improve support for V2 variant legacy checkpoints

This commit enhances support for V2 variant (epsilon and v-predict)
import and conversion to diffusers, by prompting the user to select
the proper config file during startup time autoimport as well as
in the invokeai installer script..

ldm/invoke/CLI.py

@@ -158,10 +158,16 @@ def main():
     except Exception as e:
         report_model_error(opt, e)
 
+    # completer is the readline object
+    completer = get_completer(opt, models=gen.model_manager.list_models())
+            
     # try to autoconvert new models
     if path := opt.autoimport:
         gen.model_manager.heuristic_import(
-            str(path), convert=False, commit_to_conf=opt.conf
+            str(path),
+            convert=False,
+            commit_to_conf=opt.conf,
+            config_file_callback=lambda x: _pick_configuration_file(completer,x),
         )
 
     if path := opt.autoconvert:
@@ -180,7 +186,7 @@ def main():
         )
 
     try:
-        main_loop(gen, opt)
+        main_loop(gen, opt, completer)
     except KeyboardInterrupt:
         print(
             f'\nGoodbye!\nYou can start InvokeAI again by running the "invoke.bat" (or "invoke.sh") script from {Globals.root}'
@@ -191,7 +197,7 @@ def main():
 
 
 # TODO: main_loop() has gotten busy. Needs to be refactored.
-def main_loop(gen, opt):
+def main_loop(gen, opt, completer):
     """prompt/read/execute loop"""
     global infile
     done = False
@@ -202,7 +208,6 @@ def main_loop(gen, opt):
     # The readline completer reads history from the .dream_history file located in the
     # output directory specified at the time of script launch. We do not currently support
     # changing the history file midstream when the output directory is changed.
-    completer = get_completer(opt, models=gen.model_manager.list_models())
     set_default_output_dir(opt, completer)
     if gen.model:
         add_embedding_terms(gen, completer)
@@ -661,17 +666,8 @@ def import_model(model_path: str, gen, opt, completer, convert=False):
         model_name=model_name,
         description=model_desc,
         convert=convert,
+        config_file_callback=lambda x: _pick_configuration_file(completer,x),
     )
-
-    if not imported_name:
-        if config_file := _pick_configuration_file(completer):
-            imported_name = gen.model_manager.heuristic_import(
-                model_path,
-                model_name=model_name,
-                description=model_desc,
-                convert=convert,
-                model_config_file=config_file,
-            )
     if not imported_name:
         print("** Aborting import.")
         return
@@ -687,14 +683,14 @@ def import_model(model_path: str, gen, opt, completer, convert=False):
     completer.update_models(gen.model_manager.list_models())
     print(f">> {imported_name} successfully installed")
 
-def _pick_configuration_file(completer)->Path:
+def _pick_configuration_file(completer, checkpoint_path: Path)->Path:
     print(
-"""
-Please select the type of this model:
+f"""
+Please select the type of the model at checkpoint {checkpoint_path}:
 [1] A Stable Diffusion v1.x ckpt/safetensors model
 [2] A Stable Diffusion v1.x inpainting ckpt/safetensors model
-[3] A Stable Diffusion v2.x base model (512 pixels)
-[4] A Stable Diffusion v2.x v-predictive model (768 pixels)
+[3] A Stable Diffusion v2.x base model (512 pixels; there should be no 'parameterization:' line in its yaml file)
+[4] A Stable Diffusion v2.x v-predictive model (768 pixels; look for a 'parameterization: "v"' line in its yaml file)
 [5] Other (you will be prompted to enter the config file path)
 [Q] I have no idea! Skip the import.
 """)

ldm/invoke/config/model_install_backend.py

@@ -109,6 +109,7 @@ def install_requested_models(
                 model_manager.heuristic_import(
                     path_url_or_repo,
                     convert=convert_to_diffusers,
+                    config_file_callback=_pick_configuration_file,
                     commit_to_conf=config_file_path
                 )
             except KeyboardInterrupt:
@@ -138,6 +139,45 @@ def yes_or_no(prompt: str, default_yes=True):
     else:
         return response[0] in ("y", "Y")
 
+# -------------------------------------
+def _pick_configuration_file(checkpoint_path: Path)->Path:
+    print(
+"""
+Please select the type of this model:
+[1] A Stable Diffusion v1.x ckpt/safetensors model
+[2] A Stable Diffusion v1.x inpainting ckpt/safetensors model
+[3] A Stable Diffusion v2.x base model (512 pixels; no 'parameterization:' in its yaml file)
+[4] A Stable Diffusion v2.x v-predictive model (768 pixels; look for 'parameterization: "v"' in its yaml file)
+[5] Other (you will be prompted to enter the config file path)
+[Q] I have no idea! Skip the import.
+""")
+    choices = [
+        global_config_dir() / 'stable-diffusion' / x
+        for x in [
+                'v1-inference.yaml',
+                'v1-inpainting-inference.yaml',
+                'v2-inference.yaml',
+                'v2-inference-v.yaml',
+        ]
+    ]
+
+    ok = False
+    while not ok:
+        try:
+            choice = input('select 0-5, Q > ').strip()
+            if choice.startswith(('q','Q')):
+                return
+            if choice == '5':
+                choice = Path(input('Select config file for this model> ').strip()).absolute()
+                ok = choice.exists()
+            else:
+                choice = choices[int(choice)-1]
+                ok = True
+        except (ValueError, IndexError):
+            print(f'{choice} is not a valid choice')
+        except EOFError:
+            return
+    return choice
 
 # -------------------------------------
 def get_root(root: str = None) -> str:

ldm/invoke/model_manager.py

@@ -19,7 +19,7 @@ import warnings
 from enum import Enum
 from pathlib import Path
 from shutil import move, rmtree
-from typing import Any, Optional, Union
+from typing import Any, Optional, Union, Callable
 
 import safetensors
 import safetensors.torch
@@ -765,6 +765,7 @@ class ModelManager(object):
             description: str = None,
             model_config_file: Path = None,
             commit_to_conf: Path = None,
+            config_file_callback: Callable[[Path],Path] = None,
     ) -> str:
         """
         Accept a string which could be:
@@ -838,7 +839,10 @@ class ModelManager(object):
                     Path(thing).rglob("*.safetensors")
                 ):
                     if model_name := self.heuristic_import(
-                        str(m), convert, commit_to_conf=commit_to_conf
+                            str(m),
+                            convert,
+                            commit_to_conf=commit_to_conf,
+                            config_file_callback=config_file_callback,
                     ):
                         print(f" >> {model_name} successfully imported")
                 return model_name
@@ -901,11 +905,14 @@ class ModelManager(object):
                 print(
                     f"** {thing} is a V2 checkpoint file, but its parameterization cannot be determined. Please provide configuration file path."
                 )
-                return
             else:
                 print(
                     f"** {thing} is a legacy checkpoint file but not a known Stable Diffusion model. Please provide configuration file path."
                 )
+
+            if not model_config_file and config_file_callback:
+                model_config_file = config_file_callback(model_path)
+            if not model_config_file:
                 return
 
         if model_config_file.name.startswith('v2'):