"""
MLflow Integration Utilities for LLM Workflows

This module provides MLflow integration for:
- Kubeflow Pipelines experiment tracking
- Model Registry with KServe deployment metadata
- Inference metrics logging from NATS handlers
- Experiment comparison and analysis

Configuration:
  Set MLFLOW_TRACKING_URI environment variable or use defaults:
  - In-cluster: http://mlflow.mlflow.svc.cluster.local:80
  - External: https://mlflow.lab.daviestechlabs.io

Usage:
  from mlflow_utils import get_mlflow_client, MLflowTracker
  from mlflow_utils.kfp_components import log_experiment_component
  from mlflow_utils.model_registry import register_model_for_kserve
  from mlflow_utils.inference_tracker import InferenceMetricsTracker
"""

from .client import (
    MLflowConfig,
    ensure_experiment,
    get_mlflow_client,
    get_tracking_uri,
)
from .inference_tracker import InferenceMetricsTracker
from .tracker import MLflowTracker

__all__ = [
    "get_mlflow_client",
    "get_tracking_uri",
    "ensure_experiment",
    "MLflowConfig",
    "MLflowTracker",
    "InferenceMetricsTracker",
]

__version__ = "1.0.0"