fix the "loading model" message which was logged twice when using ras…

…a run.

change formatting

fix model path return

changelog/7260.bugfix.md

@@ -0,0 +1 @@
+Fixed the 'loading model' message which was logged twice when using `rasa run`.

rasa/cli/run.py

@@ -94,7 +94,7 @@ def run(args: argparse.Namespace):
     # make sure either a model server, a remote storage, or a local model is
     # configured
 
-    from rasa.model import get_model
+    from rasa.model import verify_model_path, get_model
     from rasa.core.utils import AvailableEndpoints
 
     # start server if remote storage is configured
@@ -113,7 +113,7 @@ def run(args: argparse.Namespace):
     args.model = _validate_model_path(args.model, "model", DEFAULT_MODELS_PATH)
     local_model_set = True
     try:
-        get_model(args.model)
+        verify_model_path(args.model)
     except ModelNotFound:
         local_model_set = False
 

rasa/model.py

@@ -128,16 +128,15 @@ def should_retrain_nlu(self) -> bool:
         return self.force_training or self.nlu
 
 
-def get_model(model_path: Text = DEFAULT_MODELS_PATH) -> TempDirectoryPath:
-    """Get a model and unpack it. Raises a `ModelNotFound` exception if
-    no model could be found at the provided path.
+def verify_model_path(model_path: Text = DEFAULT_MODELS_PATH) -> Text:
+    """Verifies that a model path exists.
 
     Args:
         model_path: Path to the zipped model. If it's a directory, the latest
                     trained model is returned.
 
-    Returns:
-        Path to the unpacked model.
+    Raises:
+        ModelNotFound Exception: When no model could be found at the provided path.
 
     """
     if not model_path:
@@ -154,10 +153,30 @@ def get_model(model_path: Text = DEFAULT_MODELS_PATH) -> TempDirectoryPath:
     elif not model_path.endswith(".tar.gz"):
         raise ModelNotFound(f"Path '{model_path}' does not point to a Rasa model file.")
 
+    return model_path
+
+
+def get_model(model_path: Text = DEFAULT_MODELS_PATH) -> TempDirectoryPath:
+    """Get a model and unpack it.
+
+    Args:
+        model_path: Path to the zipped model. If it's a directory, the latest
+                    trained model is returned.
+
+    Returns:
+        Path to the unpacked model.
+
+    Raises:
+        ModelNotFound Exception: When no model could be found at the provided path.
+
+    """
+    model_path = verify_model_path(model_path)
+
     try:
         model_relative_path = os.path.relpath(model_path)
     except ValueError:
         model_relative_path = model_path
+
     logger.info(f"Loading model {model_relative_path}...")
 
     return unpack_model(model_path)

tests/test_model.py

@@ -42,6 +42,7 @@
     can_finetune,
     create_package_rasa,
     get_latest_model,
+    verify_model_path,
     get_model,
     get_model_subdirectories,
     model_fingerprint,
@@ -78,6 +79,12 @@ def test_get_model_context_manager(trained_rasa_model: str):
     assert not os.path.exists(unpacked)
 
 
+@pytest.mark.parametrize("model_path", ["foobar", "rasa", "README.md", None])
+def test_verify_model_path_exception(model_path: Optional[Text]):
+    with pytest.raises(ModelNotFound):
+        verify_model_path(model_path)
+
+
 @pytest.mark.parametrize("model_path", ["foobar", "rasa", "README.md", None])
 def test_get_model_exception(model_path: Optional[Text]):
     with pytest.raises(ModelNotFound):