# 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/1.10.9/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. |

## Cheat Sheet

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.

### Creating a new project

To create a new project, simply run:

```
rasa init
```

### Train a Model

To train a model, use:

```
rasa train
```

### 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
```

### Starting a Server

To start a server running your Rasa model, run:

```
rasa run
```

### Starting an Action Server

To run your action server:

```
rasa run actions
```

### Visualize your Stories

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

```
rasa visualize
```

### Evaluating your Model

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, 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
```

Rasa X is a toolset that helps you leverage conversations to improve your assistant.