"""
Real-Time Production AI Monitoring

Provides ProductionMonitor for multi-model monitoring, A/B testing,
drift detection, and cost optimization with real-time alerts.
"""

import json

import blazemetrics.blazemetrics_core as _ext


class ProductionMonitor:
    def __init__(self, models, metrics, alert_thresholds=None, a_b_testing=False):
        self.models = models
        self.metrics = metrics
        self.alert_thresholds = alert_thresholds or {}
        self.a_b_testing = a_b_testing

    def track_production(self):
        """
        Generator: yields metrics for each model in streaming fashion.
        """
        data = {
            "models": self.models,
            "metrics": self.metrics,
            "alert_thresholds": self.alert_thresholds,
            "a_b_testing": self.a_b_testing,
        }
        for result_json in _ext.production_monitor_tick(json.dumps(data)):
            yield json.loads(result_json)

    def auto_failover_to_backup(self):
        """
        Business logic for failover. (Placeholder trigger inside Python)
        """
        print("[Monitor] Failover triggered: switching to backup model")

    def optimize_inference_parameters(self):
        """
        Business logic for optimizing inference parameters.
        """
        print("[Monitor] Optimizing inference parameters for cost efficiency")