💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on: - Facebook Messenger - Slack - Google Hangouts - Webex Teams - Microsoft Bot Framework - Rocket.Chat - Mattermost - Telegram - Twilio - Your own custom conversational channels
or voice assistants as: - Alexa Skills - Google Home Actions
Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forth. In order for a human to have a meaningful exchange with a contextual assistant, the assistant needs to be able to use context to build on things that were previously discussed – Rasa enables you to build assistants that can do this in a scalable way.
There's a lot more background information in this blog post.
What does Rasa do? 🤔 Check out our Website
I'm new to Rasa 😄 Get Started with Rasa
I'd like to read the detailed docs 🤓 Read The Docs
I'm ready to install Rasa 🚀 Installation
I want to learn how to use Rasa 🚀 Tutorial
I have a question ❓ Rasa Community Forum
I would like to contribute 🤗 How to Contribute
There is extensive documentation in the 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.
We are very happy to receive and merge your contributions into this repository!
To contribute via pull request, follow these steps:
For more detailed instructions on how to contribute code, check out these code contributor guidelines.
You can find more information about how to contribute to Rasa (in lots of different ways!) on our website..
Your pull request will be reviewed by a maintainer, who will get back to you about any necessary changes or questions. You will also be asked to sign a Contributor License Agreement.
Rasa uses Poetry for packaging and dependency management. If you want to build it from source, you have to install Poetry first. This is how it can be done:
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python
There are several other ways to install Poetry. Please, follow the official guide to see all possible options.
pyenv install 3.7.6 pyenv local 3.7.6 # Activate Python 3.7.6 for the current project
By default, Poetry will try to use the currently activated Python version to create the virtual environment for the current project automatically. You can also create and activate a virtual environment manually — in this case, Poetry should pick it up and use it to install the dependencies. For example:
python -m venv .venv source .venv/bin/activate
You can make sure that the environment is picked up by executing
poetry env info
To install dependencies and
rasaitself in editable mode execute
First of all, install all the required dependencies:
make install install-docs
After the installation has finished, you can run and view the documentation locally using:
It should open a new tab with the local version of the docs in your browser; if not, visit http://localhost:3000 in your browser. You can now change the docs locally and the web page will automatically reload and apply your changes.
In order to run the tests, make sure that you have the development requirements installed:
make prepare-tests-ubuntu # Only on Ubuntu and Debian based systems make prepare-tests-macos # Only on macOS
Then, run the tests:
They can also be run at multiple jobs to save some time:
JOBS=[n] make test
[n]is the number of jobs desired. If omitted,
[n]will be automatically chosen by pytest.
Poetry doesn't include any solution that can help to resolve merge conflicts in the lock file
poetry.lockby default. However, there is a great tool called poetry-merge-lock. Here is how you can install it:
pip install poetry-merge-lock
Just execute this command to resolve merge conflicts in
To ensure a standardized code style we use the formatter black. To ensure our type annotations are correct we use the type checker pytype. If your code is not formatted properly or doesn't type check, GitHub 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-commitand execute
pre-commit installin 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
poetry install. To reformat files execute
If you want to check types on the codebase, install
poetry install. To check the types execute
Docusaurus v2to build docs for tagged versions and for the master branch. The static site that gets built is pushed to the
documentationbranch of this repo.
We host the site on netlify. On master branch builds (see
.github/workflows/documentation.yml), we push the built docs to the
documentationbranch. Netlify automatically re-deploys the docs pages whenever there is a change to that branch.
For Rasa Open Source, we usually commit to time-based releases, specifically on a monthly basis. This means that we commit beforehand to releasing a specific version of Rasa Open Source on a specific day, and we cannot be 100% sure what will go in a release, because certain features may not be ready.
At the beginning of each quarter, the Rasa team will review the scheduled release dates for all products and make sure they work for the projected work we have planned for the quarter, as well as work well across products.
Once the dates are settled upon, we update the respective milestones.
Releasing a new version is quite simple, as the packages are build and distributed by GitHub Actions.
Terminology: * micro release (third version part increases): 1.1.2 -> 1.1.3 * minor release (second version part increases): 1.1.3 -> 1.2.0 * major release (first version part increases): 1.2.0 -> 2.0.0
Release steps: 1. Make sure all dependencies are up to date (especially Rasa SDK) - For Rasa SDK that means first creating a new Rasa SDK release (make sure the version numbers between the new Rasa and Rasa SDK releases match) - Once the tag with the new Rasa SDK release is pushed and the package appears on pypi, the dependency in the rasa repository can be resolved (see below). 2. Switch to the branch you want to cut the release from (
masterin case of a major / minor, the current feature branch for micro releases) - Update the
pyproject.tomlwith the new release version and run
poetry update. This creates a new
poetry.lockfile with all dependencies resolved. - Commit the changes with
git commit -am "bump rasa-sdk dependency"but do not push them. They will be automatically picked up by the following step. 3. Run
make release4. Create a PR against master or the release branch (e.g.
1.2.x) 5. Once your PR is merged, tag a new release (this SHOULD always happen on master or release branches), e.g. using
bash git tag 1.2.0 -m "next release" git push origin 1.2.0GitHub will build this tag and publish the build artifacts. 6. If this is a minor release, a new release branch should be created pointing to the same commit as the tag to allow for future patch releases, e.g.
bash git checkout -b 1.2.x git push origin 1.2.x
Micro releases are simpler to cut, since they are meant to contain only bugfixes.
The only things you need to do to cut a micro are:
2.0.4micro, you will need your fixes to be on the
2.0.xrelease branch). All micros must come from a
make releaseand follow the steps + get the PR merged.
.xbranch again and push the tag!
Licensed under the Apache License, Version 2.0. Copyright 2020 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.