Command Line Interface

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

User Guide

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.
`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

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.

Interactive Learning

To start an interactive learning session with your assistant, run

rasa interactive

Talk to your Assistant

To start a chat session with your assistant on the command line, run:

rasa shell

Start a Server

To start a server running your Rasa model, run:

rasa run

Start an Action Server

To run your action server run

rasa run actions

Visualize your Stories

To open a browser tab with a graph showing your stories:

rasa visualize

Evaluating a Model on Test Data

To evaluate your model on test data, run:

rasa test

Convert Data Between Markdown and JSON

To convert NLU data from LUIS data format, WIT data format, Dialogflow data format, JSON, or Markdown to JSON or Markdown, run:

rasa data convert nlu

Export Conversations to an Event Broker

To export events from a tracker store using an event broker, run:

rasa export

Start Rasa X

You can start Rasa X locally by executing

rasa x