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

requirements.txt

@@ -0,0 +1,19 @@
+# MLflow Utils Module Requirements
+# Core MLflow
+mlflow>=2.10.0
+
+# Database backends
+psycopg2-binary>=2.9.0  # PostgreSQL (CNPG)
+boto3>=1.34.0  # S3-compatible artifact storage (optional)
+
+# For async tracking
+aiohttp>=3.9.0
+
+# YAML generation for KServe manifests
+PyYAML>=6.0
+
+# Already in chat-handler/voice-assistant requirements:
+# httpx (for health checks)
+# Used but typically installed with mlflow:
+# numpy
+# pandas