convert implemented; need router

invokeai/app/api/routers/models.py

@@ -22,6 +22,11 @@ class ImportModelResponse(BaseModel):
     info: AddModelResult = Field(description="The model info")
     status: str = Field(description="The status of the API response")
 
+class ConvertModelResponse(BaseModel):
+    name: str = Field(description="The name of the imported model")
+    info: AddModelResult = Field(description="The model info")
+    status: str = Field(description="The status of the API response")
+    
 class ModelsList(BaseModel):
     models: list[Union[tuple(OPENAPI_MODEL_CONFIGS)]]
 

invokeai/app/services/model_manager_service.py

@@ -5,8 +5,7 @@ from __future__ import annotations
 import torch
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Optional, Union, Callable, List, Tuple, types, TYPE_CHECKING
+from typing import Optional, Union, Callable, List, Set, Dict, Tuple, types, TYPE_CHECKING
-from dataclasses import dataclass
 
 from invokeai.backend.model_management.model_manager import (
     ModelManager,
@@ -14,6 +13,8 @@ from invokeai.backend.model_management.model_manager import (
     ModelType,
     SubModelType,
     ModelInfo,
+    AddModelResult,
+    SchedulerPredictionType,
 )
 from invokeai.app.models.exceptions import CanceledException
 from .config import InvokeAIAppConfig
@@ -111,7 +112,7 @@ class ModelManagerServiceBase(ABC):
         model_type: ModelType,
         model_attributes: dict,
         clobber: bool = False
-    ) -> None:
+    ) -> AddModelResult:
         """
         Update the named model with a dictionary of attributes. Will fail with an
         assertion error if the name already exists. Pass clobber=True to overwrite.
@@ -135,6 +136,27 @@ class ModelManagerServiceBase(ABC):
         """
         pass
 
+    @abstractmethod
+    def convert_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: Union[ModelType.Main,ModelType.Vae],
+    ) -> AddModelResult:
+        """
+        Convert a checkpoint file into a diffusers folder, deleting the cached
+        version and deleting the original checkpoint file if it is in the models
+        directory.
+        :param model_name: Name of the model to convert
+        :param base_model: Base model type
+        :param model_type: Type of model ['vae' or 'main']
+
+        This will raise a ValueError unless the model is not a checkpoint. It will
+        also raise a ValueError in the event that there is a similarly-named diffusers
+        directory already in place.
+        """
+        pass
+
     @abstractmethod
     def heuristic_import(self,
                          items_to_import: Set[str],
@@ -336,6 +358,26 @@ class ModelManagerService(ModelManagerServiceBase):
         self.logger.debug(f'delete model {model_name}')
         self.mgr.del_model(model_name, base_model, model_type)
 
+    def convert_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: Union[ModelType.Main,ModelType.Vae],
+    ) -> AddModelResult:
+        """
+        Convert a checkpoint file into a diffusers folder, deleting the cached
+        version and deleting the original checkpoint file if it is in the models
+        directory.
+        :param model_name: Name of the model to convert
+        :param base_model: Base model type
+        :param model_type: Type of model ['vae' or 'main']
+
+        This will raise a ValueError unless the model is not a checkpoint. It will
+        also raise a ValueError in the event that there is a similarly-named diffusers
+        directory already in place.
+        """
+        self.logger.debug(f'convert model {model_name}')        
+        return self.mgr.convert_model(model_name, base_model, model_type)
 
     def commit(self, conf_file: Optional[Path]=None):
         """

invokeai/backend/model_management/model_manager.py

@@ -234,7 +234,7 @@ import textwrap
 from dataclasses import dataclass
 from pathlib import Path
 from typing import Optional, List, Tuple, Union, Dict, Set, Callable, types
-from shutil import rmtree
+from shutil import rmtree, move
 
 import torch
 from omegaconf import OmegaConf
@@ -620,6 +620,60 @@ class ModelManager(object):
             config = model_config,
         )
 
+    def convert_model (
+            self,
+            model_name: str,
+            base_model: BaseModelType,
+            model_type: Union[ModelType.Main,ModelType.Vae],
+    ) -> AddModelResult:
+        '''
+        Convert a checkpoint file into a diffusers folder, deleting the cached
+        version and deleting the original checkpoint file if it is in the models
+        directory.
+        :param model_name: Name of the model to convert
+        :param base_model: Base model type
+        :param model_type: Type of model ['vae' or 'main']
+
+        This will raise a ValueError unless the model is a checkpoint.
+        '''
+        info = self.model_info(model_name, base_model, model_type)
+        if info["model_format"] != "checkpoint":
+            raise ValueError(f"not a checkpoint format model: {model_name}")
+
+        # We are taking advantage of a side effect of get_model() that converts check points
+        # into cached diffusers directories stored at `location`. It doesn't matter
+        # what submodeltype we request here, so we get the smallest.
+        submodel = {"submodel_type": SubModelType.Tokenizer} if model_type==ModelType.Main else {}
+        model = self.get_model(model_name,
+                               base_model,
+                               model_type,
+                               **submodel,
+                               )
+        checkpoint_path = self.app_config.root_path / info["path"]
+        old_diffusers_path = self.app_config.models_path / model.location
+        new_diffusers_path = self.app_config.models_path / base_model / model_type / model_name
+        if new_diffusers_path.exists():
+            raise ValueError(f"A diffusers model already exists at {new_path}")
+
+        try:
+            move(old_diffusers_path,new_diffusers_path)
+            info["model_format"] = "diffusers"
+            info["path"] = str(new_diffusers_path.relative_to(self.app_config.root_path))
+            info.pop('config')
+
+            result = self.add_model(model_name, base_model, model_type,
+                                    model_attributes = info,
+                                    clobber=True)
+        except:
+            # something went wrong, so don't leave dangling diffusers model in directory or it will cause a duplicate model error!
+            rmtree(new_diffusers_path)
+            raise
+        
+        if checkpoint_path.exists() and checkpoint_path.is_relative_to(self.app_config.models_path):
+            checkpoint_path.unlink()
+        
+        return result
+    
     def search_models(self, search_folder):
         self.logger.info(f"Finding Models In: {search_folder}")
         models_folder_ckpt = Path(search_folder).glob("**/*.ckpt")

invokeai/backend/model_management/models/stable_diffusion.py

@@ -116,7 +116,7 @@ class StableDiffusion1Model(DiffusersModel):
                 version=BaseModelType.StableDiffusion1,
                 model_config=config,
                 output_path=output_path,
-            )
+           )
         else:
             return model_path