MLflow is an expansive platform to build AI applications and models. We use a sliver of it that provides a tracing UI for LLM agents.

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Setting Up MLflow

Use Unpage’s built-in tracing to monitor agent execution: 
unpage mlflow serve

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Running Unpage and Capturing Traces

Unpage will automatically send traces to the MLflow server when the MLFLOW_TRACKING_URI environment variable is set. 
MLFLOW_TRACKING_URI=http://127.0.0.1:5566 unpage agent run
MLFLOW_TRACKING_URI=http://127.0.0.1:5566 unpage agent serve
View execution traces at ${MLFLOW_TRACKING_URI}/#/experiments/1?searchFilter=&orderByKey=attributes.start_time&orderByAsc=false&startTime=ALL&lifecycleFilter=Active&modelVersionFilter=All+Runs&datasetsFilter=W10%3D&compareRunsMode=TRACES to see:
  • Tool usage patterns
  • Execution timing
  • Error rates and types
  • Agent decision flows
The default MLflow server will have traces at: http://127.0.0.1:5566/#/experiments/1?searchFilter=&orderByKey=attributes.start_time&orderByAsc=false&startTime=ALL&lifecycleFilter=Active&modelVersionFilter=All+Runs&datasetsFilter=W10%3D&compareRunsMode=TRACES