langchain_community.callbacks.mlflow_callback.MlflowLogger

class langchain_community.callbacks.mlflow_callback.MlflowLogger(**kwargs: Any)

Callback Handler that logs metrics and artifacts to mlflow server.

Parameters

• name (str) – Name of the run.

• experiment (str) – Name of the experiment.

• tags (dict) – Tags to be attached for the run.

• tracking_uri (str) – MLflow tracking server uri.

• kwargs (Any) –

This handler implements the helper functions to initialize, log metrics and artifacts to the mlflow server.

Methods

__init__(**kwargs)
artifact(path)	To upload the file from given path as artifact.
finish_run()	To finish the run.
html(html, filename)	To log the input html string as html file artifact.
jsonf(data, filename)	To log the input data as json file artifact.
langchain_artifact(chain)
metric(key, value)	To log metric to mlflow server.
metrics(data[, step])	To log all metrics in the input dict.
start_run(name, tags[, run_id])	If run_id is provided, it will reuse the run with the given run_id.
table(name, dataframe)	To log the input pandas dataframe as a html table
text(text, filename)	To log the input text as text file artifact.

__init__(**kwargs: Any)

Parameters

kwargs (Any) –

artifact(path: str) → None

To upload the file from given path as artifact.

Parameters

path (str) –

Return type

None

finish_run() → None

To finish the run.

Return type

None

html(html: str, filename: str) → None

To log the input html string as html file artifact.

Parameters

• html (str) –

• filename (str) –

Return type

None

jsonf(data: Dict[str, Any], filename: str) → None

To log the input data as json file artifact.

Parameters

• data (Dict[str, Any]) –

• filename (str) –

Return type

None

langchain_artifact(chain: Any) → None

Parameters

chain (Any) –

Return type

None

metric(key: str, value: float) → None

To log metric to mlflow server.

Parameters

• key (str) –

• value (float) –

Return type

None

metrics(data: Union[Dict[str, float], Dict[str, int]], step: Optional[int] = 0) → None

To log all metrics in the input dict.

Parameters

• data (Union[Dict[str, float], Dict[str, int]]) –

• step (Optional[int]) –

Return type

None

start_run(name: str, tags: Dict[str, str], run_id: Optional[str] = None) → None

If run_id is provided, it will reuse the run with the given run_id. Otherwise, it starts a new run, auto generates the random suffix for name.

Parameters

• name (str) –

• tags (Dict[str, str]) –

• run_id (Optional[str]) –

Return type

None

table(name: str, dataframe: Any) → None

To log the input pandas dataframe as a html table

Parameters

• name (str) –

• dataframe (Any) –

Return type

None

text(text: str, filename: str) → None

To log the input text as text file artifact.

Parameters

• text (str) –

• filename (str) –

Return type

None