InvokeAI/invokeai/app/api/dependencies.py
psychedelicious 06429028c8 revert(nodes): revert making tensors/conditioning use item storage
Turns out they are just different enough in purpose that the implementations would be rather unintuitive. I've made a separate ObjectSerializer service to handle tensors and conditioning.

Refined the class a bit too.
2024-02-15 17:30:03 +11:00

153 lines
6.5 KiB
Python

# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
from logging import Logger
import torch
from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
from invokeai.app.services.object_serializer.object_serializer_ephemeral_disk import ObjectSerializerEphemeralDisk
from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
from invokeai.app.services.shared.sqlite.sqlite_util import init_db
from invokeai.backend.model_manager.metadata import ModelMetadataStore
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
from invokeai.backend.util.logging import InvokeAILogger
from invokeai.version.invokeai_version import __version__
from ..services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
from ..services.board_images.board_images_default import BoardImagesService
from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
from ..services.boards.boards_default import BoardService
from ..services.config import InvokeAIAppConfig
from ..services.download import DownloadQueueService
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.invocation_stats_default import InvocationStatsService
from ..services.invoker import Invoker
from ..services.model_install import ModelInstallService
from ..services.model_manager.model_manager_default import ModelManagerService
from ..services.model_records import ModelRecordServiceSQL
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.graph import GraphExecutionState
from ..services.urls.urls_default import LocalUrlService
from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
from .events import FastAPIEventService
# TODO: is there a better way to achieve this?
def check_internet() -> bool:
"""
Return true if the internet is reachable.
It does this by pinging huggingface.co.
"""
import urllib.request
host = "http://huggingface.co"
try:
urllib.request.urlopen(host, timeout=1)
return True
except Exception:
return False
logger = InvokeAILogger.get_logger()
class ApiDependencies:
"""Contains and initializes all dependencies for the API"""
invoker: Invoker
@staticmethod
def initialize(config: InvokeAIAppConfig, event_handler_id: int, logger: Logger = logger) -> None:
logger.info(f"InvokeAI version {__version__}")
logger.info(f"Root directory = {str(config.root_path)}")
logger.debug(f"Internet connectivity is {config.internet_available}")
output_folder = config.output_path
if output_folder is None:
raise ValueError("Output folder is not set")
image_files = DiskImageFileStorage(f"{output_folder}/images")
db = init_db(config=config, logger=logger, image_files=image_files)
configuration = config
logger = logger
board_image_records = SqliteBoardImageRecordStorage(db=db)
board_images = BoardImagesService()
board_records = SqliteBoardRecordStorage(db=db)
boards = BoardService()
events = FastAPIEventService(event_handler_id)
graph_execution_manager = ItemStorageMemory[GraphExecutionState]()
image_records = SqliteImageRecordStorage(db=db)
images = ImageService()
invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
tensors = ObjectSerializerForwardCache(ObjectSerializerEphemeralDisk[torch.Tensor](output_folder / "tensors"))
conditioning = ObjectSerializerForwardCache(
ObjectSerializerEphemeralDisk[ConditioningFieldData](output_folder / "conditioning")
)
model_manager = ModelManagerService(config, logger)
model_record_service = ModelRecordServiceSQL(db=db)
download_queue_service = DownloadQueueService(event_bus=events)
metadata_store = ModelMetadataStore(db=db)
model_install_service = ModelInstallService(
app_config=config,
record_store=model_record_service,
download_queue=download_queue_service,
metadata_store=metadata_store,
event_bus=events,
)
names = SimpleNameService()
performance_statistics = InvocationStatsService()
processor = DefaultInvocationProcessor()
queue = MemoryInvocationQueue()
session_processor = DefaultSessionProcessor()
session_queue = SqliteSessionQueue(db=db)
urls = LocalUrlService()
workflow_records = SqliteWorkflowRecordsStorage(db=db)
services = InvocationServices(
board_image_records=board_image_records,
board_images=board_images,
board_records=board_records,
boards=boards,
configuration=configuration,
events=events,
graph_execution_manager=graph_execution_manager,
image_files=image_files,
image_records=image_records,
images=images,
invocation_cache=invocation_cache,
logger=logger,
model_manager=model_manager,
model_records=model_record_service,
download_queue=download_queue_service,
model_install=model_install_service,
names=names,
performance_statistics=performance_statistics,
processor=processor,
queue=queue,
session_processor=session_processor,
session_queue=session_queue,
urls=urls,
workflow_records=workflow_records,
tensors=tensors,
conditioning=conditioning,
)
ApiDependencies.invoker = Invoker(services)
db.clean()
@staticmethod
def shutdown() -> None:
if ApiDependencies.invoker:
ApiDependencies.invoker.stop()