# 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](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/configuring-http-api/#configuring-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
```

## 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`.

## 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
```

## Create a Train-Test Split

To create a split of your NLU data, run:

```
rasa data split nlu
```

## 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

Rasa X is a toolset that helps you leverage conversations to improve your assistant. You can start Rasa X locally by executing

```
rasa x
```

You can find more information about it [here](/content/docs/rasa-x/index.html).  
  
👋 I can help you get started with Rasa and answer your technical questions.