docstring for plugin

src/neptune_mlflow_exporter/__init__.py

@@ -25,7 +25,7 @@
 @click.option(
     "--exclude-artifacts",
     "-e",
-    help="Specifies whether to also include artifacts in the upload",
+    help="Specifies whether to exclude artifacts from the upload",
     required=False,
     default=False,
     type=bool,

src/neptune_mlflow_plugin/impl/__init__.py

@@ -25,6 +25,34 @@
 
 @functools.wraps(neptune.init_run)
 def create_neptune_tracking_uri(**kwargs) -> str:
+    """Sets up a Neptune tracking URI for logging MLflow experiment metadata.
+
+    This lets you direct your metadata to Neptune instead of MLflow, without needing to change your MLflow logging code.
+
+    The function wraps neptune.init_run(), so you have the same parameters available for customizing your run or
+    limiting what is logged. The exceptions are with_id and custom_run_id, which will be ignored if provided (as calling
+    this function always creates a new Neptune run).
+    For the full list, see the Neptune documentation: https://docs.neptune.ai/api/neptune/#init_run
+
+    Examples:
+        Create default Neptune tracking URI:
+        >>> from neptune_mlflow_plugin import create_neptune_tracking_uri
+        >>> uri = create_neptune_tracking_uri()
+        >>> mlflow.set_tracking_uri(uri)
+        >>> with mlflow.start_run() as mlflow_run:
+        ...     ...
+
+        Create Neptune run with more customized options:
+        >>> uri = create_neptune_tracking_uri(
+        ...     name="my-custom-run-name",
+        ...     description="Description of the run",
+        ...     tags=["test", "mlflow"],
+        ...     source_files="**/.py",
+        ...     dependencies="infer",
+        ... )
+
+    For detailed instructions, see the Neptune-MLflow integration guide: https://docs.neptune.ai/integrations/mlflow/
+    """
     kwargs["tags"] = (
         list(kwargs["tags"]) if ("tags" in kwargs and isinstance(kwargs["tags"], set)) else kwargs.get("tags")
     )