stayready 0.1.0

Push drift events and audit entries from your MLOps pipeline to Compass StayReady.

StayReady Python SDK

Push drift events and audit entries from your MLOps pipeline to Compass StayReady — continuous AI governance monitoring for regulated sectors.

Install

pip install stayready

Quick start

import os
from stayready import StayReady

sr = StayReady(
    api_key=os.environ["STAYREADY_API_KEY"],
    model_id="your-model-uuid",  # from your StayReady dashboard
)

# Report drift when your monitoring detects it
sr.drift(
    type="data_drift",              # data_drift | concept_drift | performance_degradation | regulatory_change
    severity="High",                # Critical | High | Medium | Low
    metric="PSI",
    value=0.28,
    threshold=0.20,
    description="Population Stability Index exceeded threshold on income feature.",
    affected_domains=["Data Quality", "Model Monitoring"],
    action_required="Retrain on recent data and re-validate before next production cycle.",
)

# Log lifecycle events to the immutable audit trail
sr.audit("model_retrained", "Retrained on Q2 data, Gini improved to 0.61", actor="ml-pipeline")

Critical and High severity events trigger an email alert (and webhook, if configured) and can flag your linked GovernReady audit for re-assessment.

Integration examples

Evidently AI

psi = report.as_dict()["metrics"][0]["result"]["dataset_drift_share"]
if psi > 0.2:
    sr.drift(type="data_drift", severity="High", metric="PSI", value=psi,
             threshold=0.2, description="Evidently detected dataset drift.")

Airflow (post-training validation)

def report_validation(**ctx):
    gini = ctx["ti"].xcom_pull(key="gini")
    if gini < 0.55:
        sr.drift(type="performance_degradation", severity="Critical", metric="Gini",
                 value=gini, threshold=0.55, description="Gini below policy floor after retrain.")

Requirements

Python 3.9+. Zero dependencies (standard library only).

Support

[e-mail] · stayready.dendrons.ai