Files
InvokeAI/invokeai/app/services/image_files/image_files_disk.py
psychedelicious c42d692ea6 feat: workflow library (#5148)
* chore: bump pydantic to 2.5.2

This release fixes pydantic/pydantic#8175 and allows us to use `JsonValue`

* fix(ui): exclude public/en.json from prettier config

* fix(workflow_records): fix SQLite workflow insertion to ignore duplicates

* feat(backend): update workflows handling

Update workflows handling for Workflow Library.

**Updated Workflow Storage**

"Embedded Workflows" are workflows associated with images, and are now only stored in the image files. "Library Workflows" are not associated with images, and are stored only in DB.

This works out nicely. We have always saved workflows to files, but recently began saving them to the DB in addition to in image files. When that happened, we stopped reading workflows from files, so all the workflows that only existed in images were inaccessible. With this change, access to those workflows is restored, and no workflows are lost.

**Updated Workflow Handling in Nodes**

Prior to this change, workflows were embedded in images by passing the whole workflow JSON to a special workflow field on a node. In the node's `invoke()` function, the node was able to access this workflow and save it with the image. This (inaccurately) models workflows as a property of an image and is rather awkward technically.

A workflow is now a property of a batch/session queue item. It is available in the InvocationContext and therefore available to all nodes during `invoke()`.

**Database Migrations**

Added a `SQLiteMigrator` class to handle database migrations. Migrations were needed to accomodate the DB-related changes in this PR. See the code for details.

The `images`, `workflows` and `session_queue` tables required migrations for this PR, and are using the new migrator. Other tables/services are still creating tables themselves. A followup PR will adapt them to use the migrator.

**Other/Support Changes**

- Add a `has_workflow` column to `images` table to indicate that the image has an embedded workflow.
- Add handling for retrieving the workflow from an image in python. The image file must be fetched, the workflow extracted, and then sent to client, avoiding needing the browser to parse the image file. With the `has_workflow` column, the UI knows if there is a workflow to be fetched, and only fetches when the user requests to load the workflow.
- Add route to get the workflow from an image
- Add CRUD service/routes for the library workflows
- `workflow_images` table and services removed (no longer needed now that embedded workflows are not in the DB)

* feat(ui): updated workflow handling (WIP)

Clientside updates for the backend workflow changes.

Includes roughed-out workflow library UI.

* feat: revert SQLiteMigrator class

Will pursue this in a separate PR.

* feat(nodes): do not overwrite custom node module names

Use a different, simpler method to detect if a node is custom.

* feat(nodes): restore WithWorkflow as no-op class

This class is deprecated and no longer needed. Set its workflow attr value to None (meaning it is now a no-op), and issue a warning when an invocation subclasses it.

* fix(nodes): fix get_workflow from queue item dict func

* feat(backend): add WorkflowRecordListItemDTO

This is the id, name, description, created at and updated at workflow columns/attrs. Used to display lists of workflowsl

* chore(ui): typegen

* feat(ui): add workflow loading, deleting to workflow library UI

* feat(ui): workflow library pagination button styles

* wip

* feat: workflow library WIP

- Save to library
- Duplicate
- Filter/sort
- UI/queries

* feat: workflow library - system graphs - wip

* feat(backend): sync system workflows to db

* fix: merge conflicts

* feat: simplify default workflows

- Rename "system" -> "default"
- Simplify syncing logic
- Update UI to match

* feat(workflows): update default workflows

- Update TextToImage_SD15
- Add TextToImage_SDXL
- Add README

* feat(ui): refine workflow list UI

* fix(workflow_records): typo

* fix(tests): fix tests

* feat(ui): clean up workflow library hooks

* fix(db): fix mis-ordered db cleanup step

It was happening before pruning queue items - should happen afterwards, else you have to restart the app again to free disk space made available by the pruning.

* feat(ui): tweak reset workflow editor translations

* feat(ui): split out workflow redux state

The `nodes` slice is a rather complicated slice. Removing `workflow` makes it a bit more reasonable.

Also helps to flatten state out a bit.

* docs: update default workflows README

* fix: tidy up unused files, unrelated changes

* fix(backend): revert unrelated service organisational changes

* feat(backend): workflow_records.get_many arg "filter_text" -> "query"

* feat(ui): use custom hook in current image buttons

Already in use elsewhere, forgot to use it here.

* fix(ui): remove commented out property

* fix(ui): fix workflow loading

- Different handling for loading from library vs external
- Fix bug where only nodes and edges loaded

* fix(ui): fix save/save-as workflow naming

* fix(ui): fix circular dependency

* fix(db): fix bug with releasing without lock in db.clean()

* fix(db): remove extraneous lock

* chore: bump ruff

* fix(workflow_records): default `category` to `WorkflowCategory.User`

This allows old workflows to validate when reading them from the db or image files.

* hide workflow library buttons if feature is disabled

---------

Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-12-09 09:48:38 +11:00

156 lines
6.0 KiB
Python

# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from pathlib import Path
from queue import Queue
from typing import Dict, Optional, Union
from PIL import Image, PngImagePlugin
from PIL.Image import Image as PILImageType
from send2trash import send2trash
from invokeai.app.invocations.baseinvocation import MetadataField
from invokeai.app.services.invoker import Invoker
from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
from .image_files_base import ImageFileStorageBase
from .image_files_common import ImageFileDeleteException, ImageFileNotFoundException, ImageFileSaveException
class DiskImageFileStorage(ImageFileStorageBase):
"""Stores images on disk"""
__output_folder: Path
__cache_ids: Queue # TODO: this is an incredibly naive cache
__cache: Dict[Path, PILImageType]
__max_cache_size: int
__invoker: Invoker
def __init__(self, output_folder: Union[str, Path]):
self.__cache = {}
self.__cache_ids = Queue()
self.__max_cache_size = 10 # TODO: get this from config
self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
self.__thumbnails_folder = self.__output_folder / "thumbnails"
# Validate required output folders at launch
self.__validate_storage_folders()
def start(self, invoker: Invoker) -> None:
self.__invoker = invoker
def get(self, image_name: str) -> PILImageType:
try:
image_path = self.get_path(image_name)
cache_item = self.__get_cache(image_path)
if cache_item:
return cache_item
image = Image.open(image_path)
self.__set_cache(image_path, image)
return image
except FileNotFoundError as e:
raise ImageFileNotFoundException from e
def save(
self,
image: PILImageType,
image_name: str,
metadata: Optional[MetadataField] = None,
workflow: Optional[WorkflowWithoutID] = None,
thumbnail_size: int = 256,
) -> None:
try:
self.__validate_storage_folders()
image_path = self.get_path(image_name)
pnginfo = PngImagePlugin.PngInfo()
info_dict = {}
if metadata is not None:
metadata_json = metadata.model_dump_json()
info_dict["invokeai_metadata"] = metadata_json
pnginfo.add_text("invokeai_metadata", metadata_json)
if workflow is not None:
workflow_json = workflow.model_dump_json()
info_dict["invokeai_workflow"] = workflow_json
pnginfo.add_text("invokeai_workflow", workflow_json)
# When saving the image, the image object's info field is not populated. We need to set it
image.info = info_dict
image.save(
image_path,
"PNG",
pnginfo=pnginfo,
compress_level=self.__invoker.services.configuration.png_compress_level,
)
thumbnail_name = get_thumbnail_name(image_name)
thumbnail_path = self.get_path(thumbnail_name, thumbnail=True)
thumbnail_image = make_thumbnail(image, thumbnail_size)
thumbnail_image.save(thumbnail_path)
self.__set_cache(image_path, image)
self.__set_cache(thumbnail_path, thumbnail_image)
except Exception as e:
raise ImageFileSaveException from e
def delete(self, image_name: str) -> None:
try:
image_path = self.get_path(image_name)
if image_path.exists():
send2trash(image_path)
if image_path in self.__cache:
del self.__cache[image_path]
thumbnail_name = get_thumbnail_name(image_name)
thumbnail_path = self.get_path(thumbnail_name, True)
if thumbnail_path.exists():
send2trash(thumbnail_path)
if thumbnail_path in self.__cache:
del self.__cache[thumbnail_path]
except Exception as e:
raise ImageFileDeleteException from e
# TODO: make this a bit more flexible for e.g. cloud storage
def get_path(self, image_name: str, thumbnail: bool = False) -> Path:
path = self.__output_folder / image_name
if thumbnail:
thumbnail_name = get_thumbnail_name(image_name)
path = self.__thumbnails_folder / thumbnail_name
return path
def validate_path(self, path: Union[str, Path]) -> bool:
"""Validates the path given for an image or thumbnail."""
path = path if isinstance(path, Path) else Path(path)
return path.exists()
def get_workflow(self, image_name: str) -> WorkflowWithoutID | None:
image = self.get(image_name)
workflow = image.info.get("invokeai_workflow", None)
if workflow is not None:
return WorkflowWithoutID.model_validate_json(workflow)
return None
def __validate_storage_folders(self) -> None:
"""Checks if the required output folders exist and create them if they don't"""
folders: list[Path] = [self.__output_folder, self.__thumbnails_folder]
for folder in folders:
folder.mkdir(parents=True, exist_ok=True)
def __get_cache(self, image_name: Path) -> Optional[PILImageType]:
return None if image_name not in self.__cache else self.__cache[image_name]
def __set_cache(self, image_name: Path, image: PILImageType):
if image_name not in self.__cache:
self.__cache[image_name] = image
self.__cache_ids.put(image_name) # TODO: this should refresh position for LRU cache
if len(self.__cache) > self.__max_cache_size:
cache_id = self.__cache_ids.get()
if cache_id in self.__cache:
del self.__cache[cache_id]