final tidying before marking PR as ready for review

- Replace AnyModelLoader with ModelLoaderRegistry
- Fix type check errors in multiple files
- Remove apparently unneeded `get_model_config_enum()` method from model manager
- Remove last vestiges of old model manager
- Updated tests and documentation

resolve conflict with seamless.py

tests/backend/model_manager/model_loading/test_model_load.py

@@ -4,18 +4,27 @@ Test model loading
 
 from pathlib import Path
 
-from invokeai.app.services.model_install import ModelInstallServiceBase
-from invokeai.app.services.model_load import ModelLoadServiceBase
+from invokeai.app.services.model_manager import ModelManagerServiceBase
 from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 
-def test_loading(mm2_installer: ModelInstallServiceBase, mm2_loader: ModelLoadServiceBase, embedding_file: Path):
-    store = mm2_installer.record_store
+
+def test_loading(mm2_model_manager: ModelManagerServiceBase, embedding_file: Path):
+    store = mm2_model_manager.store
     matches = store.search_by_attr(model_name="test_embedding")
     assert len(matches) == 0
-    key = mm2_installer.register_path(embedding_file)
-    loaded_model = mm2_loader.load_model_by_config(store.get_model(key))
+    key = mm2_model_manager.install.register_path(embedding_file)
+    loaded_model = mm2_model_manager.load_model_by_config(store.get_model(key))
     assert loaded_model is not None
     assert loaded_model.config.key == key
     with loaded_model as model:
         assert isinstance(model, TextualInversionModelRaw)
+    loaded_model_2 = mm2_model_manager.load_model_by_key(key)
+    assert loaded_model.config.key == loaded_model_2.config.key
+
+    loaded_model_3 = mm2_model_manager.load_model_by_attr(
+        model_name=loaded_model.config.name,
+        model_type=loaded_model.config.type,
+        base_model=loaded_model.config.base,
+    )
+    assert loaded_model.config.key == loaded_model_3.config.key

tests/backend/model_manager/model_manager_fixtures.py

@@ -6,17 +6,17 @@ from pathlib import Path
 from typing import Any, Dict, List
 
 import pytest
-from pytest import FixtureRequest
 from pydantic import BaseModel
+from pytest import FixtureRequest
 from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.download import DownloadQueueServiceBase, DownloadQueueService
+from invokeai.app.services.download import DownloadQueueService, DownloadQueueServiceBase
 from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.services.model_manager import ModelManagerServiceBase, ModelManagerService
-from invokeai.app.services.model_load import ModelLoadServiceBase, ModelLoadService
 from invokeai.app.services.model_install import ModelInstallService, ModelInstallServiceBase
+from invokeai.app.services.model_load import ModelLoadService, ModelLoadServiceBase
+from invokeai.app.services.model_manager import ModelManagerService, ModelManagerServiceBase
 from invokeai.app.services.model_metadata import ModelMetadataStoreBase, ModelMetadataStoreSQL
 from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
 from invokeai.backend.model_manager.config import (
@@ -95,9 +95,7 @@ def mm2_app_config(mm2_root_dir: Path) -> InvokeAIAppConfig:
 
 
 @pytest.fixture
-def mm2_download_queue(mm2_session: Session,
-                       request: FixtureRequest
-                       ) -> DownloadQueueServiceBase:
+def mm2_download_queue(mm2_session: Session, request: FixtureRequest) -> DownloadQueueServiceBase:
     download_queue = DownloadQueueService(requests_session=mm2_session)
     download_queue.start()
 
@@ -107,30 +105,34 @@ def mm2_download_queue(mm2_session: Session,
     request.addfinalizer(stop_queue)
     return download_queue
 
+
 @pytest.fixture
 def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStoreBase:
     return mm2_record_store.metadata_store
 
+
 @pytest.fixture
 def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceBase) -> ModelLoadServiceBase:
     ram_cache = ModelCache(
         logger=InvokeAILogger.get_logger(),
         max_cache_size=mm2_app_config.ram_cache_size,
-        max_vram_cache_size=mm2_app_config.vram_cache_size
+        max_vram_cache_size=mm2_app_config.vram_cache_size,
     )
     convert_cache = ModelConvertCache(mm2_app_config.models_convert_cache_path)
-    return ModelLoadService(app_config=mm2_app_config,
-                            record_store=mm2_record_store,
-                            ram_cache=ram_cache,
-                            convert_cache=convert_cache,
-                          )
+    return ModelLoadService(
+        app_config=mm2_app_config,
+        ram_cache=ram_cache,
+        convert_cache=convert_cache,
+    )
+
 
 @pytest.fixture
-def mm2_installer(mm2_app_config: InvokeAIAppConfig,
-                  mm2_download_queue: DownloadQueueServiceBase,
-                  mm2_session: Session,
-                  request: FixtureRequest,
-                  ) -> ModelInstallServiceBase:
+def mm2_installer(
+    mm2_app_config: InvokeAIAppConfig,
+    mm2_download_queue: DownloadQueueServiceBase,
+    mm2_session: Session,
+    request: FixtureRequest,
+) -> ModelInstallServiceBase:
     logger = InvokeAILogger.get_logger()
     db = create_mock_sqlite_database(mm2_app_config, logger)
     events = DummyEventService()
@@ -213,15 +215,13 @@ def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceBas
     store.add_model("test_config_5", raw5)
     return store
 
+
 @pytest.fixture
-def mm2_model_manager(mm2_record_store: ModelRecordServiceBase,
-                      mm2_installer: ModelInstallServiceBase,
-                      mm2_loader: ModelLoadServiceBase) -> ModelManagerServiceBase:
-    return ModelManagerService(
-        store=mm2_record_store,
-        install=mm2_installer,
-        load=mm2_loader
-    )
+def mm2_model_manager(
+    mm2_record_store: ModelRecordServiceBase, mm2_installer: ModelInstallServiceBase, mm2_loader: ModelLoadServiceBase
+) -> ModelManagerServiceBase:
+    return ModelManagerService(store=mm2_record_store, install=mm2_installer, load=mm2_loader)
+
 
 @pytest.fixture
 def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
@@ -306,5 +306,3 @@ def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
                 ),
             )
     return sess
-
-

tests/backend/model_manager/test_lora.py

@@ -5,8 +5,8 @@
 import pytest
 import torch
 
-from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.lora import LoRALayer, LoRAModelRaw
+from invokeai.backend.model_patcher import ModelPatcher
 
 
 @pytest.mark.parametrize(

tests/backend/model_manager/test_memory_snapshot.py

@@ -1,7 +1,8 @@
 import pytest
 
-from invokeai.backend.model_manager.util.libc_util import Struct_mallinfo2
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
+from invokeai.backend.model_manager.util.libc_util import Struct_mallinfo2
+
 
 def test_memory_snapshot_capture():
     """Smoke test of MemorySnapshot.capture()."""