# 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 [Running the Server](https://legacy-docs-v1.rasa.com/1.3.10/user-guide/running-the-server/#running-the-server) 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 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.

```bash
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`.
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`.

## Interactive Learning

To start an interactive learning session with your assistant, run

```
rasa interactive
```

If you provide a trained model using the `--model` argument, the interactive learning process
is started with the provided model. If no model is specified, `rasa interactive` will
train a new Rasa model with the data located in `data/` if no other directory was passed to the
`--data` flag. After training the initial model, the interactive learning session starts.
Training will be skipped if the training data and config haven’t changed.

For more information on the additional parameters, see [Running the Server](https://legacy-docs-v1.rasa.com/1.3.10/user-guide/running-the-server/#running-the-server).

👋 I can help you get started with Rasa and answer your technical questions.