feat: Add MLflow integration utilities

- client: Connection management and helpers
- tracker: General experiment tracking
- inference_tracker: Async metrics for NATS handlers
- model_registry: Model registration with KServe metadata
- kfp_components: Kubeflow Pipeline components
- experiment_comparison: Run comparison tools
- cli: Command-line interface

mlflow_utils/__init__.py

@@ -0,0 +1,40 @@
+"""
+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 (
+    get_mlflow_client,
+    get_tracking_uri,
+    ensure_experiment,
+    MLflowConfig,
+)
+from .tracker import MLflowTracker
+from .inference_tracker import InferenceMetricsTracker
+
+__all__ = [
+    "get_mlflow_client",
+    "get_tracking_uri", 
+    "ensure_experiment",
+    "MLflowConfig",
+    "MLflowTracker",
+    "InferenceMetricsTracker",
+]
+
+__version__ = "1.0.0"