Ensure proper spacing in error messages (#2399)

* Ensure proper spacing in error messages

* update TOC (#2406)

---------

Co-authored-by: Alex Strick van Linschoten <strickvl@users.noreply.github.com>

src/zenml/cli/stack_components.py

@@ -941,7 +941,7 @@ def register_stack_component_flavor_command(source: str) -> None:
                 source_root = source_utils.get_source_root()
 
                 cli_utils.error(
-                    f"Flavor registration failed! ZenML tried loading the"
+                    f"Flavor registration failed! ZenML tried loading the "
                     f"module `{source}` from path `{source_root}`. If this is "
                     "not what you expect, then please ensure you have run "
                     "`zenml init` at the root of your repository.\n\n"

src/zenml/integrations/kserve/steps/kserve_deployer.py

@@ -353,7 +353,7 @@ def kserve_custom_model_deployer_step(
     # verify that a custom deployer is defined
     if not params.custom_deploy_parameters:
         raise ValueError(
-            "Custom deploy parameter which contains the path of the",
+            "Custom deploy parameter which contains the path of the ",
             "custom predict function is required for custom model deployment.",
         )
 

src/zenml/integrations/mlflow/steps/mlflow_deployer.py

@@ -228,10 +228,10 @@ def mlflow_model_registry_deployer_step(
     """
     if not registry_model_version and not registry_model_stage:
         raise ValueError(
-            "Either registry_model_version or registry_model_stage must"
-            "be provided in addition to registry_model_name to the MLflow"
-            "model registry deployer step. Since the"
-            "mlflow_model_registry_deployer_step is used in conjunction with"
+            "Either registry_model_version or registry_model_stage must "
+            "be provided in addition to registry_model_name to the MLflow "
+            "model registry deployer step. Since the "
+            "mlflow_model_registry_deployer_step is used in conjunction with "
             "the mlflow_model_registry."
         )
 

src/zenml/integrations/seldon/steps/seldon_deployer.py

@@ -378,15 +378,15 @@ def seldon_mlflow_registry_deployer_step(
     # Seldon Core model deployer are available
     if not registry_model_name:
         raise ValueError(
-            "registry_model_name must be provided to the MLflow"
+            "registry_model_name must be provided to the MLflow "
             "model registry deployer step."
         )
     elif not registry_model_version and not registry_model_stage:
         raise ValueError(
-            "Either registry_model_version or registry_model_stage must"
-            "be provided in addition to registry_model_name to the MLflow"
-            "model registry deployer step. Since the"
-            "mlflow_model_registry_deployer_step is used in conjunction with"
+            "Either registry_model_version or registry_model_stage must "
+            "be provided in addition to registry_model_name to the MLflow "
+            "model registry deployer step. Since the "
+            "mlflow_model_registry_deployer_step is used in conjunction with "
             "the mlflow_model_registry."
         )
     if service_config.implementation != "MLFLOW_SERVER":

src/zenml/integrations/skypilot/orchestrators/skypilot_base_vm_orchestrator.py

@@ -174,7 +174,7 @@ def prepare_or_run_pipeline(
             )
         if deployment.schedule:
             logger.warning(
-                "Skypilot Orchestrator currently does not support the"
+                "Skypilot Orchestrator currently does not support the "
                 "use of schedules. The `schedule` will be ignored "
                 "and the pipeline will be run immediately."
             )

src/zenml/orchestrators/local_docker/local_docker_orchestrator.py

@@ -112,7 +112,7 @@ def prepare_or_run_pipeline(
         """
         if deployment.schedule:
             logger.warning(
-                "Local Docker Orchestrator currently does not support the"
+                "Local Docker Orchestrator currently does not support the "
                 "use of schedules. The `schedule` will be ignored "
                 "and the pipeline will be run immediately."
             )