Kitaru

logging

Structured metadata logging.

kitaru.log() attaches structured key-value metadata to the current checkpoint or execution. It is context-sensitive: inside a checkpoint it attaches to that checkpoint; inside a flow but outside a checkpoint it attaches to the execution.

Example

from kitaru import checkpoint

@checkpoint
def call_model(prompt: str) -> str:
    response = model.generate(prompt)
    kitaru.log(
        tokens=response.usage.total_tokens,
        cost=response.usage.cost,
        model=response.model,
    )
    return response.text
funclog(**kwargs) -> None

Attach structured metadata to the current checkpoint or execution.

Standard keys include cost, tokens, latency, but arbitrary user-defined keys are accepted.

Notes

Values should be JSON-serializable. Metadata is persisted through ZenML's run-metadata APIs. Multiple calls in the same scope append metadata entries; repeated keys with dictionary values are merged on hydration, while repeated non-dictionary keys resolve to latest value.

paramkwargsAny
= {}

Returns

None