Tutorial: Rasa Basics

These docs are for version 1.x of Rasa Open Source. Docs for the new version 2.0 can be found here.

Tutorial: Rasa Basics

This page explains the basics of building an assistant with Rasa and shows the structure of a Rasa project. You can test it out right here without installing anything. You can also install Rasa and follow along in your command line.

The glossary contains an overview of the most common terms you’ll see in the Rasa documentation.

Steps

1. Create a New Project

The first step is to create a new Rasa project. To do this, run:

rasa init --no-prompt

The rasa init command creates all the files that a Rasa project needs and trains a simple bot on some sample data. This creates the following files:

File Description
__init__.py an empty file that helps python find your actions
actions.py code for your custom actions
config.yml configuration of your NLU and Core models
credentials.yml details for connecting to other services
data/nlu.md your NLU training data
data/stories.md your stories
domain.yml your assistant’s domain
endpoints.yml details for connecting to channels like fb messenger
models/<timestamp>.tar.gz your initial model

2. View Your NLU Training Data

To see the NLU training data created by the rasa init command:

cat data/nlu.md

The lines starting with ## define the names of your intents, which are groups of messages with the same meaning.

3. Define Your Model Configuration

View your model configuration file by running:

cat config.yml

4. Write Your First Stories

To view the example stories inside the file data/stories.md, run:

cat data/stories.md

5. Define a Domain

To define a Domain, run:

cat domain.yml

6. Train a Model

To train a model, run:

rasa train

The rasa train command will look for both NLU and Core data and will train a combined model.

7. Test Your Assistant

After training a model, test that your assistant behaves as expected by running:

rasa test

8. Talk to Your Assistant

Start talking to your assistant by running:

rasa shell

Next Steps

Now that you’ve built your first Rasa bot: