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Add-on for accessing MlFlow tracking server behing GCP IAP.

Project description


AiBox Lab
mlflow-gcp-iap

MlFlow add-on to access IAP-enabled tracking server on GCP.

Python PyPI

Quickstart

Install the library using your favorite package manager:

uv add mlflow-gcp-iap
uv pip install mlflow-gcp-iap
pip install mlflow-gcp-iap

Once the library is installed, you must configure it by running mlflow-gcp-iap setup. The CLI will ask for the required configuration.

It is essential that the GCP Application Default Credentials is configured locally, and that the user and service account have sufficient permissions. For the user, permissions related to Service Account Impersonation and token creation are required. For the service account, only the permission to access the IAP-protected MlFlow tracking server is mandatory.

To check whether the configuration works correctly, run mlflow-gcp-iap test. This command runs the script src/mlflow_gcp_iap/test.py, which creates a run on the MlFlow server.

The library provides a simple context manager that automatically refresh tokens and update the MlFlow environment variables. The intended usage is as follows:

import mlflow

from mlflow_gcp_iap import TokenRefresher


if __name__ == "__main__":
    with TokenRefresher():
        with mlflow.start_run(run_name="my-run"):
            mlflow.log_params({"a": 10, "b": 20})
            mlflow.log_metrics({"MSE": 0.0})

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