support conversion of v2 models

- This PR introduces a CLI prompt for the proper configuration file to
  use when converting a ckpt file, in order to support both inpainting
  and v2 models files.

- When user tries to directly !import a v2 model, it prints out a proper
  warning that v2 ckpts are not directly supported.

ldm/invoke/CLI.py

@@ -657,15 +657,8 @@ def import_ckpt_model(path_or_url: Union[Path, str], gen, opt, completer) -> Opt
         model_name=default_name,
         model_description=default_description
     )
-    config_file = None
+    if not (config_file := _ask_for_config_file(path_or_url, completer)):
-    default = Path(Globals.root,'configs/stable-diffusion/v1-inference.yaml')
+        return
-
-    completer.complete_extensions(('.yaml','.yml'))
-    completer.set_line(str(default))
-    done = False
-    while not done:
-        config_file = input('Configuration file for this model: ').strip()
-        done = os.path.exists(config_file)
 
     completer.complete_extensions(('.ckpt','.safetensors'))
     vae = None
@@ -693,8 +686,14 @@ def import_ckpt_model(path_or_url: Union[Path, str], gen, opt, completer) -> Opt
 def _verify_load(model_name:str, gen)->bool:
     print('>> Verifying that new model loads...')
     current_model = gen.model_name
-    if not gen.model_manager.get_model(model_name):
+    try:
+        if not gen.model_manager.get_model(model_name):
+            return False
+    except Exception as e:
+        print(f'** model failed to load: {str(e)}')
+        print('** note that importing 2.X checkpoints is not supported. Please use !convert_model instead.')
         return False
+    
     do_switch = input('Keep model loaded? [y] ')
     if len(do_switch)==0 or do_switch[0] in ('y','Y'):
         gen.set_model(model_name)
@@ -709,6 +708,35 @@ def _get_model_name_and_desc(model_manager,completer,model_name:str='',model_des
     model_description = input(f'Description for this model [{model_description}]: ').strip() or model_description
     return model_name, model_description
 
+def _ask_for_config_file(model_path: Union[str,Path], completer)->Path:
+    default = 1
+    if re.search('inpaint',str(model_path),flags=re.IGNORECASE):
+        default = 3
+    choices={
+        '1': 'v1-inference.yaml',
+        '2': 'v2-inference-v.yaml',
+        '3': 'v1-inpainting-inference.yaml',
+    }
+    print(f'''What type of model is this?:
+[1] A model based on Stable Diffusion 1.X
+[2] A model based on Stable Diffusion 2.X
+[3] An inpainting model based on Stable Diffusion 1.X
+[4] Something else''')
+    choice = input(f'Your choice: [{default}] ')
+    choice = choice.strip() or default
+    if config_file := choices.get(choice,None):
+        return Path('configs','stable-diffusion',config_file)
+
+    # otherwise ask user to select
+    done = False
+    completer.complete_extensions(('.yaml','.yml'))
+    completer.set_line(str(Path(Globals.root,'configs/stable-diffusion/')))
+    while not done:
+        config_path = input('Configuration file for this model (leave blank to abort): ').strip()
+        done = not config_path or os.path.exists(config_path)
+    return config_path
+
+
 def optimize_model(model_name_or_path:str, gen, opt, completer):
     manager = gen.model_manager
     ckpt_path = None
@@ -731,12 +759,9 @@ def optimize_model(model_name_or_path:str, gen, opt, completer):
             ckpt_path.stem,
             f'Converted model {ckpt_path.stem}'
         )
-        is_inpainting = input('Is this an inpainting model? [n] ').startswith(('y','Y'))
+        original_config_file = _ask_for_config_file(model_name_or_path, completer)
-        original_config_file = Path(
+        if not original_config_file:
-            'configs',
+            return
-            'stable-diffusion',
-            'v1-inpainting-inference.yaml' if is_inpainting else 'v1-inference.yaml'
-        )
     else:
         print(f'** {model_name_or_path} is neither an existing model nor the path to a .ckpt file')
         return