mostly working

ldm/invoke/config/model_install.py

@@ -243,7 +243,7 @@ class addModelsForm(npyscreen.FormMultiPageAction):
 
         # URLs and the like
         self.parentApp.import_model_paths = self.import_model_paths.value.split()
-        self.parentApp.convert_to_diffusers = self.convert_models.value != 0
+        self.parentApp.convert_to_diffusers = self.convert_models.value == 1
 
 # big chunk of dead code
 # was intended to be a status area in which output of installation steps (including tqdm) was logged in real time

ldm/invoke/config/model_install_backend.py

@@ -92,11 +92,16 @@ def install_requested_models(
     if external_models and len(external_models)>0:
         print("== INSTALLING EXTERNAL MODELS ==")
         for path_url_or_repo in external_models:
+            try:
                 model_manager.heuristic_import(
                     path_url_or_repo,
                     convert=convert_to_diffusers,
                     commit_to_conf=config_file_path
                 )
+            except KeyboardInterrupt:
+                sys.exit(-1)
+            except Exception:
+                pass
             
 # -------------------------------------
 def yes_or_no(prompt: str, default_yes=True):

ldm/invoke/generator/diffusers_pipeline.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import dataclasses
 import inspect
+import psutil
 import secrets
 import sys
 from dataclasses import dataclass, field

ldm/invoke/model_manager.py

@@ -643,7 +643,7 @@ class ModelManager(object):
         self.add_model(model_name, new_config, True)
         if commit_to_conf:
             self.commit(commit_to_conf)
-        return True
+        return model_name
 
     def import_ckpt_model(
         self,
@@ -710,6 +710,8 @@ class ModelManager(object):
         model_path = None
         thing = path_url_or_repo  # to save typing
 
+        print(f'here i am; thing={thing}, convert={convert}')
+        
         if thing.startswith(('http:','https:','ftp:')):
             print(f'* {thing} appears to be a URL')
             model_path = self._resolve_path(thing, 'models/ldm/stable-diffusion-v1')  # _resolve_path does a download if needed
@@ -720,17 +722,23 @@ class ModelManager(object):
             
         elif Path(thing).is_dir() and Path(thing, 'model_index.json').exists():
             print(f'* {thing} appears to be a diffusers file on disk')
-            self.import_diffusers_model(thing, commit_to_conf=commit_to_conf)
+            model_name = self.import_diffusers_model(
+                thing,
+                vae=dict(repo_id='stabilityai/sd-vae-ft-mse'),                
+                commit_to_conf=commit_to_conf
+            )
 
         elif Path(thing).is_dir():
             print(f'* {thing} appears to be a directory. Will scan for models to import')
             for m in list(Path(thing).rglob('*.ckpt')) + list(Path(thing).rglob('*.safetensors')):
-                self.heuristic_import(m, convert, commit_to_conf=commit_to_conf)
+                print('***',m)
+                self.heuristic_import(str(m), convert, commit_to_conf=commit_to_conf)
             return
 
         elif re.match(r'^[\w.+-]+/[\w.+-]+$', thing):
             print(f'* {thing} appears to be a HuggingFace diffusers repo_id')
-            self.import_diffuser_model(thing, commit_to_conf=commit_to_conf)
+            model_name = self.import_diffuser_model(thing, commit_to_conf=commit_to_conf)
+            pipeline,_,_,_ = self._load_diffusers_model(self.config[model_name])
 
         else:
             print(f"* {thing}: Unknown thing. Please provide a URL, file path, directory or HuggingFace repo_id")
@@ -749,7 +757,7 @@ class ModelManager(object):
             print(f'* {thing} appears to be an SD-v2 model; model will be converted to diffusers format')
             model_config_file = Path(Globals.root,'configs/stable-diffusion/v2-inference-v.yaml')
             convert = True
-        elif re.search('inpaint', model_path, flags=re.IGNORECASE):
+        elif re.search('inpaint', str(model_path), flags=re.IGNORECASE):
             print(f'* {thing} appears to be an SD-v1 inpainting model')
             model_config_file = Path(Globals.root,'configs/stable-diffusion/v1-inpainting-inference.yaml')
         else:
@@ -833,7 +841,7 @@ class ModelManager(object):
             return
 
         model_name = model_name or diffusers_path.name
-        model_description = model_description or "Optimized version of {model_name}"
+        model_description = model_description or f"Optimized version of {model_name}"
         print(f">> Optimizing {model_name} (30-60s)")
         try:
             # By passing the specified VAE to the conversion function, the autoencoder

ldm/util.py

@@ -318,8 +318,6 @@ def download_with_resume(url: str, dest: Path, access_token: str = None) -> Path
     else:
         dest.parent.mkdir(parents=True, exist_ok=True)
 
-    print(f'DEBUG: after many manipulations, dest={dest}')
-
     header = {"Authorization": f"Bearer {access_token}"} if access_token else {}
     open_mode = "wb"
     exist_size = 0