Billy D.
2df3f27af7
- 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
41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
"""
|
|
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"
|