Metadata-Version: 2.4
Name: robusto-cloud
Version: 0.1.1
Summary: Python client for Robusto Cloud — adversarial robustness testing and hardening for ML models
Author-email: Cortexa Labs <support@cortexa-labs.com>
License-Expression: LicenseRef-Proprietary
Project-URL: Homepage, https://cortexa-labs.com
Project-URL: Documentation, https://cortexa-labs.com/docs
Project-URL: Repository, https://github.com/Cortexa-Labs-Inc/Cortexa-Labs-Robusto
Project-URL: Changelog, https://github.com/Cortexa-Labs-Inc/Cortexa-Labs-Robusto/releases
Keywords: adversarial,robustness,machine-learning,hardening,security,AI-safety
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests>=2.20
Dynamic: license-file

# Robusto

**Adversarial robustness hardening for ML models.**

Upload your pre-trained PyTorch model, Robusto stress-tests it against adversarial attacks and returns a hardened version with a compliance report.

```
pip install robusto-cloud → robusto configure → robusto init → hardened model + report
```

## Quick Start

```bash
pip install robusto-cloud
robusto configure          # save your API key
robusto init               # interactive: pick model, dataset, domain, attacks → submit
```

Or scripted:

```bash
robusto harden -m model.pt -d data.csv --domain tabular --mode standard
robusto watch <job_id>
robusto download <job_id>
```

Or in Python:

```python
from robusto import Robusto

client = Robusto()
job = client.harden(model_path="model.pt", dataset_path="data.csv", domain="tabular")
result = client.wait(job["job_id"])
client.download_model(job["job_id"], "hardened_model.pt")
client.download_report(job["job_id"], "report.pdf")
```

## Domains

Image, Tabular, Graph, Point Cloud, Sensor

## Modes

| Mode | Use case |
|------|----------|
| `low` | Quick audit |
| `standard` | Balanced (recommended) |
| `rigorous` | Full compliance |

## Documentation

- [**SDK Guide**](docs/SDK-Usage-Guide.md) — install, configure, CLI + Python usage, full API reference
- [**API Reference**](docs/API.md) — REST endpoints, auth, error codes
- [**Compliance Reports**](docs/CONCEPTS.md) — NIST AI RMF + EU AI Act mapping

## Running Locally (contributors)

```bash
git clone https://github.com/Cortexa-Labs-Inc/Cortexa-Labs-Robusto.git
cd Cortexa-Labs-Robusto
pip install -r requirements.txt && pip install -e .
export ROBUSTO_API_KEY=my-local-key
python -m robusto.server
```

Then point the SDK at localhost:

```python
client = Robusto(api_key="my-local-key", base_url="http://localhost:8000/api/v1")
```

## License

Proprietary. Copyright 2026 Cortexa Labs.
