Command Line Interface

These docs are for version 1.x of Rasa Open Source.

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Command Line Interface

The command line interface (CLI) gives you easy-to-remember commands for common tasks.

Command Effect
rasa init Creates a new project with example training data, actions, and config files.
rasa train Trains a model using your NLU data and stories, saves trained model in ./models.
rasa interactive Starts an interactive learning session to create new training data by chatting.
rasa shell Loads your trained model and lets you talk to your assistant on the command line.
rasa run Starts a Rasa server with your trained model. See the Configuring the HTTP API docs for details.
rasa run actions Starts an action server using the Rasa SDK.
rasa visualize Visualizes stories.
rasa test Tests a trained Rasa model using your test NLU data and stories.
rasa data split nlu Performs a split of your NLU data according to the specified percentages.
rasa data convert nlu Converts NLU training data between different formats.
rasa export Export conversations from a tracker store to an event broker.
rasa x Launch Rasa X locally.
rasa -h Shows all available commands.

Create a new project

A single command sets up a complete project for you with some example training data.

rasa init

This creates the following files:

.
├── __init__.py
├── actions.py
├── config.yml
├── credentials.yml
├── data
│   ├── nlu.md
│   └── stories.md
├── domain.yml
├── endpoints.yml
└── models
    └── <timestamp>.tar.gz

The rasa init command will ask you if you want to train an initial model using this data. If you answer no, the models directory will be empty.

Train a Model

The main command is:

rasa train

This command trains a Rasa model that combines a Rasa NLU and a Rasa Core model. If you only want to train an NLU or a Core model, you can run rasa train nlu or rasa train core. However, Rasa will automatically skip training Core or NLU if the training data and config haven’t changed.

rasa train will store the trained model in the directory defined by --out. The name of the model is per default <timestamp>.tar.gz. If you want to name your model differently, you can specify the name using --fixed-model-name.