Want to explore first?
You can explore Rasa Open Source online using the Rasa Playground even before you install. At the end of the tutorial you can download the resulting assistant, install Rasa on your machine and continue development locally.Rasa Playground
You can install Rasa Open Source using pip (requires Python 3.6, 3.7 or 3.8).
You are now ready to go! So what's next? You can create a new project by running:
You can learn about the most important Rasa commands in the Command Line Interface.
Step-by-step Installation Guide
Prefer following video instructions? Watch our installation series on Youtube, it explains the installation in walkthroughs for all major platforms.
1. Python Environment Setup
Check if your Python environment is already configured:
If these packages are already installed, these commands should display version numbers for each step, and you can skip to the next step.
Otherwise, proceed with the instructions below to install them.
Fetch the relevant packages using
apt, and install virtualenv using
2. Virtual Environment Setup
This step is optional, but we strongly recommend isolating python projects using virtual environments. Tools like virtualenv and virtualenvwrapper provide isolated Python environments, which are cleaner than installing packages system-wide (as they prevent dependency conflicts). They also let you install packages without root privileges.
Create a new virtual environment by choosing a Python interpreter and making a
./venv directory to hold it:
Activate the virtual environment:
3. Install Rasa Open Source
- Ubuntu / macOS / Windows
First make sure your
pip version is up to date:
To install Rasa Open Source:
When you run Rasa Open Source for the first time, you’ll see a message notifying you about anonymous usage data that is being collected. You can read more about how that data is pulled out and what it is used for in the telemetry documentation.
Congratulations! You have successfully installed Rasa Open Source!
Next step: Use the Rasa Playground to prototype your first assistant in the browser and download it afterwards
Building from Source
If you want to use the development version of Rasa Open Source, you can get it from GitHub:
For some machine learning algorithms you need to install additional python packages. They aren't installed by default to keep the footprint small.
The page on Tuning Your Model will help you pick the right configuration for your assistant and alert you to additional dependencies.
Just give me everything!
If you don't mind the additional dependencies lying around, you can use
to install all needed dependencies for every configuration.
Dependencies for spaCy
For more information on spaCy models, check out the spaCy docs.
You can install it with the following commands:
This will install Rasa Open Source as well as spaCy and its language model
for the English language, but many other languages are availabe too.
We recommend using at least the "medium" sized models (
_md) instead of the spaCy's
en_core_web_sm model. Small models require less
memory to run, but will likely reduce intent classification performance.
Dependencies for MITIE
and then download the
The file you need is
total_word_feature_extractor.dat. Save this
anywhere. If you want to use MITIE, you need to
tell it where to find this file (in this example it was saved in the
data folder of the project directory).
To upgrade your installed version of Rasa Open Source to the latest version from PyPI:
To download a specific version, specify the version number: