InvokeAI/invokeai/app/services/invocation_services.py
psychedelicious fe0391c86b feat(nodes): use ItemStorageABC for tensors and conditioning
Turns out `ItemStorageABC` was almost identical to `PickleStorageBase`. Instead of maintaining separate classes, we can use `ItemStorageABC` for both.

There's only one change needed - the `ItemStorageABC.set` method must return the newly stored item's ID. This allows us to let the service handle the responsibility of naming the item, but still create the requisite output objects during node execution.

The naming implementation is improved here. It extracts the name of the generic and appends a UUID to that string when saving items.
2024-02-15 17:30:03 +11:00

97 lines
4.2 KiB
Python

# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from logging import Logger
import torch
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
from .board_image_records.board_image_records_base import BoardImageRecordStorageBase
from .board_images.board_images_base import BoardImagesServiceABC
from .board_records.board_records_base import BoardRecordStorageBase
from .boards.boards_base import BoardServiceABC
from .config import InvokeAIAppConfig
from .download import DownloadQueueServiceBase
from .events.events_base import EventServiceBase
from .image_files.image_files_base import ImageFileStorageBase
from .image_records.image_records_base import ImageRecordStorageBase
from .images.images_base import ImageServiceABC
from .invocation_cache.invocation_cache_base import InvocationCacheBase
from .invocation_processor.invocation_processor_base import InvocationProcessorABC
from .invocation_queue.invocation_queue_base import InvocationQueueABC
from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
from .item_storage.item_storage_base import ItemStorageABC
from .model_install import ModelInstallServiceBase
from .model_manager.model_manager_base import ModelManagerServiceBase
from .model_records import ModelRecordServiceBase
from .names.names_base import NameServiceBase
from .session_processor.session_processor_base import SessionProcessorBase
from .session_queue.session_queue_base import SessionQueueBase
from .shared.graph import GraphExecutionState
from .urls.urls_base import UrlServiceBase
from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
class InvocationServices:
"""Services that can be used by invocations"""
def __init__(
self,
board_images: "BoardImagesServiceABC",
board_image_records: "BoardImageRecordStorageBase",
boards: "BoardServiceABC",
board_records: "BoardRecordStorageBase",
configuration: "InvokeAIAppConfig",
events: "EventServiceBase",
graph_execution_manager: "ItemStorageABC[GraphExecutionState]",
images: "ImageServiceABC",
image_files: "ImageFileStorageBase",
image_records: "ImageRecordStorageBase",
logger: "Logger",
model_manager: "ModelManagerServiceBase",
model_records: "ModelRecordServiceBase",
download_queue: "DownloadQueueServiceBase",
model_install: "ModelInstallServiceBase",
processor: "InvocationProcessorABC",
performance_statistics: "InvocationStatsServiceBase",
queue: "InvocationQueueABC",
session_queue: "SessionQueueBase",
session_processor: "SessionProcessorBase",
invocation_cache: "InvocationCacheBase",
names: "NameServiceBase",
urls: "UrlServiceBase",
workflow_records: "WorkflowRecordsStorageBase",
tensors: "ItemStorageABC[torch.Tensor]",
conditioning: "ItemStorageABC[ConditioningFieldData]",
):
self.board_images = board_images
self.board_image_records = board_image_records
self.boards = boards
self.board_records = board_records
self.configuration = configuration
self.events = events
self.graph_execution_manager = graph_execution_manager
self.images = images
self.image_files = image_files
self.image_records = image_records
self.logger = logger
self.model_manager = model_manager
self.model_records = model_records
self.download_queue = download_queue
self.model_install = model_install
self.processor = processor
self.performance_statistics = performance_statistics
self.queue = queue
self.session_queue = session_queue
self.session_processor = session_processor
self.invocation_cache = invocation_cache
self.names = names
self.urls = urls
self.workflow_records = workflow_records
self.tensors = tensors
self.conditioning = conditioning