MlflowLogger#

class langchain_community.callbacks.mlflow_callback.MlflowLogger(**kwargs: Any)[source]#

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)[source]#

Parameters:: kwargs (Any)

artifact(path: str) → None[source]#

To upload the file from given path as artifact.

Parameters:: path (str)
Return type:: None

finish_run() → None[source]#

To finish the run.

Return type:: None

html(html: str, filename: str) → None[source]#

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[source]#

To log the input data as json file artifact.

Parameters:

data (Dict[str, Any])
filename (str)

Return type:

None

langchain_artifact(chain: Any) → None[source]#

Parameters:: chain (Any)
Return type:: None

metric(key: str, value: float) → None[source]#

To log metric to mlflow server.

Parameters:

key (str)
value (float)

Return type:

None

metrics(data: Dict[str, float] | Dict[str, int], step: int | None = 0) → None[source]#

To log all metrics in the input dict.

Parameters:

data (Dict[str, float] | Dict[str, int])
step (int | None)

Return type:

None

start_run(name: str, tags: Dict[str, str], run_id: str | None = None) → None[source]#

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 (str | None)

Return type:

None

table(name: str, dataframe: Any) → None[source]#

To log the input pandas dataframe as a html table

Parameters:

name (str)
dataframe (Any)

Return type:

None

text(text: str, filename: str) → None[source]#

To log the input text as text file artifact.

Parameters:

text (str)
filename (str)

Return type:

None