# mlvault-mlflow

MLflow artifact store plugin for [mlvault](https://pypi.org/project/mlvault/) — store your MLflow artifacts with encrypted cloud storage.

## Install

```bash
pip install mlvault mlvault-mlflow
mlvault init
```

## Usage

Set the artifact store when creating an MLflow experiment:

```python
import mlflow

mlflow.create_experiment("my-experiment", artifact_location="mlvault://my-project")
mlflow.set_experiment("my-experiment")
```

Then log artifacts as normal:

```python
with mlflow.start_run() as run:
    mlflow.log_artifact("checkpoint.pt")
    run_id = run.info.run_id
```

After training, push to cloud storage:

```bash
mlvault commit <mlflow_run_id>
```

See the [mlvault README](https://pypi.org/project/mlvault/) for full documentation.

## License

MIT
