The mlflow command provides functionality to set up MLflow for debugging and monitoring agent performance and behavior.

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Usage

unpage mlflow [OPTIONS] COMMAND [ARGS]...

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Commands

CommandDescription
serveStart an MLflow tracking server for agent debugging

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Subcommand: serve

Starts a local MLflow tracking server that can be used to capture and visualize agent runs, prompts, and responses.

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Usage

unpage mlflow serve [OPTIONS]

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Options

OptionDescription
--profile TEXTUse profiles to manage multiple graphs [env var: UNPAGE_PROFILE] [default: default]
--port INTEGERPort for MLflow server to listen on [default: 5566]
-h, --helpShow help message and exit

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Examples

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Start MLflow Server

# Start MLflow server with default settings
unpage mlflow serve

# Start MLflow on a custom port
unpage mlflow serve --port 8080

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Use MLflow with Agents

To use MLflow tracking with your agents, set the environment variable before running: 
# Set the MLflow tracking URI
export MLFLOW_TRACKING_URI=http://127.0.0.1:5566

# Run an agent with tracing enabled
unpage agent run my-agent '{"alert": "Disk usage exceeds 80%"}'