mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
725c03cf87
Consolidate graph processing logic into session processor. With graphs as the unit of work, and the session queue distributing graphs, we no longer need the invocation queue or processor. Instead, the session processor dequeues the next session and processes it in a simple loop, greatly simplifying the app. - Remove `graph_execution_manager` service. - Remove `queue` (invocation queue) service. - Remove `processor` (invocation processor) service. - Remove queue-related logic from `Invoker`. It now only starts and stops the services, providing them with access to other services. - Remove unused `invocation_retrieval_error` and `session_retrieval_error` events, these are no longer needed. - Clean up stats service now that it is less coupled to the rest of the app. - Refactor cancellation logic - cancellations now originate from session queue (i.e. HTTP cancel endpoint) and are emitted as events. Processor gets the events and sets the canceled event. Access to this event is provided to the invocation context for e.g. the step callback. - Remove `sessions` router; it provided access to `graph_executions` but that no longer exists.
139 lines
5.7 KiB
Python
139 lines
5.7 KiB
Python
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
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from logging import Logger
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import torch
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from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
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from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
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from invokeai.app.services.shared.sqlite.sqlite_util import init_db
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from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
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from invokeai.backend.util.logging import InvokeAILogger
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from invokeai.version.invokeai_version import __version__
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from ..services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
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from ..services.board_images.board_images_default import BoardImagesService
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from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
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from ..services.boards.boards_default import BoardService
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from ..services.config import InvokeAIAppConfig
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from ..services.download import DownloadQueueService
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from ..services.image_files.image_files_disk import DiskImageFileStorage
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from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
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from ..services.images.images_default import ImageService
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from ..services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
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from ..services.invocation_services import InvocationServices
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from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
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from ..services.invoker import Invoker
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from ..services.model_manager.model_manager_default import ModelManagerService
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from ..services.model_metadata import ModelMetadataStoreSQL
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from ..services.model_records import ModelRecordServiceSQL
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from ..services.names.names_default import SimpleNameService
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from ..services.session_processor.session_processor_default import DefaultSessionProcessor
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from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
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from ..services.urls.urls_default import LocalUrlService
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from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
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from .events import FastAPIEventService
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# TODO: is there a better way to achieve this?
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def check_internet() -> bool:
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"""
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Return true if the internet is reachable.
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It does this by pinging huggingface.co.
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"""
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import urllib.request
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host = "http://huggingface.co"
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try:
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urllib.request.urlopen(host, timeout=1)
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return True
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except Exception:
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return False
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logger = InvokeAILogger.get_logger()
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class ApiDependencies:
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"""Contains and initializes all dependencies for the API"""
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invoker: Invoker
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@staticmethod
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def initialize(config: InvokeAIAppConfig, event_handler_id: int, logger: Logger = logger) -> None:
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logger.info(f"InvokeAI version {__version__}")
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logger.info(f"Root directory = {str(config.root_path)}")
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logger.debug(f"Internet connectivity is {config.internet_available}")
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output_folder = config.output_path
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if output_folder is None:
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raise ValueError("Output folder is not set")
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image_files = DiskImageFileStorage(f"{output_folder}/images")
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db = init_db(config=config, logger=logger, image_files=image_files)
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configuration = config
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logger = logger
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board_image_records = SqliteBoardImageRecordStorage(db=db)
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board_images = BoardImagesService()
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board_records = SqliteBoardRecordStorage(db=db)
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boards = BoardService()
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events = FastAPIEventService(event_handler_id)
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image_records = SqliteImageRecordStorage(db=db)
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images = ImageService()
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invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
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tensors = ObjectSerializerForwardCache(
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ObjectSerializerDisk[torch.Tensor](output_folder / "tensors", ephemeral=True)
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)
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conditioning = ObjectSerializerForwardCache(
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ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True)
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)
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download_queue_service = DownloadQueueService(event_bus=events)
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model_metadata_service = ModelMetadataStoreSQL(db=db)
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model_manager = ModelManagerService.build_model_manager(
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app_config=configuration,
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model_record_service=ModelRecordServiceSQL(db=db, metadata_store=model_metadata_service),
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download_queue=download_queue_service,
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events=events,
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)
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names = SimpleNameService()
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performance_statistics = InvocationStatsService()
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session_processor = DefaultSessionProcessor()
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session_queue = SqliteSessionQueue(db=db)
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urls = LocalUrlService()
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workflow_records = SqliteWorkflowRecordsStorage(db=db)
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services = InvocationServices(
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board_image_records=board_image_records,
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board_images=board_images,
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board_records=board_records,
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boards=boards,
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configuration=configuration,
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events=events,
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image_files=image_files,
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image_records=image_records,
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images=images,
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invocation_cache=invocation_cache,
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logger=logger,
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model_manager=model_manager,
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download_queue=download_queue_service,
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names=names,
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performance_statistics=performance_statistics,
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session_processor=session_processor,
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session_queue=session_queue,
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urls=urls,
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workflow_records=workflow_records,
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tensors=tensors,
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conditioning=conditioning,
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)
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ApiDependencies.invoker = Invoker(services)
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db.clean()
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@staticmethod
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def shutdown() -> None:
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if ApiDependencies.invoker:
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ApiDependencies.invoker.stop()
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