mlflow-tracing

What problem does it solve?

This Skill enables easy integration of MLflow tracing into existing Python agents, facilitating monitoring and observability for AI workflows.

Core Features & Use Cases

• MLflow Integration: Inserts tracing setup code into agent.py to connect with MLflow tracking server.
• Flexible Deployment: Supports both local execution and deployment on OpenShift clusters.
• Use Case: Automate the addition of MLflow observability to a production agent, ensuring trace data is properly captured and stored for analysis.

Quick Start

Provide instructions to manually set environment variables and run the agent script directly in a terminal.