to get help
There is extensive documentation at Rasa Docs. Make sure to select the correct version so you are looking at the docs for the version you installed.
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:
- create an issue describing the feature you want to work on (or have a look at issues with the label help wanted)
- write your code, tests and documentation
- create a pull request describing your changes
Your 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 requirements-dev.txt
After the installation has finished, you can run and view the documentation locally using:
make livedocs-nlu
make livedocs-core
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.
Running the Tests
In order to run the tests make sure that you have the development requirements installed.
make test
Steps to release a new version
Releasing a new version is quite simple, as the packages are build and distributed by travis. The following things need to be done to release a new version
- update rasa/version.py to reflect the correct version number
- edit the CHANGELOG.rst, create a new section for the release (eg by moving the items from the collected master section) and create a new master logging section
- edit the migration guide to provide assistance for users updating to the new version
- commit all the above changes and tag a new release, e.g. using
travis will build this tag and push a package to pypigit tag -f 0.7.0 -m "Some helpful line describing the release" git push origin 0.7.0
- only if it is a major release, a new branch should be created pointing to the same commit as the tag to allow for future minor patches, e.g.
git checkout -b 0.7.x git push origin 0.7.x
Code Style
To ensure a standardized code style we use the formatter black. If your code is not formatted properly, travis will fail to build.
If you want to automatically format your code on every commit, you can use pre-commit.
Just install it via pip install pre-commit
and execute pre-commit install
in the root folder.
This will add a hook to the repository, which reformats files on every commit.
If you want to set it up manually, install black via pip install black
.
To reformat files execute
black .
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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