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💬 Open source library for natural language understanding and machine learning-based dialogue management. - All things around intent classification, entity extraction and action predictions - DIY NLP and chatbot framework.

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Rasa (Rasa Core + Rasa NLU)

Join the chat on Rasa Community Forum PyPI version Supported Python Versions Build Status Coverage Status Documentation Status FOSSA Status

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.



Where to get help

There is extensive documentation at Rasa Docs. Make sure to select the correct version to make sure 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:

  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 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

  1. update rasa/version.py to reflect the correct version number
  2. 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
  3. edit the migration guide to provide assistance for users updating to the new version
  4. commit all the above changes and tag a new release, e.g. using
    git tag -f 0.7.0 -m "Some helpful line describing the release"
    git push origin 0.7.0
    
    travis will build this tag and push a package to pypi
  5. 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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💬 Open source library for natural language understanding and machine learning-based dialogue management. - All things around intent classification, entity extraction and action predictions - DIY NLP and chatbot framework.

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