Download all model types. (#3944)

Author: lstein

invokeai/backend/install/invokeai_configure.py

@@ -558,7 +558,7 @@ def default_user_selections(program_opts: Namespace) -> InstallSelections:
 
 # -------------------------------------
 def initialize_rootdir(root: Path, yes_to_all: bool = False):
-    logger.info("** INITIALIZING INVOKEAI RUNTIME DIRECTORY **")
+    logger.info("Initializing InvokeAI runtime directory")
     for name in (
             "models",
             "databases",
@@ -788,15 +788,14 @@ def main():
                 sys.exit(0)
 
         if opt.skip_support_models:
-            logger.info("SKIPPING SUPPORT MODEL DOWNLOADS PER USER REQUEST")
+            logger.info("Skipping support models at user's request")
         else:
-            logger.info("CHECKING/UPDATING SUPPORT MODELS")
+            logger.info("Installing support models")
             download_support_models()
 
         if opt.skip_sd_weights:
-            logger.warning("SKIPPING DIFFUSION WEIGHTS DOWNLOAD PER USER REQUEST")
+            logger.warning("Skipping diffusion weights download per user request")
         elif models_to_download:
-            logger.info("DOWNLOADING DIFFUSION WEIGHTS")
             process_and_execute(opt, models_to_download)
 
         postscript(errors=errors)

invokeai/backend/install/model_install_backend.py

@@ -149,16 +149,17 @@ def list_models(self, model_type):
         for i in installed:
             print(f"{i['model_name']}\t{i['base_model']}\t{i['path']}")
 
-    def starter_models(self)->Set[str]:
+    # logic here a little reversed to maintain backward compatibility
+    def starter_models(self, all_models: bool=False)->Set[str]:
         models = set()
         for key, value in self.datasets.items():
             name,base,model_type = ModelManager.parse_key(key)
-            if model_type==ModelType.Main:
+            if all_models or model_type==ModelType.Main:
                 models.add(key)
         return models
 
     def recommended_models(self)->Set[str]:
-        starters = self.starter_models()
+        starters = self.starter_models(all_models=True)
         return set([x for x in starters if self.datasets[x].get('recommended',False)])
 
     def default_model(self)->str: