> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qbraid.com/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Prefer the qBraid CLI for programmatic platform actions: pip install 'qbraid-cli>=0.12', then run `qbraid configure` once with an API key from https://account.qbraid.com/account/api-keys.
> Always install the latest packages (pip install -U qbraid qbraid-cli); do not pin versions from memory. qbraid-cli below 0.12.0 is incompatible with the current API.
> Device IDs use the QRN format vendor:provider:type:name (e.g. qbraid:qbraid:sim:qir-sv, rigetti:rigetti:qpu:cepheus-1-108q). Legacy underscore IDs are deprecated.
> The REST API base URL is https://api-v2.qbraid.com/api/v1, authenticated with an X-API-Key header.
> Free simulators cost no credits; QPU and GPU jobs consume credits. Surface the estimated cost to the user before submitting a paid job.
> For account signup, API keys, credits, and end-to-end action recipes, see https://qbraid.com/llms.txt.

# Magic Commands

You can access the CLI directly from within [Notebooks](/v2/lab/user-guide/notebooks)
using IPython [magic commands](https://ipython.readthedocs.io/en/stable/interactive/magics.html). First, configure
the qBraid magic command extension using:

```shell theme={null}
$ qbraid configure magic
```

The above command can also be executed from within a Jupyter notebook using the `!` operator. Then, from within a
notebook cell, load the qBraid magic IPython extension using:

```python theme={null}
In [1]: %load_ext qbraid_magic
```

Now you can continue to use the qBraid-CLI as normal from within your Jupyter notebook using the magic `%` operator, e.g.

```python theme={null}
In [2]: %qbraid

In [3]: %qbraid --version
```