Some doc finetuning

openeo/rest/datacube.py

@@ -1852,8 +1852,7 @@ def predict_curve(
 
         :param parameters:
         :param function: "child callback" function, see :ref:`callbackfunctions`
-        :dimension:
-        @return:
+        :param dimension:
         """
         return self.process(process_id="predict_curve", arguments={
             "data": THIS,
@@ -1866,11 +1865,15 @@ def predict_curve(
     @openeo_process(mode="reduce_dimension")
     def predict_random_forest(self, model: Union[str, RESTJob, MlModel], dimension: str = "bands"):
         """
-        Apply ``reduce_dimension`` process with a `predict_random_forest` reducer.
+        Apply ``reduce_dimension`` process with a ``predict_random_forest`` reducer.
+
+        :param model: a reference to a trained model, one of
 
-        :param model: a :py:class:`MlModel` (e.g. loaded from :py:meth:`~openeo.Connection.load_ml_model`)
-            or a reference to such a model: a URL (``str``) to a STAC Item (implementing the `ml-model` extension)
-            a job id (``str``) or a :py:class:`RESTJob` instance of a batch job that saved a single model.
+                - a :py:class:`MlModel` instance (e.g. loaded from :py:meth:`Connection.load_ml_model`)
+                - a :py:class:`RESTJob` instance of a batch job that saved a single random forest model
+                - a job id (``str``) of a batch job that saved a single random forest model
+                - a STAC item URL (``str``) to load the random forest from.
+                  (The STAC Item must implement the `ml-model` extension.)
         :param dimension: dimension along which to apply the ``reduce_dimension`` process.
 
         .. versionadded:: 0.10.0