Merge branch 'lstein/logging-improvements' of github.com:invoke-ai/InvokeAI into lstein/logging-improvements

.github/workflows/test-invoke-pip.yml

@@ -125,6 +125,7 @@ jobs:
           --no-nsfw_checker
           --precision=float32
           --always_use_cpu
+          --use_memory_db
           --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
           --from_file ${{ env.TEST_PROMPTS }}
 

invokeai/app/cli_app.py

@@ -13,10 +13,13 @@ from typing import (
 
 from pydantic import BaseModel, ValidationError
 from pydantic.fields import Field
+from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
+from invokeai.app.services.images import ImageService
+from invokeai.app.services.metadata import CoreMetadataService
+from invokeai.app.services.urls import LocalUrlService
 
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.services.metadata import PngMetadataService
 from .services.default_graphs import create_system_graphs
 from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 
@@ -188,6 +191,9 @@ def invoke_all(context: CliContext):
         raise SessionError()
 
 
+logger = logger.InvokeAILogger.getLogger()
+
+
 def invoke_cli():
     # this gets the basic configuration
     config = get_invokeai_config()
@@ -206,24 +212,43 @@ def invoke_cli():
     
     events = EventServiceBase()
     output_folder = config.output_path
-    metadata = PngMetadataService()
 
     # TODO: build a file/path manager?
+    if config.use_memory_db:
+        db_location = ":memory:"
+    else:
         db_location = os.path.join(output_folder, "invokeai.db")
 
+    logger.info(f'InvokeAI database location is "{db_location}"')
+
+    graph_execution_manager = SqliteItemStorage[GraphExecutionState](
+            filename=db_location, table_name="graph_executions"
+        )
+
+    urls = LocalUrlService()
+    metadata = CoreMetadataService()
+    image_record_storage = SqliteImageRecordStorage(db_location)
+    image_file_storage = DiskImageFileStorage(f"{output_folder}/images")
+
+    images = ImageService(
+        image_record_storage=image_record_storage,
+        image_file_storage=image_file_storage,
+        metadata=metadata,
+        url=urls,
+        logger=logger,
+        graph_execution_manager=graph_execution_manager,
+    )
+
     services = InvocationServices(
         model_manager=model_manager,
         events=events,
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents')),
-        images=DiskImageFileStorage(f'{output_folder}/images', metadata_service=metadata),
+        images=images,
-        metadata=metadata,
         queue=MemoryInvocationQueue(),
         graph_library=SqliteItemStorage[LibraryGraph](
             filename=db_location, table_name="graphs"
         ),
-        graph_execution_manager=SqliteItemStorage[GraphExecutionState](
+        graph_execution_manager=graph_execution_manager,
-            filename=db_location, table_name="graph_executions"
-        ),
         processor=DefaultInvocationProcessor(),
         restoration=RestorationServices(config,logger=logger),
         logger=logger,

invokeai/app/services/config.py

@@ -352,6 +352,7 @@ setting environment variables INVOKEAI_<setting>.
     sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
     xformers_enabled    : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
 
+
     root                : Path = Field(default=_find_root(), description='InvokeAI runtime root directory', category='Paths')
     autoconvert_dir     : Path = Field(default=None, description='Path to a directory of ckpt files to be converted into diffusers and imported on startup.', category='Paths')
     conf_path           : Path = Field(default='configs/models.yaml', description='Path to models definition file', category='Paths')
@@ -361,6 +362,7 @@ setting environment variables INVOKEAI_<setting>.
     lora_dir            : Path = Field(default='loras', description='Path to InvokeAI LoRA model directory', category='Paths')
     outdir              : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
     from_file           : Path = Field(default=None, description='Take command input from the indicated file (command-line client only)', category='Paths')
+    use_memory_db       : bool = Field(default=False, description='Use in-memory database for storing image metadata', category='Paths')
 
     model               : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
     embeddings          : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
@@ -515,7 +517,7 @@ class PagingArgumentParser(argparse.ArgumentParser):
         text = self.format_help()
         pydoc.pager(text)
 
-def get_invokeai_config(cls:Type[InvokeAISettings]=InvokeAIAppConfig,**kwargs)->InvokeAISettings:
+def get_invokeai_config(cls:Type[InvokeAISettings]=InvokeAIAppConfig,**kwargs)->InvokeAIAppConfig:
     '''
     This returns a singleton InvokeAIAppConfig configuration object.
     '''

invokeai/app/services/invocation_services.py

@@ -1,18 +1,17 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
+from __future__ import annotations
 from typing import TYPE_CHECKING
-from logging import Logger
-
-from invokeai.app.services.images import ImageService
-from invokeai.backend import ModelManager
-from .events import EventServiceBase
-from .latent_storage import LatentsStorageBase
-from .restoration_services import RestorationServices
-from .invocation_queue import InvocationQueueABC
-from .item_storage import ItemStorageABC
-from .config import InvokeAISettings
-
 
 if TYPE_CHECKING:
+    from logging import Logger
+    from invokeai.app.services.images import ImageService
+    from invokeai.backend import ModelManager
+    from invokeai.app.services.events import EventServiceBase
+    from invokeai.app.services.latent_storage import LatentsStorageBase
+    from invokeai.app.services.restoration_services import RestorationServices
+    from invokeai.app.services.invocation_queue import InvocationQueueABC
+    from invokeai.app.services.item_storage import ItemStorageABC
+    from invokeai.app.services.config import InvokeAISettings
     from invokeai.app.services.graph import GraphExecutionState, LibraryGraph
     from invokeai.app.services.invoker import InvocationProcessorABC
 
@@ -20,32 +19,33 @@ if TYPE_CHECKING:
 class InvocationServices:
     """Services that can be used by invocations"""
 
-    events: EventServiceBase
+    # TODO: Just forward-declared everything due to circular dependencies. Fix structure.
-    latents: LatentsStorageBase
+    events: "EventServiceBase"
-    queue: InvocationQueueABC
+    latents: "LatentsStorageBase"
-    model_manager: ModelManager
+    queue: "InvocationQueueABC"
-    restoration: RestorationServices
+    model_manager: "ModelManager"
-    configuration: InvokeAISettings
+    restoration: "RestorationServices"
-    images: ImageService
+    configuration: "InvokeAISettings"
+    images: "ImageService"
 
     # NOTE: we must forward-declare any types that include invocations, since invocations can use services
-    graph_library: ItemStorageABC["LibraryGraph"]
+    graph_library: "ItemStorageABC"["LibraryGraph"]
-    graph_execution_manager: ItemStorageABC["GraphExecutionState"]
+    graph_execution_manager: "ItemStorageABC"["GraphExecutionState"]
     processor: "InvocationProcessorABC"
 
     def __init__(
         self,
-        model_manager: ModelManager,
+        model_manager: "ModelManager",
-        events: EventServiceBase,
+        events: "EventServiceBase",
-        logger: Logger,
+        logger: "Logger",
-        latents: LatentsStorageBase,
+        latents: "LatentsStorageBase",
-        images: ImageService,
+        images: "ImageService",
-        queue: InvocationQueueABC,
+        queue: "InvocationQueueABC",
-        graph_library: ItemStorageABC["LibraryGraph"],
+        graph_library: "ItemStorageABC"["LibraryGraph"],
-        graph_execution_manager: ItemStorageABC["GraphExecutionState"],
+        graph_execution_manager: "ItemStorageABC"["GraphExecutionState"],
         processor: "InvocationProcessorABC",
-        restoration: RestorationServices,
+        restoration: "RestorationServices",
-        configuration: InvokeAISettings = None,
+        configuration: "InvokeAISettings",
     ):
         self.model_manager = model_manager
         self.events = events

invokeai/app/services/processor.py

@@ -1,10 +1,7 @@
 import time
 import traceback
 from threading import Event, Thread, BoundedSemaphore
-from typing import Any, TypeGuard
 
-from invokeai.app.invocations.image import ImageOutput
-from invokeai.app.models.image import ImageType
 from ..invocations.baseinvocation import InvocationContext
 from .invocation_queue import InvocationQueueItem
 from .invoker import InvocationProcessorABC, Invoker

tests/nodes/test_graph_execution_state.py

@@ -35,6 +35,7 @@ def mock_services():
         graph_execution_manager = SqliteItemStorage[GraphExecutionState](filename = sqlite_memory, table_name = 'graph_executions'),
         processor = DefaultInvocationProcessor(),
         restoration = None, # type: ignore
+        configuration = None, # type: ignore
     )
 
 def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[BaseInvocation, BaseInvocationOutput]:

tests/nodes/test_invoker.py

@@ -33,6 +33,7 @@ def mock_services() -> InvocationServices:
         graph_execution_manager = SqliteItemStorage[GraphExecutionState](filename = sqlite_memory, table_name = 'graph_executions'),
         processor = DefaultInvocationProcessor(),
         restoration = None, # type: ignore
+        configuration = None, # type: ignore
     )
 
 @pytest.fixture()

tests/nodes/test_nodes.py

@@ -49,7 +49,7 @@ class ImageTestInvocation(BaseInvocation):
     prompt: str = Field(default = "")
 
     def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
-        return ImageTestInvocationOutput(image=ImageField(image_name=self.id, width=512, height=512, mode="", info={}))
+        return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 class PromptCollectionTestInvocationOutput(BaseInvocationOutput):
     type: Literal['test_prompt_collection_output'] = 'test_prompt_collection_output'