## 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/1.5.3/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
```
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.

### 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
```
Normally, training stories in the directory `data` are visualized. If your stories are located somewhere else, you can specify their location with `--stories`.

### Evaluate a Model on Test Data

To evaluate your model on test data, run:
```
rasa test
```
Specify the model to test using `--model`.