> ## 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.

# qbraid

> The qBraid CLI — A unified interface for AI agents, quantum computing, Python environments, and cloud compute.

Version: [0.13.2](https://pypi.org/project/qbraid-cli/0.13.2)

Whether you're running AI coding agents locally or on cloud servers,
managing quantum experiments across providers, or setting up reproducible
Python environments — qBraid brings it all into one CLI.

**Usage**:

```console theme={null}
$ qbraid [OPTIONS] COMMAND [ARGS]...
```

**Options**:

* `-v, --version`: Show the version and exit.
* `--install-completion`: Install completion for the current shell.
* `--show-completion`: Show completion for the current shell, to copy it or customize the installation.
* `--help`: Show this message and exit.

**Commands**:

* `admin`: CI/CD commands for qBraid maintainers.
* `agents`: Manage AI coding agent sessions.
* `compute`: Manage cloud compute and SSH.
* `lab`: Launch qBraid Lab (JupyterLab).
* `configure`: Configure CLI settings.
* `account`: Manage qBraid account.
* `devices`: Browse quantum devices.
* `jobs`: Submit and track quantum computing jobs.
* `projects`: Browse and install qBraid Hub projects.
* `skills`: Create, install, and share AI coding skills.
* `troubleshoot`: Diagnose qBraid platform issues.
* `envs`: Manage Python environments.
* `kernels`: Add, remove, and repair Jupyter kernels.
* `pip`: Run pip command in active qBraid environment.