feat: refactor services folder/module structure

Refactor services folder/module structure.

**Motivation**

While working on our services I've repeatedly encountered circular imports and a general lack of clarity regarding where to put things. The structure introduced goes a long way towards resolving those issues, setting us up for a clean structure going forward.

**Services**

Services are now in their own folder with a few files:

- `services/{service_name}/__init__.py`: init as needed, mostly empty now
- `services/{service_name}/{service_name}_base.py`: the base class for the service
- `services/{service_name}/{service_name}_{impl_type}.py`: the default concrete implementation of the service - typically one of `sqlite`, `default`, or `memory`
- `services/{service_name}/{service_name}_common.py`: any common items - models, exceptions, utilities, etc

Though it's a bit verbose to have the service name both as the folder name and the prefix for files, I found it is _extremely_ confusing to have all of the base classes just be named `base.py`. So, at the cost of some verbosity when importing things, I've included the service name in the filename.

There are some minor logic changes. For example, in `InvocationProcessor`, instead of assigning the model manager service to a variable to be used later in the file, the service is used directly via the `Invoker`.

**Shared**

Things that are used across disparate services are in `services/shared/`:

- `default_graphs.py`: previously in `services/`
- `graphs.py`: previously in `services/`
- `paginatation`: generic pagination models used in a few services
- `sqlite`: the `SqliteDatabase` class, other sqlite-specific things

invokeai/app/api/dependencies.py

@@ -2,33 +2,34 @@
 
 from logging import Logger
 
-from invokeai.app.services.board_image_record_storage import SqliteBoardImageRecordStorage
-from invokeai.app.services.board_images import BoardImagesService
-from invokeai.app.services.board_record_storage import SqliteBoardRecordStorage
-from invokeai.app.services.boards import BoardService
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
-from invokeai.app.services.images import ImageService
-from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.resource_name import SimpleNameService
-from invokeai.app.services.session_processor.session_processor_default import DefaultSessionProcessor
-from invokeai.app.services.session_queue.session_queue_sqlite import SqliteSessionQueue
-from invokeai.app.services.shared.sqlite import SqliteDatabase
-from invokeai.app.services.urls import LocalUrlService
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
 
-from ..services.default_graphs import create_system_graphs
+from ..services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
-from ..services.graph import GraphExecutionState, LibraryGraph
+from ..services.board_images.board_images_default import BoardImagesService
-from ..services.image_file_storage import DiskImageFileStorage
+from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
-from ..services.invocation_queue import MemoryInvocationQueue
+from ..services.boards.boards_default import BoardService
+from ..services.config import InvokeAIAppConfig
+from ..services.image_files.image_files_disk import DiskImageFileStorage
+from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
+from ..services.images.images_default import ImageService
+from ..services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
+from ..services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
+from ..services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from ..services.invocation_services import InvocationServices
-from ..services.invocation_stats import InvocationStatsService
+from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
 from ..services.invoker import Invoker
-from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
+from ..services.item_storage.item_storage_sqlite import SqliteItemStorage
-from ..services.model_manager_service import ModelManagerService
+from ..services.latents_storage.latents_storage_disk import DiskLatentsStorage
-from ..services.processor import DefaultInvocationProcessor
+from ..services.latents_storage.latents_storage_forward_cache import ForwardCacheLatentsStorage
-from ..services.sqlite import SqliteItemStorage
+from ..services.model_manager.model_manager_default import ModelManagerService
+from ..services.names.names_default import SimpleNameService
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor
+from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
+from ..services.shared.default_graphs import create_system_graphs
+from ..services.shared.graph import GraphExecutionState, LibraryGraph
+from ..services.shared.sqlite import SqliteDatabase
+from ..services.urls.urls_default import LocalUrlService
 from .events import FastAPIEventService
 
 

invokeai/app/api/events.py

@@ -7,7 +7,7 @@ from typing import Any
 
 from fastapi_events.dispatcher import dispatch
 
-from ..services.events import EventServiceBase
+from ..services.events.events_base import EventServiceBase
 
 
 class FastAPIEventService(EventServiceBase):

invokeai/app/api/routers/boards.py

@@ -4,8 +4,8 @@ from fastapi import Body, HTTPException, Path, Query
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
-from invokeai.app.services.board_record_storage import BoardChanges
+from invokeai.app.services.board_records.board_records_common import BoardChanges
-from invokeai.app.services.models.board_record import BoardDTO
+from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
 from ..dependencies import ApiDependencies

invokeai/app/api/routers/images.py

@@ -8,8 +8,8 @@ from PIL import Image
 from pydantic import BaseModel, Field
 
 from invokeai.app.invocations.metadata import ImageMetadata
-from invokeai.app.models.image import ImageCategory, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
-from invokeai.app.services.models.image_record import ImageDTO, ImageRecordChanges, ImageUrlsDTO
+from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
 from ..dependencies import ApiDependencies

invokeai/app/api/routers/session_queue.py

@@ -18,9 +18,9 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueItemDTO,
     SessionQueueStatus,
 )
+from invokeai.app.services.shared.graph import Graph
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
 
-from ...services.graph import Graph
 from ..dependencies import ApiDependencies
 
 session_queue_router = APIRouter(prefix="/v1/queue", tags=["queue"])

invokeai/app/api/routers/sessions.py

@@ -11,7 +11,7 @@ from invokeai.app.services.shared.pagination import PaginatedResults
 # Importing * is bad karma but needed here for node detection
 from ...invocations import *  # noqa: F401 F403
 from ...invocations.baseinvocation import BaseInvocation
-from ...services.graph import Edge, EdgeConnection, Graph, GraphExecutionState, NodeAlreadyExecutedError
+from ...services.shared.graph import Edge, EdgeConnection, Graph, GraphExecutionState, NodeAlreadyExecutedError
 from ..dependencies import ApiDependencies
 
 session_router = APIRouter(prefix="/v1/sessions", tags=["sessions"])

invokeai/app/api/sockets.py

@@ -5,7 +5,7 @@ from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event
 from socketio import ASGIApp, AsyncServer
 
-from ..services.events import EventServiceBase
+from ..services.events.events_base import EventServiceBase
 
 
 class SocketIO:

invokeai/app/invocations/baseinvocation.py

@@ -28,7 +28,7 @@ from pydantic import BaseModel, Field, validator
 from pydantic.fields import ModelField, Undefined
 from pydantic.typing import NoArgAnyCallable
 
-from invokeai.app.services.config.invokeai_config import InvokeAIAppConfig
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
 
 if TYPE_CHECKING:
     from ..services.invocation_services import InvocationServices

invokeai/app/invocations/controlnet_image_processors.py

@@ -27,9 +27,9 @@ from PIL import Image
 from pydantic import BaseModel, Field, validator
 
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 
 from ...backend.model_management import BaseModelType
-from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,

invokeai/app/invocations/cv.py

@@ -6,7 +6,7 @@ import numpy
 from PIL import Image, ImageOps
 
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.models.image import ImageCategory, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 
 from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 

invokeai/app/invocations/image.py

@@ -9,10 +9,10 @@ from PIL import Image, ImageChops, ImageFilter, ImageOps
 
 from invokeai.app.invocations.metadata import CoreMetadata
 from invokeai.app.invocations.primitives import BoardField, ColorField, ImageField, ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
-from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import BaseInvocation, FieldDescriptions, Input, InputField, InvocationContext, invocation
 
 

invokeai/app/invocations/infill.py

@@ -7,12 +7,12 @@ import numpy as np
 from PIL import Image, ImageOps
 
 from invokeai.app.invocations.primitives import ColorField, ImageField, ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.util.misc import SEED_MAX, get_random_seed
 from invokeai.backend.image_util.cv2_inpaint import cv2_inpaint
 from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
-from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 

invokeai/app/invocations/latent.py

@@ -34,6 +34,7 @@ from invokeai.app.invocations.primitives import (
     build_latents_output,
 )
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.util.controlnet_utils import prepare_control_image
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
@@ -54,7 +55,6 @@ from ...backend.stable_diffusion.diffusers_pipeline import (
 from ...backend.stable_diffusion.diffusion.shared_invokeai_diffusion import PostprocessingSettings
 from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from ...backend.util.devices import choose_precision, choose_torch_device
-from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,

invokeai/app/invocations/onnx.py

@@ -14,13 +14,13 @@ from tqdm import tqdm
 
 from invokeai.app.invocations.metadata import CoreMetadata
 from invokeai.app.invocations.primitives import ConditioningField, ConditioningOutput, ImageField, ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend import BaseModelType, ModelType, SubModelType
 
 from ...backend.model_management import ONNXModelPatcher
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.util import choose_torch_device
-from ..models.image import ImageCategory, ResourceOrigin
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,

invokeai/app/invocations/upscale.py

@@ -10,7 +10,7 @@ from PIL import Image
 from realesrgan import RealESRGANer
 
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.models.image import ImageCategory, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.backend.util.devices import choose_torch_device
 
 from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation

invokeai/app/models/exceptions.py

@@ -1,4 +0,0 @@
-class CanceledException(Exception):
-    """Execution canceled by user."""
-
-    pass

invokeai/app/models/image.py

@@ -1,71 +0,0 @@
-from enum import Enum
-
-from pydantic import BaseModel, Field
-
-from invokeai.app.util.metaenum import MetaEnum
-
-
-class ProgressImage(BaseModel):
-    """The progress image sent intermittently during processing"""
-
-    width: int = Field(description="The effective width of the image in pixels")
-    height: int = Field(description="The effective height of the image in pixels")
-    dataURL: str = Field(description="The image data as a b64 data URL")
-
-
-class ResourceOrigin(str, Enum, metaclass=MetaEnum):
-    """The origin of a resource (eg image).
-
-    - INTERNAL: The resource was created by the application.
-    - EXTERNAL: The resource was not created by the application.
-    This may be a user-initiated upload, or an internal application upload (eg Canvas init image).
-    """
-
-    INTERNAL = "internal"
-    """The resource was created by the application."""
-    EXTERNAL = "external"
-    """The resource was not created by the application.
-    This may be a user-initiated upload, or an internal application upload (eg Canvas init image).
-    """
-
-
-class InvalidOriginException(ValueError):
-    """Raised when a provided value is not a valid ResourceOrigin.
-
-    Subclasses `ValueError`.
-    """
-
-    def __init__(self, message="Invalid resource origin."):
-        super().__init__(message)
-
-
-class ImageCategory(str, Enum, metaclass=MetaEnum):
-    """The category of an image.
-
-    - GENERAL: The image is an output, init image, or otherwise an image without a specialized purpose.
-    - MASK: The image is a mask image.
-    - CONTROL: The image is a ControlNet control image.
-    - USER: The image is a user-provide image.
-    - OTHER: The image is some other type of image with a specialized purpose. To be used by external nodes.
-    """
-
-    GENERAL = "general"
-    """GENERAL: The image is an output, init image, or otherwise an image without a specialized purpose."""
-    MASK = "mask"
-    """MASK: The image is a mask image."""
-    CONTROL = "control"
-    """CONTROL: The image is a ControlNet control image."""
-    USER = "user"
-    """USER: The image is a user-provide image."""
-    OTHER = "other"
-    """OTHER: The image is some other type of image with a specialized purpose. To be used by external nodes."""
-
-
-class InvalidImageCategoryException(ValueError):
-    """Raised when a provided value is not a valid ImageCategory.
-
-    Subclasses `ValueError`.
-    """
-
-    def __init__(self, message="Invalid image category."):
-        super().__init__(message)

invokeai/app/services/board_image_records/board_image_records_base.py

@@ -0,0 +1,47 @@
+from abc import ABC, abstractmethod
+from typing import Optional
+
+
+class BoardImageRecordStorageBase(ABC):
+    """Abstract base class for the one-to-many board-image relationship record storage."""
+
+    @abstractmethod
+    def add_image_to_board(
+        self,
+        board_id: str,
+        image_name: str,
+    ) -> None:
+        """Adds an image to a board."""
+        pass
+
+    @abstractmethod
+    def remove_image_from_board(
+        self,
+        image_name: str,
+    ) -> None:
+        """Removes an image from a board."""
+        pass
+
+    @abstractmethod
+    def get_all_board_image_names_for_board(
+        self,
+        board_id: str,
+    ) -> list[str]:
+        """Gets all board images for a board, as a list of the image names."""
+        pass
+
+    @abstractmethod
+    def get_board_for_image(
+        self,
+        image_name: str,
+    ) -> Optional[str]:
+        """Gets an image's board id, if it has one."""
+        pass
+
+    @abstractmethod
+    def get_image_count_for_board(
+        self,
+        board_id: str,
+    ) -> int:
+        """Gets the number of images for a board."""
+        pass

invokeai/app/services/board_image_records/board_image_records_sqlite.py

@@ -1,56 +1,12 @@
 import sqlite3
 import threading
-from abc import ABC, abstractmethod
 from typing import Optional, cast
 
-from invokeai.app.services.models.image_record import ImageRecord, deserialize_image_record
+from invokeai.app.services.image_records.image_records_common import ImageRecord, deserialize_image_record
-from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 
-
+from .board_image_records_base import BoardImageRecordStorageBase
-class BoardImageRecordStorageBase(ABC):
-    """Abstract base class for the one-to-many board-image relationship record storage."""
-
-    @abstractmethod
-    def add_image_to_board(
-        self,
-        board_id: str,
-        image_name: str,
-    ) -> None:
-        """Adds an image to a board."""
-        pass
-
-    @abstractmethod
-    def remove_image_from_board(
-        self,
-        image_name: str,
-    ) -> None:
-        """Removes an image from a board."""
-        pass
-
-    @abstractmethod
-    def get_all_board_image_names_for_board(
-        self,
-        board_id: str,
-    ) -> list[str]:
-        """Gets all board images for a board, as a list of the image names."""
-        pass
-
-    @abstractmethod
-    def get_board_for_image(
-        self,
-        image_name: str,
-    ) -> Optional[str]:
-        """Gets an image's board id, if it has one."""
-        pass
-
-    @abstractmethod
-    def get_image_count_for_board(
-        self,
-        board_id: str,
-    ) -> int:
-        """Gets the number of images for a board."""
-        pass
 
 
 class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):

invokeai/app/services/board_images.py

@@ -1,85 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Optional
-
-from invokeai.app.services.board_record_storage import BoardRecord
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.models.board_record import BoardDTO
-
-
-class BoardImagesServiceABC(ABC):
-    """High-level service for board-image relationship management."""
-
-    @abstractmethod
-    def add_image_to_board(
-        self,
-        board_id: str,
-        image_name: str,
-    ) -> None:
-        """Adds an image to a board."""
-        pass
-
-    @abstractmethod
-    def remove_image_from_board(
-        self,
-        image_name: str,
-    ) -> None:
-        """Removes an image from a board."""
-        pass
-
-    @abstractmethod
-    def get_all_board_image_names_for_board(
-        self,
-        board_id: str,
-    ) -> list[str]:
-        """Gets all board images for a board, as a list of the image names."""
-        pass
-
-    @abstractmethod
-    def get_board_for_image(
-        self,
-        image_name: str,
-    ) -> Optional[str]:
-        """Gets an image's board id, if it has one."""
-        pass
-
-
-class BoardImagesService(BoardImagesServiceABC):
-    __invoker: Invoker
-
-    def start(self, invoker: Invoker) -> None:
-        self.__invoker = invoker
-
-    def add_image_to_board(
-        self,
-        board_id: str,
-        image_name: str,
-    ) -> None:
-        self.__invoker.services.board_image_records.add_image_to_board(board_id, image_name)
-
-    def remove_image_from_board(
-        self,
-        image_name: str,
-    ) -> None:
-        self.__invoker.services.board_image_records.remove_image_from_board(image_name)
-
-    def get_all_board_image_names_for_board(
-        self,
-        board_id: str,
-    ) -> list[str]:
-        return self.__invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
-
-    def get_board_for_image(
-        self,
-        image_name: str,
-    ) -> Optional[str]:
-        board_id = self.__invoker.services.board_image_records.get_board_for_image(image_name)
-        return board_id
-
-
-def board_record_to_dto(board_record: BoardRecord, cover_image_name: Optional[str], image_count: int) -> BoardDTO:
-    """Converts a board record to a board DTO."""
-    return BoardDTO(
-        **board_record.dict(exclude={"cover_image_name"}),
-        cover_image_name=cover_image_name,
-        image_count=image_count,
-    )

invokeai/app/services/board_images/board_images_base.py

@@ -0,0 +1,39 @@
+from abc import ABC, abstractmethod
+from typing import Optional
+
+
+class BoardImagesServiceABC(ABC):
+    """High-level service for board-image relationship management."""
+
+    @abstractmethod
+    def add_image_to_board(
+        self,
+        board_id: str,
+        image_name: str,
+    ) -> None:
+        """Adds an image to a board."""
+        pass
+
+    @abstractmethod
+    def remove_image_from_board(
+        self,
+        image_name: str,
+    ) -> None:
+        """Removes an image from a board."""
+        pass
+
+    @abstractmethod
+    def get_all_board_image_names_for_board(
+        self,
+        board_id: str,
+    ) -> list[str]:
+        """Gets all board images for a board, as a list of the image names."""
+        pass
+
+    @abstractmethod
+    def get_board_for_image(
+        self,
+        image_name: str,
+    ) -> Optional[str]:
+        """Gets an image's board id, if it has one."""
+        pass

invokeai/app/services/board_images/board_images_default.py

@@ -0,0 +1,38 @@
+from typing import Optional
+
+from invokeai.app.services.invoker import Invoker
+
+from .board_images_base import BoardImagesServiceABC
+
+
+class BoardImagesService(BoardImagesServiceABC):
+    __invoker: Invoker
+
+    def start(self, invoker: Invoker) -> None:
+        self.__invoker = invoker
+
+    def add_image_to_board(
+        self,
+        board_id: str,
+        image_name: str,
+    ) -> None:
+        self.__invoker.services.board_image_records.add_image_to_board(board_id, image_name)
+
+    def remove_image_from_board(
+        self,
+        image_name: str,
+    ) -> None:
+        self.__invoker.services.board_image_records.remove_image_from_board(image_name)
+
+    def get_all_board_image_names_for_board(
+        self,
+        board_id: str,
+    ) -> list[str]:
+        return self.__invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
+
+    def get_board_for_image(
+        self,
+        image_name: str,
+    ) -> Optional[str]:
+        board_id = self.__invoker.services.board_image_records.get_board_for_image(image_name)
+        return board_id

invokeai/app/services/board_records/board_records_base.py

@@ -0,0 +1,55 @@
+from abc import ABC, abstractmethod
+
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+
+from .board_records_common import BoardChanges, BoardRecord
+
+
+class BoardRecordStorageBase(ABC):
+    """Low-level service responsible for interfacing with the board record store."""
+
+    @abstractmethod
+    def delete(self, board_id: str) -> None:
+        """Deletes a board record."""
+        pass
+
+    @abstractmethod
+    def save(
+        self,
+        board_name: str,
+    ) -> BoardRecord:
+        """Saves a board record."""
+        pass
+
+    @abstractmethod
+    def get(
+        self,
+        board_id: str,
+    ) -> BoardRecord:
+        """Gets a board record."""
+        pass
+
+    @abstractmethod
+    def update(
+        self,
+        board_id: str,
+        changes: BoardChanges,
+    ) -> BoardRecord:
+        """Updates a board record."""
+        pass
+
+    @abstractmethod
+    def get_many(
+        self,
+        offset: int = 0,
+        limit: int = 10,
+    ) -> OffsetPaginatedResults[BoardRecord]:
+        """Gets many board records."""
+        pass
+
+    @abstractmethod
+    def get_all(
+        self,
+    ) -> list[BoardRecord]:
+        """Gets all board records."""
+        pass

invokeai/app/services/board_records/board_records_common.py

@@ -1,7 +1,7 @@
 from datetime import datetime
 from typing import Optional, Union
 
-from pydantic import Field
+from pydantic import BaseModel, Extra, Field
 
 from invokeai.app.util.misc import get_iso_timestamp
 from invokeai.app.util.model_exclude_null import BaseModelExcludeNull
@@ -24,15 +24,6 @@ class BoardRecord(BaseModelExcludeNull):
     """The name of the cover image of the board."""
 
 
-class BoardDTO(BoardRecord):
-    """Deserialized board record with cover image URL and image count."""
-
-    cover_image_name: Optional[str] = Field(description="The name of the board's cover image.")
-    """The URL of the thumbnail of the most recent image in the board."""
-    image_count: int = Field(description="The number of images in the board.")
-    """The number of images in the board."""
-
-
 def deserialize_board_record(board_dict: dict) -> BoardRecord:
     """Deserializes a board record."""
 
@@ -53,3 +44,29 @@ def deserialize_board_record(board_dict: dict) -> BoardRecord:
         updated_at=updated_at,
         deleted_at=deleted_at,
     )
+
+
+class BoardChanges(BaseModel, extra=Extra.forbid):
+    board_name: Optional[str] = Field(description="The board's new name.")
+    cover_image_name: Optional[str] = Field(description="The name of the board's new cover image.")
+
+
+class BoardRecordNotFoundException(Exception):
+    """Raised when an board record is not found."""
+
+    def __init__(self, message="Board record not found"):
+        super().__init__(message)
+
+
+class BoardRecordSaveException(Exception):
+    """Raised when an board record cannot be saved."""
+
+    def __init__(self, message="Board record not saved"):
+        super().__init__(message)
+
+
+class BoardRecordDeleteException(Exception):
+    """Raised when an board record cannot be deleted."""
+
+    def __init__(self, message="Board record not deleted"):
+        super().__init__(message)

invokeai/app/services/board_records/board_records_sqlite.py

@@ -1,90 +1,20 @@
 import sqlite3
 import threading
-from abc import ABC, abstractmethod
+from typing import Union, cast
-from typing import Optional, Union, cast
 
-from pydantic import BaseModel, Extra, Field
-
-from invokeai.app.services.models.board_record import BoardRecord, deserialize_board_record
-from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.app.util.misc import uuid_string
 
-
+from .board_records_base import BoardRecordStorageBase
-class BoardChanges(BaseModel, extra=Extra.forbid):
+from .board_records_common import (
-    board_name: Optional[str] = Field(description="The board's new name.")
+    BoardChanges,
-    cover_image_name: Optional[str] = Field(description="The name of the board's new cover image.")
+    BoardRecord,
-
+    BoardRecordDeleteException,
-
+    BoardRecordNotFoundException,
-class BoardRecordNotFoundException(Exception):
+    BoardRecordSaveException,
-    """Raised when an board record is not found."""
+    deserialize_board_record,
-
+)
-    def __init__(self, message="Board record not found"):
-        super().__init__(message)
-
-
-class BoardRecordSaveException(Exception):
-    """Raised when an board record cannot be saved."""
-
-    def __init__(self, message="Board record not saved"):
-        super().__init__(message)
-
-
-class BoardRecordDeleteException(Exception):
-    """Raised when an board record cannot be deleted."""
-
-    def __init__(self, message="Board record not deleted"):
-        super().__init__(message)
-
-
-class BoardRecordStorageBase(ABC):
-    """Low-level service responsible for interfacing with the board record store."""
-
-    @abstractmethod
-    def delete(self, board_id: str) -> None:
-        """Deletes a board record."""
-        pass
-
-    @abstractmethod
-    def save(
-        self,
-        board_name: str,
-    ) -> BoardRecord:
-        """Saves a board record."""
-        pass
-
-    @abstractmethod
-    def get(
-        self,
-        board_id: str,
-    ) -> BoardRecord:
-        """Gets a board record."""
-        pass
-
-    @abstractmethod
-    def update(
-        self,
-        board_id: str,
-        changes: BoardChanges,
-    ) -> BoardRecord:
-        """Updates a board record."""
-        pass
-
-    @abstractmethod
-    def get_many(
-        self,
-        offset: int = 0,
-        limit: int = 10,
-    ) -> OffsetPaginatedResults[BoardRecord]:
-        """Gets many board records."""
-        pass
-
-    @abstractmethod
-    def get_all(
-        self,
-    ) -> list[BoardRecord]:
-        """Gets all board records."""
-        pass
 
 
 class SqliteBoardRecordStorage(BoardRecordStorageBase):

invokeai/app/services/boards/boards_base.py

@@ -0,0 +1,59 @@
+from abc import ABC, abstractmethod
+
+from invokeai.app.services.board_records.board_records_common import BoardChanges
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+
+from .boards_common import BoardDTO
+
+
+class BoardServiceABC(ABC):
+    """High-level service for board management."""
+
+    @abstractmethod
+    def create(
+        self,
+        board_name: str,
+    ) -> BoardDTO:
+        """Creates a board."""
+        pass
+
+    @abstractmethod
+    def get_dto(
+        self,
+        board_id: str,
+    ) -> BoardDTO:
+        """Gets a board."""
+        pass
+
+    @abstractmethod
+    def update(
+        self,
+        board_id: str,
+        changes: BoardChanges,
+    ) -> BoardDTO:
+        """Updates a board."""
+        pass
+
+    @abstractmethod
+    def delete(
+        self,
+        board_id: str,
+    ) -> None:
+        """Deletes a board."""
+        pass
+
+    @abstractmethod
+    def get_many(
+        self,
+        offset: int = 0,
+        limit: int = 10,
+    ) -> OffsetPaginatedResults[BoardDTO]:
+        """Gets many boards."""
+        pass
+
+    @abstractmethod
+    def get_all(
+        self,
+    ) -> list[BoardDTO]:
+        """Gets all boards."""
+        pass

invokeai/app/services/boards/boards_common.py

@@ -0,0 +1,23 @@
+from typing import Optional
+
+from pydantic import Field
+
+from ..board_records.board_records_common import BoardRecord
+
+
+class BoardDTO(BoardRecord):
+    """Deserialized board record with cover image URL and image count."""
+
+    cover_image_name: Optional[str] = Field(description="The name of the board's cover image.")
+    """The URL of the thumbnail of the most recent image in the board."""
+    image_count: int = Field(description="The number of images in the board.")
+    """The number of images in the board."""
+
+
+def board_record_to_dto(board_record: BoardRecord, cover_image_name: Optional[str], image_count: int) -> BoardDTO:
+    """Converts a board record to a board DTO."""
+    return BoardDTO(
+        **board_record.dict(exclude={"cover_image_name"}),
+        cover_image_name=cover_image_name,
+        image_count=image_count,
+    )

invokeai/app/services/boards/boards_default.py

@@ -1,63 +1,10 @@
-from abc import ABC, abstractmethod
+from invokeai.app.services.board_records.board_records_common import BoardChanges
-
+from invokeai.app.services.boards.boards_common import BoardDTO
-from invokeai.app.services.board_images import board_record_to_dto
-from invokeai.app.services.board_record_storage import BoardChanges
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.models.board_record import BoardDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
-
+from .boards_base import BoardServiceABC
-class BoardServiceABC(ABC):
+from .boards_common import board_record_to_dto
-    """High-level service for board management."""
-
-    @abstractmethod
-    def create(
-        self,
-        board_name: str,
-    ) -> BoardDTO:
-        """Creates a board."""
-        pass
-
-    @abstractmethod
-    def get_dto(
-        self,
-        board_id: str,
-    ) -> BoardDTO:
-        """Gets a board."""
-        pass
-
-    @abstractmethod
-    def update(
-        self,
-        board_id: str,
-        changes: BoardChanges,
-    ) -> BoardDTO:
-        """Updates a board."""
-        pass
-
-    @abstractmethod
-    def delete(
-        self,
-        board_id: str,
-    ) -> None:
-        """Deletes a board."""
-        pass
-
-    @abstractmethod
-    def get_many(
-        self,
-        offset: int = 0,
-        limit: int = 10,
-    ) -> OffsetPaginatedResults[BoardDTO]:
-        """Gets many boards."""
-        pass
-
-    @abstractmethod
-    def get_all(
-        self,
-    ) -> list[BoardDTO]:
-        """Gets all boards."""
-        pass
 
 
 class BoardService(BoardServiceABC):

invokeai/app/services/config/__init__.py

@@ -2,5 +2,5 @@
 Init file for InvokeAI configure package
 """
 
-from .base import PagingArgumentParser  # noqa F401
+from .config_base import PagingArgumentParser  # noqa F401
-from .invokeai_config import InvokeAIAppConfig, get_invokeai_config  # noqa F401
+from .config_default import InvokeAIAppConfig, get_invokeai_config  # noqa F401

invokeai/app/services/config/config_base.py

@@ -12,7 +12,6 @@ from __future__ import annotations
 
 import argparse
 import os
-import pydoc
 import sys
 from argparse import ArgumentParser
 from pathlib import Path
@@ -21,16 +20,7 @@ from typing import ClassVar, Dict, List, Literal, Optional, Union, get_args, get
 from omegaconf import DictConfig, ListConfig, OmegaConf
 from pydantic import BaseSettings
 
-
+from invokeai.app.services.config.config_common import PagingArgumentParser, int_or_float_or_str
-class PagingArgumentParser(argparse.ArgumentParser):
-    """
-    A custom ArgumentParser that uses pydoc to page its output.
-    It also supports reading defaults from an init file.
-    """
-
-    def print_help(self, file=None):
-        text = self.format_help()
-        pydoc.pager(text)
 
 
 class InvokeAISettings(BaseSettings):
@@ -223,18 +213,3 @@ class InvokeAISettings(BaseSettings):
                 action=argparse.BooleanOptionalAction if field.type_ == bool else "store",
                 help=field.field_info.description,
             )
-
-
-def int_or_float_or_str(value: str) -> Union[int, float, str]:
-    """
-    Workaround for argparse type checking.
-    """
-    try:
-        return int(value)
-    except Exception as e:  # noqa F841
-        pass
-    try:
-        return float(value)
-    except Exception as e:  # noqa F841
-        pass
-    return str(value)

invokeai/app/services/config/config_common.py

@@ -0,0 +1,41 @@
+# Copyright (c) 2023 Lincoln Stein (https://github.com/lstein) and the InvokeAI Development Team
+
+"""
+Base class for the InvokeAI configuration system.
+It defines a type of pydantic BaseSettings object that
+is able to read and write from an omegaconf-based config file,
+with overriding of settings from environment variables and/or
+the command line.
+"""
+
+from __future__ import annotations
+
+import argparse
+import pydoc
+from typing import Union
+
+
+class PagingArgumentParser(argparse.ArgumentParser):
+    """
+    A custom ArgumentParser that uses pydoc to page its output.
+    It also supports reading defaults from an init file.
+    """
+
+    def print_help(self, file=None):
+        text = self.format_help()
+        pydoc.pager(text)
+
+
+def int_or_float_or_str(value: str) -> Union[int, float, str]:
+    """
+    Workaround for argparse type checking.
+    """
+    try:
+        return int(value)
+    except Exception as e:  # noqa F841
+        pass
+    try:
+        return float(value)
+    except Exception as e:  # noqa F841
+        pass
+    return str(value)

invokeai/app/services/config/config_default.py

@@ -177,7 +177,7 @@ from typing import ClassVar, Dict, List, Literal, Optional, Union, get_type_hint
 from omegaconf import DictConfig, OmegaConf
 from pydantic import Field, parse_obj_as
 
-from .base import InvokeAISettings
+from .config_base import InvokeAISettings
 
 INIT_FILE = Path("invokeai.yaml")
 DB_FILE = Path("invokeai.db")

invokeai/app/services/events/events_base.py

@@ -2,8 +2,8 @@
 
 from typing import Any, Optional
 
-from invokeai.app.models.image import ProgressImage
+from invokeai.app.invocations.model import ModelInfo
-from invokeai.app.services.model_manager_service import BaseModelType, ModelInfo, ModelType, SubModelType
+from invokeai.app.services.invocation_processor.invocation_processor_common import ProgressImage
 from invokeai.app.services.session_queue.session_queue_common import (
     BatchStatus,
     EnqueueBatchResult,
@@ -11,6 +11,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueStatus,
 )
 from invokeai.app.util.misc import get_timestamp
+from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 
 
 class EventServiceBase:

invokeai/app/services/image_files/image_files_base.py

@@ -0,0 +1,42 @@
+from abc import ABC, abstractmethod
+from typing import Optional
+
+from PIL.Image import Image as PILImageType
+
+
+class ImageFileStorageBase(ABC):
+    """Low-level service responsible for storing and retrieving image files."""
+
+    @abstractmethod
+    def get(self, image_name: str) -> PILImageType:
+        """Retrieves an image as PIL Image."""
+        pass
+
+    @abstractmethod
+    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
+        """Gets the internal path to an image or thumbnail."""
+        pass
+
+    # TODO: We need to validate paths before starlette makes the FileResponse, else we get a
+    # 500 internal server error. I don't like having this method on the service.
+    @abstractmethod
+    def validate_path(self, path: str) -> bool:
+        """Validates the path given for an image or thumbnail."""
+        pass
+
+    @abstractmethod
+    def save(
+        self,
+        image: PILImageType,
+        image_name: str,
+        metadata: Optional[dict] = None,
+        workflow: Optional[str] = None,
+        thumbnail_size: int = 256,
+    ) -> None:
+        """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
+        pass
+
+    @abstractmethod
+    def delete(self, image_name: str) -> None:
+        """Deletes an image and its thumbnail (if one exists)."""
+        pass

invokeai/app/services/image_files/image_files_common.py

@@ -0,0 +1,20 @@
+# TODO: Should these excpetions subclass existing python exceptions?
+class ImageFileNotFoundException(Exception):
+    """Raised when an image file is not found in storage."""
+
+    def __init__(self, message="Image file not found"):
+        super().__init__(message)
+
+
+class ImageFileSaveException(Exception):
+    """Raised when an image cannot be saved."""
+
+    def __init__(self, message="Image file not saved"):
+        super().__init__(message)
+
+
+class ImageFileDeleteException(Exception):
+    """Raised when an image cannot be deleted."""
+
+    def __init__(self, message="Image file not deleted"):
+        super().__init__(message)

invokeai/app/services/image_files/image_files_disk.py

@@ -1,6 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
 import json
-from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
 from typing import Dict, Optional, Union
@@ -12,65 +11,8 @@ from send2trash import send2trash
 from invokeai.app.services.config.invokeai_config import InvokeAIAppConfig
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
-
+from .image_files_base import ImageFileStorageBase
-# TODO: Should these excpetions subclass existing python exceptions?
+from .image_files_common import ImageFileDeleteException, ImageFileNotFoundException, ImageFileSaveException
-class ImageFileNotFoundException(Exception):
-    """Raised when an image file is not found in storage."""
-
-    def __init__(self, message="Image file not found"):
-        super().__init__(message)
-
-
-class ImageFileSaveException(Exception):
-    """Raised when an image cannot be saved."""
-
-    def __init__(self, message="Image file not saved"):
-        super().__init__(message)
-
-
-class ImageFileDeleteException(Exception):
-    """Raised when an image cannot be deleted."""
-
-    def __init__(self, message="Image file not deleted"):
-        super().__init__(message)
-
-
-class ImageFileStorageBase(ABC):
-    """Low-level service responsible for storing and retrieving image files."""
-
-    @abstractmethod
-    def get(self, image_name: str) -> PILImageType:
-        """Retrieves an image as PIL Image."""
-        pass
-
-    @abstractmethod
-    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
-        """Gets the internal path to an image or thumbnail."""
-        pass
-
-    # TODO: We need to validate paths before starlette makes the FileResponse, else we get a
-    # 500 internal server error. I don't like having this method on the service.
-    @abstractmethod
-    def validate_path(self, path: str) -> bool:
-        """Validates the path given for an image or thumbnail."""
-        pass
-
-    @abstractmethod
-    def save(
-        self,
-        image: PILImageType,
-        image_name: str,
-        metadata: Optional[dict] = None,
-        workflow: Optional[str] = None,
-        thumbnail_size: int = 256,
-    ) -> None:
-        """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
-        pass
-
-    @abstractmethod
-    def delete(self, image_name: str) -> None:
-        """Deletes an image and its thumbnail (if one exists)."""
-        pass
 
 
 class DiskImageFileStorage(ImageFileStorageBase):

invokeai/app/services/image_records/image_records_base.py

@@ -0,0 +1,84 @@
+from abc import ABC, abstractmethod
+from datetime import datetime
+from typing import Optional
+
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+
+from .image_records_common import ImageCategory, ImageRecord, ImageRecordChanges, ResourceOrigin
+
+
+class ImageRecordStorageBase(ABC):
+    """Low-level service responsible for interfacing with the image record store."""
+
+    # TODO: Implement an `update()` method
+
+    @abstractmethod
+    def get(self, image_name: str) -> ImageRecord:
+        """Gets an image record."""
+        pass
+
+    @abstractmethod
+    def get_metadata(self, image_name: str) -> Optional[dict]:
+        """Gets an image's metadata'."""
+        pass
+
+    @abstractmethod
+    def update(
+        self,
+        image_name: str,
+        changes: ImageRecordChanges,
+    ) -> None:
+        """Updates an image record."""
+        pass
+
+    @abstractmethod
+    def get_many(
+        self,
+        offset: Optional[int] = None,
+        limit: Optional[int] = None,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+    ) -> OffsetPaginatedResults[ImageRecord]:
+        """Gets a page of image records."""
+        pass
+
+    # TODO: The database has a nullable `deleted_at` column, currently unused.
+    # Should we implement soft deletes? Would need coordination with ImageFileStorage.
+    @abstractmethod
+    def delete(self, image_name: str) -> None:
+        """Deletes an image record."""
+        pass
+
+    @abstractmethod
+    def delete_many(self, image_names: list[str]) -> None:
+        """Deletes many image records."""
+        pass
+
+    @abstractmethod
+    def delete_intermediates(self) -> list[str]:
+        """Deletes all intermediate image records, returning a list of deleted image names."""
+        pass
+
+    @abstractmethod
+    def save(
+        self,
+        image_name: str,
+        image_origin: ResourceOrigin,
+        image_category: ImageCategory,
+        width: int,
+        height: int,
+        session_id: Optional[str],
+        node_id: Optional[str],
+        metadata: Optional[dict],
+        is_intermediate: bool = False,
+        starred: bool = False,
+    ) -> datetime:
+        """Saves an image record."""
+        pass
+
+    @abstractmethod
+    def get_most_recent_image_for_board(self, board_id: str) -> Optional[ImageRecord]:
+        """Gets the most recent image for a board."""
+        pass

invokeai/app/services/image_records/image_records_common.py

@@ -1,13 +1,117 @@
+# TODO: Should these excpetions subclass existing python exceptions?
 import datetime
+from enum import Enum
 from typing import Optional, Union
 
 from pydantic import Extra, Field, StrictBool, StrictStr
 
-from invokeai.app.models.image import ImageCategory, ResourceOrigin
+from invokeai.app.util.metaenum import MetaEnum
 from invokeai.app.util.misc import get_iso_timestamp
 from invokeai.app.util.model_exclude_null import BaseModelExcludeNull
 
 
+class ResourceOrigin(str, Enum, metaclass=MetaEnum):
+    """The origin of a resource (eg image).
+
+    - INTERNAL: The resource was created by the application.
+    - EXTERNAL: The resource was not created by the application.
+    This may be a user-initiated upload, or an internal application upload (eg Canvas init image).
+    """
+
+    INTERNAL = "internal"
+    """The resource was created by the application."""
+    EXTERNAL = "external"
+    """The resource was not created by the application.
+    This may be a user-initiated upload, or an internal application upload (eg Canvas init image).
+    """
+
+
+class InvalidOriginException(ValueError):
+    """Raised when a provided value is not a valid ResourceOrigin.
+
+    Subclasses `ValueError`.
+    """
+
+    def __init__(self, message="Invalid resource origin."):
+        super().__init__(message)
+
+
+class ImageCategory(str, Enum, metaclass=MetaEnum):
+    """The category of an image.
+
+    - GENERAL: The image is an output, init image, or otherwise an image without a specialized purpose.
+    - MASK: The image is a mask image.
+    - CONTROL: The image is a ControlNet control image.
+    - USER: The image is a user-provide image.
+    - OTHER: The image is some other type of image with a specialized purpose. To be used by external nodes.
+    """
+
+    GENERAL = "general"
+    """GENERAL: The image is an output, init image, or otherwise an image without a specialized purpose."""
+    MASK = "mask"
+    """MASK: The image is a mask image."""
+    CONTROL = "control"
+    """CONTROL: The image is a ControlNet control image."""
+    USER = "user"
+    """USER: The image is a user-provide image."""
+    OTHER = "other"
+    """OTHER: The image is some other type of image with a specialized purpose. To be used by external nodes."""
+
+
+class InvalidImageCategoryException(ValueError):
+    """Raised when a provided value is not a valid ImageCategory.
+
+    Subclasses `ValueError`.
+    """
+
+    def __init__(self, message="Invalid image category."):
+        super().__init__(message)
+
+
+class ImageRecordNotFoundException(Exception):
+    """Raised when an image record is not found."""
+
+    def __init__(self, message="Image record not found"):
+        super().__init__(message)
+
+
+class ImageRecordSaveException(Exception):
+    """Raised when an image record cannot be saved."""
+
+    def __init__(self, message="Image record not saved"):
+        super().__init__(message)
+
+
+class ImageRecordDeleteException(Exception):
+    """Raised when an image record cannot be deleted."""
+
+    def __init__(self, message="Image record not deleted"):
+        super().__init__(message)
+
+
+IMAGE_DTO_COLS = ", ".join(
+    list(
+        map(
+            lambda c: "images." + c,
+            [
+                "image_name",
+                "image_origin",
+                "image_category",
+                "width",
+                "height",
+                "session_id",
+                "node_id",
+                "is_intermediate",
+                "created_at",
+                "updated_at",
+                "deleted_at",
+                "starred",
+            ],
+        )
+    )
+)
+
+
 class ImageRecord(BaseModelExcludeNull):
     """Deserialized image record without metadata."""
 
@@ -66,41 +170,6 @@ class ImageRecordChanges(BaseModelExcludeNull, extra=Extra.forbid):
     """The image's new `starred` state."""
 
 
-class ImageUrlsDTO(BaseModelExcludeNull):
-    """The URLs for an image and its thumbnail."""
-
-    image_name: str = Field(description="The unique name of the image.")
-    """The unique name of the image."""
-    image_url: str = Field(description="The URL of the image.")
-    """The URL of the image."""
-    thumbnail_url: str = Field(description="The URL of the image's thumbnail.")
-    """The URL of the image's thumbnail."""
-
-
-class ImageDTO(ImageRecord, ImageUrlsDTO):
-    """Deserialized image record, enriched for the frontend."""
-
-    board_id: Optional[str] = Field(description="The id of the board the image belongs to, if one exists.")
-    """The id of the board the image belongs to, if one exists."""
-
-    pass
-
-
-def image_record_to_dto(
-    image_record: ImageRecord,
-    image_url: str,
-    thumbnail_url: str,
-    board_id: Optional[str],
-) -> ImageDTO:
-    """Converts an image record to an image DTO."""
-    return ImageDTO(
-        **image_record.dict(),
-        image_url=image_url,
-        thumbnail_url=thumbnail_url,
-        board_id=board_id,
-    )
-
-
 def deserialize_image_record(image_dict: dict) -> ImageRecord:
     """Deserializes an image record."""
 

invokeai/app/services/image_records/image_records_sqlite.py

@@ -1,136 +1,24 @@
 import json
 import sqlite3
 import threading
-from abc import ABC, abstractmethod
 from datetime import datetime
 from typing import Optional, cast
 
-from invokeai.app.models.image import ImageCategory, ResourceOrigin
-from invokeai.app.services.models.image_record import ImageRecord, ImageRecordChanges, deserialize_image_record
-from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 
-
+from .image_records_base import ImageRecordStorageBase
-# TODO: Should these excpetions subclass existing python exceptions?
+from .image_records_common import (
-class ImageRecordNotFoundException(Exception):
+    IMAGE_DTO_COLS,
-    """Raised when an image record is not found."""
+    ImageCategory,
-
+    ImageRecord,
-    def __init__(self, message="Image record not found"):
+    ImageRecordChanges,
-        super().__init__(message)
+    ImageRecordDeleteException,
-
+    ImageRecordNotFoundException,
-
+    ImageRecordSaveException,
-class ImageRecordSaveException(Exception):
+    ResourceOrigin,
-    """Raised when an image record cannot be saved."""
+    deserialize_image_record,
-
-    def __init__(self, message="Image record not saved"):
-        super().__init__(message)
-
-
-class ImageRecordDeleteException(Exception):
-    """Raised when an image record cannot be deleted."""
-
-    def __init__(self, message="Image record not deleted"):
-        super().__init__(message)
-
-
-IMAGE_DTO_COLS = ", ".join(
-    list(
-        map(
-            lambda c: "images." + c,
-            [
-                "image_name",
-                "image_origin",
-                "image_category",
-                "width",
-                "height",
-                "session_id",
-                "node_id",
-                "is_intermediate",
-                "created_at",
-                "updated_at",
-                "deleted_at",
-                "starred",
-            ],
 )
-    )
-)
-
-
-class ImageRecordStorageBase(ABC):
-    """Low-level service responsible for interfacing with the image record store."""
-
-    # TODO: Implement an `update()` method
-
-    @abstractmethod
-    def get(self, image_name: str) -> ImageRecord:
-        """Gets an image record."""
-        pass
-
-    @abstractmethod
-    def get_metadata(self, image_name: str) -> Optional[dict]:
-        """Gets an image's metadata'."""
-        pass
-
-    @abstractmethod
-    def update(
-        self,
-        image_name: str,
-        changes: ImageRecordChanges,
-    ) -> None:
-        """Updates an image record."""
-        pass
-
-    @abstractmethod
-    def get_many(
-        self,
-        offset: Optional[int] = None,
-        limit: Optional[int] = None,
-        image_origin: Optional[ResourceOrigin] = None,
-        categories: Optional[list[ImageCategory]] = None,
-        is_intermediate: Optional[bool] = None,
-        board_id: Optional[str] = None,
-    ) -> OffsetPaginatedResults[ImageRecord]:
-        """Gets a page of image records."""
-        pass
-
-    # TODO: The database has a nullable `deleted_at` column, currently unused.
-    # Should we implement soft deletes? Would need coordination with ImageFileStorage.
-    @abstractmethod
-    def delete(self, image_name: str) -> None:
-        """Deletes an image record."""
-        pass
-
-    @abstractmethod
-    def delete_many(self, image_names: list[str]) -> None:
-        """Deletes many image records."""
-        pass
-
-    @abstractmethod
-    def delete_intermediates(self) -> list[str]:
-        """Deletes all intermediate image records, returning a list of deleted image names."""
-        pass
-
-    @abstractmethod
-    def save(
-        self,
-        image_name: str,
-        image_origin: ResourceOrigin,
-        image_category: ImageCategory,
-        width: int,
-        height: int,
-        session_id: Optional[str],
-        node_id: Optional[str],
-        metadata: Optional[dict],
-        is_intermediate: bool = False,
-        starred: bool = False,
-    ) -> datetime:
-        """Saves an image record."""
-        pass
-
-    @abstractmethod
-    def get_most_recent_image_for_board(self, board_id: str) -> Optional[ImageRecord]:
-        """Gets the most recent image for a board."""
-        pass
 
 
 class SqliteImageRecordStorage(ImageRecordStorageBase):

invokeai/app/services/images/images_base.py

@@ -0,0 +1,129 @@
+from abc import ABC, abstractmethod
+from typing import Callable, Optional
+
+from PIL.Image import Image as PILImageType
+
+from invokeai.app.invocations.metadata import ImageMetadata
+from invokeai.app.services.image_records.image_records_common import (
+    ImageCategory,
+    ImageRecord,
+    ImageRecordChanges,
+    ResourceOrigin,
+)
+from invokeai.app.services.images.images_common import ImageDTO
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+
+
+class ImageServiceABC(ABC):
+    """High-level service for image management."""
+
+    _on_changed_callbacks: list[Callable[[ImageDTO], None]]
+    _on_deleted_callbacks: list[Callable[[str], None]]
+
+    def __init__(self) -> None:
+        self._on_changed_callbacks = list()
+        self._on_deleted_callbacks = list()
+
+    def on_changed(self, on_changed: Callable[[ImageDTO], None]) -> None:
+        """Register a callback for when an image is changed"""
+        self._on_changed_callbacks.append(on_changed)
+
+    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
+        """Register a callback for when an image is deleted"""
+        self._on_deleted_callbacks.append(on_deleted)
+
+    def _on_changed(self, item: ImageDTO) -> None:
+        for callback in self._on_changed_callbacks:
+            callback(item)
+
+    def _on_deleted(self, item_id: str) -> None:
+        for callback in self._on_deleted_callbacks:
+            callback(item_id)
+
+    @abstractmethod
+    def create(
+        self,
+        image: PILImageType,
+        image_origin: ResourceOrigin,
+        image_category: ImageCategory,
+        node_id: Optional[str] = None,
+        session_id: Optional[str] = None,
+        board_id: Optional[str] = None,
+        is_intermediate: bool = False,
+        metadata: Optional[dict] = None,
+        workflow: Optional[str] = None,
+    ) -> ImageDTO:
+        """Creates an image, storing the file and its metadata."""
+        pass
+
+    @abstractmethod
+    def update(
+        self,
+        image_name: str,
+        changes: ImageRecordChanges,
+    ) -> ImageDTO:
+        """Updates an image."""
+        pass
+
+    @abstractmethod
+    def get_pil_image(self, image_name: str) -> PILImageType:
+        """Gets an image as a PIL image."""
+        pass
+
+    @abstractmethod
+    def get_record(self, image_name: str) -> ImageRecord:
+        """Gets an image record."""
+        pass
+
+    @abstractmethod
+    def get_dto(self, image_name: str) -> ImageDTO:
+        """Gets an image DTO."""
+        pass
+
+    @abstractmethod
+    def get_metadata(self, image_name: str) -> ImageMetadata:
+        """Gets an image's metadata."""
+        pass
+
+    @abstractmethod
+    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
+        """Gets an image's path."""
+        pass
+
+    @abstractmethod
+    def validate_path(self, path: str) -> bool:
+        """Validates an image's path."""
+        pass
+
+    @abstractmethod
+    def get_url(self, image_name: str, thumbnail: bool = False) -> str:
+        """Gets an image's or thumbnail's URL."""
+        pass
+
+    @abstractmethod
+    def get_many(
+        self,
+        offset: int = 0,
+        limit: int = 10,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+    ) -> OffsetPaginatedResults[ImageDTO]:
+        """Gets a paginated list of image DTOs."""
+        pass
+
+    @abstractmethod
+    def delete(self, image_name: str):
+        """Deletes an image."""
+        pass
+
+    @abstractmethod
+    def delete_intermediates(self) -> int:
+        """Deletes all intermediate images."""
+        pass
+
+    @abstractmethod
+    def delete_images_on_board(self, board_id: str):
+        """Deletes all images on a board."""
+        pass

invokeai/app/services/images/images_common.py

@@ -0,0 +1,41 @@
+from typing import Optional
+
+from pydantic import Field
+
+from invokeai.app.services.image_records.image_records_common import ImageRecord
+from invokeai.app.util.model_exclude_null import BaseModelExcludeNull
+
+
+class ImageUrlsDTO(BaseModelExcludeNull):
+    """The URLs for an image and its thumbnail."""
+
+    image_name: str = Field(description="The unique name of the image.")
+    """The unique name of the image."""
+    image_url: str = Field(description="The URL of the image.")
+    """The URL of the image."""
+    thumbnail_url: str = Field(description="The URL of the image's thumbnail.")
+    """The URL of the image's thumbnail."""
+
+
+class ImageDTO(ImageRecord, ImageUrlsDTO):
+    """Deserialized image record, enriched for the frontend."""
+
+    board_id: Optional[str] = Field(description="The id of the board the image belongs to, if one exists.")
+    """The id of the board the image belongs to, if one exists."""
+
+    pass
+
+
+def image_record_to_dto(
+    image_record: ImageRecord,
+    image_url: str,
+    thumbnail_url: str,
+    board_id: Optional[str],
+) -> ImageDTO:
+    """Converts an image record to an image DTO."""
+    return ImageDTO(
+        **image_record.dict(),
+        image_url=image_url,
+        thumbnail_url=thumbnail_url,
+        board_id=board_id,
+    )

invokeai/app/services/images/images_default.py

@@ -1,144 +1,30 @@
-from abc import ABC, abstractmethod
+from typing import Optional
-from typing import Callable, Optional
 
 from PIL.Image import Image as PILImageType
 
 from invokeai.app.invocations.metadata import ImageMetadata
-from invokeai.app.models.image import (
+from invokeai.app.services.invoker import Invoker
-    ImageCategory,
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-    InvalidImageCategoryException,
+from invokeai.app.util.metadata import get_metadata_graph_from_raw_session
-    InvalidOriginException,
+
-    ResourceOrigin,
+from ..image_files.image_files_common import (
-)
-from invokeai.app.services.image_file_storage import (
     ImageFileDeleteException,
     ImageFileNotFoundException,
     ImageFileSaveException,
 )
-from invokeai.app.services.image_record_storage import (
+from ..image_records.image_records_common import (
+    ImageCategory,
+    ImageRecord,
+    ImageRecordChanges,
     ImageRecordDeleteException,
     ImageRecordNotFoundException,
     ImageRecordSaveException,
+    InvalidImageCategoryException,
+    InvalidOriginException,
+    ResourceOrigin,
 )
-from invokeai.app.services.invoker import Invoker
+from .images_base import ImageServiceABC
-from invokeai.app.services.models.image_record import ImageDTO, ImageRecord, ImageRecordChanges, image_record_to_dto
+from .images_common import ImageDTO, image_record_to_dto
-from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.util.metadata import get_metadata_graph_from_raw_session
-
-
-class ImageServiceABC(ABC):
-    """High-level service for image management."""
-
-    _on_changed_callbacks: list[Callable[[ImageDTO], None]]
-    _on_deleted_callbacks: list[Callable[[str], None]]
-
-    def __init__(self) -> None:
-        self._on_changed_callbacks = list()
-        self._on_deleted_callbacks = list()
-
-    def on_changed(self, on_changed: Callable[[ImageDTO], None]) -> None:
-        """Register a callback for when an image is changed"""
-        self._on_changed_callbacks.append(on_changed)
-
-    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
-        """Register a callback for when an image is deleted"""
-        self._on_deleted_callbacks.append(on_deleted)
-
-    def _on_changed(self, item: ImageDTO) -> None:
-        for callback in self._on_changed_callbacks:
-            callback(item)
-
-    def _on_deleted(self, item_id: str) -> None:
-        for callback in self._on_deleted_callbacks:
-            callback(item_id)
-
-    @abstractmethod
-    def create(
-        self,
-        image: PILImageType,
-        image_origin: ResourceOrigin,
-        image_category: ImageCategory,
-        node_id: Optional[str] = None,
-        session_id: Optional[str] = None,
-        board_id: Optional[str] = None,
-        is_intermediate: bool = False,
-        metadata: Optional[dict] = None,
-        workflow: Optional[str] = None,
-    ) -> ImageDTO:
-        """Creates an image, storing the file and its metadata."""
-        pass
-
-    @abstractmethod
-    def update(
-        self,
-        image_name: str,
-        changes: ImageRecordChanges,
-    ) -> ImageDTO:
-        """Updates an image."""
-        pass
-
-    @abstractmethod
-    def get_pil_image(self, image_name: str) -> PILImageType:
-        """Gets an image as a PIL image."""
-        pass
-
-    @abstractmethod
-    def get_record(self, image_name: str) -> ImageRecord:
-        """Gets an image record."""
-        pass
-
-    @abstractmethod
-    def get_dto(self, image_name: str) -> ImageDTO:
-        """Gets an image DTO."""
-        pass
-
-    @abstractmethod
-    def get_metadata(self, image_name: str) -> ImageMetadata:
-        """Gets an image's metadata."""
-        pass
-
-    @abstractmethod
-    def get_path(self, image_name: str, thumbnail: bool = False) -> str:
-        """Gets an image's path."""
-        pass
-
-    @abstractmethod
-    def validate_path(self, path: str) -> bool:
-        """Validates an image's path."""
-        pass
-
-    @abstractmethod
-    def get_url(self, image_name: str, thumbnail: bool = False) -> str:
-        """Gets an image's or thumbnail's URL."""
-        pass
-
-    @abstractmethod
-    def get_many(
-        self,
-        offset: int = 0,
-        limit: int = 10,
-        image_origin: Optional[ResourceOrigin] = None,
-        categories: Optional[list[ImageCategory]] = None,
-        is_intermediate: Optional[bool] = None,
-        board_id: Optional[str] = None,
-    ) -> OffsetPaginatedResults[ImageDTO]:
-        """Gets a paginated list of image DTOs."""
-        pass
-
-    @abstractmethod
-    def delete(self, image_name: str):
-        """Deletes an image."""
-        pass
-
-    @abstractmethod
-    def delete_intermediates(self) -> int:
-        """Deletes all intermediate images."""
-        pass
-
-    @abstractmethod
-    def delete_images_on_board(self, board_id: str):
-        """Deletes all images on a board."""
-        pass
 
 
 class ImageService(ImageServiceABC):

invokeai/app/services/invocation_processor/invocation_processor_base.py

@@ -0,0 +1,5 @@
+from abc import ABC
+
+
+class InvocationProcessorABC(ABC):
+    pass

invokeai/app/services/invocation_processor/invocation_processor_common.py

@@ -0,0 +1,15 @@
+from pydantic import BaseModel, Field
+
+
+class ProgressImage(BaseModel):
+    """The progress image sent intermittently during processing"""
+
+    width: int = Field(description="The effective width of the image in pixels")
+    height: int = Field(description="The effective height of the image in pixels")
+    dataURL: str = Field(description="The image data as a b64 data URL")
+
+
+class CanceledException(Exception):
+    """Execution canceled by user."""
+
+    pass

invokeai/app/services/invocation_processor/invocation_processor_default.py

@@ -4,11 +4,12 @@ from threading import BoundedSemaphore, Event, Thread
 from typing import Optional
 
 import invokeai.backend.util.logging as logger
+from invokeai.app.invocations.baseinvocation import InvocationContext
+from invokeai.app.services.invocation_queue.invocation_queue_common import InvocationQueueItem
 
-from ..invocations.baseinvocation import InvocationContext
+from ..invoker import Invoker
-from ..models.exceptions import CanceledException
+from .invocation_processor_base import InvocationProcessorABC
-from .invocation_queue import InvocationQueueItem
+from .invocation_processor_common import CanceledException
-from .invoker import InvocationProcessorABC, Invoker
 
 
 class DefaultInvocationProcessor(InvocationProcessorABC):

invokeai/app/services/invocation_queue/invocation_queue_base.py

@@ -0,0 +1,26 @@
+# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+
+from abc import ABC, abstractmethod
+from typing import Optional
+
+from .invocation_queue_common import InvocationQueueItem
+
+
+class InvocationQueueABC(ABC):
+    """Abstract base class for all invocation queues"""
+
+    @abstractmethod
+    def get(self) -> InvocationQueueItem:
+        pass
+
+    @abstractmethod
+    def put(self, item: Optional[InvocationQueueItem]) -> None:
+        pass
+
+    @abstractmethod
+    def cancel(self, graph_execution_state_id: str) -> None:
+        pass
+
+    @abstractmethod
+    def is_canceled(self, graph_execution_state_id: str) -> bool:
+        pass

invokeai/app/services/invocation_queue/invocation_queue_common.py

@@ -0,0 +1,19 @@
+# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+
+import time
+
+from pydantic import BaseModel, Field
+
+
+class InvocationQueueItem(BaseModel):
+    graph_execution_state_id: str = Field(description="The ID of the graph execution state")
+    invocation_id: str = Field(description="The ID of the node being invoked")
+    session_queue_id: str = Field(description="The ID of the session queue from which this invocation queue item came")
+    session_queue_item_id: int = Field(
+        description="The ID of session queue item from which this invocation queue item came"
+    )
+    session_queue_batch_id: str = Field(
+        description="The ID of the session batch from which this invocation queue item came"
+    )
+    invoke_all: bool = Field(default=False)
+    timestamp: float = Field(default_factory=time.time)

invokeai/app/services/invocation_queue/invocation_queue_memory.py

@@ -1,45 +1,11 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
 import time
-from abc import ABC, abstractmethod
 from queue import Queue
 from typing import Optional
 
-from pydantic import BaseModel, Field
+from .invocation_queue_base import InvocationQueueABC
-
+from .invocation_queue_common import InvocationQueueItem
-
-class InvocationQueueItem(BaseModel):
-    graph_execution_state_id: str = Field(description="The ID of the graph execution state")
-    invocation_id: str = Field(description="The ID of the node being invoked")
-    session_queue_id: str = Field(description="The ID of the session queue from which this invocation queue item came")
-    session_queue_item_id: int = Field(
-        description="The ID of session queue item from which this invocation queue item came"
-    )
-    session_queue_batch_id: str = Field(
-        description="The ID of the session batch from which this invocation queue item came"
-    )
-    invoke_all: bool = Field(default=False)
-    timestamp: float = Field(default_factory=time.time)
-
-
-class InvocationQueueABC(ABC):
-    """Abstract base class for all invocation queues"""
-
-    @abstractmethod
-    def get(self) -> InvocationQueueItem:
-        pass
-
-    @abstractmethod
-    def put(self, item: Optional[InvocationQueueItem]) -> None:
-        pass
-
-    @abstractmethod
-    def cancel(self, graph_execution_state_id: str) -> None:
-        pass
-
-    @abstractmethod
-    def is_canceled(self, graph_execution_state_id: str) -> bool:
-        pass
 
 
 class MemoryInvocationQueue(InvocationQueueABC):

invokeai/app/services/invocation_services.py

@@ -6,27 +6,27 @@ from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from logging import Logger
 
-    from invokeai.app.services.board_image_record_storage import BoardImageRecordStorageBase
+    from .board_image_records.board_image_records_base import BoardImageRecordStorageBase
-    from invokeai.app.services.board_images import BoardImagesServiceABC
+    from .board_images.board_images_base import BoardImagesServiceABC
-    from invokeai.app.services.board_record_storage import BoardRecordStorageBase
+    from .board_records.board_records_base import BoardRecordStorageBase
-    from invokeai.app.services.boards import BoardServiceABC
+    from .boards.boards_base import BoardServiceABC
-    from invokeai.app.services.config import InvokeAIAppConfig
+    from .config import InvokeAIAppConfig
-    from invokeai.app.services.events import EventServiceBase
+    from .events.events_base import EventServiceBase
-    from invokeai.app.services.graph import GraphExecutionState, LibraryGraph
+    from .image_files.image_files_base import ImageFileStorageBase
-    from invokeai.app.services.image_file_storage import ImageFileStorageBase
+    from .image_records.image_records_base import ImageRecordStorageBase
-    from invokeai.app.services.image_record_storage import ImageRecordStorageBase
+    from .images.images_base import ImageServiceABC
-    from invokeai.app.services.images import ImageServiceABC
+    from .invocation_cache.invocation_cache_base import InvocationCacheBase
-    from invokeai.app.services.invocation_cache.invocation_cache_base import InvocationCacheBase
+    from .invocation_processor.invocation_processor_base import InvocationProcessorABC
-    from invokeai.app.services.invocation_queue import InvocationQueueABC
+    from .invocation_queue.invocation_queue_base import InvocationQueueABC
-    from invokeai.app.services.invocation_stats import InvocationStatsServiceBase
+    from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
-    from invokeai.app.services.invoker import InvocationProcessorABC
+    from .item_storage.item_storage_base import ItemStorageABC
-    from invokeai.app.services.item_storage import ItemStorageABC
+    from .latents_storage.latents_storage_base import LatentsStorageBase
-    from invokeai.app.services.latent_storage import LatentsStorageBase
+    from .model_manager.model_manager_base import ModelManagerServiceBase
-    from invokeai.app.services.model_manager_service import ModelManagerServiceBase
+    from .names.names_base import NameServiceBase
-    from invokeai.app.services.resource_name import NameServiceBase
+    from .session_processor.session_processor_base import SessionProcessorBase
-    from invokeai.app.services.session_processor.session_processor_base import SessionProcessorBase
+    from .session_queue.session_queue_base import SessionQueueBase
-    from invokeai.app.services.session_queue.session_queue_base import SessionQueueBase
+    from .shared.graph import GraphExecutionState, LibraryGraph
-    from invokeai.app.services.urls import UrlServiceBase
+    from .urls.urls_base import UrlServiceBase
 
 
 class InvocationServices:

invokeai/app/services/invocation_stats/invocation_stats_base.py

@@ -0,0 +1,121 @@
+# Copyright 2023 Lincoln D. Stein <lincoln.stein@gmail.com>
+"""Utility to collect execution time and GPU usage stats on invocations in flight
+
+Usage:
+
+statistics = InvocationStatsService(graph_execution_manager)
+with statistics.collect_stats(invocation, graph_execution_state.id):
+      ... execute graphs...
+statistics.log_stats()
+
+Typical output:
+[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> Graph stats: c7764585-9c68-4d9d-a199-55e8186790f3
+[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> Node                 Calls  Seconds  VRAM Used
+[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> main_model_loader        1   0.005s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> clip_skip                1   0.004s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> compel                   2   0.512s     0.26G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> rand_int                 1   0.001s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> range_of_size            1   0.001s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> iterate                  1   0.001s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> metadata_accumulator     1   0.002s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> noise                    1   0.002s     0.01G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> t2l                      1   3.541s     1.93G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> l2i                      1   0.679s     0.58G
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> TOTAL GRAPH EXECUTION TIME:  4.749s
+[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> Current VRAM utilization 0.01G
+
+The abstract base class for this class is InvocationStatsServiceBase. An implementing class which
+writes to the system log is stored in InvocationServices.performance_statistics.
+"""
+
+from abc import ABC, abstractmethod
+from contextlib import AbstractContextManager
+from typing import Dict
+
+from invokeai.app.invocations.baseinvocation import BaseInvocation
+from invokeai.backend.model_management.model_cache import CacheStats
+
+from .invocation_stats_common import NodeLog
+
+
+class InvocationStatsServiceBase(ABC):
+    "Abstract base class for recording node memory/time performance statistics"
+
+    # {graph_id => NodeLog}
+    _stats: Dict[str, NodeLog]
+    _cache_stats: Dict[str, CacheStats]
+    ram_used: float
+    ram_changed: float
+
+    @abstractmethod
+    def __init__(self):
+        """
+        Initialize the InvocationStatsService and reset counters to zero
+        """
+        pass
+
+    @abstractmethod
+    def collect_stats(
+        self,
+        invocation: BaseInvocation,
+        graph_execution_state_id: str,
+    ) -> AbstractContextManager:
+        """
+        Return a context object that will capture the statistics on the execution
+        of invocaation. Use with: to place around the part of the code that executes the invocation.
+        :param invocation: BaseInvocation object from the current graph.
+        :param graph_execution_state_id: The id of the current session.
+        """
+        pass
+
+    @abstractmethod
+    def reset_stats(self, graph_execution_state_id: str):
+        """
+        Reset all statistics for the indicated graph
+        :param graph_execution_state_id
+        """
+        pass
+
+    @abstractmethod
+    def reset_all_stats(self):
+        """Zero all statistics"""
+        pass
+
+    @abstractmethod
+    def update_invocation_stats(
+        self,
+        graph_id: str,
+        invocation_type: str,
+        time_used: float,
+        vram_used: float,
+    ):
+        """
+        Add timing information on execution of a node. Usually
+        used internally.
+        :param graph_id: ID of the graph that is currently executing
+        :param invocation_type: String literal type of the node
+        :param time_used: Time used by node's exection (sec)
+        :param vram_used: Maximum VRAM used during exection (GB)
+        """
+        pass
+
+    @abstractmethod
+    def log_stats(self):
+        """
+        Write out the accumulated statistics to the log or somewhere else.
+        """
+        pass
+
+    @abstractmethod
+    def update_mem_stats(
+        self,
+        ram_used: float,
+        ram_changed: float,
+    ):
+        """
+        Update the collector with RAM memory usage info.
+
+        :param ram_used: How much RAM is currently in use.
+        :param ram_changed: How much RAM changed since last generation.
+        """
+        pass

invokeai/app/services/invocation_stats/invocation_stats_common.py

@@ -0,0 +1,25 @@
+from dataclasses import dataclass, field
+from typing import Dict
+
+# size of GIG in bytes
+GIG = 1073741824
+
+
+@dataclass
+class NodeStats:
+    """Class for tracking execution stats of an invocation node"""
+
+    calls: int = 0
+    time_used: float = 0.0  # seconds
+    max_vram: float = 0.0  # GB
+    cache_hits: int = 0
+    cache_misses: int = 0
+    cache_high_watermark: int = 0
+
+
+@dataclass
+class NodeLog:
+    """Class for tracking node usage"""
+
+    # {node_type => NodeStats}
+    nodes: Dict[str, NodeStats] = field(default_factory=dict)

invokeai/app/services/invocation_stats/invocation_stats_default.py

@@ -1,154 +1,17 @@
-# Copyright 2023 Lincoln D. Stein <lincoln.stein@gmail.com>
-"""Utility to collect execution time and GPU usage stats on invocations in flight
-
-Usage:
-
-statistics = InvocationStatsService(graph_execution_manager)
-with statistics.collect_stats(invocation, graph_execution_state.id):
-      ... execute graphs...
-statistics.log_stats()
-
-Typical output:
-[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> Graph stats: c7764585-9c68-4d9d-a199-55e8186790f3
-[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> Node                 Calls  Seconds  VRAM Used
-[2023-08-02 18:03:04,507]::[InvokeAI]::INFO --> main_model_loader        1   0.005s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> clip_skip                1   0.004s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> compel                   2   0.512s     0.26G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> rand_int                 1   0.001s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> range_of_size            1   0.001s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> iterate                  1   0.001s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> metadata_accumulator     1   0.002s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> noise                    1   0.002s     0.01G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> t2l                      1   3.541s     1.93G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> l2i                      1   0.679s     0.58G
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> TOTAL GRAPH EXECUTION TIME:  4.749s
-[2023-08-02 18:03:04,508]::[InvokeAI]::INFO --> Current VRAM utilization 0.01G
-
-The abstract base class for this class is InvocationStatsServiceBase. An implementing class which
-writes to the system log is stored in InvocationServices.performance_statistics.
-"""
-
 import time
-from abc import ABC, abstractmethod
-from contextlib import AbstractContextManager
-from dataclasses import dataclass, field
 from typing import Dict
 
 import psutil
 import torch
 
 import invokeai.backend.util.logging as logger
+from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.model_manager.model_manager_base import ModelManagerServiceBase
 from invokeai.backend.model_management.model_cache import CacheStats
 
-from ..invocations.baseinvocation import BaseInvocation
+from .invocation_stats_base import InvocationStatsServiceBase
-from .model_manager_service import ModelManagerServiceBase
+from .invocation_stats_common import GIG, NodeLog, NodeStats
-
-# size of GIG in bytes
-GIG = 1073741824
-
-
-@dataclass
-class NodeStats:
-    """Class for tracking execution stats of an invocation node"""
-
-    calls: int = 0
-    time_used: float = 0.0  # seconds
-    max_vram: float = 0.0  # GB
-    cache_hits: int = 0
-    cache_misses: int = 0
-    cache_high_watermark: int = 0
-
-
-@dataclass
-class NodeLog:
-    """Class for tracking node usage"""
-
-    # {node_type => NodeStats}
-    nodes: Dict[str, NodeStats] = field(default_factory=dict)
-
-
-class InvocationStatsServiceBase(ABC):
-    "Abstract base class for recording node memory/time performance statistics"
-
-    # {graph_id => NodeLog}
-    _stats: Dict[str, NodeLog]
-    _cache_stats: Dict[str, CacheStats]
-    ram_used: float
-    ram_changed: float
-
-    @abstractmethod
-    def __init__(self):
-        """
-        Initialize the InvocationStatsService and reset counters to zero
-        """
-        pass
-
-    @abstractmethod
-    def collect_stats(
-        self,
-        invocation: BaseInvocation,
-        graph_execution_state_id: str,
-    ) -> AbstractContextManager:
-        """
-        Return a context object that will capture the statistics on the execution
-        of invocaation. Use with: to place around the part of the code that executes the invocation.
-        :param invocation: BaseInvocation object from the current graph.
-        :param graph_execution_state: GraphExecutionState object from the current session.
-        """
-        pass
-
-    @abstractmethod
-    def reset_stats(self, graph_execution_state_id: str):
-        """
-        Reset all statistics for the indicated graph
-        :param graph_execution_state_id
-        """
-        pass
-
-    @abstractmethod
-    def reset_all_stats(self):
-        """Zero all statistics"""
-        pass
-
-    @abstractmethod
-    def update_invocation_stats(
-        self,
-        graph_id: str,
-        invocation_type: str,
-        time_used: float,
-        vram_used: float,
-    ):
-        """
-        Add timing information on execution of a node. Usually
-        used internally.
-        :param graph_id: ID of the graph that is currently executing
-        :param invocation_type: String literal type of the node
-        :param time_used: Time used by node's exection (sec)
-        :param vram_used: Maximum VRAM used during exection (GB)
-        """
-        pass
-
-    @abstractmethod
-    def log_stats(self):
-        """
-        Write out the accumulated statistics to the log or somewhere else.
-        """
-        pass
-
-    @abstractmethod
-    def update_mem_stats(
-        self,
-        ram_used: float,
-        ram_changed: float,
-    ):
-        """
-        Update the collector with RAM memory usage info.
-
-        :param ram_used: How much RAM is currently in use.
-        :param ram_changed: How much RAM changed since last generation.
-        """
-        pass
 
 
 class InvocationStatsService(InvocationStatsServiceBase):

invokeai/app/services/invoker.py

@@ -1,11 +1,10 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from abc import ABC
 from typing import Optional
 
-from .graph import Graph, GraphExecutionState
+from .invocation_queue.invocation_queue_common import InvocationQueueItem
-from .invocation_queue import InvocationQueueItem
 from .invocation_services import InvocationServices
+from .shared.graph import Graph, GraphExecutionState
 
 
 class Invoker:
@@ -84,7 +83,3 @@ class Invoker:
             self.__stop_service(getattr(self.services, service))
 
         self.services.queue.put(None)
-
-
-class InvocationProcessorABC(ABC):
-    pass

invokeai/app/services/item_storage/item_storage_base.py

@@ -9,6 +9,8 @@ T = TypeVar("T", bound=BaseModel)
 
 
 class ItemStorageABC(ABC, Generic[T]):
+    """Provides storage for a single type of item. The type must be a Pydantic model."""
+
     _on_changed_callbacks: list[Callable[[T], None]]
     _on_deleted_callbacks: list[Callable[[str], None]]
 

invokeai/app/services/item_storage/item_storage_sqlite.py

@@ -4,15 +4,13 @@ from typing import Generic, Optional, TypeVar, get_args
 
 from pydantic import BaseModel, parse_raw_as
 
-from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.app.services.shared.pagination import PaginatedResults
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 
-from .item_storage import ItemStorageABC
+from .item_storage_base import ItemStorageABC
 
 T = TypeVar("T", bound=BaseModel)
 
-sqlite_memory = ":memory:"
-
 
 class SqliteItemStorage(ItemStorageABC, Generic[T]):
     _table_name: str
@@ -47,7 +45,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
             self._lock.release()
 
     def _parse_item(self, item: str) -> T:
-        item_type = get_args(self.__orig_class__)[0]
+        # __orig_class__ is technically an implementation detail of the typing module, not a supported API
+        item_type = get_args(self.__orig_class__)[0]  # type: ignore
         return parse_raw_as(item_type, item)
 
     def set(self, item: T):

invokeai/app/services/latent_storage.py

@@ -1,119 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-
-from abc import ABC, abstractmethod
-from pathlib import Path
-from queue import Queue
-from typing import Callable, Dict, Optional, Union
-
-import torch
-
-
-class LatentsStorageBase(ABC):
-    """Responsible for storing and retrieving latents."""
-
-    _on_changed_callbacks: list[Callable[[torch.Tensor], None]]
-    _on_deleted_callbacks: list[Callable[[str], None]]
-
-    def __init__(self) -> None:
-        self._on_changed_callbacks = list()
-        self._on_deleted_callbacks = list()
-
-    @abstractmethod
-    def get(self, name: str) -> torch.Tensor:
-        pass
-
-    @abstractmethod
-    def save(self, name: str, data: torch.Tensor) -> None:
-        pass
-
-    @abstractmethod
-    def delete(self, name: str) -> None:
-        pass
-
-    def on_changed(self, on_changed: Callable[[torch.Tensor], None]) -> None:
-        """Register a callback for when an item is changed"""
-        self._on_changed_callbacks.append(on_changed)
-
-    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
-        """Register a callback for when an item is deleted"""
-        self._on_deleted_callbacks.append(on_deleted)
-
-    def _on_changed(self, item: torch.Tensor) -> None:
-        for callback in self._on_changed_callbacks:
-            callback(item)
-
-    def _on_deleted(self, item_id: str) -> None:
-        for callback in self._on_deleted_callbacks:
-            callback(item_id)
-
-
-class ForwardCacheLatentsStorage(LatentsStorageBase):
-    """Caches the latest N latents in memory, writing-thorugh to and reading from underlying storage"""
-
-    __cache: Dict[str, torch.Tensor]
-    __cache_ids: Queue
-    __max_cache_size: int
-    __underlying_storage: LatentsStorageBase
-
-    def __init__(self, underlying_storage: LatentsStorageBase, max_cache_size: int = 20):
-        super().__init__()
-        self.__underlying_storage = underlying_storage
-        self.__cache = dict()
-        self.__cache_ids = Queue()
-        self.__max_cache_size = max_cache_size
-
-    def get(self, name: str) -> torch.Tensor:
-        cache_item = self.__get_cache(name)
-        if cache_item is not None:
-            return cache_item
-
-        latent = self.__underlying_storage.get(name)
-        self.__set_cache(name, latent)
-        return latent
-
-    def save(self, name: str, data: torch.Tensor) -> None:
-        self.__underlying_storage.save(name, data)
-        self.__set_cache(name, data)
-        self._on_changed(data)
-
-    def delete(self, name: str) -> None:
-        self.__underlying_storage.delete(name)
-        if name in self.__cache:
-            del self.__cache[name]
-        self._on_deleted(name)
-
-    def __get_cache(self, name: str) -> Optional[torch.Tensor]:
-        return None if name not in self.__cache else self.__cache[name]
-
-    def __set_cache(self, name: str, data: torch.Tensor):
-        if name not in self.__cache:
-            self.__cache[name] = data
-            self.__cache_ids.put(name)
-            if self.__cache_ids.qsize() > self.__max_cache_size:
-                self.__cache.pop(self.__cache_ids.get())
-
-
-class DiskLatentsStorage(LatentsStorageBase):
-    """Stores latents in a folder on disk without caching"""
-
-    __output_folder: Union[str, Path]
-
-    def __init__(self, output_folder: Union[str, Path]):
-        self.__output_folder = output_folder if isinstance(output_folder, Path) else Path(output_folder)
-        self.__output_folder.mkdir(parents=True, exist_ok=True)
-
-    def get(self, name: str) -> torch.Tensor:
-        latent_path = self.get_path(name)
-        return torch.load(latent_path)
-
-    def save(self, name: str, data: torch.Tensor) -> None:
-        self.__output_folder.mkdir(parents=True, exist_ok=True)
-        latent_path = self.get_path(name)
-        torch.save(data, latent_path)
-
-    def delete(self, name: str) -> None:
-        latent_path = self.get_path(name)
-        latent_path.unlink()
-
-    def get_path(self, name: str) -> Path:
-        return self.__output_folder / name

invokeai/app/services/latents_storage/latents_storage_base.py

@@ -0,0 +1,45 @@
+# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
+
+from abc import ABC, abstractmethod
+from typing import Callable
+
+import torch
+
+
+class LatentsStorageBase(ABC):
+    """Responsible for storing and retrieving latents."""
+
+    _on_changed_callbacks: list[Callable[[torch.Tensor], None]]
+    _on_deleted_callbacks: list[Callable[[str], None]]
+
+    def __init__(self) -> None:
+        self._on_changed_callbacks = list()
+        self._on_deleted_callbacks = list()
+
+    @abstractmethod
+    def get(self, name: str) -> torch.Tensor:
+        pass
+
+    @abstractmethod
+    def save(self, name: str, data: torch.Tensor) -> None:
+        pass
+
+    @abstractmethod
+    def delete(self, name: str) -> None:
+        pass
+
+    def on_changed(self, on_changed: Callable[[torch.Tensor], None]) -> None:
+        """Register a callback for when an item is changed"""
+        self._on_changed_callbacks.append(on_changed)
+
+    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
+        """Register a callback for when an item is deleted"""
+        self._on_deleted_callbacks.append(on_deleted)
+
+    def _on_changed(self, item: torch.Tensor) -> None:
+        for callback in self._on_changed_callbacks:
+            callback(item)
+
+    def _on_deleted(self, item_id: str) -> None:
+        for callback in self._on_deleted_callbacks:
+            callback(item_id)

invokeai/app/services/latents_storage/latents_storage_disk.py

@@ -0,0 +1,34 @@
+# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
+
+from pathlib import Path
+from typing import Union
+
+import torch
+
+from .latents_storage_base import LatentsStorageBase
+
+
+class DiskLatentsStorage(LatentsStorageBase):
+    """Stores latents in a folder on disk without caching"""
+
+    __output_folder: Path
+
+    def __init__(self, output_folder: Union[str, Path]):
+        self.__output_folder = output_folder if isinstance(output_folder, Path) else Path(output_folder)
+        self.__output_folder.mkdir(parents=True, exist_ok=True)
+
+    def get(self, name: str) -> torch.Tensor:
+        latent_path = self.get_path(name)
+        return torch.load(latent_path)
+
+    def save(self, name: str, data: torch.Tensor) -> None:
+        self.__output_folder.mkdir(parents=True, exist_ok=True)
+        latent_path = self.get_path(name)
+        torch.save(data, latent_path)
+
+    def delete(self, name: str) -> None:
+        latent_path = self.get_path(name)
+        latent_path.unlink()
+
+    def get_path(self, name: str) -> Path:
+        return self.__output_folder / name

invokeai/app/services/latents_storage/latents_storage_forward_cache.py

@@ -0,0 +1,54 @@
+# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
+
+from queue import Queue
+from typing import Dict, Optional
+
+import torch
+
+from .latents_storage_base import LatentsStorageBase
+
+
+class ForwardCacheLatentsStorage(LatentsStorageBase):
+    """Caches the latest N latents in memory, writing-thorugh to and reading from underlying storage"""
+
+    __cache: Dict[str, torch.Tensor]
+    __cache_ids: Queue
+    __max_cache_size: int
+    __underlying_storage: LatentsStorageBase
+
+    def __init__(self, underlying_storage: LatentsStorageBase, max_cache_size: int = 20):
+        super().__init__()
+        self.__underlying_storage = underlying_storage
+        self.__cache = dict()
+        self.__cache_ids = Queue()
+        self.__max_cache_size = max_cache_size
+
+    def get(self, name: str) -> torch.Tensor:
+        cache_item = self.__get_cache(name)
+        if cache_item is not None:
+            return cache_item
+
+        latent = self.__underlying_storage.get(name)
+        self.__set_cache(name, latent)
+        return latent
+
+    def save(self, name: str, data: torch.Tensor) -> None:
+        self.__underlying_storage.save(name, data)
+        self.__set_cache(name, data)
+        self._on_changed(data)
+
+    def delete(self, name: str) -> None:
+        self.__underlying_storage.delete(name)
+        if name in self.__cache:
+            del self.__cache[name]
+        self._on_deleted(name)
+
+    def __get_cache(self, name: str) -> Optional[torch.Tensor]:
+        return None if name not in self.__cache else self.__cache[name]
+
+    def __set_cache(self, name: str, data: torch.Tensor):
+        if name not in self.__cache:
+            self.__cache[name] = data
+            self.__cache_ids.put(name)
+            if self.__cache_ids.qsize() > self.__max_cache_size:
+                self.__cache.pop(self.__cache_ids.get())

invokeai/app/services/model_manager/model_manager_base.py

@@ -0,0 +1,286 @@
+# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from logging import Logger
+from pathlib import Path
+from typing import TYPE_CHECKING, Callable, List, Literal, Optional, Tuple, Union
+
+from pydantic import Field
+
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.backend.model_management import (
+    AddModelResult,
+    BaseModelType,
+    MergeInterpolationMethod,
+    ModelInfo,
+    ModelType,
+    SchedulerPredictionType,
+    SubModelType,
+)
+from invokeai.backend.model_management.model_cache import CacheStats
+
+if TYPE_CHECKING:
+    from invokeai.app.invocations.baseinvocation import BaseInvocation, InvocationContext
+
+
+class ModelManagerServiceBase(ABC):
+    """Responsible for managing models on disk and in memory"""
+
+    @abstractmethod
+    def __init__(
+        self,
+        config: InvokeAIAppConfig,
+        logger: Logger,
+    ):
+        """
+        Initialize with the path to the models.yaml config file.
+        Optional parameters are the torch device type, precision, max_models,
+        and sequential_offload boolean. Note that the default device
+        type and precision are set up for a CUDA system running at half precision.
+        """
+        pass
+
+    @abstractmethod
+    def get_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        node: Optional[BaseInvocation] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> ModelInfo:
+        """Retrieve the indicated model with name and type.
+        submodel can be used to get a part (such as the vae)
+        of a diffusers pipeline."""
+        pass
+
+    @property
+    @abstractmethod
+    def logger(self):
+        pass
+
+    @abstractmethod
+    def model_exists(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+    ) -> bool:
+        pass
+
+    @abstractmethod
+    def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
+        """
+        Given a model name returns a dict-like (OmegaConf) object describing it.
+        Uses the exact format as the omegaconf stanza.
+        """
+        pass
+
+    @abstractmethod
+    def list_models(self, base_model: Optional[BaseModelType] = None, model_type: Optional[ModelType] = None) -> dict:
+        """
+        Return a dict of models in the format:
+        { model_type1:
+          { model_name1: {'status': 'active'|'cached'|'not loaded',
+                         'model_name' : name,
+                         'model_type' : SDModelType,
+                         'description': description,
+                         'format': 'folder'|'safetensors'|'ckpt'
+                         },
+            model_name2: { etc }
+          },
+          model_type2:
+            { model_name_n: etc
+        }
+        """
+        pass
+
+    @abstractmethod
+    def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
+        """
+        Return information about the model using the same format as list_models()
+        """
+        pass
+
+    @abstractmethod
+    def model_names(self) -> List[Tuple[str, BaseModelType, ModelType]]:
+        """
+        Returns a list of all the model names known.
+        """
+        pass
+
+    @abstractmethod
+    def add_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        model_attributes: dict,
+        clobber: bool = False,
+    ) -> 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.
+        On a successful update, the config will be changed in memory. Will fail
+        with an assertion error if provided attributes are incorrect or
+        the model name is missing. Call commit() to write changes to disk.
+        """
+        pass
+
+    @abstractmethod
+    def update_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        model_attributes: dict,
+    ) -> AddModelResult:
+        """
+        Update the named model with a dictionary of attributes. Will fail with a
+        ModelNotFoundException if the name does not already exist.
+
+        On a successful update, the config will be changed in memory. Will fail
+        with an assertion error if provided attributes are incorrect or
+        the model name is missing. Call commit() to write changes to disk.
+        """
+        pass
+
+    @abstractmethod
+    def del_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+    ):
+        """
+        Delete the named model from configuration. If delete_files is true,
+        then the underlying weight file or diffusers directory will be deleted
+        as well. Call commit() to write to disk.
+        """
+        pass
+
+    @abstractmethod
+    def rename_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        new_name: str,
+    ):
+        """
+        Rename the indicated model.
+        """
+        pass
+
+    @abstractmethod
+    def list_checkpoint_configs(self) -> List[Path]:
+        """
+        List the checkpoint config paths from ROOT/configs/stable-diffusion.
+        """
+        pass
+
+    @abstractmethod
+    def convert_model(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: Literal[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],
+        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
+    ) -> dict[str, AddModelResult]:
+        """Import a list of paths, repo_ids or URLs. Returns the set of
+        successfully imported items.
+        :param items_to_import: Set of strings corresponding to models to be imported.
+        :param prediction_type_helper: A callback that receives the Path of a Stable Diffusion 2 checkpoint model and returns a SchedulerPredictionType.
+
+        The prediction type helper is necessary to distinguish between
+        models based on Stable Diffusion 2 Base (requiring
+        SchedulerPredictionType.Epsilson) and Stable Diffusion 768
+        (requiring SchedulerPredictionType.VPrediction). It is
+        generally impossible to do this programmatically, so the
+        prediction_type_helper usually asks the user to choose.
+
+        The result is a set of successfully installed models. Each element
+        of the set is a dict corresponding to the newly-created OmegaConf stanza for
+        that model.
+        """
+        pass
+
+    @abstractmethod
+    def merge_models(
+        self,
+        model_names: List[str] = Field(
+            default=None, min_items=2, max_items=3, description="List of model names to merge"
+        ),
+        base_model: Union[BaseModelType, str] = Field(
+            default=None, description="Base model shared by all models to be merged"
+        ),
+        merged_model_name: str = Field(default=None, description="Name of destination model after merging"),
+        alpha: Optional[float] = 0.5,
+        interp: Optional[MergeInterpolationMethod] = None,
+        force: Optional[bool] = False,
+        merge_dest_directory: Optional[Path] = None,
+    ) -> AddModelResult:
+        """
+        Merge two to three diffusrs pipeline models and save as a new model.
+        :param model_names: List of 2-3 models to merge
+        :param base_model: Base model to use for all models
+        :param merged_model_name: Name of destination merged model
+        :param alpha: Alpha strength to apply to 2d and 3d model
+        :param interp: Interpolation method. None (default)
+        :param merge_dest_directory: Save the merged model to the designated directory (with 'merged_model_name' appended)
+        """
+        pass
+
+    @abstractmethod
+    def search_for_models(self, directory: Path) -> List[Path]:
+        """
+        Return list of all models found in the designated directory.
+        """
+        pass
+
+    @abstractmethod
+    def sync_to_config(self):
+        """
+        Re-read models.yaml, rescan the models directory, and reimport models
+        in the autoimport directories. Call after making changes outside the
+        model manager API.
+        """
+        pass
+
+    @abstractmethod
+    def collect_cache_stats(self, cache_stats: CacheStats):
+        """
+        Reset model cache statistics for graph with graph_id.
+        """
+        pass
+
+    @abstractmethod
+    def commit(self, conf_file: Optional[Path] = None) -> None:
+        """
+        Write current configuration out to the indicated file.
+        If no conf_file is provided, then replaces the
+        original file/database used to initialize the object.
+        """
+        pass

invokeai/app/services/model_manager/model_manager_default.py

@@ -2,16 +2,15 @@
 
 from __future__ import annotations
 
-from abc import ABC, abstractmethod
 from logging import Logger
 from pathlib import Path
-from types import ModuleType
 from typing import TYPE_CHECKING, Callable, List, Literal, Optional, Tuple, Union
 
 import torch
 from pydantic import Field
 
-from invokeai.app.models.exceptions import CanceledException
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
 from invokeai.backend.model_management import (
     AddModelResult,
     BaseModelType,
@@ -26,273 +25,12 @@ from invokeai.backend.model_management import (
 )
 from invokeai.backend.model_management.model_cache import CacheStats
 from invokeai.backend.model_management.model_search import FindModels
+from invokeai.backend.util import choose_precision, choose_torch_device
 
-from ...backend.util import choose_precision, choose_torch_device
+from .model_manager_base import ModelManagerServiceBase
-from .config import InvokeAIAppConfig
 
 if TYPE_CHECKING:
-    from ..invocations.baseinvocation import BaseInvocation, InvocationContext
+    from invokeai.app.invocations.baseinvocation import InvocationContext
-
-
-class ModelManagerServiceBase(ABC):
-    """Responsible for managing models on disk and in memory"""
-
-    @abstractmethod
-    def __init__(
-        self,
-        config: InvokeAIAppConfig,
-        logger: ModuleType,
-    ):
-        """
-        Initialize with the path to the models.yaml config file.
-        Optional parameters are the torch device type, precision, max_models,
-        and sequential_offload boolean. Note that the default device
-        type and precision are set up for a CUDA system running at half precision.
-        """
-        pass
-
-    @abstractmethod
-    def get_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        node: Optional[BaseInvocation] = None,
-        context: Optional[InvocationContext] = None,
-    ) -> ModelInfo:
-        """Retrieve the indicated model with name and type.
-        submodel can be used to get a part (such as the vae)
-        of a diffusers pipeline."""
-        pass
-
-    @property
-    @abstractmethod
-    def logger(self):
-        pass
-
-    @abstractmethod
-    def model_exists(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> bool:
-        pass
-
-    @abstractmethod
-    def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
-        """
-        Given a model name returns a dict-like (OmegaConf) object describing it.
-        Uses the exact format as the omegaconf stanza.
-        """
-        pass
-
-    @abstractmethod
-    def list_models(self, base_model: Optional[BaseModelType] = None, model_type: Optional[ModelType] = None) -> dict:
-        """
-        Return a dict of models in the format:
-        { model_type1:
-          { model_name1: {'status': 'active'|'cached'|'not loaded',
-                         'model_name' : name,
-                         'model_type' : SDModelType,
-                         'description': description,
-                         'format': 'folder'|'safetensors'|'ckpt'
-                         },
-            model_name2: { etc }
-          },
-          model_type2:
-            { model_name_n: etc
-        }
-        """
-        pass
-
-    @abstractmethod
-    def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
-        """
-        Return information about the model using the same format as list_models()
-        """
-        pass
-
-    @abstractmethod
-    def model_names(self) -> List[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns a list of all the model names known.
-        """
-        pass
-
-    @abstractmethod
-    def add_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-        clobber: bool = False,
-    ) -> 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.
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        pass
-
-    @abstractmethod
-    def update_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with a
-        ModelNotFoundException if the name does not already exist.
-
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        pass
-
-    @abstractmethod
-    def del_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        """
-        Delete the named model from configuration. If delete_files is true,
-        then the underlying weight file or diffusers directory will be deleted
-        as well. Call commit() to write to disk.
-        """
-        pass
-
-    @abstractmethod
-    def rename_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        new_name: str,
-    ):
-        """
-        Rename the indicated model.
-        """
-        pass
-
-    @abstractmethod
-    def list_checkpoint_configs(self) -> List[Path]:
-        """
-        List the checkpoint config paths from ROOT/configs/stable-diffusion.
-        """
-        pass
-
-    @abstractmethod
-    def convert_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: Literal[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],
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-    ) -> dict[str, AddModelResult]:
-        """Import a list of paths, repo_ids or URLs. Returns the set of
-        successfully imported items.
-        :param items_to_import: Set of strings corresponding to models to be imported.
-        :param prediction_type_helper: A callback that receives the Path of a Stable Diffusion 2 checkpoint model and returns a SchedulerPredictionType.
-
-        The prediction type helper is necessary to distinguish between
-        models based on Stable Diffusion 2 Base (requiring
-        SchedulerPredictionType.Epsilson) and Stable Diffusion 768
-        (requiring SchedulerPredictionType.VPrediction). It is
-        generally impossible to do this programmatically, so the
-        prediction_type_helper usually asks the user to choose.
-
-        The result is a set of successfully installed models. Each element
-        of the set is a dict corresponding to the newly-created OmegaConf stanza for
-        that model.
-        """
-        pass
-
-    @abstractmethod
-    def merge_models(
-        self,
-        model_names: List[str] = Field(
-            default=None, min_items=2, max_items=3, description="List of model names to merge"
-        ),
-        base_model: Union[BaseModelType, str] = Field(
-            default=None, description="Base model shared by all models to be merged"
-        ),
-        merged_model_name: str = Field(default=None, description="Name of destination model after merging"),
-        alpha: Optional[float] = 0.5,
-        interp: Optional[MergeInterpolationMethod] = None,
-        force: Optional[bool] = False,
-        merge_dest_directory: Optional[Path] = None,
-    ) -> AddModelResult:
-        """
-        Merge two to three diffusrs pipeline models and save as a new model.
-        :param model_names: List of 2-3 models to merge
-        :param base_model: Base model to use for all models
-        :param merged_model_name: Name of destination merged model
-        :param alpha: Alpha strength to apply to 2d and 3d model
-        :param interp: Interpolation method. None (default)
-        :param merge_dest_directory: Save the merged model to the designated directory (with 'merged_model_name' appended)
-        """
-        pass
-
-    @abstractmethod
-    def search_for_models(self, directory: Path) -> List[Path]:
-        """
-        Return list of all models found in the designated directory.
-        """
-        pass
-
-    @abstractmethod
-    def sync_to_config(self):
-        """
-        Re-read models.yaml, rescan the models directory, and reimport models
-        in the autoimport directories. Call after making changes outside the
-        model manager API.
-        """
-        pass
-
-    @abstractmethod
-    def collect_cache_stats(self, cache_stats: CacheStats):
-        """
-        Reset model cache statistics for graph with graph_id.
-        """
-        pass
-
-    @abstractmethod
-    def commit(self, conf_file: Optional[Path] = None) -> None:
-        """
-        Write current configuration out to the indicated file.
-        If no conf_file is provided, then replaces the
-        original file/database used to initialize the object.
-        """
-        pass
 
 
 # simple implementation

invokeai/app/services/names/names_base.py

@@ -0,0 +1,11 @@
+from abc import ABC, abstractmethod
+
+
+class NameServiceBase(ABC):
+    """Low-level service responsible for naming resources (images, latents, etc)."""
+
+    # TODO: Add customizable naming schemes
+    @abstractmethod
+    def create_image_name(self) -> str:
+        """Creates a name for an image."""
+        pass

invokeai/app/services/names/names_common.py

@@ -0,0 +1,8 @@
+from enum import Enum, EnumMeta
+
+
+class ResourceType(str, Enum, metaclass=EnumMeta):
+    """Enum for resource types."""
+
+    IMAGE = "image"
+    LATENT = "latent"

invokeai/app/services/names/names_default.py

@@ -0,0 +1,13 @@
+from invokeai.app.util.misc import uuid_string
+
+from .names_base import NameServiceBase
+
+
+class SimpleNameService(NameServiceBase):
+    """Creates image names from UUIDs."""
+
+    # TODO: Add customizable naming schemes
+    def create_image_name(self) -> str:
+        uuid_str = uuid_string()
+        filename = f"{uuid_str}.png"
+        return filename

invokeai/app/services/resource_name.py

@@ -1,31 +0,0 @@
-from abc import ABC, abstractmethod
-from enum import Enum, EnumMeta
-
-from invokeai.app.util.misc import uuid_string
-
-
-class ResourceType(str, Enum, metaclass=EnumMeta):
-    """Enum for resource types."""
-
-    IMAGE = "image"
-    LATENT = "latent"
-
-
-class NameServiceBase(ABC):
-    """Low-level service responsible for naming resources (images, latents, etc)."""
-
-    # TODO: Add customizable naming schemes
-    @abstractmethod
-    def create_image_name(self) -> str:
-        """Creates a name for an image."""
-        pass
-
-
-class SimpleNameService(NameServiceBase):
-    """Creates image names from UUIDs."""
-
-    # TODO: Add customizable naming schemes
-    def create_image_name(self) -> str:
-        uuid_str = uuid_string()
-        filename = f"{uuid_str}.png"
-        return filename

invokeai/app/services/session_processor/session_processor_default.py

@@ -7,7 +7,7 @@ from typing import Optional
 from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event as FastAPIEvent
 
-from invokeai.app.services.events import EventServiceBase
+from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
 
 from ..invoker import Invoker

invokeai/app/services/session_queue/session_queue_base.py

@@ -1,7 +1,6 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from invokeai.app.services.graph import Graph
 from invokeai.app.services.session_queue.session_queue_common import (
     QUEUE_ITEM_STATUS,
     Batch,
@@ -18,6 +17,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueItemDTO,
     SessionQueueStatus,
 )
+from invokeai.app.services.shared.graph import Graph
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
 
 

invokeai/app/services/session_queue/session_queue_common.py

@@ -7,7 +7,7 @@ from pydantic import BaseModel, Field, StrictStr, parse_raw_as, root_validator,
 from pydantic.json import pydantic_encoder
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
-from invokeai.app.services.graph import Graph, GraphExecutionState, NodeNotFoundError
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState, NodeNotFoundError
 from invokeai.app.util.misc import uuid_string
 
 # region Errors

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -5,8 +5,7 @@ from typing import Optional, Union, cast
 from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event as FastAPIEvent
 
-from invokeai.app.services.events import EventServiceBase
+from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.services.graph import Graph
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.session_queue.session_queue_base import SessionQueueBase
 from invokeai.app.services.session_queue.session_queue_common import (
@@ -29,8 +28,9 @@ from invokeai.app.services.session_queue.session_queue_common import (
     calc_session_count,
     prepare_values_to_insert,
 )
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.graph import Graph
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 
 
 class SqliteSessionQueue(SessionQueueBase):

invokeai/app/services/shared/default_graphs.py

@@ -1,10 +1,11 @@
-from ..invocations.compel import CompelInvocation
+from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
-from ..invocations.image import ImageNSFWBlurInvocation
+
-from ..invocations.latent import DenoiseLatentsInvocation, LatentsToImageInvocation
+from ...invocations.compel import CompelInvocation
-from ..invocations.noise import NoiseInvocation
+from ...invocations.image import ImageNSFWBlurInvocation
-from ..invocations.primitives import IntegerInvocation
+from ...invocations.latent import DenoiseLatentsInvocation, LatentsToImageInvocation
+from ...invocations.noise import NoiseInvocation
+from ...invocations.primitives import IntegerInvocation
 from .graph import Edge, EdgeConnection, ExposedNodeInput, ExposedNodeOutput, Graph, LibraryGraph
-from .item_storage import ItemStorageABC
 
 default_text_to_image_graph_id = "539b2af5-2b4d-4d8c-8071-e54a3255fc74"
 

invokeai/app/services/shared/graph.py

@@ -8,11 +8,9 @@ import networkx as nx
 from pydantic import BaseModel, root_validator, validator
 from pydantic.fields import Field
 
-from invokeai.app.util.misc import uuid_string
-
 # Importing * is bad karma but needed here for node detection
-from ..invocations import *  # noqa: F401 F403
+from invokeai.app.invocations import *  # noqa: F401 F403
-from ..invocations.baseinvocation import (
+from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     Input,
@@ -23,6 +21,7 @@ from ..invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
+from invokeai.app.util.misc import uuid_string
 
 # in 3.10 this would be "from types import NoneType"
 NoneType = type(None)

invokeai/app/services/shared/sqlite.py

@@ -4,6 +4,8 @@ from logging import Logger
 
 from invokeai.app.services.config import InvokeAIAppConfig
 
+sqlite_memory = ":memory:"
+
 
 class SqliteDatabase:
     conn: sqlite3.Connection
@@ -16,7 +18,7 @@ class SqliteDatabase:
         self._config = config
 
         if self._config.use_memory_db:
-            location = ":memory:"
+            location = sqlite_memory
             logger.info("Using in-memory database")
         else:
             db_path = self._config.db_path

invokeai/app/services/urls/urls_base.py

@@ -0,0 +1,10 @@
+from abc import ABC, abstractmethod
+
+
+class UrlServiceBase(ABC):
+    """Responsible for building URLs for resources."""
+
+    @abstractmethod
+    def get_image_url(self, image_name: str, thumbnail: bool = False) -> str:
+        """Gets the URL for an image or thumbnail."""
+        pass

invokeai/app/services/urls/urls_default.py

@@ -1,14 +1,6 @@
 import os
-from abc import ABC, abstractmethod
 
-
+from .urls_base import UrlServiceBase
-class UrlServiceBase(ABC):
-    """Responsible for building URLs for resources."""
-
-    @abstractmethod
-    def get_image_url(self, image_name: str, thumbnail: bool = False) -> str:
-        """Gets the URL for an image or thumbnail."""
-        pass
 
 
 class LocalUrlService(UrlServiceBase):

invokeai/app/util/metadata.py

@@ -3,7 +3,7 @@ from typing import Optional
 
 from pydantic import ValidationError
 
-from invokeai.app.services.graph import Edge
+from invokeai.app.services.shared.graph import Edge
 
 
 def get_metadata_graph_from_raw_session(session_raw: str) -> Optional[dict]:

invokeai/app/util/step_callback.py

@@ -1,8 +1,7 @@
 import torch
 from PIL import Image
 
-from invokeai.app.models.exceptions import CanceledException
+from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException, ProgressImage
-from invokeai.app.models.image import ProgressImage
 
 from ...backend.model_management.models import BaseModelType
 from ...backend.stable_diffusion import PipelineIntermediateState

tests/nodes/test_graph_execution_state.py

@@ -1,5 +1,4 @@
 import logging
-import threading
 
 import pytest
 
@@ -10,20 +9,27 @@ from .test_nodes import (  # isort: split
     TestEventService,
     TextToImageTestInvocation,
 )
-import sqlite3
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
 from invokeai.app.invocations.collections import RangeInvocation
 from invokeai.app.invocations.math import AddInvocation, MultiplyInvocation
-from invokeai.app.services.config.invokeai_config import InvokeAIAppConfig
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.graph import CollectInvocation, Graph, GraphExecutionState, IterateInvocation, LibraryGraph
 from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_queue import MemoryInvocationQueue
+from invokeai.app.services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
+from invokeai.app.services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats import InvocationStatsService
+from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
-from invokeai.app.services.processor import DefaultInvocationProcessor
+from invokeai.app.services.item_storage.item_storage_sqlite import SqliteItemStorage
 from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
-from invokeai.app.services.sqlite import SqliteItemStorage, sqlite_memory
+from invokeai.app.services.shared.graph import (
+    CollectInvocation,
+    Graph,
+    GraphExecutionState,
+    IterateInvocation,
+    LibraryGraph,
+)
+from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.backend.util.logging import InvokeAILogger
 
 from .test_invoker import create_edge
 
@@ -42,29 +48,33 @@ def simple_graph():
 # the test invocations.
 @pytest.fixture
 def mock_services() -> InvocationServices:
-    lock = threading.Lock()
+    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
+    db = SqliteDatabase(configuration, InvokeAILogger.get_logger())
     # NOTE: none of these are actually called by the test invocations
-    db_conn = sqlite3.connect(sqlite_memory, check_same_thread=False)
+    graph_execution_manager = SqliteItemStorage[GraphExecutionState](db=db, table_name="graph_executions")
-    graph_execution_manager = SqliteItemStorage[GraphExecutionState](
-        conn=db_conn, table_name="graph_executions", lock=lock
-    )
     return InvocationServices(
-        model_manager=None,  # type: ignore
+        board_image_records=None,  # type: ignore
-        events=TestEventService(),
-        logger=logging,  # type: ignore
-        images=None,  # type: ignore
-        latents=None,  # type: ignore
-        boards=None,  # type: ignore
         board_images=None,  # type: ignore
-        queue=MemoryInvocationQueue(),
+        board_records=None,  # type: ignore
-        graph_library=SqliteItemStorage[LibraryGraph](conn=db_conn, table_name="graphs", lock=lock),
+        boards=None,  # type: ignore
+        configuration=configuration,
+        events=TestEventService(),
         graph_execution_manager=graph_execution_manager,
-        performance_statistics=InvocationStatsService(graph_execution_manager),
+        graph_library=SqliteItemStorage[LibraryGraph](db=db, table_name="graphs"),
+        image_files=None,  # type: ignore
+        image_records=None,  # type: ignore
+        images=None,  # type: ignore
+        invocation_cache=MemoryInvocationCache(max_cache_size=0),
+        latents=None,  # type: ignore
+        logger=logging,  # type: ignore
+        model_manager=None,  # type: ignore
+        names=None,  # type: ignore
+        performance_statistics=InvocationStatsService(),
         processor=DefaultInvocationProcessor(),
-        configuration=InvokeAIAppConfig(node_cache_size=0),  # type: ignore
+        queue=MemoryInvocationQueue(),
-        session_queue=None,  # type: ignore
         session_processor=None,  # type: ignore
-        invocation_cache=MemoryInvocationCache(),  # type: ignore
+        session_queue=None,  # type: ignore
+        urls=None,  # type: ignore
     )
 
 

tests/nodes/test_invoker.py

@@ -1,10 +1,9 @@
 import logging
-import sqlite3
-import threading
 
 import pytest
 
-from invokeai.app.services.config.invokeai_config import InvokeAIAppConfig
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.backend.util.logging import InvokeAILogger
 
 # This import must happen before other invoke imports or test in other files(!!) break
 from .test_nodes import (  # isort: split
@@ -16,15 +15,16 @@ from .test_nodes import (  # isort: split
     wait_until,
 )
 
-from invokeai.app.services.graph import Graph, GraphExecutionState, GraphInvocation, LibraryGraph
 from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_queue import MemoryInvocationQueue
+from invokeai.app.services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
+from invokeai.app.services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats import InvocationStatsService
+from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.processor import DefaultInvocationProcessor
+from invokeai.app.services.item_storage.item_storage_sqlite import SqliteItemStorage
 from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
-from invokeai.app.services.sqlite import SqliteItemStorage, sqlite_memory
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation, LibraryGraph
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 
 
 @pytest.fixture
@@ -52,29 +52,34 @@ def graph_with_subgraph():
 # the test invocations.
 @pytest.fixture
 def mock_services() -> InvocationServices:
-    lock = threading.Lock()
+    db = SqliteDatabase(InvokeAIAppConfig(use_memory_db=True), InvokeAILogger.get_logger())
+    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
+
     # NOTE: none of these are actually called by the test invocations
-    db_conn = sqlite3.connect(sqlite_memory, check_same_thread=False)
+    graph_execution_manager = SqliteItemStorage[GraphExecutionState](db=db, table_name="graph_executions")
-    graph_execution_manager = SqliteItemStorage[GraphExecutionState](
-        conn=db_conn, table_name="graph_executions", lock=lock
-    )
     return InvocationServices(
-        model_manager=None,  # type: ignore
+        board_image_records=None,  # type: ignore
-        events=TestEventService(),
-        logger=logging,  # type: ignore
-        images=None,  # type: ignore
-        latents=None,  # type: ignore
-        boards=None,  # type: ignore
         board_images=None,  # type: ignore
-        queue=MemoryInvocationQueue(),
+        board_records=None,  # type: ignore
-        graph_library=SqliteItemStorage[LibraryGraph](conn=db_conn, table_name="graphs", lock=lock),
+        boards=None,  # type: ignore
+        configuration=configuration,
+        events=TestEventService(),
         graph_execution_manager=graph_execution_manager,
-        processor=DefaultInvocationProcessor(),
+        graph_library=SqliteItemStorage[LibraryGraph](db=db, table_name="graphs"),
-        performance_statistics=InvocationStatsService(graph_execution_manager),
+        image_files=None,  # type: ignore
-        configuration=InvokeAIAppConfig(node_cache_size=0),  # type: ignore
+        image_records=None,  # type: ignore
-        session_queue=None,  # type: ignore
+        images=None,  # type: ignore
-        session_processor=None,  # type: ignore
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
+        latents=None,  # type: ignore
+        logger=logging,  # type: ignore
+        model_manager=None,  # type: ignore
+        names=None,  # type: ignore
+        performance_statistics=InvocationStatsService(),
+        processor=DefaultInvocationProcessor(),
+        queue=MemoryInvocationQueue(),
+        session_processor=None,  # type: ignore
+        session_queue=None,  # type: ignore
+        urls=None,  # type: ignore
     )
 
 

tests/nodes/test_node_graph.py

@@ -11,8 +11,8 @@ from invokeai.app.invocations.image import ShowImageInvocation
 from invokeai.app.invocations.math import AddInvocation, SubtractInvocation
 from invokeai.app.invocations.primitives import FloatInvocation, IntegerInvocation
 from invokeai.app.invocations.upscale import ESRGANInvocation
-from invokeai.app.services.default_graphs import create_text_to_image
+from invokeai.app.services.shared.default_graphs import create_text_to_image
-from invokeai.app.services.graph import (
+from invokeai.app.services.shared.graph import (
     CollectInvocation,
     Edge,
     EdgeConnection,

tests/nodes/test_nodes.py

@@ -82,8 +82,8 @@ class PromptCollectionTestInvocation(BaseInvocation):
 
 
 # Importing these must happen after test invocations are defined or they won't register
-from invokeai.app.services.events import EventServiceBase  # noqa: E402
+from invokeai.app.services.events.events_base import EventServiceBase  # noqa: E402
-from invokeai.app.services.graph import Edge, EdgeConnection  # noqa: E402
+from invokeai.app.services.shared.graph import Edge, EdgeConnection  # noqa: E402
 
 
 def create_edge(from_id: str, from_field: str, to_id: str, to_field: str) -> Edge:

tests/nodes/test_session_queue.py

@@ -1,7 +1,6 @@
 import pytest
 from pydantic import ValidationError, parse_raw_as
 
-from invokeai.app.services.graph import Graph, GraphExecutionState, GraphInvocation
 from invokeai.app.services.session_queue.session_queue_common import (
     Batch,
     BatchDataCollection,
@@ -12,6 +11,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     populate_graph,
     prepare_values_to_insert,
 )
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation
 from tests.nodes.test_nodes import PromptTestInvocation
 
 

tests/nodes/test_sqlite.py

@@ -1,10 +1,10 @@
-import sqlite3
-import threading
-
 import pytest
 from pydantic import BaseModel, Field
 
-from invokeai.app.services.sqlite import SqliteItemStorage, sqlite_memory
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.item_storage.item_storage_sqlite import SqliteItemStorage
+from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.backend.util.logging import InvokeAILogger
 
 
 class TestModel(BaseModel):
@@ -14,8 +14,8 @@ class TestModel(BaseModel):
 
 @pytest.fixture
 def db() -> SqliteItemStorage[TestModel]:
-    db_conn = sqlite3.connect(sqlite_memory, check_same_thread=False)
+    sqlite_db = SqliteDatabase(InvokeAIAppConfig(use_memory_db=True), InvokeAILogger.get_logger())
-    return SqliteItemStorage[TestModel](db_conn, table_name="test", id_field="id", lock=threading.Lock())
+    return SqliteItemStorage[TestModel](db=sqlite_db, table_name="test", id_field="id")
 
 
 def test_sqlite_service_can_create_and_get(db: SqliteItemStorage[TestModel]):

tests/test_model_manager.py

@@ -2,7 +2,7 @@ from pathlib import Path
 
 import pytest
 
-from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.backend import BaseModelType, ModelManager, ModelType, SubModelType
 
 BASIC_MODEL_NAME = ("SDXL base", BaseModelType.StableDiffusionXL, ModelType.Main)