implement changes requested by @kyle0654 for PR #3221

- Add argparse groups to command-line switches.
- Do not let the `link` and `link_node` arguments leak into invocation objects.
- Remove `type` field from `LibraryGraph`

README.md

@@ -33,6 +33,8 @@
 
 </div>
 
+_**Note: The UI is not fully functional on `main`. If you need a stable UI based on `main`, use the `pre-nodes` tag while we [migrate to a new backend](https://github.com/invoke-ai/InvokeAI/discussions/3246).**_
+
 InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.
 
 **Quick links**: [[How to Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a href="https://invoke-ai.github.io/InvokeAI/">Documentation and Tutorials</a>] [<a href="https://github.com/invoke-ai/InvokeAI/">Code and Downloads</a>] [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>] [<a href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion, Ideas & Q&A</a>]

invokeai/app/api/dependencies.py

@@ -3,11 +3,14 @@
 import os
 from argparse import Namespace
 
+from invokeai.app.services.metadata import PngMetadataService, MetadataServiceBase
+
 from ..services.default_graphs import create_system_graphs
 
 from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 
-from ...backend import Globals
+from ...backend.globals import Globals, copy_conf_to_globals
+from ..services.config import InvokeAIWebConfig
 from ..services.model_manager_initializer import get_model_manager
 from ..services.restoration_services import RestorationServices
 from ..services.graph import GraphExecutionState, LibraryGraph
@@ -43,11 +46,7 @@ class ApiDependencies:
 
     @staticmethod
     def initialize(config, event_handler_id: int):
-        Globals.try_patchmatch = config.patchmatch
-        Globals.always_use_cpu = config.always_use_cpu
-        Globals.internet_available = config.internet_available and check_internet()
-        Globals.disable_xformers = not config.xformers
-        Globals.ckpt_convert = config.ckpt_convert
+        copy_conf_to_globals(config)
 
         # TODO: Use a logger
         print(f">> Internet connectivity is {Globals.internet_available}")
@@ -60,7 +59,9 @@ class ApiDependencies:
 
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents'))
 
-        images = DiskImageStorage(f'{output_folder}/images')
+        metadata = PngMetadataService()
+
+        images = DiskImageStorage(f'{output_folder}/images', metadata_service=metadata)
 
         # TODO: build a file/path manager?
         db_location = os.path.join(output_folder, "invokeai.db")
@@ -70,6 +71,7 @@ class ApiDependencies:
             events=events,
             latents=latents,
             images=images,
+            metadata=metadata,
             queue=MemoryInvocationQueue(),
             graph_library=SqliteItemStorage[LibraryGraph](
                 filename=db_location, table_name="graphs"
@@ -79,6 +81,7 @@ class ApiDependencies:
             ),
             processor=DefaultInvocationProcessor(),
             restoration=RestorationServices(config),
+            configuration=config,
         )
 
         create_system_graphs(services.graph_library)

invokeai/app/api/events.py

@@ -45,7 +45,7 @@ class FastAPIEventService(EventServiceBase):
                 )
 
             except Empty:
-                await asyncio.sleep(0.001)
+                await asyncio.sleep(0.1)
                 pass
 
             except asyncio.CancelledError as e:

invokeai/app/api/models/images.py

@@ -1,7 +1,19 @@
+from typing import Optional
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageType
-from invokeai.app.models.metadata import ImageMetadata
+from invokeai.app.services.metadata import InvokeAIMetadata
+
+
+class ImageResponseMetadata(BaseModel):
+    """An image's metadata. Used only in HTTP responses."""
+
+    created: int = Field(description="The creation timestamp of the image")
+    width: int = Field(description="The width of the image in pixels")
+    height: int = Field(description="The height of the image in pixels")
+    invokeai: Optional[InvokeAIMetadata] = Field(
+        description="The image's InvokeAI-specific metadata"
+    )
 
 
 class ImageResponse(BaseModel):
@@ -11,4 +23,18 @@ class ImageResponse(BaseModel):
     image_name: str = Field(description="The name of the image")
     image_url: str = Field(description="The url of the image")
     thumbnail_url: str = Field(description="The url of the image's thumbnail")
-    metadata: ImageMetadata = Field(description="The image's metadata")
+    metadata: ImageResponseMetadata = Field(description="The image's metadata")
+
+
+class ProgressImage(BaseModel):
+    """The progress image sent intermittently during processing"""
+
+    width: int = Field(description="The effective width of the image in pixels")
+    height: int = Field(description="The effective height of the image in pixels")
+    dataURL: str = Field(description="The image data as a b64 data URL")
+
+
+class SavedImage(BaseModel):
+    image_name: str = Field(description="The name of the saved image")
+    thumbnail_name: str = Field(description="The name of the saved thumbnail")
+    created: int = Field(description="The created timestamp of the saved image")

invokeai/app/api/routers/images.py

@@ -1,13 +1,19 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
+import io
 from datetime import datetime, timezone
+import json
+import os
+from typing import Any
 import uuid
 
-from fastapi import Path, Query, Request, UploadFile
+from fastapi import Body, HTTPException, Path, Query, Request, UploadFile
 from fastapi.responses import FileResponse, Response
 from fastapi.routing import APIRouter
 from PIL import Image
-from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.api.models.images import (
+    ImageResponse,
+    ImageResponseMetadata,
+)
 from invokeai.app.services.item_storage import PaginatedResults
 
 from ...services.image_storage import ImageType
@@ -15,70 +21,128 @@ from ..dependencies import ApiDependencies
 
 images_router = APIRouter(prefix="/v1/images", tags=["images"])
 
+
 @images_router.get("/{image_type}/{image_name}", operation_id="get_image")
 async def get_image(
     image_type: ImageType = Path(description="The type of image to get"),
     image_name: str = Path(description="The name of the image to get"),
-):
-    """Gets a result"""
-    # TODO: This is not really secure at all. At least make sure only output results are served
-    filename = ApiDependencies.invoker.services.images.get_path(image_type, image_name)
-    return FileResponse(filename)
+) -> FileResponse:
+    """Gets an image"""
 
-@images_router.get("/{image_type}/thumbnails/{image_name}", operation_id="get_thumbnail")
+    path = ApiDependencies.invoker.services.images.get_path(
+        image_type=image_type, image_name=image_name
+    )
+
+    if ApiDependencies.invoker.services.images.validate_path(path):
+        return FileResponse(path)
+    else:
+        raise HTTPException(status_code=404)
+
+
+@images_router.delete("/{image_type}/{image_name}", operation_id="delete_image")
+async def delete_image(
+    image_type: ImageType = Path(description="The type of image to delete"),
+    image_name: str = Path(description="The name of the image to delete"),
+) -> None:
+    """Deletes an image and its thumbnail"""
+
+    ApiDependencies.invoker.services.images.delete(
+        image_type=image_type, image_name=image_name
+    )
+
+
+@images_router.get(
+    "/{thumbnail_type}/thumbnails/{thumbnail_name}", operation_id="get_thumbnail"
+)
 async def get_thumbnail(
-    image_type: ImageType = Path(description="The type of image to get"),
-    image_name: str = Path(description="The name of the image to get"),
-):
+    thumbnail_type: ImageType = Path(description="The type of thumbnail to get"),
+    thumbnail_name: str = Path(description="The name of the thumbnail to get"),
+) -> FileResponse | Response:
     """Gets a thumbnail"""
-    # TODO: This is not really secure at all. At least make sure only output results are served
-    filename = ApiDependencies.invoker.services.images.get_path(image_type, 'thumbnails/' + image_name)
-    return FileResponse(filename)
+
+    path = ApiDependencies.invoker.services.images.get_path(
+        image_type=thumbnail_type, image_name=thumbnail_name, is_thumbnail=True
+    )
+
+    if ApiDependencies.invoker.services.images.validate_path(path):
+        return FileResponse(path)
+    else:
+        raise HTTPException(status_code=404)
 
 
 @images_router.post(
     "/uploads/",
     operation_id="upload_image",
     responses={
-        201: {"description": "The image was uploaded successfully"},
-        404: {"description": "Session not found"},
+        201: {
+            "description": "The image was uploaded successfully",
+            "model": ImageResponse,
+        },
+        415: {"description": "Image upload failed"},
     },
+    status_code=201,
 )
-async def upload_image(file: UploadFile, request: Request):
+async def upload_image(
+    file: UploadFile, request: Request, response: Response
+) -> ImageResponse:
     if not file.content_type.startswith("image"):
-        return Response(status_code=415)
+        raise HTTPException(status_code=415, detail="Not an image")
 
     contents = await file.read()
+
     try:
-        im = Image.open(contents)
+        img = Image.open(io.BytesIO(contents))
     except:
         # Error opening the image
-        return Response(status_code=415)
+        raise HTTPException(status_code=415, detail="Failed to read image")
 
     filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
-    ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, im)
 
-    return Response(
-        status_code=201,
-        headers={
-            "Location": request.url_for(
-                "get_image", image_type=ImageType.UPLOAD.value, image_name=filename
-            )
-        },
+    saved_image = ApiDependencies.invoker.services.images.save(
+        ImageType.UPLOAD, filename, img
     )
 
+    invokeai_metadata = ApiDependencies.invoker.services.metadata.get_metadata(img)
+
+    image_url = ApiDependencies.invoker.services.images.get_uri(
+        ImageType.UPLOAD, saved_image.image_name
+    )
+
+    thumbnail_url = ApiDependencies.invoker.services.images.get_uri(
+        ImageType.UPLOAD, saved_image.image_name, True
+    )
+
+    res = ImageResponse(
+        image_type=ImageType.UPLOAD,
+        image_name=saved_image.image_name,
+        image_url=image_url,
+        thumbnail_url=thumbnail_url,
+        metadata=ImageResponseMetadata(
+            created=saved_image.created,
+            width=img.width,
+            height=img.height,
+            invokeai=invokeai_metadata,
+        ),
+    )
+
+    response.status_code = 201
+    response.headers["Location"] = image_url
+
+    return res
+
+
 @images_router.get(
     "/",
     operation_id="list_images",
     responses={200: {"model": PaginatedResults[ImageResponse]}},
 )
 async def list_images(
-    image_type: ImageType = Query(default=ImageType.RESULT, description="The type of images to get"),
+    image_type: ImageType = Query(
+        default=ImageType.RESULT, description="The type of images to get"
+    ),
     page: int = Query(default=0, description="The page of images to get"),
     per_page: int = Query(default=10, description="The number of images per page"),
 ) -> PaginatedResults[ImageResponse]:
     """Gets a list of images"""
-    result = ApiDependencies.invoker.services.images.list(
-        image_type, page, per_page
-    )
+    result = ApiDependencies.invoker.services.images.list(image_type, page, per_page)
     return result

invokeai/app/api/routers/models.py

@@ -8,10 +8,6 @@ from fastapi.routing import APIRouter, HTTPException
 from pydantic import BaseModel, Field, parse_obj_as
 from pathlib import Path
 from ..dependencies import ApiDependencies
-from invokeai.backend.globals import Globals, global_converted_ckpts_dir
-from invokeai.backend.args import Args
-
-
 
 models_router = APIRouter(prefix="/v1/models", tags=["models"])
 
@@ -248,4 +244,4 @@ async def delete_model(model_name: str) -> None:
         #         )
         #         print(f">> Models Merged: {models_to_merge}")
         #         print(f">> New Model Added: {model_merge_info['merged_model_name']}")
-        #     except Exception as e:
+        #     except Exception as e:

invokeai/app/api/routers/sessions.py

@@ -2,8 +2,7 @@
 
 from typing import Annotated, List, Optional, Union
 
-from fastapi import Body, Path, Query
-from fastapi.responses import Response
+from fastapi import Body, HTTPException, Path, Query, Response
 from fastapi.routing import APIRouter
 from pydantic.fields import Field
 
@@ -76,7 +75,7 @@ async def get_session(
     """Gets a session"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
     else:
         return session
 
@@ -99,7 +98,7 @@ async def add_node(
     """Adds a node to the graph"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     try:
         session.add_node(node)
@@ -108,9 +107,9 @@ async def add_node(
         )  # TODO: can this be done automatically, or add node through an API?
         return session.id
     except NodeAlreadyExecutedError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
     except IndexError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
 
 @session_router.put(
@@ -132,7 +131,7 @@ async def update_node(
     """Updates a node in the graph and removes all linked edges"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     try:
         session.update_node(node_path, node)
@@ -141,9 +140,9 @@ async def update_node(
         )  # TODO: can this be done automatically, or add node through an API?
         return session
     except NodeAlreadyExecutedError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
     except IndexError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
 
 @session_router.delete(
@@ -162,7 +161,7 @@ async def delete_node(
     """Deletes a node in the graph and removes all linked edges"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     try:
         session.delete_node(node_path)
@@ -171,9 +170,9 @@ async def delete_node(
         )  # TODO: can this be done automatically, or add node through an API?
         return session
     except NodeAlreadyExecutedError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
     except IndexError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
 
 @session_router.post(
@@ -192,7 +191,7 @@ async def add_edge(
     """Adds an edge to the graph"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     try:
         session.add_edge(edge)
@@ -201,9 +200,9 @@ async def add_edge(
         )  # TODO: can this be done automatically, or add node through an API?
         return session
     except NodeAlreadyExecutedError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
     except IndexError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
 
 # TODO: the edge being in the path here is really ugly, find a better solution
@@ -226,7 +225,7 @@ async def delete_edge(
     """Deletes an edge from the graph"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     try:
         edge = Edge(
@@ -239,9 +238,9 @@ async def delete_edge(
         )  # TODO: can this be done automatically, or add node through an API?
         return session
     except NodeAlreadyExecutedError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
     except IndexError:
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
 
 @session_router.put(
@@ -259,14 +258,14 @@ async def invoke_session(
     all: bool = Query(
         default=False, description="Whether or not to invoke all remaining invocations"
     ),
-) -> None:
+) -> Response:
     """Invokes a session"""
     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
     if session is None:
-        return Response(status_code=404)
+        raise HTTPException(status_code=404)
 
     if session.is_complete():
-        return Response(status_code=400)
+        raise HTTPException(status_code=400)
 
     ApiDependencies.invoker.invoke(session, invoke_all=all)
     return Response(status_code=202)
@@ -281,7 +280,7 @@ async def invoke_session(
 )
 async def cancel_session_invoke(
     session_id: str = Path(description="The id of the session to cancel"),
-) -> None:
+) -> Response:
     """Invokes a session"""
     ApiDependencies.invoker.cancel(session_id)
     return Response(status_code=202)

invokeai/app/api_app.py

@@ -12,12 +12,11 @@ from fastapi_events.handlers.local import local_handler
 from fastapi_events.middleware import EventHandlerASGIMiddleware
 from pydantic.schema import schema
 
-from ..backend import Args
 from .api.dependencies import ApiDependencies
 from .api.routers import images, sessions, models
 from .api.sockets import SocketIO
-from .invocations import *
 from .invocations.baseinvocation import BaseInvocation
+from .services.config import InvokeAIWebConfig
 
 # Create the app
 # TODO: create this all in a method so configuration/etc. can be passed in?
@@ -33,30 +32,15 @@ app.add_middleware(
     middleware_id=event_handler_id,
 )
 
-# Add CORS
-# TODO: use configuration for this
-origins = []
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=origins,
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
 socket_io = SocketIO(app)
 
-config = {}
-
+web_config = {}
 
 # Add startup event to load dependencies
 @app.on_event("startup")
 async def startup_event():
-    config = Args()
-    config.parse_args()
-
     ApiDependencies.initialize(
-        config=config, event_handler_id=event_handler_id
+        config=web_config, event_handler_id=event_handler_id
     )
 
 
@@ -146,12 +130,21 @@ def overridden_redoc():
 
 
 def invoke_api():
+    # parse command-line settings, environment and the init file
+    # (this is a module global)
+    global web_config
+    web_config = InvokeAIWebConfig()
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=web_config.allow_origins,
+        allow_credentials=web_config.allow_credentials,
+        allow_methods=web_config.allow_methods,
+        allow_headers=web_config.allow_headers,
+    )
     # Start our own event loop for eventing usage
-    # TODO: determine if there's a better way to do this
     loop = asyncio.new_event_loop()
-    config = uvicorn.Config(app=app, host="0.0.0.0", port=9090, loop=loop)
+    config = uvicorn.Config(app=app, host=web_config.host, port=web_config.port, loop=loop)
     # Use access_log to turn off logging
-
     server = uvicorn.Server(config)
     loop.run_until_complete(server.serve())
 

invokeai/app/cli/commands.py

@@ -1,91 +1,52 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
+# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
 
 from abc import ABC, abstractmethod
 import argparse
-from typing import Any, Callable, Iterable, Literal, get_args, get_origin, get_type_hints
-from pydantic import BaseModel, Field
+from typing import Any, Callable, Iterable, Literal, Union, get_args, get_type_hints
+from pydantic import Field
 import networkx as nx
 import matplotlib.pyplot as plt
 
 from ..invocations.baseinvocation import BaseInvocation
+from ..services.config import InvokeAISettings
 from ..invocations.image import ImageField
-from ..services.graph import GraphExecutionState, LibraryGraph, GraphInvocation, Edge
+from ..services.graph import GraphExecutionState, LibraryGraph, Edge
 from ..services.invoker import Invoker
 
-
-def add_field_argument(command_parser, name: str, field, default_override = None):
-    default = default_override if default_override is not None else field.default if field.default_factory is None else field.default_factory()
-    if get_origin(field.type_) == Literal:
-        allowed_values = get_args(field.type_)
-        allowed_types = set()
-        for val in allowed_values:
-            allowed_types.add(type(val))
-        allowed_types_list = list(allowed_types)
-        field_type = allowed_types_list[0] if len(allowed_types) == 1 else Union[allowed_types_list]  # type: ignore
-
-        command_parser.add_argument(
-            f"--{name}",
-            dest=name,
-            type=field_type,
-            default=default,
-            choices=allowed_values,
-            help=field.field_info.description,
-        )
-    else:
-        command_parser.add_argument(
-            f"--{name}",
-            dest=name,
-            type=field.type_,
-            default=default,
-            help=field.field_info.description,
-        )
-
-
 def add_parsers(
     subparsers,
     commands: list[type],
     command_field: str = "type",
     exclude_fields: list[str] = ["id", "type"],
-    add_arguments: Callable[[argparse.ArgumentParser], None]|None = None
+    add_arguments: Union[Callable[[argparse.ArgumentParser], None], None] = None
     ):
     """Adds parsers for each command to the subparsers"""
 
     # Create subparsers for each command
     for command in commands:
-        hints = get_type_hints(command)
-        cmd_name = get_args(hints[command_field])[0]
-        command_parser = subparsers.add_parser(cmd_name, help=command.__doc__)
-
+        name = command.cmd_name()
+        command_parser = subparsers.add_parser(name, help=command.__doc__)
         if add_arguments is not None:
             add_arguments(command_parser)
-
-        # Convert all fields to arguments
-        fields = command.__fields__ # type: ignore
-        for name, field in fields.items():
-            if name in exclude_fields:
-                continue
-
-            add_field_argument(command_parser, name, field)
-
+        command.add_parser_arguments(command_parser)
 
 def add_graph_parsers(
     subparsers,
     graphs: list[LibraryGraph],
-    add_arguments: Callable[[argparse.ArgumentParser], None]|None = None
+    add_arguments: Union[Callable[[argparse.ArgumentParser], None], None] = None
 ):
     for graph in graphs:
         command_parser = subparsers.add_parser(graph.name, help=graph.description)
         
         if add_arguments is not None:
-            add_arguments(command_parser)
+            graph.add_parser_arguments(command_parser)
 
         # Add arguments for inputs
         for exposed_input in graph.exposed_inputs:
             node = graph.graph.get_node(exposed_input.node_path)
             field = node.__fields__[exposed_input.field]
             default_override = getattr(node, exposed_input.field)
-            add_field_argument(command_parser, exposed_input.alias, field, default_override)
-
+            graph.add_field_argument(command_parser, exposed_input.alias, field, default_override)
 
 class CliContext:
     invoker: Invoker
@@ -130,7 +91,7 @@ class ExitCli(Exception):
     pass
 
 
-class BaseCommand(ABC, BaseModel):
+class BaseCommand(ABC, InvokeAISettings):
     """A CLI command"""
 
     # All commands must include a type name like this:

invokeai/app/cli/completer.py

@@ -10,9 +10,10 @@ import shlex
 from pathlib import Path
 from typing import List, Dict, Literal, get_args, get_type_hints, get_origin
 
-from ...backend import ModelManager, Globals
+from ...backend import ModelManager
 from ..invocations.baseinvocation import BaseInvocation
 from .commands import BaseCommand
+from ..services.invocation_services import InvocationServices
 
 # singleton object, class variable
 completer = None
@@ -130,13 +131,13 @@ class Completer(object):
             readline.redisplay()
             self.linebuffer = None
     
-def set_autocompleter(model_manager: ModelManager) -> Completer:
+def set_autocompleter(services: InvocationServices) -> Completer:
     global completer
     
     if completer:
         return completer
     
-    completer = Completer(model_manager)
+    completer = Completer(services.model_manager)
 
     readline.set_completer(completer.complete)
     # pyreadline3 does not have a set_auto_history() method
@@ -152,7 +153,7 @@ def set_autocompleter(model_manager: ModelManager) -> Completer:
     readline.parse_and_bind("set skip-completed-text on")
     readline.parse_and_bind("set show-all-if-ambiguous on")
 
-    histfile = Path(Globals.root, ".invoke_history")
+    histfile = Path(services.configuration.root_dir / ".invoke_history")
     try:
         readline.read_history_file(histfile)
         readline.set_history_length(1000)

invokeai/app/cli_app.py

@@ -13,11 +13,12 @@ from typing import (
 from pydantic import BaseModel
 from pydantic.fields import Field
 
+from invokeai.app.services.metadata import PngMetadataService
+
 from .services.default_graphs import create_system_graphs
 
 from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
 
-from ..backend import Args
 from .cli.commands import BaseCommand, CliContext, ExitCli, add_graph_parsers, add_parsers, get_graph_execution_history
 from .cli.completer import set_autocompleter
 from .invocations import *
@@ -33,7 +34,8 @@ from .services.invocation_services import InvocationServices
 from .services.invoker import Invoker
 from .services.processor import DefaultInvocationProcessor
 from .services.sqlite import SqliteItemStorage
-
+from .services.config import InvokeAIAppConfig
+from ..backend.globals import copy_conf_to_globals   # temporary workaround for code depending on Globals
 
 class CliCommand(BaseModel):
     command: Union[BaseCommand.get_commands() + BaseInvocation.get_invocations()] = Field(discriminator="type")  # type: ignore
@@ -188,21 +190,19 @@ def invoke_all(context: CliContext):
 
 
 def invoke_cli():
-    config = Args()
-    config.parse_args()
+    config = InvokeAIAppConfig()
+    copy_conf_to_globals(config)   # temporary workaround
     model_manager = get_model_manager(config)
 
     # This initializes the autocompleter and returns it.
     # Currently nothing is done with the returned Completer
     # object, but the object can be used to change autocompletion
     # behavior on the fly, if desired.
-    completer = set_autocompleter(model_manager)
 
     events = EventServiceBase()
 
-    output_folder = os.path.abspath(
-        os.path.join(os.path.dirname(__file__), "../../../outputs")
-    )
+    output_folder = config.output_path
+    metadata = PngMetadataService()
 
     # TODO: build a file/path manager?
     db_location = os.path.join(output_folder, "invokeai.db")
@@ -211,7 +211,8 @@ def invoke_cli():
         model_manager=model_manager,
         events=events,
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents')),
-        images=DiskImageStorage(f'{output_folder}/images'),
+        images=DiskImageStorage(f'{output_folder}/images', metadata_service=metadata),
+        metadata=metadata,
         queue=MemoryInvocationQueue(),
         graph_library=SqliteItemStorage[LibraryGraph](
             filename=db_location, table_name="graphs"
@@ -221,6 +222,7 @@ def invoke_cli():
         ),
         processor=DefaultInvocationProcessor(),
         restoration=RestorationServices(config),
+        configuration=config,
     )
 
     system_graphs = create_system_graphs(services.graph_library)
@@ -237,6 +239,8 @@ def invoke_cli():
 
     context = CliContext(invoker, session, parser)
 
+    set_autocompleter(services)
+
     while True:
         try:
             cmd_input = input("invoke> ")
@@ -280,8 +284,17 @@ def invoke_cli():
                     command = CliCommand(command = invocation)
                     context.graph_nodes[invocation.id] = system_graph.id
                 else:
-                    args["id"] = current_id
-                    command = CliCommand(command=args)
+                    if "id" in args:
+                        args["id"] = args["id"] or current_id
+                        
+                    # remove extraneous fields from initialization
+                    exclude = ['link','link_node']
+                    command_args = dict()
+                    for key,value in args.items():
+                        if key not in exclude:
+                            command_args[key]=value
+                            
+                    command = CliCommand(command=command_args)
 
                 if command is None:
                     continue

invokeai/app/invocations/baseinvocation.py

@@ -4,10 +4,10 @@ from abc import ABC, abstractmethod
 from inspect import signature
 from typing import get_args, get_type_hints, Dict, List, Literal, TypedDict
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, BaseSettings, Field
 
 from ..services.invocation_services import InvocationServices
-
+from ..services.config import InvokeAISettings
 
 class InvocationContext:
     services: InvocationServices
@@ -36,7 +36,7 @@ class BaseInvocationOutput(BaseModel):
         return tuple(subclasses)
 
 
-class BaseInvocation(ABC, BaseModel):
+class BaseInvocation(ABC, InvokeAISettings):
     """A node to process inputs and produce outputs.
     May use dependency injection in __init__ to receive providers.
     """
@@ -95,14 +95,14 @@ class UIConfig(TypedDict, total=False):
         ],
     ]
     tags: List[str]
-
+    title: str
 
 class CustomisedSchemaExtra(TypedDict):
     ui: UIConfig
 
 
-class InvocationConfig(BaseModel.Config):
-    """Customizes pydantic's BaseModel.Config class for use by Invocations.
+class InvocationConfig(BaseSettings.Config):
+    """Customizes pydantic's BaseSettings.Config class for use by Invocations.
 
     Provide `schema_extra` a `ui` dict to add hints for generated UIs.
 

invokeai/app/invocations/collections.py

@@ -1,16 +1,17 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal
+from typing import Literal, Optional
 
-import cv2 as cv
 import numpy as np
 import numpy.random
-from PIL import Image, ImageOps
 from pydantic import Field
 
-from ..services.image_storage import ImageType
-from .baseinvocation import BaseInvocation, InvocationContext, BaseInvocationOutput
-from .image import ImageField, ImageOutput
+from .baseinvocation import (
+    BaseInvocation,
+    InvocationConfig,
+    InvocationContext,
+    BaseInvocationOutput,
+)
 
 
 class IntCollectionOutput(BaseInvocationOutput):
@@ -33,7 +34,9 @@ class RangeInvocation(BaseInvocation):
     step: int = Field(default=1, description="The step of the range")
 
     def invoke(self, context: InvocationContext) -> IntCollectionOutput:
-        return IntCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
+        return IntCollectionOutput(
+            collection=list(range(self.start, self.stop, self.step))
+        )
 
 
 class RandomRangeInvocation(BaseInvocation):
@@ -43,8 +46,19 @@ class RandomRangeInvocation(BaseInvocation):
 
     # Inputs
     low: int = Field(default=0, description="The inclusive low value")
-    high: int = Field(default=np.iinfo(np.int32).max, description="The exclusive high value")
+    high: int = Field(
+        default=np.iinfo(np.int32).max, description="The exclusive high value"
+    )
     size: int = Field(default=1, description="The number of values to generate")
+    seed: Optional[int] = Field(
+        ge=0,
+        le=np.iinfo(np.int32).max,
+        description="The seed for the RNG",
+        default_factory=lambda: numpy.random.randint(0, np.iinfo(np.int32).max),
+    )
 
     def invoke(self, context: InvocationContext) -> IntCollectionOutput:
-        return IntCollectionOutput(collection=list(numpy.random.randint(self.low, self.high, size=self.size)))
+        rng = np.random.default_rng(self.seed)
+        return IntCollectionOutput(
+            collection=list(rng.integers(low=self.low, high=self.high, size=self.size))
+        )

invokeai/app/invocations/cv.py

@@ -9,7 +9,7 @@ from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 
 class CvInvocationConfig(BaseModel):
@@ -56,7 +56,14 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_inpainted)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+        
+        context.services.images.save(image_type, image_name, image_inpainted, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image_inpainted,
+        )

invokeai/app/invocations/generate.py

@@ -9,13 +9,12 @@ from torch import Tensor
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from invokeai.app.invocations.util.get_model import choose_model
+from invokeai.app.invocations.util.choose_model import choose_model
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
 from ...backend.stable_diffusion import PipelineIntermediateState
-from ..models.exceptions import CanceledException
-from ..util.step_callback import diffusers_step_callback_adapter
+from ..util.step_callback import stable_diffusion_step_callback
 
 SAMPLER_NAME_VALUES = Literal[tuple(InvokeAIGenerator.schedulers())]
 
@@ -58,28 +57,31 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
     ) -> None:
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-        
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         # Handle invalid model parameter
         model = choose_model(context.services.model_manager, self.model)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         outputs = Txt2Img(model).generate(
             prompt=self.prompt,
-            step_callback=partial(self.dispatch_progress, context),
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
             **self.dict(
                 exclude={"prompt"}
             ),  # Shorthand for passing all of the parameters above manually
@@ -95,9 +97,18 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, generate_output.image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(
+            image_type, image_name, generate_output.image, metadata
+        )
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=generate_output.image,
         )
 
 
@@ -117,20 +128,17 @@ class ImageToImageInvocation(TextToImageInvocation):
     )
 
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
-    ) -> None:  
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
+    ) -> None:
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = (
@@ -145,15 +153,21 @@ class ImageToImageInvocation(TextToImageInvocation):
         # Handle invalid model parameter
         model = choose_model(context.services.model_manager, self.model)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         outputs = Img2Img(model).generate(
-                prompt=self.prompt,
-                init_image=image,
-                init_mask=mask,
-                step_callback=partial(self.dispatch_progress, context),
-                **self.dict(
-                    exclude={"prompt", "image", "mask"}
-                ),  # Shorthand for passing all of the parameters above manually
-            )
+            prompt=self.prompt,
+            init_image=image,
+            init_mask=mask,
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
+            **self.dict(
+                exclude={"prompt", "image", "mask"}
+            ),  # Shorthand for passing all of the parameters above manually
+        )
 
         # Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
         # each time it is called. We only need the first one.
@@ -168,11 +182,19 @@ class ImageToImageInvocation(TextToImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
 
+        context.services.images.save(image_type, image_name, result_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image,
+        )
+
+
 class InpaintInvocation(ImageToImageInvocation):
     """Generates an image using inpaint."""
 
@@ -188,20 +210,17 @@ class InpaintInvocation(ImageToImageInvocation):
     )
 
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
-    ) -> None:  
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
+    ) -> None:
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = (
@@ -218,17 +237,23 @@ class InpaintInvocation(ImageToImageInvocation):
         )
 
         # Handle invalid model parameter
-        model = choose_model(context.services.model_manager, self.model)   
+        model = choose_model(context.services.model_manager, self.model)
+
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
 
         outputs = Inpaint(model).generate(
-                prompt=self.prompt,
-                init_img=image,
-                init_mask=mask,
-                step_callback=partial(self.dispatch_progress, context),
-                **self.dict(
-                    exclude={"prompt", "image", "mask"}
-                ),  # Shorthand for passing all of the parameters above manually
-            )
+            prompt=self.prompt,
+            init_img=image,
+            init_mask=mask,
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
+            **self.dict(
+                exclude={"prompt", "image", "mask"}
+            ),  # Shorthand for passing all of the parameters above manually
+        )
 
         # Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
         # each time it is called. We only need the first one.
@@ -243,7 +268,14 @@ class InpaintInvocation(ImageToImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, result_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image,
         )

invokeai/app/invocations/image.py

@@ -1,6 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from datetime import datetime, timezone
 from typing import Literal, Optional
 
 import numpy
@@ -8,8 +7,12 @@ from PIL import Image, ImageFilter, ImageOps
 from pydantic import BaseModel, Field
 
 from ..models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
-from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    InvocationContext,
+    InvocationConfig,
+)
 
 
 class PILInvocationConfig(BaseModel):
@@ -22,50 +25,73 @@ class PILInvocationConfig(BaseModel):
             },
         }
 
+
 class ImageOutput(BaseInvocationOutput):
     """Base class for invocations that output an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["image"] = "image"
     image:      ImageField = Field(default=None, description="The output image")
-    #fmt: on
+    width:   Optional[int] = Field(default=None, description="The width of the image in pixels")
+    height:  Optional[int] = Field(default=None, description="The height of the image in pixels")
+    # fmt: on
 
     class Config:
         schema_extra = {
-            'required': [
-                'type',
-                'image',
-            ]
+            "required": ["type", "image", "width", "height", "mode"]
         }
 
+
+def build_image_output(
+    image_type: ImageType, image_name: str, image: Image.Image
+) -> ImageOutput:
+    """Builds an ImageOutput and its ImageField"""
+    image_field = ImageField(
+        image_name=image_name,
+        image_type=image_type,
+    )
+    return ImageOutput(
+        image=image_field,
+        width=image.width,
+        height=image.height,
+        mode=image.mode,
+    )
+
+
 class MaskOutput(BaseInvocationOutput):
     """Base class for invocations that output a mask"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["mask"] = "mask"
     mask:      ImageField = Field(default=None, description="The output mask")
-    #fmt: on
+    # fmt: on
 
     class Config:
         schema_extra = {
-            'required': [
-                'type',
-                'mask',
+            "required": [
+                "type",
+                "mask",
             ]
         }
 
-# TODO: this isn't really necessary anymore
+
 class LoadImageInvocation(BaseInvocation):
-    """Load an image from a filename and provide it as output."""
-    #fmt: off
+    """Load an image and provide it as output."""
+
+    # fmt: off
     type: Literal["load_image"] = "load_image"
 
     # Inputs
     image_type: ImageType = Field(description="The type of the image")
     image_name:       str = Field(description="The name of the image")
-    #fmt: on
-
+    # fmt: on
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        return ImageOutput(
-            image=ImageField(image_type=self.image_type, image_name=self.image_name)
+        image = context.services.images.get(self.image_type, self.image_name)
+
+        return build_image_output(
+            image_type=self.image_type,
+            image_name=self.image_name,
+            image=image,
         )
 
 
@@ -86,16 +112,17 @@ class ShowImageInvocation(BaseInvocation):
 
         # TODO: how to handle failure?
 
-        return ImageOutput(
-            image=ImageField(
-                image_type=self.image.image_type, image_name=self.image.image_name
-            )
+        return build_image_output(
+            image_type=self.image.image_type,
+            image_name=self.image.image_name,
+            image=image,
         )
 
 
 class CropImageInvocation(BaseInvocation, PILInvocationConfig):
     """Crops an image to a specified box. The box can be outside of the image."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["crop"] = "crop"
 
     # Inputs
@@ -104,7 +131,7 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
     y:      int = Field(default=0, description="The top y coordinate of the crop rectangle")
     width:  int = Field(default=512, gt=0, description="The width of the crop rectangle")
     height: int = Field(default=512, gt=0, description="The height of the crop rectangle")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
@@ -120,15 +147,23 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_crop)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+        
+        context.services.images.save(image_type, image_name, image_crop, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image_crop,
         )
 
 
 class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
     """Pastes an image into another image."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["paste"] = "paste"
 
     # Inputs
@@ -137,7 +172,7 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
     mask: Optional[ImageField] = Field(default=None, description="The mask to use when pasting")
     x:                     int = Field(default=0, description="The left x coordinate at which to paste the image")
     y:                     int = Field(default=0, description="The top y coordinate at which to paste the image")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         base_image = context.services.images.get(
@@ -170,21 +205,29 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, new_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+        
+        context.services.images.save(image_type, image_name, new_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=new_image,
         )
 
 
 class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
     """Extracts the alpha channel of an image as a mask."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["tomask"] = "tomask"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to create the mask from")
     invert:      bool = Field(default=False, description="Whether or not to invert the mask")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> MaskOutput:
         image = context.services.images.get(
@@ -199,22 +242,27 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_mask)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, image_mask, metadata)
         return MaskOutput(mask=ImageField(image_type=image_type, image_name=image_name))
 
 
 class BlurInvocation(BaseInvocation, PILInvocationConfig):
     """Blurs an image"""
 
-    #fmt: off
+    # fmt: off
     type: Literal["blur"] = "blur"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to blur")
     radius:     float = Field(default=8.0, ge=0, description="The blur radius")
     blur_type: Literal["gaussian", "box"] = Field(default="gaussian", description="The type of blur")
-    #fmt: on
-    
+    # fmt: on
+
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
             self.image.image_type, self.image.image_name
@@ -231,22 +279,28 @@ class BlurInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, blur_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, blur_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=blur_image
         )
 
 
 class LerpInvocation(BaseInvocation, PILInvocationConfig):
     """Linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["lerp"] = "lerp"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to lerp")
     min: int = Field(default=0, ge=0, le=255, description="The minimum output value")
     max: int = Field(default=255, ge=0, le=255, description="The maximum output value")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
@@ -262,23 +316,29 @@ class LerpInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, lerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, lerp_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=lerp_image
         )
 
 
 class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
     """Inverse linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["ilerp"] = "ilerp"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to lerp")
     min: int = Field(default=0, ge=0, le=255, description="The minimum input value")
     max: int = Field(default=255, ge=0, le=255, description="The maximum input value")
-    #fmt: on
-    
+    # fmt: on
+
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
             self.image.image_type, self.image.image_name
@@ -298,7 +358,12 @@ class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, ilerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, ilerp_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=ilerp_image
         )

invokeai/app/invocations/latent.py

@@ -5,9 +5,9 @@ from typing import Literal, Optional
 from pydantic import BaseModel, Field
 import torch
 
-from invokeai.app.models.exceptions import CanceledException
-from invokeai.app.invocations.util.get_model import choose_model
-from invokeai.app.util.step_callback import diffusers_step_callback_adapter
+from invokeai.app.invocations.util.choose_model import choose_model
+
+from invokeai.app.util.step_callback import stable_diffusion_step_callback
 
 from ...backend.model_management.model_manager import ModelManager
 from ...backend.util.devices import choose_torch_device, torch_dtype
@@ -19,7 +19,7 @@ from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationCont
 import numpy as np
 from ..services.image_storage import ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageField, ImageOutput, build_image_output
 from ...backend.stable_diffusion import PipelineIntermediateState
 from diffusers.schedulers import SchedulerMixin as Scheduler
 import diffusers
@@ -31,6 +31,8 @@ class LatentsField(BaseModel):
 
     latents_name: Optional[str] = Field(default=None, description="The name of the latents")
 
+    class Config:
+        schema_extra = {"required": ["latents_name"]}
 
 class LatentsOutput(BaseInvocationOutput):
     """Base class for invocations that output latents"""
@@ -144,11 +146,8 @@ class TextToLatentsInvocation(BaseInvocation):
     # TODO: consider making prompt optional to enable providing prompt through a link
     # fmt: off
     prompt: Optional[str] = Field(description="The prompt to generate an image from")
-    seed:        int = Field(default=-1,ge=-1, le=np.iinfo(np.uint32).max, description="The seed to use (-1 for a random seed)", )
     noise: Optional[LatentsField] = Field(description="The noise to use")
     steps:       int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
-    width:       int = Field(default=512, multiple_of=64, gt=0, description="The width of the resulting image", )
-    height:      int = Field(default=512, multiple_of=64, gt=0, description="The height of the resulting image", )
     cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
     scheduler: SAMPLER_NAME_VALUES = Field(default="k_lms", description="The scheduler to use" )
     seamless:   bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
@@ -170,21 +169,14 @@ class TextToLatentsInvocation(BaseInvocation):
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
+        self, context: InvocationContext, source_node_id: str, intermediate_state: PipelineIntermediateState
     ) -> None:
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
-
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def get_model(self, model_manager: ModelManager) -> StableDiffusionGeneratorPipeline:
         model_info = choose_model(model_manager, self.model)
@@ -231,8 +223,12 @@ class TextToLatentsInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         noise = context.services.latents.get(self.noise.latents_name)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         def step_callback(state: PipelineIntermediateState):
-            self.dispatch_progress(context, state)
+            self.dispatch_progress(context, source_node_id, state)
 
         model = self.get_model(context.services.model_manager)
         conditioning_data = self.get_conditioning_data(model)
@@ -281,8 +277,12 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
         noise = context.services.latents.get(self.noise.latents_name)
         latent = context.services.latents.get(self.latents.latents_name)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         def step_callback(state: PipelineIntermediateState):
-            self.dispatch_progress(context, state)
+            self.dispatch_progress(context, source_node_id, state)
 
         model = self.get_model(context.services.model_manager)
         conditioning_data = self.get_conditioning_data(model)
@@ -355,7 +355,79 @@ class LatentsToImageInvocation(BaseInvocation):
             image_name = context.services.images.create_name(
                 context.graph_execution_state_id, self.id
             )
-            context.services.images.save(image_type, image_name, image)
-            return ImageOutput(
-                image=ImageField(image_type=image_type, image_name=image_name)
+
+            metadata = context.services.metadata.build_metadata(
+                session_id=context.graph_execution_state_id, node=self
             )
+
+            torch.cuda.empty_cache()
+
+            context.services.images.save(image_type, image_name, image, metadata)
+            return build_image_output(
+                image_type=image_type, image_name=image_name, image=image
+            )
+
+
+LATENTS_INTERPOLATION_MODE = Literal[
+    "nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"
+]
+
+
+class ResizeLatentsInvocation(BaseInvocation):
+    """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
+
+    type: Literal["lresize"] = "lresize"
+
+    # Inputs
+    latents: Optional[LatentsField]             = Field(description="The latents to resize")
+    width: int                                  = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
+    height: int                                 = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
+    mode: Optional[LATENTS_INTERPOLATION_MODE]  = Field(default="bilinear", description="The interpolation mode")
+    antialias: Optional[bool]                   = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
+
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
+        latents = context.services.latents.get(self.latents.latents_name)
+
+        resized_latents = torch.nn.functional.interpolate(
+            latents,
+            size=(self.height // 8, self.width // 8),
+            mode=self.mode,
+            antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
+        )
+
+        # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
+        torch.cuda.empty_cache()
+
+        name = f"{context.graph_execution_state_id}__{self.id}"
+        context.services.latents.set(name, resized_latents)
+        return LatentsOutput(latents=LatentsField(latents_name=name))
+
+
+class ScaleLatentsInvocation(BaseInvocation):
+    """Scales latents by a given factor."""
+
+    type: Literal["lscale"] = "lscale"
+
+    # Inputs
+    latents: Optional[LatentsField]             = Field(description="The latents to scale")
+    scale_factor: float                         = Field(gt=0, description="The factor by which to scale the latents")
+    mode: Optional[LATENTS_INTERPOLATION_MODE]  = Field(default="bilinear", description="The interpolation mode")
+    antialias: Optional[bool]                   = Field(default=False, description="Whether or not to antialias (applied in bilinear and bicubic modes only)")
+
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
+        latents = context.services.latents.get(self.latents.latents_name)
+
+        # resizing
+        resized_latents = torch.nn.functional.interpolate(
+            latents,
+            scale_factor=self.scale_factor,
+            mode=self.mode,
+            antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
+        )
+
+        # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
+        torch.cuda.empty_cache()
+
+        name = f"{context.graph_execution_state_id}__{self.id}"
+        context.services.latents.set(name, resized_latents)
+        return LatentsOutput(latents=LatentsField(latents_name=name))

invokeai/app/invocations/reconstruct.py

@@ -1,12 +1,11 @@
-from datetime import datetime, timezone
 from typing import Literal, Union
 
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
+
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 class RestoreFaceInvocation(BaseInvocation):
     """Restores faces in an image."""
@@ -44,7 +43,14 @@ class RestoreFaceInvocation(BaseInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+
+        context.services.images.save(image_type, image_name, results[0][0], metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )

invokeai/app/invocations/upscale.py

@@ -1,14 +1,12 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from datetime import datetime, timezone
 from typing import Literal, Union
 
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 
 class UpscaleInvocation(BaseInvocation):
@@ -49,7 +47,14 @@ class UpscaleInvocation(BaseInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+
+        context.services.images.save(image_type, image_name, results[0][0], metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )

invokeai/app/invocations/util/choose_model.py

@@ -1,11 +1,14 @@
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.backend.model_management.model_manager import ModelManager
 
 
 def choose_model(model_manager: ModelManager, model_name: str):
     """Returns the default model if the `model_name` not a valid model, else returns the selected model."""
     if model_manager.valid_model(model_name):
-        return model_manager.get_model(model_name)
+        model = model_manager.get_model(model_name)
     else:
-        print(f"* Warning: '{model_name}' is not a valid model name. Using default model instead.")
-        return model_manager.get_model()
+        model = model_manager.get_model()
+        print(
+            f"* Warning: '{model_name}' is not a valid model name. Using default model \'{model['model_name']}\' instead."
+        )
+
+    return model

invokeai/app/models/image.py

@@ -9,6 +9,14 @@ class ImageType(str, Enum):
     UPLOAD = "uploads"
 
 
+def is_image_type(obj):
+    try:
+        ImageType(obj)
+    except ValueError:
+        return False
+    return True
+
+
 class ImageField(BaseModel):
     """An image field used for passing image objects between invocations"""
 
@@ -18,9 +26,4 @@ class ImageField(BaseModel):
     image_name: Optional[str] = Field(default=None, description="The name of the image")
 
     class Config:
-        schema_extra = {
-            "required": [
-                "image_type",
-                "image_name",
-            ]
-        }
+        schema_extra = {"required": ["image_type", "image_name"]}

invokeai/app/models/metadata.py

@@ -1,11 +0,0 @@
-from typing import Optional
-from pydantic import BaseModel, Field
-
-class ImageMetadata(BaseModel):
-    """An image's metadata"""
-
-    timestamp: float = Field(description="The creation timestamp of the image")
-    width: int = Field(description="The width of the image in pixels")
-    height: int = Field(description="The height of the image in pixels")
-    # TODO: figure out metadata
-    sd_metadata: Optional[dict] = Field(default={}, description="The image's SD-specific metadata")

invokeai/app/services/config.py

@@ -0,0 +1,379 @@
+# Copyright (c) 2023 Lincoln Stein (https://github.com/lstein)
+
+'''Invokeai configuration system.
+
+Arguments and fields are taken from the pydantic definition of the
+model.  Defaults can be set by creating a yaml configuration file that
+has top-level keys corresponding to an invocation name, a command, or
+"globals" for global values such as `xformers_enabled`. Currently
+graphs cannot be configured this way, but their constituents can be.
+
+[file: invokeai.yaml]
+
+ globals:
+   nsfw_checker: False
+   max_loaded_models: 5
+ 
+ txt2img:
+   steps: 20
+   scheduler: k_heun
+   width: 768
+ 
+ img2img:
+   width: 1024
+   height: 1024
+
+The default name of the configuration file is `invokeai.yaml`, located
+in INVOKEAI_ROOT. You can use any OmegaConf dictionary by passing it
+to the config object at initialization time:
+
+ omegaconf = OmegaConf.load('/tmp/init.yaml')
+ conf = InvokeAIAppConfig(conf=omegaconf)
+
+By default, InvokeAIAppConfig will parse the contents of argv at
+initialization time. You may pass a list of strings in the optional
+`argv` argument to use instead of the system argv:
+
+ conf = InvokeAIAppConfig(arg=['--xformers_enabled'])
+
+It is also possible to set a value at initialization time. This value
+has highest priority.
+
+ conf = InvokeAIAppConfig(xformers_enabled=True)
+
+Any setting can be overwritten by setting an environment variable of
+form: "INVOKEAI_<command>_<value>", as in:
+
+  export INVOKEAI_txt2img_steps=30
+
+Order of precedence (from highest):
+   1) initialization options
+   2) command line options
+   3) environment variable options
+   4) config file options
+   5) pydantic defaults
+
+Typical usage:
+
+ from invokeai.app.services.config import InvokeAIAppConfig
+ from invokeai.invocations.generate import TextToImageInvocation
+
+ # get global configuration and print its nsfw_checker value
+ conf = InvokeAIAppConfig()
+ print(conf.nsfw_checker)
+
+ # get the text2image invocation and print its step value
+ text2image = TextToImageInvocation()
+ print(text2image.steps)
+
+Computed properties:
+
+The InvokeAIAppConfig object has a series of properties that
+resolve paths relative to the runtime root directory. They each return
+a Path object:
+
+ root_path          - path to InvokeAI root
+ output_path        - path to default outputs directory
+ model_conf_path    - path to models.yaml
+ conf               - alias for the above
+ embedding_path     - path to the embeddings directory
+ lora_path          - path to the LoRA directory
+ 
+
+'''
+import argparse
+import os
+import sys
+from argparse import ArgumentParser
+from omegaconf import OmegaConf, DictConfig
+from pathlib import Path
+from pydantic import BaseSettings, Field, parse_obj_as
+from typing import Any, ClassVar, Dict, List, Literal, Union, get_origin, get_type_hints, get_args
+
+INIT_FILE = Path('invokeai.yaml')
+LEGACY_INIT_FILE = Path('invokeai.init')
+
+class InvokeAISettings(BaseSettings):
+    '''
+    Runtime configuration settings in which default values are
+    read from an omegaconf .yaml file.
+    '''
+    initconf             : ClassVar[DictConfig] = None
+    argparse_groups      : ClassVar[Dict] = {}
+
+    def parse_args(self, argv: list=sys.argv[1:]):
+        parser = self.get_parser()
+        opt, _ = parser.parse_known_args(argv)
+        for name in self.__fields__:
+            if name not in self._excluded():
+                setattr(self, name, getattr(opt,name))
+
+    @classmethod
+    def add_parser_arguments(cls, parser):
+        env_prefix = cls.Config.env_prefix if hasattr(cls.Config,'env_prefix') else 'INVOKEAI_'
+        if 'type' in get_type_hints(cls):
+            default_settings_stanza = get_args(get_type_hints(cls)['type'])[0]
+        else:
+            default_settings_stanza = 'globals'
+        initconf = cls.initconf.get(default_settings_stanza) if cls.initconf and default_settings_stanza in cls.initconf else None
+
+        fields = cls.__fields__
+        cls.argparse_groups = {}
+        for name, field in fields.items():
+            if name not in cls._excluded():
+                env_name = env_prefix+f'{cls.cmd_name()}_{name}'
+                if initconf and name in initconf:
+                    field.default = initconf.get(name)
+                if env_name in os.environ:
+                    field.default = os.environ[env_name]
+                cls.add_field_argument(parser, name, field)
+
+
+    @classmethod
+    def cmd_name(self, command_field: str='type')->str:
+        hints = get_type_hints(self)
+        if command_field in hints:
+            return get_args(hints[command_field])[0]
+        else:
+            return 'globals'
+
+    @classmethod
+    def get_parser(cls)->ArgumentParser:
+        parser = ArgumentParser(
+            prog=cls.cmd_name(),
+            description=cls.__doc__,
+        )
+        cls.add_parser_arguments(parser)
+        return parser
+
+    @classmethod
+    def add_subparser(cls, parser: argparse.ArgumentParser):
+        parser.add_parser(cls.cmd_name(), help=cls.__doc__)
+
+    @classmethod
+    def _excluded(self)->List[str]:
+        return ['type','initconf']
+    
+    class Config:
+        env_file_encoding = 'utf-8'
+        arbitrary_types_allowed = True
+        env_prefix = 'INVOKEAI_'
+        case_sensitive = True
+        @classmethod
+        def customise_sources(
+            cls,
+            init_settings,
+            env_settings,
+            file_secret_settings,
+        ):
+            return (
+                init_settings,
+                cls._omegaconf_settings_source,
+                env_settings,
+                file_secret_settings,
+            )
+
+        @classmethod
+        def _omegaconf_settings_source(cls, settings: BaseSettings) -> dict[str, Any]:
+            if initconf := InvokeAISettings.initconf:
+                return initconf.get(settings.cmd_name(),{})
+            else:
+                return {}
+
+    @classmethod
+    def add_field_argument(cls, command_parser, name: str, field, default_override = None):
+        default = default_override if default_override is not None else field.default if field.default_factory is None else field.default_factory()
+        if category := field.field_info.extra.get("category"):
+            if category not in cls.argparse_groups:
+                cls.argparse_groups[category] = command_parser.add_argument_group(category)
+            argparse_group = cls.argparse_groups[category]
+        else:
+            argparse_group = command_parser
+        
+        if get_origin(field.type_) == Literal:
+            allowed_values = get_args(field.type_)
+            allowed_types = set()
+            for val in allowed_values:
+                allowed_types.add(type(val))
+            allowed_types_list = list(allowed_types)
+            field_type = allowed_types_list[0] if len(allowed_types) == 1 else Union[allowed_types_list]  # type: ignore
+
+            argparse_group.add_argument(
+                f"--{name}",
+                dest=name,
+                type=field_type,
+                default=default,
+                choices=allowed_values,
+                help=field.field_info.description,
+            )
+        else:
+            argparse_group.add_argument(
+                f"--{name}",
+                dest=name,
+                type=field.type_,
+                default=default,
+                action=argparse.BooleanOptionalAction if field.type_==bool else 'store',
+                help=field.field_info.description,
+            )
+def _find_root()->Path:
+    if os.environ.get("INVOKEAI_ROOT"):
+        root = Path(os.environ.get("INVOKEAI_ROOT")).resolve()
+    elif (
+            os.environ.get("VIRTUAL_ENV")
+            and (Path(os.environ.get("VIRTUAL_ENV"), "..", INIT_FILE).exists()
+                 or
+                 Path(os.environ.get("VIRTUAL_ENV"), "..", LEGACY_INIT_FILE).exists()
+                 )
+    ):
+        root = Path(os.environ.get("VIRTUAL_ENV"), "..").resolve()
+    else:
+        root = Path("~/invokeai").expanduser().resolve()
+    return root
+
+class InvokeAIAppConfig(InvokeAISettings):
+    '''
+    Application-wide settings.
+    '''
+    #fmt: off
+    type: Literal["globals"] = "globals"
+    root                : Path = Field(default=_find_root(), description='InvokeAI runtime root directory', category='Paths')
+    infile              : Path = Field(default=None, description='Path to a file of prompt commands to bulk generate from', category='Paths')
+    conf_path           : Path = Field(default='configs/models.yaml', description='Path to models definition file', category='Paths')
+    model               : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
+    outdir              : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
+    embedding_dir       : Path = Field(default='embeddings', description='Path to InvokeAI textual inversion aembeddings directory', category='Paths')
+    lora_dir            : Path = Field(default='loras', description='Path to InvokeAI LoRA model 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')
+    gfpgan_model_dir    : Path = Field(default="./models/gfpgan/GFPGANv1.4.pth", description='Path to GFPGAN models directory.', category='Paths')
+    embeddings          : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
+    xformers_enabled    : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
+    sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
+    precision           : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='float16',description='Floating point precision', category='Memory/Performance')
+    max_loaded_models   : int = Field(default=2, gt=0, description="Maximum number of models to keep in memory for rapid switching", category='Memory/Performance')
+    always_use_cpu      : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
+    free_gpu_mem        : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
+    nsfw_checker        : bool = Field(default=True, description="Enable/disable the NSFW checker", category='Features')
+    restore             : bool = Field(default=True, description="Enable/disable face restoration code", category='Features')
+    esrgan              : bool = Field(default=True, description="Enable/disable upscaling code", category='Features')
+    patchmatch          : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features')
+    internet_available  : bool = Field(default=True, description="If true, attempt to download models on the fly; otherwise only use local models", category='Features')
+    log_tokenization    : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features')
+    #fmt: on
+
+    def __init__(self, conf: DictConfig = None, argv: List[str]=None, **kwargs):
+        '''
+        Initialize InvokeAIAppconfig.
+        :param conf: alternate Omegaconf dictionary object
+        :param argv: aternate sys.argv list
+        :param **kwargs: attributes to initialize with
+        '''
+        super().__init__(**kwargs)
+        
+        # Set the runtime root directory. We parse command-line switches here
+        # in order to pick up the --root_dir option.
+        self.parse_args(argv)
+        if not conf:
+            try:
+                conf = OmegaConf.load(self.root_dir / INIT_FILE)
+            except:
+                pass
+        InvokeAISettings.initconf = conf
+
+        # parse args again in order to pick up settings in configuration file
+        self.parse_args(argv)
+
+        # restore initialization values
+        hints = get_type_hints(self)
+        for k in kwargs:
+            setattr(self,k,parse_obj_as(hints[k],kwargs[k]))
+
+    @property
+    def root_path(self)->Path:
+        '''
+        Path to the runtime root directory
+        '''
+        if self.root:
+            return self.root.expanduser()
+        else:
+            return self.find_root()
+
+    @property
+    def root_dir(self)->Path:
+        '''
+        Alias for above.
+        '''
+        return self.root_path
+
+    def _resolve(self,partial_path:Path)->Path:
+        return (self.root_path / partial_path).resolve()
+
+    @property
+    def output_path(self)->Path:
+        '''
+        Path to defaults outputs directory.
+        '''
+        return self._resolve(self.outdir)
+
+    @property
+    def model_conf_path(self)->Path:
+        '''
+        Path to models configuration file.
+        '''
+        return self._resolve(self.conf_path)
+
+    @property
+    def conf(self)->Path:
+        '''
+        Path to models configuration file (alias for model_conf_path).
+        '''
+        return self.model_conf_path
+
+    @property
+    def embedding_path(self)->Path:
+        '''
+        Path to the textual inversion embeddings directory.
+        '''
+        return self._resolve(self.embedding_dir) if self.embedding_dir else None
+    
+    @property
+    def lora_path(self)->Path:
+        '''
+        Path to the LoRA models directory.
+        '''
+        return self._resolve(self.lora_dir) if self.lora_dir else None
+
+    @property
+    def autoconvert_path(self)->Path:
+        '''
+        Path to the directory containing models to be imported automatically at startup.
+        '''
+        return self._resolve(self.autoconvert_dir) if self.autoconvert_dir else None
+
+    @property
+    def gfpgan_model_path(self)->Path:
+        '''
+        Path to the GFPGAN model.
+        '''
+        return self._resolve(self.gfpgan_model_dir) if self.gfpgan_model_dir else None
+
+    @staticmethod
+    def find_root()->Path:
+        '''
+        Choose the runtime root directory when not specified on command line or
+        init file.
+        '''
+        return _find_root()
+
+class InvokeAIWebConfig(InvokeAIAppConfig):
+    '''
+    Web-specific settings
+    '''
+    #fmt: off
+    type               : Literal["web"] = "web"
+    allow_origins      : List = Field(default=[], description="Allowed CORS origins", category='Cross-Origin Resource Sharing')
+    allow_credentials  : bool = Field(default=True, description="Allow CORS credentials", category='Cross-Origin Resource Sharing')
+    allow_methods      : List = Field(default=["*"], description="Methods allowed for CORS", category='Cross-Origin Resource Sharing')
+    allow_headers      : List = Field(default=["*"], description="Headers allowed for CORS", category='Cross-Origin Resource Sharing')
+    host               : str = Field(default="127.0.0.1", description="IP address to bind to", category='Web Server')
+    port               : int = Field(default=9090, description="Port to bind to", category='Web Server')
+    #fmt: on

invokeai/app/services/events.py

@@ -1,10 +1,9 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Any, Dict, TypedDict
+from typing import Any, Dict, TypedDict, Union
+from invokeai.app.api.models.images import ProgressImage
+from invokeai.app.util.misc import get_timestamp
 
-ProgressImage = TypedDict(
-    "ProgressImage", {"dataURL": str, "width": int, "height": int}
-)
 
 class EventServiceBase:
     session_event: str = "session_event"
@@ -14,7 +13,8 @@ class EventServiceBase:
     def dispatch(self, event_name: str, payload: Any) -> None:
         pass
 
-    def __emit_session_event(self, event_name: str, payload: Dict) -> None:
+    def __emit_session_event(self, event_name: str, payload: dict) -> None:
+        payload["timestamp"] = get_timestamp()
         self.dispatch(
             event_name=EventServiceBase.session_event,
             payload=dict(event=event_name, data=payload),
@@ -25,7 +25,8 @@ class EventServiceBase:
     def emit_generator_progress(
         self,
         graph_execution_state_id: str,
-        invocation_id: str,
+        node: dict,
+        source_node_id: str,
         progress_image: ProgressImage | None,
         step: int,
         total_steps: int,
@@ -35,48 +36,60 @@ class EventServiceBase:
             event_name="generator_progress",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
-                progress_image=progress_image,
+                node=node,
+                source_node_id=source_node_id,
+                progress_image=progress_image.dict() if progress_image is not None else None,
                 step=step,
                 total_steps=total_steps,
             ),
         )
 
     def emit_invocation_complete(
-        self, graph_execution_state_id: str, invocation_id: str, result: Dict
+        self,
+        graph_execution_state_id: str,
+        result: dict,
+        node: dict,
+        source_node_id: str,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_session_event(
             event_name="invocation_complete",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
                 result=result,
             ),
         )
 
     def emit_invocation_error(
-        self, graph_execution_state_id: str, invocation_id: str, error: str
+        self,
+        graph_execution_state_id: str,
+        node: dict,
+        source_node_id: str,
+        error: str,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_session_event(
             event_name="invocation_error",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
                 error=error,
             ),
         )
 
     def emit_invocation_started(
-        self, graph_execution_state_id: str, invocation_id: str
+        self, graph_execution_state_id: str, node: dict, source_node_id: str
     ) -> None:
         """Emitted when an invocation has started"""
         self.__emit_session_event(
             event_name="invocation_started",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
             ),
         )
 
@@ -84,5 +97,7 @@ class EventServiceBase:
         """Emitted when a session has completed all invocations"""
         self.__emit_session_event(
             event_name="graph_execution_state_complete",
-            payload=dict(graph_execution_state_id=graph_execution_state_id),
+            payload=dict(
+                graph_execution_state_id=graph_execution_state_id,
+            ),
         )

invokeai/app/services/graph.py

@@ -3,7 +3,6 @@
 import copy
 import itertools
 import uuid
-from types import NoneType
 from typing import (
     Annotated,
     Any,
@@ -14,9 +13,10 @@ from typing import (
     get_origin,
     get_type_hints,
 )
+NoneType = type(None)
 
 import networkx as nx
-from pydantic import BaseModel, root_validator, validator
+from pydantic import BaseModel, root_validator, validator, Extra
 from pydantic.fields import Field
 
 from ..invocations import *
@@ -25,6 +25,7 @@ from ..invocations.baseinvocation import (
     BaseInvocationOutput,
     InvocationContext,
 )
+from .config import InvokeAISettings
 
 
 class EdgeConnection(BaseModel):
@@ -211,9 +212,10 @@ class CollectInvocation(BaseInvocation):
 InvocationsUnion = Union[BaseInvocation.get_invocations()]  # type: ignore
 InvocationOutputsUnion = Union[BaseInvocationOutput.get_all_subclasses_tuple()]  # type: ignore
 
-
-class Graph(BaseModel):
+class Graph(InvokeAISettings):
     id: str = Field(description="The id of this graph", default_factory=lambda: uuid.uuid4().__str__())
+    type: Literal["graph"] = "graph"
+
     # TODO: use a list (and never use dict in a BaseModel) because pydantic/fastapi hates me
     nodes: dict[str, Annotated[InvocationsUnion, Field(discriminator="type")]] = Field(
         description="The nodes in this graph", default_factory=dict
@@ -749,7 +751,7 @@ class GraphExecutionState(BaseModel):
     """Tracks the state of a graph execution"""
 
     id: str = Field(description="The id of the execution state", default_factory=lambda: uuid.uuid4().__str__())
-
+    
     # TODO: Store a reference to the graph instead of the actual graph?
     graph: Graph = Field(description="The graph being executed")
 
@@ -805,7 +807,7 @@ class GraphExecutionState(BaseModel):
             ]
         }
 
-    def next(self) -> BaseInvocation | None:
+    def next(self) -> Union[BaseInvocation, None]:
         """Gets the next node ready to execute."""
 
         # TODO: enable multiple nodes to execute simultaneously by tracking currently executing nodes
@@ -1154,7 +1156,7 @@ class ExposedNodeOutput(BaseModel):
     field: str = Field(description="The field name of the output")
     alias: str = Field(description="The alias of the output")
 
-class LibraryGraph(BaseModel):
+class LibraryGraph(InvokeAISettings):
     id: str = Field(description="The unique identifier for this library graph", default_factory=uuid.uuid4)
     graph: Graph = Field(description="The graph")
     name: str = Field(description="The name of the graph")
@@ -1162,6 +1164,9 @@ class LibraryGraph(BaseModel):
     exposed_inputs: list[ExposedNodeInput] = Field(description="The inputs exposed by this graph", default_factory=list)
     exposed_outputs: list[ExposedNodeOutput] = Field(description="The outputs exposed by this graph", default_factory=list)
 
+    class Config:
+        extra='allow'
+
     @validator('exposed_inputs', 'exposed_outputs')
     def validate_exposed_aliases(cls, v):
         if len(v) != len(set(i.alias for i in v)):

invokeai/app/services/image_storage.py

@@ -1,24 +1,29 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-import datetime
 import os
 from glob import glob
 from abc import ABC, abstractmethod
-from enum import Enum
 from pathlib import Path
 from queue import Queue
-from typing import Callable, Dict, List
+from typing import Dict, List
 
 from PIL.Image import Image
 import PIL.Image as PILImage
-from pydantic import BaseModel
-from invokeai.app.api.models.images import ImageResponse
-from invokeai.app.models.image import ImageField, ImageType
-from invokeai.app.models.metadata import ImageMetadata
+from send2trash import send2trash
+from invokeai.app.api.models.images import (
+    ImageResponse,
+    ImageResponseMetadata,
+    SavedImage,
+)
+from invokeai.app.models.image import ImageType
+from invokeai.app.services.metadata import (
+    InvokeAIMetadata,
+    MetadataServiceBase,
+    build_invokeai_metadata_pnginfo,
+)
 from invokeai.app.services.item_storage import PaginatedResults
-from invokeai.app.util.save_thumbnail import save_thumbnail
-
-from invokeai.backend.image_util import PngWriter
+from invokeai.app.util.misc import get_timestamp
+from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
 
 class ImageStorageBase(ABC):
@@ -26,12 +31,14 @@ class ImageStorageBase(ABC):
 
     @abstractmethod
     def get(self, image_type: ImageType, image_name: str) -> Image:
+        """Retrieves an image as PIL Image."""
         pass
 
     @abstractmethod
     def list(
         self, image_type: ImageType, page: int = 0, per_page: int = 10
     ) -> PaginatedResults[ImageResponse]:
+        """Gets a paginated list of images."""
         pass
 
     # TODO: make this a bit more flexible for e.g. cloud storage
@@ -39,35 +46,59 @@ class ImageStorageBase(ABC):
     def get_path(
         self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
     ) -> str:
+        """Gets the internal path to an image or its thumbnail."""
+        pass
+
+    # TODO: make this a bit more flexible for e.g. cloud storage
+    @abstractmethod
+    def get_uri(
+        self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
+    ) -> str:
+        """Gets the external URI to an image or its thumbnail."""
+        pass
+
+    # TODO: make this a bit more flexible for e.g. cloud storage
+    @abstractmethod
+    def validate_path(self, path: str) -> bool:
+        """Validates an image path."""
         pass
 
     @abstractmethod
-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
+    def save(
+        self,
+        image_type: ImageType,
+        image_name: str,
+        image: Image,
+        metadata: InvokeAIMetadata | None = None,
+    ) -> SavedImage:
+        """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
         pass
 
     @abstractmethod
     def delete(self, image_type: ImageType, image_name: str) -> None:
+        """Deletes an image and its thumbnail (if one exists)."""
         pass
 
     def create_name(self, context_id: str, node_id: str) -> str:
-        return f"{context_id}_{node_id}_{str(int(datetime.datetime.now(datetime.timezone.utc).timestamp()))}.png"
+        """Creates a unique contextual image filename."""
+        return f"{context_id}_{node_id}_{str(get_timestamp())}.png"
 
 
 class DiskImageStorage(ImageStorageBase):
     """Stores images on disk"""
 
     __output_folder: str
-    __pngWriter: PngWriter
     __cache_ids: Queue  # TODO: this is an incredibly naive cache
     __cache: Dict[str, Image]
     __max_cache_size: int
+    __metadata_service: MetadataServiceBase
 
-    def __init__(self, output_folder: str):
+    def __init__(self, output_folder: str, metadata_service: MetadataServiceBase):
         self.__output_folder = output_folder
-        self.__pngWriter = PngWriter(output_folder)
         self.__cache = dict()
         self.__cache_ids = Queue()
         self.__max_cache_size = 10  # TODO: get this from config
+        self.__metadata_service = metadata_service
 
         Path(output_folder).mkdir(parents=True, exist_ok=True)
 
@@ -100,18 +131,22 @@ class DiskImageStorage(ImageStorageBase):
         for path in page_of_image_paths:
             filename = os.path.basename(path)
             img = PILImage.open(path)
+
+            invokeai_metadata = self.__metadata_service.get_metadata(img)
+
             page_of_images.append(
                 ImageResponse(
                     image_type=image_type.value,
                     image_name=filename,
                     # TODO: DiskImageStorage should not be building URLs...?
-                    image_url=f"api/v1/images/{image_type.value}/{filename}",
-                    thumbnail_url=f"api/v1/images/{image_type.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
-                    # TODO: Creation of this object should happen elsewhere, just making it fit here so it works
-                    metadata=ImageMetadata(
-                        timestamp=os.path.getctime(path),
+                    image_url=self.get_uri(image_type, filename),
+                    thumbnail_url=self.get_uri(image_type, filename, True),
+                    # TODO: Creation of this object should happen elsewhere (?), just making it fit here so it works
+                    metadata=ImageResponseMetadata(
+                        created=int(os.path.getctime(path)),
                         width=img.width,
                         height=img.height,
+                        invokeai=invokeai_metadata,
                     ),
                 )
             )
@@ -142,43 +177,89 @@ class DiskImageStorage(ImageStorageBase):
     def get_path(
         self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
     ) -> str:
+        # strip out any relative path shenanigans
+        basename = os.path.basename(image_name)
+
         if is_thumbnail:
             path = os.path.join(
-                self.__output_folder, image_type, "thumbnails", image_name
+                self.__output_folder, image_type, "thumbnails", basename
             )
         else:
-            path = os.path.join(self.__output_folder, image_type, image_name)
-        return path
+            path = os.path.join(self.__output_folder, image_type, basename)
 
-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
-        image_subpath = os.path.join(image_type, image_name)
-        self.__pngWriter.save_image_and_prompt_to_png(
-            image, "", image_subpath, None
-        )  # TODO: just pass full path to png writer
-        save_thumbnail(
-            image=image,
-            filename=image_name,
-            path=os.path.join(self.__output_folder, image_type, "thumbnails"),
-        )
+        abspath = os.path.abspath(path)
+
+        return abspath
+
+    def get_uri(
+        self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
+    ) -> str:
+        # strip out any relative path shenanigans
+        basename = os.path.basename(image_name)
+
+        if is_thumbnail:
+            thumbnail_basename = get_thumbnail_name(basename)
+            uri = f"api/v1/images/{image_type.value}/thumbnails/{thumbnail_basename}"
+        else:
+            uri = f"api/v1/images/{image_type.value}/{basename}"
+
+        return uri
+
+    def validate_path(self, path: str) -> bool:
+        try:
+            os.stat(path)
+            return True
+        except Exception:
+            return False
+
+    def save(
+        self,
+        image_type: ImageType,
+        image_name: str,
+        image: Image,
+        metadata: InvokeAIMetadata | None = None,
+    ) -> SavedImage:
         image_path = self.get_path(image_type, image_name)
+
+        # TODO: Reading the image and then saving it strips the metadata...
+        if metadata:
+            pnginfo = build_invokeai_metadata_pnginfo(metadata=metadata)
+            image.save(image_path, "PNG", pnginfo=pnginfo)
+        else:
+            image.save(image_path)  # this saved image has an empty info
+
+        thumbnail_name = get_thumbnail_name(image_name)
+        thumbnail_path = self.get_path(image_type, thumbnail_name, is_thumbnail=True)
+        thumbnail_image = make_thumbnail(image)
+        thumbnail_image.save(thumbnail_path)
+
         self.__set_cache(image_path, image)
+        self.__set_cache(thumbnail_path, thumbnail_image)
+
+        return SavedImage(
+            image_name=image_name,
+            thumbnail_name=thumbnail_name,
+            created=int(os.path.getctime(image_path)),
+        )
 
     def delete(self, image_type: ImageType, image_name: str) -> None:
-        image_path = self.get_path(image_type, image_name)
-        thumbnail_path = self.get_path(image_type, image_name, True)
-        if os.path.exists(image_path):
-            os.remove(image_path)
+        basename = os.path.basename(image_name)
+        image_path = self.get_path(image_type, basename)
 
+        if os.path.exists(image_path):
+            send2trash(image_path)
         if image_path in self.__cache:
             del self.__cache[image_path]
 
-        if os.path.exists(thumbnail_path):
-            os.remove(thumbnail_path)
+        thumbnail_name = get_thumbnail_name(image_name)
+        thumbnail_path = self.get_path(image_type, thumbnail_name, True)
 
+        if os.path.exists(thumbnail_path):
+            send2trash(thumbnail_path)
         if thumbnail_path in self.__cache:
             del self.__cache[thumbnail_path]
 
-    def __get_cache(self, image_name: str) -> Image:
+    def __get_cache(self, image_name: str) -> Image | None:
         return None if image_name not in self.__cache else self.__cache[image_name]
 
     def __set_cache(self, image_name: str, image: Image):

invokeai/app/services/invocation_queue.py

@@ -3,7 +3,7 @@
 import time
 from abc import ABC, abstractmethod
 from queue import Queue
-
+from typing import Union
 from pydantic import BaseModel, Field
 
 
@@ -22,7 +22,7 @@ class InvocationQueueABC(ABC):
         pass
 
     @abstractmethod
-    def put(self, item: InvocationQueueItem | None) -> None:
+    def put(self, item: Union[InvocationQueueItem, None]) -> None:
         pass
 
     @abstractmethod
@@ -57,7 +57,7 @@ class MemoryInvocationQueue(InvocationQueueABC):
 
         return item
 
-    def put(self, item: InvocationQueueItem | None) -> None:
+    def put(self, item: Union[InvocationQueueItem, None]) -> None:
         self.__queue.put(item)
 
     def cancel(self, graph_execution_state_id: str) -> None:

invokeai/app/services/invocation_services.py

@@ -1,4 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+from invokeai.app.services.metadata import MetadataServiceBase
 from invokeai.backend import ModelManager
 
 from .events import EventServiceBase
@@ -7,6 +8,7 @@ from .image_storage import ImageStorageBase
 from .restoration_services import RestorationServices
 from .invocation_queue import InvocationQueueABC
 from .item_storage import ItemStorageABC
+from .config import InvokeAISettings
 
 class InvocationServices:
     """Services that can be used by invocations"""
@@ -14,9 +16,11 @@ class InvocationServices:
     events: EventServiceBase
     latents: LatentsStorageBase
     images: ImageStorageBase
+    metadata: MetadataServiceBase
     queue: InvocationQueueABC
     model_manager: ModelManager
     restoration: RestorationServices
+    configuration: InvokeAISettings
 
     # NOTE: we must forward-declare any types that include invocations, since invocations can use services
     graph_library: ItemStorageABC["LibraryGraph"]
@@ -29,18 +33,22 @@ class InvocationServices:
             events: EventServiceBase,
             latents: LatentsStorageBase,
             images: ImageStorageBase,
+            metadata: MetadataServiceBase,
             queue: InvocationQueueABC,
             graph_library: ItemStorageABC["LibraryGraph"],
             graph_execution_manager: ItemStorageABC["GraphExecutionState"],
             processor: "InvocationProcessorABC",
             restoration: RestorationServices,
+            configuration: InvokeAISettings=None,
     ):
         self.model_manager = model_manager
         self.events = events
         self.latents = latents
         self.images = images
+        self.metadata = metadata
         self.queue = queue
         self.graph_library = graph_library
         self.graph_execution_manager = graph_execution_manager
         self.processor = processor
         self.restoration = restoration
+        self.configuration = configuration

invokeai/app/services/invoker.py

@@ -2,6 +2,7 @@
 
 from abc import ABC
 from threading import Event, Thread
+from typing import Union
 
 from ..invocations.baseinvocation import InvocationContext
 from .graph import Graph, GraphExecutionState
@@ -21,7 +22,7 @@ class Invoker:
 
     def invoke(
         self, graph_execution_state: GraphExecutionState, invoke_all: bool = False
-    ) -> str | None:
+    ) -> Union[str, None]:
         """Determines the next node to invoke and returns the id of the invoked node, or None if there are no nodes to execute"""
 
         # Get the next invocation
@@ -44,7 +45,7 @@ class Invoker:
 
         return invocation.id
 
-    def create_execution_state(self, graph: Graph | None = None) -> GraphExecutionState:
+    def create_execution_state(self, graph: Union[Graph, None] = None) -> GraphExecutionState:
         """Creates a new execution state for the given graph"""
         new_state = GraphExecutionState(graph=Graph() if graph is None else graph)
         self.services.graph_execution_manager.set(new_state)

invokeai/app/services/latent_storage.py

@@ -4,7 +4,7 @@ import os
 from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
-from typing import Dict
+from typing import Dict, Union
 
 import torch
 
@@ -56,7 +56,7 @@ class ForwardCacheLatentsStorage(LatentsStorageBase):
         if name in self.__cache:
             del self.__cache[name]
 
-    def __get_cache(self, name: str) -> torch.Tensor|None:
+    def __get_cache(self, name: str) -> Union[torch.Tensor,None]:
         return None if name not in self.__cache else self.__cache[name]
 
     def __set_cache(self, name: str, data: torch.Tensor):
@@ -90,4 +90,4 @@ class DiskLatentsStorage(LatentsStorageBase):
 
     def get_path(self, name: str) -> str:
         return os.path.join(self.__output_folder, name)
-    
+    

invokeai/app/services/metadata.py

@@ -0,0 +1,96 @@
+import json
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Optional, TypedDict
+from PIL import Image, PngImagePlugin
+from pydantic import BaseModel
+
+from invokeai.app.models.image import ImageType, is_image_type
+
+
+class MetadataImageField(TypedDict):
+    """Pydantic-less ImageField, used for metadata parsing."""
+
+    image_type: ImageType
+    image_name: str
+
+
+class MetadataLatentsField(TypedDict):
+    """Pydantic-less LatentsField, used for metadata parsing."""
+
+    latents_name: str
+
+
+# TODO: This is a placeholder for `InvocationsUnion` pending resolution of circular imports
+NodeMetadata = Dict[
+    str, str | int | float | bool | MetadataImageField | MetadataLatentsField
+]
+
+
+class InvokeAIMetadata(TypedDict, total=False):
+    """InvokeAI-specific metadata format."""
+
+    session_id: Optional[str]
+    node: Optional[NodeMetadata]
+
+
+def build_invokeai_metadata_pnginfo(
+    metadata: InvokeAIMetadata | None,
+) -> PngImagePlugin.PngInfo:
+    """Builds a PngInfo object with key `"invokeai"` and value `metadata`"""
+    pnginfo = PngImagePlugin.PngInfo()
+
+    if metadata is not None:
+        pnginfo.add_text("invokeai", json.dumps(metadata))
+
+    return pnginfo
+
+
+class MetadataServiceBase(ABC):
+    @abstractmethod
+    def get_metadata(self, image: Image.Image) -> InvokeAIMetadata | None:
+        """Gets the InvokeAI metadata from a PIL Image, skipping invalid values"""
+        pass
+
+    @abstractmethod
+    def build_metadata(
+        self, session_id: str, node: BaseModel
+    ) -> InvokeAIMetadata | None:
+        """Builds an InvokeAIMetadata object"""
+        pass
+
+
+class PngMetadataService(MetadataServiceBase):
+    """Handles loading and building metadata for images."""
+
+    # TODO: Use `InvocationsUnion` to **validate** metadata as representing a fully-functioning node
+    def _load_metadata(self, image: Image.Image) -> dict | None:
+        """Loads a specific info entry from a PIL Image."""
+
+        try:
+            info = image.info.get("invokeai")
+
+            if type(info) is not str:
+                return None
+
+            loaded_metadata = json.loads(info)
+
+            if type(loaded_metadata) is not dict:
+                return None
+
+            if len(loaded_metadata.items()) == 0:
+                return None
+
+            return loaded_metadata
+        except:
+            return None
+
+    def get_metadata(self, image: Image.Image) -> dict | None:
+        """Retrieves an image's metadata as a dict"""
+        loaded_metadata = self._load_metadata(image)
+
+        return loaded_metadata
+
+    def build_metadata(self, session_id: str, node: BaseModel) -> InvokeAIMetadata:
+        metadata = InvokeAIMetadata(session_id=session_id, node=node.dict())
+
+        return metadata

invokeai/app/services/model_manager_initializer.py

@@ -7,21 +7,20 @@ from omegaconf import OmegaConf
 from pathlib import Path
 
 import invokeai.version
+from .config import InvokeAISettings
 from ...backend import ModelManager
 from ...backend.util import choose_precision, choose_torch_device
-from ...backend import Globals
 
 # TODO: Replace with an abstract class base ModelManagerBase
-def get_model_manager(config: Args) -> ModelManager:
-    if not config.conf:
-        config_file = os.path.join(Globals.root, "configs", "models.yaml")
-        if not os.path.exists(config_file):
-            report_model_error(
-                config, FileNotFoundError(f"The file {config_file} could not be found.")
-            )
+def get_model_manager(config:InvokeAISettings) -> ModelManager:
+    model_config = config.model_conf_path
+    if not model_config.exists():
+        report_model_error(
+            config, FileNotFoundError(f"The file {model_config} could not be found.")
+        )
 
     print(f">> {invokeai.version.__app_name__}, version {invokeai.version.__version__}")
-    print(f'>> InvokeAI runtime directory is "{Globals.root}"')
+    print(f'>> InvokeAI runtime directory is "{config.root_dir}"')
 
     # these two lines prevent a horrible warning message from appearing
     # when the frozen CLIP tokenizer is imported
@@ -31,20 +30,7 @@ def get_model_manager(config: Args) -> ModelManager:
     import diffusers
 
     diffusers.logging.set_verbosity_error()
-
-    # normalize the config directory relative to root
-    if not os.path.isabs(config.conf):
-        config.conf = os.path.normpath(os.path.join(Globals.root, config.conf))
-
-    if config.embeddings:
-        if not os.path.isabs(config.embedding_path):
-            embedding_path = os.path.normpath(
-                os.path.join(Globals.root, config.embedding_path)
-            )
-        else:
-            embedding_path = config.embedding_path
-    else:
-        embedding_path = None
+    embedding_path = config.embedding_path
 
     # migrate legacy models
     ModelManager.migrate_models()
@@ -57,11 +43,11 @@ def get_model_manager(config: Args) -> ModelManager:
         else choose_precision(device)
         
         model_manager = ModelManager(
-            OmegaConf.load(config.conf),
+            OmegaConf.load(model_config),
             precision=precision,
             device_type=device,
             max_loaded_models=config.max_loaded_models,
-            embedding_path = Path(embedding_path),
+            embedding_path = embedding_path,
         )
     except (FileNotFoundError, TypeError, AssertionError) as e:
         report_model_error(config, e)
@@ -71,12 +57,10 @@ def get_model_manager(config: Args) -> ModelManager:
 
     # try to autoconvert new models
     # autoimport new .ckpt files
-    if path := config.autoconvert:
-        model_manager.autoconvert_weights(
-            conf_path=config.conf,
-            weights_directory=path,
+    if config.autoconvert_path:
+        model_manager.heuristic_import(
+            config.autoconvert_path,
         )
-
     return model_manager
 
 def report_model_error(opt: Namespace, e: Exception):

invokeai/app/services/processor.py

@@ -43,10 +43,14 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     queue_item.invocation_id
                 )
 
+                # get the source node id to provide to clients (the prepared node id is not as useful)
+                source_node_id = graph_execution_state.prepared_source_mapping[invocation.id]
+
                 # Send starting event
                 self.__invoker.services.events.emit_invocation_started(
                     graph_execution_state_id=graph_execution_state.id,
-                    invocation_id=invocation.id,
+                    node=invocation.dict(),
+                    source_node_id=source_node_id
                 )
 
                 # Invoke
@@ -75,7 +79,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send complete event
                     self.__invoker.services.events.emit_invocation_complete(
                         graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        node=invocation.dict(),
+                        source_node_id=source_node_id,
                         result=outputs.dict(),
                     )
 
@@ -99,7 +104,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send error event
                     self.__invoker.services.events.emit_invocation_error(
                         graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        node=invocation.dict(),
+                        source_node_id=source_node_id,
                         error=error,
                     )
 

invokeai/app/services/sqlite.py

@@ -35,7 +35,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
         self._create_table()
 
     def _create_table(self):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""CREATE TABLE IF NOT EXISTS {self._table_name} (
                 item TEXT,
@@ -44,27 +45,34 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
             self._cursor.execute(
                 f"""CREATE UNIQUE INDEX IF NOT EXISTS {self._table_name}_id ON {self._table_name}(id);"""
             )
-            self._conn.commit()
+        finally:
+            self._lock.release()
 
     def _parse_item(self, item: str) -> T:
         item_type = get_args(self.__orig_class__)[0]
         return parse_raw_as(item_type, item)
 
     def set(self, item: T):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""INSERT OR REPLACE INTO {self._table_name} (item) VALUES (?);""",
                 (item.json(),),
             )
             self._conn.commit()
+        finally:
+            self._lock.release()
         self._on_changed(item)
 
     def get(self, id: str) -> Union[T, None]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} WHERE id = ?;""", (str(id),)
             )
             result = self._cursor.fetchone()
+        finally:
+            self._lock.release()
 
         if not result:
             return None
@@ -72,15 +80,19 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
         return self._parse_item(result[0])
 
     def delete(self, id: str):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""DELETE FROM {self._table_name} WHERE id = ?;""", (str(id),)
             )
             self._conn.commit()
+        finally:
+            self._lock.release()
         self._on_deleted(id)
 
     def list(self, page: int = 0, per_page: int = 10) -> PaginatedResults[T]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} LIMIT ? OFFSET ?;""",
                 (per_page, page * per_page),
@@ -91,6 +103,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
 
             self._cursor.execute(f"""SELECT count(*) FROM {self._table_name};""")
             count = self._cursor.fetchone()[0]
+        finally:
+            self._lock.release()
 
         pageCount = int(count / per_page) + 1
 
@@ -101,7 +115,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
     def search(
         self, query: str, page: int = 0, per_page: int = 10
     ) -> PaginatedResults[T]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} WHERE item LIKE ? LIMIT ? OFFSET ?;""",
                 (f"%{query}%", per_page, page * per_page),
@@ -115,6 +130,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
                 (f"%{query}%",),
             )
             count = self._cursor.fetchone()[0]
+        finally:
+            self._lock.release()
 
         pageCount = int(count / per_page) + 1
 

invokeai/app/util/misc.py

@@ -0,0 +1,5 @@
+import datetime
+
+
+def get_timestamp():
+    return int(datetime.datetime.now(datetime.timezone.utc).timestamp())

invokeai/app/util/save_thumbnail.py

@@ -1,25 +0,0 @@
-import os
-from PIL import Image
-
-
-def save_thumbnail(
-    image: Image.Image,
-    filename: str,
-    path: str,
-    size: int = 256,
-) -> str:
-    """
-    Saves a thumbnail of an image, returning its path.
-    """
-    base_filename = os.path.splitext(filename)[0]
-    thumbnail_path = os.path.join(path, base_filename + ".webp")
-
-    if os.path.exists(thumbnail_path):
-        return thumbnail_path
-
-    image_copy = image.copy()
-    image_copy.thumbnail(size=(size, size))
-
-    image_copy.save(thumbnail_path, "WEBP")
-
-    return thumbnail_path

invokeai/app/util/step_callback.py

@@ -1,16 +1,41 @@
-import torch
+from invokeai.app.api.models.images import ProgressImage
+from invokeai.app.models.exceptions import CanceledException
 from ..invocations.baseinvocation import InvocationContext
 from ...backend.util.util import image_to_dataURL
 from ...backend.generator.base import Generator
 from ...backend.stable_diffusion import PipelineIntermediateState
 
-def fast_latents_step_callback(
-    sample: torch.Tensor,
-    step: int,
-    steps: int,
-    id: str,
+
+def stable_diffusion_step_callback(
     context: InvocationContext,
+    intermediate_state: PipelineIntermediateState,
+    node: dict,
+    source_node_id: str,
 ):
+    if context.services.queue.is_canceled(context.graph_execution_state_id):
+        raise CanceledException
+
+    # Some schedulers report not only the noisy latents at the current timestep,
+    # but also their estimate so far of what the de-noised latents will be. Use
+    # that estimate if it is available.
+    if intermediate_state.predicted_original is not None:
+        sample = intermediate_state.predicted_original
+    else:
+        sample = intermediate_state.latents
+
+    # TODO: This does not seem to be needed any more?
+    # # txt2img provides a Tensor in the step_callback
+    # # img2img provides a PipelineIntermediateState
+    # if isinstance(sample, PipelineIntermediateState):
+    #     # this was an img2img
+    #     print('img2img')
+    #     latents = sample.latents
+    #     step = sample.step
+    # else:
+    #     print('txt2img')
+    #     latents = sample
+    #     step = intermediate_state.step
+
     # TODO: only output a preview image when requested
     image = Generator.sample_to_lowres_estimated_image(sample)
 
@@ -21,23 +46,10 @@ def fast_latents_step_callback(
     dataURL = image_to_dataURL(image, image_format="JPEG")
 
     context.services.events.emit_generator_progress(
-        context.graph_execution_state_id,
-        id,
-        {"width": width, "height": height, "dataURL": dataURL},
-        step,
-        steps,
+        graph_execution_state_id=context.graph_execution_state_id,
+        node=node,
+        source_node_id=source_node_id,
+        progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
+        step=intermediate_state.step,
+        total_steps=node["steps"],
     )
-
-
-def diffusers_step_callback_adapter(*cb_args, **kwargs):
-    """
-    txt2img gives us a Tensor in the step_callbak, while img2img gives us a PipelineIntermediateState.
-    This adapter grabs the needed data and passes it along to the callback function.
-    """
-    if isinstance(cb_args[0], PipelineIntermediateState):
-        progress_state: PipelineIntermediateState = cb_args[0]
-        return fast_latents_step_callback(
-            progress_state.latents, progress_state.step, **kwargs
-        )
-    else:
-        return fast_latents_step_callback(*cb_args, **kwargs)

invokeai/app/util/thumbnails.py

@@ -0,0 +1,15 @@
+import os
+from PIL import Image
+
+
+def get_thumbnail_name(image_name: str) -> str:
+    """Formats given an image name, returns the appropriate thumbnail image name"""
+    thumbnail_name = os.path.splitext(image_name)[0] + ".webp"
+    return thumbnail_name
+
+
+def make_thumbnail(image: Image.Image, size: int = 256) -> Image.Image:
+    """Makes a thumbnail from a PIL Image"""
+    thumbnail = image.copy()
+    thumbnail.thumbnail(size=(size, size))
+    return thumbnail

invokeai/backend/__init__.py

@@ -10,7 +10,7 @@ from .generator import (
     Img2Img,
     Inpaint
 )
-from .model_management import ModelManager
+from .model_management import ModelManager, SDModelComponent
 from .safety_checker import SafetyChecker
 from .args import Args
 from .globals import Globals

invokeai/backend/globals.py

@@ -16,6 +16,7 @@ import os.path as osp
 from argparse import Namespace
 from pathlib import Path
 from typing import Union
+from pydantic import BaseSettings
 
 Globals = Namespace()
 
@@ -120,3 +121,15 @@ def global_cache_dir(subdir: Union[str, Path] = "") -> Path:
         return Path(home, subdir)
     else:
         return Path(Globals.root, "models", subdir)
+
+def copy_conf_to_globals(conf: Union[dict,BaseSettings]):
+    '''
+    Given a dict or dict-like object, copy its keys and
+    values into the Globals Namespace. This is a transitional
+    workaround until we remove Globals entirely.
+    '''
+    if isinstance(conf,BaseSettings):
+        conf = conf.dict()
+    for key in conf.keys():
+        if key is not None:
+            setattr(Globals,key,conf[key])

invokeai/backend/model_management/__init__.py

@@ -5,6 +5,7 @@ from .convert_ckpt_to_diffusers import (
     convert_ckpt_to_diffusers,
     load_pipeline_from_original_stable_diffusion_ckpt,
 )
-from .model_manager import ModelManager
+from .model_manager import ModelManager,SDModelComponent
+
 
 

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -445,8 +445,15 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
     @property
     def _submodels(self) -> Sequence[torch.nn.Module]:
         module_names, _, _ = self.extract_init_dict(dict(self.config))
-        values = [getattr(self, name) for name in module_names.keys()]
-        return [m for m in values if isinstance(m, torch.nn.Module)]
+        submodels = []
+        for name in module_names.keys():
+            if hasattr(self, name):
+                value = getattr(self, name)
+            else:
+                value = getattr(self.config, name)
+            if isinstance(value, torch.nn.Module):
+                submodels.append(value)
+        return submodels
 
     def image_from_embeddings(
         self,
@@ -544,7 +551,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             yield PipelineIntermediateState(
                 run_id=run_id,
                 step=-1,
-                timestep=self.scheduler.num_train_timesteps,
+                timestep=self.scheduler.config.num_train_timesteps,
                 latents=latents,
             )
 
@@ -915,7 +922,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
     @property
     def channels(self) -> int:
         """Compatible with DiffusionWrapper"""
-        return self.unet.in_channels
+        return self.unet.config.in_channels
 
     def decode_latents(self, latents):
         # Explicit call to get the vae loaded, since `decode` isn't the forward method.

invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py

@@ -10,8 +10,7 @@ import diffusers
 import psutil
 import torch
 from compel.cross_attention_control import Arguments
-from diffusers.models.cross_attention import AttnProcessor
-from diffusers.models.unet_2d_condition import UNet2DConditionModel
+from diffusers.models.attention_processor import AttentionProcessor
 from torch import nn
 
 from ...util import torch_dtype
@@ -188,7 +187,7 @@ class Context:
 
 class InvokeAICrossAttentionMixin:
     """
-    Enable InvokeAI-flavoured CrossAttention calculation, which does aggressive low-memory slicing and calls
+    Enable InvokeAI-flavoured Attention calculation, which does aggressive low-memory slicing and calls
     through both to an attention_slice_wrangler and a slicing_strategy_getter for custom attention map wrangling
     and dymamic slicing strategy selection.
     """
@@ -209,7 +208,7 @@ class InvokeAICrossAttentionMixin:
         Set custom attention calculator to be called when attention is calculated
         :param wrangler: Callback, with args (module, suggested_attention_slice, dim, offset, slice_size),
         which returns either the suggested_attention_slice or an adjusted equivalent.
-            `module` is the current CrossAttention module for which the callback is being invoked.
+            `module` is the current Attention module for which the callback is being invoked.
             `suggested_attention_slice` is the default-calculated attention slice
             `dim` is -1 if the attenion map has not been sliced, or 0 or 1 for dimension-0 or dimension-1 slicing.
                 If `dim` is >= 0, `offset` and `slice_size` specify the slice start and length.
@@ -345,11 +344,11 @@ class InvokeAICrossAttentionMixin:
 def restore_default_cross_attention(
     model,
     is_running_diffusers: bool,
-    restore_attention_processor: Optional[AttnProcessor] = None,
+    restore_attention_processor: Optional[AttentionProcessor] = None,
 ):
     if is_running_diffusers:
         unet = model
-        unet.set_attn_processor(restore_attention_processor or CrossAttnProcessor())
+        unet.set_attn_processor(restore_attention_processor or AttnProcessor())
     else:
         remove_attention_function(model)
 
@@ -408,12 +407,9 @@ def override_cross_attention(model, context: Context, is_running_diffusers=False
 def get_cross_attention_modules(
     model, which: CrossAttentionType
 ) -> list[tuple[str, InvokeAICrossAttentionMixin]]:
-    from ldm.modules.attention import CrossAttention  # avoid circular import
 
     cross_attention_class: type = (
         InvokeAIDiffusersCrossAttention
-        if isinstance(model, UNet2DConditionModel)
-        else CrossAttention
     )
     which_attn = "attn1" if which is CrossAttentionType.SELF else "attn2"
     attention_module_tuples = [
@@ -428,10 +424,10 @@ def get_cross_attention_modules(
         print(
             f"Error! CrossAttentionControl found an unexpected number of {cross_attention_class} modules in the model "
             + f"(expected {expected_count}, found {cross_attention_modules_in_model_count}). Either monkey-patching failed "
-            + f"or some assumption has changed about the structure of the model itself. Please fix the monkey-patching, "
+            + "or some assumption has changed about the structure of the model itself. Please fix the monkey-patching, "
             + f"and/or update the {expected_count} above to an appropriate number, and/or find and inform someone who knows "
-            + f"what it means. This error is non-fatal, but it is likely that .swap() and attention map display will not "
-            + f"work properly until it is fixed."
+            + "what it means. This error is non-fatal, but it is likely that .swap() and attention map display will not "
+            + "work properly until it is fixed."
         )
     return attention_module_tuples
 
@@ -550,7 +546,7 @@ def get_mem_free_total(device):
 
 
 class InvokeAIDiffusersCrossAttention(
-    diffusers.models.attention.CrossAttention, InvokeAICrossAttentionMixin
+    diffusers.models.attention.Attention, InvokeAICrossAttentionMixin
 ):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
@@ -572,8 +568,8 @@ class InvokeAIDiffusersCrossAttention(
 """
 # base implementation
 
-class CrossAttnProcessor:
-    def __call__(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None):
+class AttnProcessor:
+    def __call__(self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None):
         batch_size, sequence_length, _ = hidden_states.shape
         attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length)
 
@@ -601,9 +597,9 @@ class CrossAttnProcessor:
 from dataclasses import dataclass, field
 
 import torch
-from diffusers.models.cross_attention import (
-    CrossAttention,
-    CrossAttnProcessor,
+from diffusers.models.attention_processor import (
+    Attention,
+    AttnProcessor,
     SlicedAttnProcessor,
 )
 
@@ -653,7 +649,7 @@ class SlicedSwapCrossAttnProcesser(SlicedAttnProcessor):
 
     def __call__(
         self,
-        attn: CrossAttention,
+        attn: Attention,
         hidden_states,
         encoder_hidden_states=None,
         attention_mask=None,

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -5,7 +5,7 @@ from typing import Any, Callable, Dict, Optional, Union
 
 import numpy as np
 import torch
-from diffusers.models.cross_attention import AttnProcessor
+from diffusers.models.attention_processor import AttentionProcessor
 from typing_extensions import TypeAlias
 
 from invokeai.backend.globals import Globals
@@ -101,7 +101,7 @@ class InvokeAIDiffuserComponent:
 
     def override_cross_attention(
         self, conditioning: ExtraConditioningInfo, step_count: int
-    ) -> Dict[str, AttnProcessor]:
+    ) -> Dict[str, AttentionProcessor]:
         """
         setup cross attention .swap control. for diffusers this replaces the attention processor, so
         the previous attention processor is returned so that the caller can restore it later.
@@ -118,7 +118,7 @@ class InvokeAIDiffuserComponent:
         )
 
     def restore_default_cross_attention(
-        self, restore_attention_processor: Optional["AttnProcessor"] = None
+        self, restore_attention_processor: Optional["AttentionProcessor"] = None
     ):
         self.conditioning = None
         self.cross_attention_control_context = None
@@ -262,7 +262,7 @@ class InvokeAIDiffuserComponent:
             # TODO remove when compvis codepath support is dropped
             if step_index is None and sigma is None:
                 raise ValueError(
-                    f"Either step_index or sigma is required when doing cross attention control, but both are None."
+                    "Either step_index or sigma is required when doing cross attention control, but both are None."
                 )
             percent_through = self.estimate_percent_through(step_index, sigma)
         return percent_through
@@ -599,7 +599,6 @@ class InvokeAIDiffuserComponent:
         )
 
         # below is fugly omg
-        num_actual_conditionings = len(c_or_weighted_c_list)
         conditionings = [uc] + [c for c, weight in weighted_cond_list]
         weights = [1] + [weight for c, weight in weighted_cond_list]
         chunk_count = ceil(len(conditionings) / 2)

invokeai/frontend/install/invokeai_update.py

@@ -1,10 +1,9 @@
-"""
+'''
 Minimalist updater script. Prompts user for the tag or branch to update to and runs
 pip install <path_to_git_source>.
-"""
+'''
 import os
 import platform
-
 import requests
 from rich import box, print
 from rich.console import Console, Group, group
@@ -16,8 +15,10 @@ from rich.text import Text
 
 from invokeai.version import __version__
 
-INVOKE_AI_SRC = "https://github.com/invoke-ai/InvokeAI/archive"
-INVOKE_AI_REL = "https://api.github.com/repos/invoke-ai/InvokeAI/releases"
+INVOKE_AI_SRC="https://github.com/invoke-ai/InvokeAI/archive"
+INVOKE_AI_TAG="https://github.com/invoke-ai/InvokeAI/archive/refs/tags"
+INVOKE_AI_BRANCH="https://github.com/invoke-ai/InvokeAI/archive/refs/heads"
+INVOKE_AI_REL="https://api.github.com/repos/invoke-ai/InvokeAI/releases"
 
 OS = platform.uname().system
 ARCH = platform.uname().machine
@@ -28,22 +29,22 @@ if OS == "Windows":
 else:
     console = Console(style=Style(color="grey74", bgcolor="grey19"))
 
-
-def get_versions() -> dict:
+def get_versions()->dict:
     return requests.get(url=INVOKE_AI_REL).json()
 
-
 def welcome(versions: dict):
+    
     @group()
     def text():
-        yield f"InvokeAI Version: [bold yellow]{__version__}"
-        yield ""
-        yield "This script will update InvokeAI to the latest release, or to a development version of your choice."
-        yield ""
-        yield "[bold yellow]Options:"
-        yield f"""[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
+        yield f'InvokeAI Version: [bold yellow]{__version__}'
+        yield ''
+        yield 'This script will update InvokeAI to the latest release, or to a development version of your choice.'
+        yield ''
+        yield '[bold yellow]Options:'
+        yield f'''[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
 [2] Update to the bleeding-edge development version ([italic]main[/italic])
-[3] Manually enter the tag or branch name you wish to update"""
+[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
+[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to'''        
 
     console.rule()
     print(
@@ -59,33 +60,41 @@ def welcome(versions: dict):
     )
     console.line()
 
-
 def main():
     versions = get_versions()
     welcome(versions)
 
     tag = None
-    choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
+    branch = None
+    release = None
+    choice = Prompt.ask('Choice:',choices=['1','2','3','4'],default='1')
+    
+    if choice=='1':
+        release = versions[0]['tag_name']
+    elif choice=='2':
+        release = 'main'
+    elif choice=='3':
+        tag = Prompt.ask('Enter an InvokeAI tag name')
+    elif choice=='4':
+        branch = Prompt.ask('Enter an InvokeAI branch name')
 
-    if choice == "1":
-        tag = versions[0]["tag_name"]
-    elif choice == "2":
-        tag = "main"
-    elif choice == "3":
-        tag = Prompt.ask("Enter an InvokeAI tag or branch name")
-
-    print(f":crossed_fingers: Upgrading to [yellow]{tag}[/yellow]")
-    cmd = f"pip install {INVOKE_AI_SRC}/{tag}.zip --use-pep517"
-    print("")
-    print("")
-    if os.system(cmd) == 0:
-        print(f":heavy_check_mark: Upgrade successful")
+    print(f':crossed_fingers: Upgrading to [yellow]{tag if tag else release}[/yellow]')
+    if release:
+        cmd = f'pip install {INVOKE_AI_SRC}/{release}.zip --use-pep517 --upgrade'
+    elif tag:
+        cmd = f'pip install {INVOKE_AI_TAG}/{tag}.zip --use-pep517 --upgrade'
     else:
-        print(f":exclamation: [bold red]Upgrade failed[/red bold]")
-
-
+        cmd = f'pip install {INVOKE_AI_BRANCH}/{branch}.zip --use-pep517 --upgrade'
+    print('')
+    print('')
+    if os.system(cmd)==0:
+        print(f':heavy_check_mark: Upgrade successful')
+    else:
+        print(f':exclamation: [bold red]Upgrade failed[/red bold]')
+    
 if __name__ == "__main__":
     try:
         main()
     except KeyboardInterrupt:
         pass
+

invokeai/frontend/web/.eslintignore

@@ -6,3 +6,5 @@ stats.html
 index.html
 .yarn/
 *.scss
+src/services/api/
+src/services/fixtures/*

invokeai/frontend/web/.prettierignore

@@ -3,4 +3,8 @@ dist/
 node_modules/
 patches/
 stats.html
+index.html
 .yarn/
+*.scss
+src/services/api/
+src/services/fixtures/*

invokeai/frontend/web/config/vite.app.config.ts

@@ -0,0 +1,40 @@
+import react from '@vitejs/plugin-react-swc';
+import { visualizer } from 'rollup-plugin-visualizer';
+import { PluginOption, UserConfig } from 'vite';
+import eslint from 'vite-plugin-eslint';
+import tsconfigPaths from 'vite-tsconfig-paths';
+
+export const appConfig: UserConfig = {
+  base: './',
+  plugins: [
+    react(),
+    eslint(),
+    tsconfigPaths(),
+    visualizer() as unknown as PluginOption,
+  ],
+  build: {
+    chunkSizeWarningLimit: 1500,
+  },
+  server: {
+    // Proxy HTTP requests to the flask server
+    proxy: {
+      // Proxy socket.io to the nodes socketio server
+      '/ws/socket.io': {
+        target: 'ws://127.0.0.1:9090',
+        ws: true,
+      },
+      // Proxy openapi schema definiton
+      '/openapi.json': {
+        target: 'http://127.0.0.1:9090/openapi.json',
+        rewrite: (path) => path.replace(/^\/openapi.json/, ''),
+        changeOrigin: true,
+      },
+      // proxy nodes api
+      '/api/v1': {
+        target: 'http://127.0.0.1:9090/api/v1',
+        rewrite: (path) => path.replace(/^\/api\/v1/, ''),
+        changeOrigin: true,
+      },
+    },
+  },
+};

invokeai/frontend/web/config/vite.package.config.ts

@@ -0,0 +1,47 @@
+import react from '@vitejs/plugin-react-swc';
+import path from 'path';
+import { visualizer } from 'rollup-plugin-visualizer';
+import { PluginOption, UserConfig } from 'vite';
+import dts from 'vite-plugin-dts';
+import eslint from 'vite-plugin-eslint';
+import tsconfigPaths from 'vite-tsconfig-paths';
+
+export const packageConfig: UserConfig = {
+  base: './',
+  plugins: [
+    react(),
+    eslint(),
+    tsconfigPaths(),
+    visualizer() as unknown as PluginOption,
+    dts({
+      insertTypesEntry: true,
+    }),
+  ],
+  build: {
+    chunkSizeWarningLimit: 1500,
+    lib: {
+      entry: path.resolve(__dirname, '../src/index.ts'),
+      name: 'InvokeAIUI',
+      fileName: (format) => `invoke-ai-ui.${format}.js`,
+    },
+    rollupOptions: {
+      external: ['react', 'react-dom', '@emotion/react'],
+      output: {
+        globals: {
+          react: 'React',
+          'react-dom': 'ReactDOM',
+        },
+      },
+    },
+  },
+  resolve: {
+    alias: {
+      app: path.resolve(__dirname, '../src/app'),
+      assets: path.resolve(__dirname, '../src/assets'),
+      common: path.resolve(__dirname, '../src/common'),
+      features: path.resolve(__dirname, '../src/features'),
+      services: path.resolve(__dirname, '../src/services'),
+      theme: path.resolve(__dirname, '../src/theme'),
+    },
+  },
+};

invokeai/frontend/web/docs/API_CLIENT.md

@@ -0,0 +1,87 @@
+# Generated axios API client
+
+- [Generated axios API client](#generated-axios-api-client)
+  - [Generation](#generation)
+    - [Generate the API client from the nodes web server](#generate-the-api-client-from-the-nodes-web-server)
+    - [Generate the API client from JSON](#generate-the-api-client-from-json)
+      - [Getting the JSON from the nodes web server](#getting-the-json-from-the-nodes-web-server)
+      - [Getting the JSON with a python script](#getting-the-json-with-a-python-script)
+      - [Generate the API client](#generate-the-api-client)
+  - [The generated client](#the-generated-client)
+  - [API client customisation](#api-client-customisation)
+
+This API client is generated by an [openapi code generator](https://github.com/ferdikoomen/openapi-typescript-codegen).
+
+All files in `invokeai/frontend/web/src/services/api/` are made by the generator.
+
+## Generation
+
+The axios client may be generated by from the OpenAPI schema from the nodes web server, or from JSON.
+
+### Generate the API client from the nodes web server
+
+We need to start the nodes web server, which serves the OpenAPI schema to the generator.
+
+1. Start the nodes web server.
+
+```bash
+# from the repo root
+python scripts/invoke-new.py --web
+```
+
+2. Generate the API client.
+
+```bash
+# from invokeai/frontend/web/
+yarn api:web
+```
+
+### Generate the API client from JSON
+
+The JSON can be acquired from the nodes web server, or with a python script.
+
+#### Getting the JSON from the nodes web server
+
+Start the nodes web server as described above, then download the file.
+
+```bash
+# from invokeai/frontend/web/
+curl http://localhost:9090/openapi.json -o openapi.json
+```
+
+#### Getting the JSON with a python script
+
+Run this python script from the repo root, so it can access the nodes server modules.
+
+The script will output `openapi.json` in the repo root. Then we need to move it to `invokeai/frontend/web/`.
+
+```bash
+# from the repo root
+python invokeai/app/util/generate_openapi_json.py
+mv invokeai/app/util/openapi.json invokeai/frontend/web/services/fixtures/
+```
+
+#### Generate the API client
+
+Now we can generate the API client from the JSON.
+
+```bash
+# from invokeai/frontend/web/
+yarn api:file
+```
+
+## The generated client
+
+The client will be written to `invokeai/frontend/web/services/api/`:
+
+- `axios` client
+- TS types
+- An easily parseable schema, which we can use to generate UI
+
+## API client customisation
+
+The generator has a default `request.ts` file that implements a base `axios` client. The generated client uses this base client.
+
+One shortcoming of this is base client is it does not provide response headers unless the response body is empty. To fix this, we provide our own lightly-patched `request.ts`.
+
+To access the headers, call `getHeaders(response)` on any response from the generated api client. This function is exported from `invokeai/frontend/web/src/services/util/getHeaders.ts`.

invokeai/frontend/web/docs/EVENTS.md

@@ -0,0 +1,21 @@
+# Events
+
+Events via `socket.io`
+
+## `actions.ts`
+
+Redux actions for all socket events. Payloads all include a timestamp, and optionally some other data.
+
+Any reducer (or middleware) can respond to the actions.
+
+## `middleware.ts`
+
+Redux middleware for events.
+
+Handles dispatching the event actions. Only put logic here if it can't really go anywhere else.
+
+For example, on connect we want to load images to the gallery if it's not populated. This requires dispatching a thunk, so we need to directly dispatch this in the middleware.
+
+## `types.ts`
+
+Hand-written types for the socket events. Cannot generate these from the server, but fortunately they are few and simple.

invokeai/frontend/web/docs/NODE_EDITOR.md

@@ -0,0 +1,17 @@
+# Node Editor Design
+
+WIP
+
+nodes
+
+everything in `src/features/nodes/`
+
+have a look at `state.nodes.invocation`
+
+- on socket connect, if no schema saved, fetch `localhost:9090/openapi.json`, save JSON to `state.nodes.schema`
+- on fulfilled schema fetch, `parseSchema()` the schema. this outputs a `Record<string, Invocation>` which is saved to `state.nodes.invocations` - `Invocation` is like a template for the node
+- when you add a node, the the `Invocation` template is passed to `InvocationComponent.tsx` to build the UI component for that node
+- inputs/outputs have field types - and each field type gets an `FieldComponent` which includes a dispatcher to write state changes to redux `nodesSlice`
+- `reactflow` sends changes to nodes/edges to redux
+- to invoke, `buildNodesGraph()` state, then send this
+- changed onClick Invoke button actions to build the schema, then when schema builds it dispatches the actual network request to create the session - see `session.ts`

invokeai/frontend/web/docs/PACKAGE_SCRIPTS.md

@@ -0,0 +1,29 @@
+# Package Scripts
+
+WIP walkthrough of `package.json` scripts.
+
+## `theme` & `theme:watch`
+
+These run the Chakra CLI to generate types for the theme, or watch for code change and re-generate the types.
+
+The CLI essentially monkeypatches Chakra's files in `node_modules`.
+
+## `postinstall`
+
+The `postinstall` script patches a few packages and runs the Chakra CLI to generate types for the theme.
+
+### Patch `@chakra-ui/cli`
+
+See: <https://github.com/chakra-ui/chakra-ui/issues/7394>
+
+### Patch `redux-persist`
+
+We want to persist the canvas state to `localStorage` but many canvas operations change data very quickly, so we need to debounce the writes to `localStorage`.
+
+`redux-persist` is unfortunately unmaintained. The repo's current code is nonfunctional, but the last release's code depends on a package that was removed from `npm` for being malware, so we cannot just fork it.
+
+So, we have to patch it directly. Perhaps a better way would be to write a debounced storage adapter, but I couldn't figure out how to do that.
+
+### Patch `redux-deep-persist`
+
+This package makes blacklisting and whitelisting persist configs very simple, but we have to patch it to match `redux-persist` for the types to work.

invokeai/frontend/web/docs/README.md

@@ -1,10 +1,16 @@
 # InvokeAI Web UI
 
+- [InvokeAI Web UI](#invokeai-web-ui)
+  - [Stack](#stack)
+  - [Contributing](#contributing)
+    - [Dev Environment](#dev-environment)
+    - [Production builds](#production-builds)
+
 The UI is a fairly straightforward Typescript React app. The only really fancy stuff is the Unified Canvas.
 
 Code in `invokeai/frontend/web/` if you want to have a look.
 
-## Details
+## Stack
 
 State management is Redux via [Redux Toolkit](https://github.com/reduxjs/redux-toolkit). Communication with server is a mix of HTTP and [socket.io](https://github.com/socketio/socket.io-client) (with a custom redux middleware to help).
 
@@ -32,7 +38,7 @@ Start everything in dev mode:
 
 1. Start the dev server: `yarn dev`
 2. Start the InvokeAI UI per usual: `invokeai --web`
-3. Point your browser to the dev server address e.g. `http://localhost:5173/`
+3. Point your browser to the dev server address e.g. <http://localhost:5173/>
 
 ### Production builds
 

invokeai/frontend/web/index.d.ts

@@ -1,78 +0,0 @@
-import React, { PropsWithChildren } from 'react';
-import { IAIPopoverProps } from '../web/src/common/components/IAIPopover';
-import { IAIIconButtonProps } from '../web/src/common/components/IAIIconButton';
-
-export {};
-
-declare module 'redux-socket.io-middleware';
-
-declare global {
-  /* eslint-disable @typescript-eslint/no-explicit-any */
-  interface Array<T> {
-    /**
-     * Returns the value of the last element in the array where predicate is true, and undefined
-     * otherwise.
-     * @param predicate findLast calls predicate once for each element of the array, in descending
-     * order, until it finds one where predicate returns true. If such an element is found, findLast
-     * immediately returns that element value. Otherwise, findLast returns undefined.
-     * @param thisArg If provided, it will be used as the this value for each invocation of
-     * predicate. If it is not provided, undefined is used instead.
-     */
-    findLast<S extends T>(
-      predicate: (value: T, index: number, array: T[]) => value is S,
-      thisArg?: any
-    ): S | undefined;
-    findLast(
-      predicate: (value: T, index: number, array: T[]) => unknown,
-      thisArg?: any
-    ): T | undefined;
-
-    /**
-     * Returns the index of the last element in the array where predicate is true, and -1
-     * otherwise.
-     * @param predicate findLastIndex calls predicate once for each element of the array, in descending
-     * order, until it finds one where predicate returns true. If such an element is found,
-     * findLastIndex immediately returns that element index. Otherwise, findLastIndex returns -1.
-     * @param thisArg If provided, it will be used as the this value for each invocation of
-     * predicate. If it is not provided, undefined is used instead.
-     */
-    findLastIndex(
-      predicate: (value: T, index: number, array: T[]) => unknown,
-      thisArg?: any
-    ): number;
-  }
-  /* eslint-enable @typescript-eslint/no-explicit-any */
-}
-
-declare module '@invoke-ai/invoke-ai-ui' {
-  declare class ThemeChanger extends React.Component<ThemeChangerProps> {
-    public constructor(props: ThemeChangerProps);
-  }
-
-  declare class InvokeAiLogoComponent extends React.Component<InvokeAILogoComponentProps> {
-    public constructor(props: InvokeAILogoComponentProps);
-  }
-
-  declare class IAIPopover extends React.Component<IAIPopoverProps> {
-    public constructor(props: IAIPopoverProps);
-  }
-
-  declare class IAIIconButton extends React.Component<IAIIconButtonProps> {
-    public constructor(props: IAIIconButtonProps);
-  }
-
-  declare class SettingsModal extends React.Component<SettingsModalProps> {
-    public constructor(props: SettingsModalProps);
-  }
-}
-
-declare function Invoke(props: PropsWithChildren): JSX.Element;
-
-export {
-  ThemeChanger,
-  InvokeAiLogoComponent,
-  IAIPopover,
-  IAIIconButton,
-  SettingsModal,
-};
-export = Invoke;

invokeai/frontend/web/package.json

@@ -1,11 +1,31 @@
 {
-  "name": "invoke-ai-ui",
+  "name": "@invoke-ai/invoke-ai-ui",
   "private": true,
   "version": "0.0.1",
+  "publishConfig": {
+    "access": "restricted",
+    "registry": "https://npm.pkg.github.com"
+  },
+  "main": "./dist/invoke-ai-ui.umd.js",
+  "module": "./dist/invoke-ai-ui.es.js",
+  "exports": {
+    ".": {
+      "import": "./dist/invoke-ai-ui.es.js",
+      "require": "./dist/invoke-ai-ui.umd.js"
+    }
+  },
+  "types": "./dist/index.d.ts",
+  "files": [
+    "dist"
+  ],
   "scripts": {
     "prepare": "cd ../../../ && husky install invokeai/frontend/web/.husky",
     "dev": "concurrently \"vite dev\" \"yarn run theme:watch\"",
+    "dev:nodes": "concurrently \"vite dev --mode nodes\" \"yarn run theme:watch\"",
+    "dev:host": "concurrently \"vite dev --host\" \"yarn run theme:watch\"",
     "build": "yarn run lint && vite build",
+    "api:web": "openapi -i http://localhost:9090/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
+    "api:file": "openapi -i src/services/fixtures/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
     "preview": "vite preview",
     "lint:madge": "madge --circular src/main.tsx",
     "lint:eslint": "eslint --max-warnings=0 .",
@@ -36,70 +56,93 @@
   },
   "dependencies": {
     "@chakra-ui/anatomy": "^2.1.1",
-    "@chakra-ui/cli": "^2.3.0",
-    "@chakra-ui/icons": "^2.0.17",
-    "@chakra-ui/react": "^2.5.1",
-    "@chakra-ui/styled-system": "^2.6.1",
+    "@chakra-ui/icons": "^2.0.19",
+    "@chakra-ui/react": "^2.6.0",
+    "@chakra-ui/styled-system": "^2.9.0",
     "@chakra-ui/theme-tools": "^2.0.16",
+    "@dagrejs/graphlib": "^2.1.12",
     "@emotion/react": "^11.10.6",
     "@emotion/styled": "^11.10.6",
-    "@reduxjs/toolkit": "^1.9.2",
+    "@fontsource/inter": "^4.5.15",
+    "@reduxjs/toolkit": "^1.9.5",
+    "@roarr/browser-log-writer": "^1.1.5",
     "chakra-ui-contextmenu": "^1.0.5",
     "dateformat": "^5.0.3",
     "formik": "^2.2.9",
-    "framer-motion": "^9.0.4",
-    "i18next": "^22.4.10",
+    "framer-motion": "^10.12.4",
+    "fuse.js": "^6.6.2",
+    "i18next": "^22.4.15",
     "i18next-browser-languagedetector": "^7.0.1",
-    "i18next-http-backend": "^2.1.1",
-    "konva": "^8.4.2",
-    "lodash": "^4.17.21",
-    "patch-package": "^6.5.1",
+    "i18next-http-backend": "^2.2.0",
+    "konva": "^9.0.1",
+    "lodash-es": "^4.17.21",
+    "patch-package": "^7.0.0",
     "re-resizable": "^6.9.9",
     "react": "^18.2.0",
     "react-colorful": "^5.6.1",
     "react-dom": "^18.2.0",
     "react-dropzone": "^14.2.3",
-    "react-hotkeys-hook": "4.3.5",
-    "react-i18next": "^12.1.5",
+    "react-hotkeys-hook": "4.4.0",
+    "react-i18next": "^12.2.2",
     "react-icons": "^4.7.1",
-    "react-konva": "^18.2.4",
-    "react-konva-utils": "^0.3.2",
+    "react-konva": "^18.2.7",
+    "react-konva-utils": "^1.0.4",
     "react-redux": "^8.0.5",
+    "react-rnd": "^10.4.1",
     "react-transition-group": "^4.4.5",
-    "react-zoom-pan-pinch": "^2.6.1",
+    "react-use": "^17.4.0",
+    "react-zoom-pan-pinch": "^3.0.7",
+    "reactflow": "^11.7.0",
     "redux-deep-persist": "^1.0.7",
+    "redux-dynamic-middlewares": "^2.2.0",
     "redux-persist": "^6.0.0",
+    "roarr": "^7.15.0",
+    "serialize-error": "^11.0.0",
     "socket.io-client": "^4.6.0",
     "use-image": "^1.1.0",
     "uuid": "^9.0.0"
   },
+  "peerDependencies": {
+    "@chakra-ui/cli": "^2.4.0",
+    "react": "^18.2.0",
+    "react-dom": "^18.2.0",
+    "ts-toolbelt": "^9.6.0"
+  },
   "devDependencies": {
-    "@fontsource/inter": "^4.5.15",
+    "@chakra-ui/cli": "^2.4.0",
     "@types/dateformat": "^5.0.0",
-    "@types/react": "^18.0.28",
-    "@types/react-dom": "^18.0.11",
+    "@types/lodash-es": "^4.14.194",
+    "@types/node": "^18.16.2",
+    "@types/react": "^18.2.0",
+    "@types/react-dom": "^18.2.1",
     "@types/react-transition-group": "^4.4.5",
     "@types/uuid": "^9.0.0",
-    "@typescript-eslint/eslint-plugin": "^5.52.0",
-    "@typescript-eslint/parser": "^5.52.0",
-    "@vitejs/plugin-react-swc": "^3.2.0",
+    "@typescript-eslint/eslint-plugin": "^5.59.1",
+    "@typescript-eslint/parser": "^5.59.1",
+    "@vitejs/plugin-react-swc": "^3.3.0",
+    "axios": "^1.4.0",
     "babel-plugin-transform-imports": "^2.0.0",
-    "concurrently": "^7.6.0",
-    "eslint": "^8.34.0",
-    "eslint-config-prettier": "^8.6.0",
+    "concurrently": "^8.0.1",
+    "eslint": "^8.39.0",
+    "eslint-config-prettier": "^8.8.0",
     "eslint-plugin-prettier": "^4.2.1",
     "eslint-plugin-react": "^7.32.2",
     "eslint-plugin-react-hooks": "^4.6.0",
+    "form-data": "^4.0.0",
     "husky": "^8.0.3",
-    "lint-staged": "^13.1.2",
+    "lint-staged": "^13.2.2",
     "madge": "^6.0.0",
+    "openapi-types": "^12.1.0",
+    "openapi-typescript-codegen": "^0.24.0",
     "postinstall-postinstall": "^2.1.0",
-    "prettier": "^2.8.4",
+    "prettier": "^2.8.8",
     "rollup-plugin-visualizer": "^5.9.0",
-    "terser": "^5.16.4",
-    "vite": "^4.1.2",
+    "terser": "^5.17.1",
+    "ts-toolbelt": "^9.6.0",
+    "vite": "^4.3.3",
+    "vite-plugin-dts": "^2.3.0",
     "vite-plugin-eslint": "^1.8.1",
-    "vite-tsconfig-paths": "^4.0.5",
+    "vite-tsconfig-paths": "^4.2.0",
     "yarn": "^1.22.19"
   }
 }

invokeai/frontend/web/public/locales/de.json

@@ -18,7 +18,7 @@
         "training": "Training",
         "trainingDesc1": "Ein spezieller Arbeitsablauf zum Trainieren Ihrer eigenen Embeddings und Checkpoints mit Textual Inversion und Dreambooth über die Weboberfläche.",
         "trainingDesc2": "InvokeAI unterstützt bereits das Training von benutzerdefinierten Embeddings mit Textual Inversion unter Verwendung des Hauptskripts.",
-        "upload": "Upload",
+        "upload": "Hochladen",
         "close": "Schließen",
         "load": "Laden",
         "statusConnected": "Verbunden",
@@ -41,12 +41,34 @@
         "statusUpscaling": "Hochskalierung",
         "statusUpscalingESRGAN": "Hochskalierung (ESRGAN)",
         "statusLoadingModel": "Laden des Modells",
-        "statusModelChanged": "Modell Geändert"
+        "statusModelChanged": "Modell Geändert",
+        "cancel": "Abbruch",
+        "accept": "Annehmen",
+        "back": "Zurück",
+        "langEnglish": "Englisch",
+        "langDutch": "Niederländisch",
+        "langFrench": "Französisch",
+        "oceanTheme": "Ozean",
+        "langItalian": "Italienisch",
+        "langPortuguese": "Portogisisch",
+        "langRussian": "Russisch",
+        "langUkranian": "Ukrainisch",
+        "hotkeysLabel": "Tastenkombinationen",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "txt2img": "Text zu Bild",
+        "postprocessing": "Nachbearbeitung",
+        "langPolish": "Polnisch",
+        "langJapanese": "Japanisch",
+        "langArabic": "Arabisch",
+        "langKorean": "Koreanisch",
+        "langHebrew": "Hebräisch",
+        "langSpanish": "Spanisch"
     },
     "gallery": {
         "generations": "Erzeugungen",
         "showGenerations": "Zeige Erzeugnisse",
-        "uploads": "Uploads",
+        "uploads": "Hochgelades",
         "showUploads": "Zeige Uploads",
         "galleryImageSize": "Bildgröße",
         "galleryImageResetSize": "Größe zurücksetzen",
@@ -312,7 +334,11 @@
         "deleteModel": "Model löschen",
         "deleteConfig": "Konfiguration löschen",
         "deleteMsg1": "Möchten Sie diesen Model-Eintrag wirklich aus InvokeAI löschen?",
-        "deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen."
+        "deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen.",
+        "customConfig": "Benutzerdefinierte Konfiguration",
+        "invokeRoot": "InvokeAI Ordner",
+        "formMessageDiffusersVAELocationDesc": "Falls nicht angegeben, sucht InvokeAI nach der VAE-Datei innerhalb des oben angegebenen Modell Speicherortes.",
+        "checkpointModels": "Kontrollpunkte"
     },
     "parameters": {
         "images": "Bilder",
@@ -370,7 +396,10 @@
         "useInitImg": "Ausgangsbild verwenden",
         "deleteImage": "Bild löschen",
         "initialImage": "Ursprüngliches Bild",
-        "showOptionsPanel": "Optionsleiste zeigen"
+        "showOptionsPanel": "Optionsleiste zeigen",
+        "cancel": {
+            "setType": "Abbruchart festlegen"
+        }
     },
     "settings": {
         "displayInProgress": "Bilder in Bearbeitung anzeigen",
@@ -489,5 +518,25 @@
         "betaDarkenOutside": "Außen abdunkeln",
         "betaLimitToBox": "Begrenzung auf das Feld",
         "betaPreserveMasked": "Maskiertes bewahren"
+    },
+    "accessibility": {
+        "modelSelect": "Model Auswahl",
+        "uploadImage": "Bild hochladen",
+        "previousImage": "Voriges Bild",
+        "useThisParameter": "Benutze diesen Parameter",
+        "copyMetadataJson": "Kopiere metadata JSON",
+        "zoomIn": "Vergrößern",
+        "rotateClockwise": "Im Uhrzeigersinn drehen",
+        "flipHorizontally": "Horizontal drehen",
+        "flipVertically": "Vertikal drehen",
+        "modifyConfig": "Optionen einstellen",
+        "toggleAutoscroll": "Auroscroll ein/ausschalten",
+        "toggleLogViewer": "Log Betrachter ein/ausschalten",
+        "showGallery": "Zeige Galerie",
+        "showOptionsPanel": "Zeige Optionen",
+        "reset": "Zurücksetzen",
+        "nextImage": "Nächstes Bild",
+        "zoomOut": "Verkleinern",
+        "rotateCounterClockwise": "Gegen den Uhrzeigersinn verdrehen"
     }
 }

invokeai/frontend/web/public/locales/en.json

@@ -8,7 +8,7 @@
         "nextImage": "Next Image",
         "useThisParameter": "Use this parameter",
         "copyMetadataJson": "Copy metadata JSON",
-        "exitViewer": "ExitViewer",
+        "exitViewer": "Exit Viewer",
         "zoomIn": "Zoom In",
         "zoomOut": "Zoom Out",
         "rotateCounterClockwise": "Rotate Counter-Clockwise",
@@ -19,7 +19,8 @@
         "toggleAutoscroll": "Toggle autoscroll",
         "toggleLogViewer": "Toggle Log Viewer",
         "showGallery": "Show Gallery",
-        "showOptionsPanel": "Show Options Panel"
+        "showOptionsPanel": "Show Options Panel",
+        "menu": "Menu"
     },
     "common": {
         "hotkeysLabel": "Hotkeys",
@@ -52,6 +53,7 @@
         "txt2img": "Text To Image",
         "img2img": "Image To Image",
         "unifiedCanvas": "Unified Canvas",
+        "linear": "Linear",
         "nodes": "Nodes",
         "postprocessing": "Post Processing",
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
@@ -61,7 +63,7 @@
         "postProcessDesc3": "The Invoke AI Command Line Interface offers various other features including Embiggen.",
         "training": "Training",
         "trainingDesc1": "A dedicated workflow for training your own embeddings and checkpoints using Textual Inversion and Dreambooth from the web interface.",
-        "trainingDesc2": "InvokeAI already supports training custom embeddings using Textual Inversion using the main script.",
+        "trainingDesc2": "InvokeAI already supports training custom embeddourings using Textual Inversion using the main script.",
         "upload": "Upload",
         "close": "Close",
         "cancel": "Cancel",
@@ -95,7 +97,12 @@
         "statusMergedModels": "Models Merged",
         "pinOptionsPanel": "Pin Options Panel",
         "loading": "Loading",
-        "loadingInvokeAI": "Loading Invoke AI"
+        "loadingInvokeAI": "Loading Invoke AI",
+        "random": "Random",
+        "generate": "Generate",
+        "openInNewTab": "Open in New Tab",
+        "dontAskMeAgain": "Don't ask me again",
+        "areYouSure": "Are you sure?"
     },
     "gallery": {
         "generations": "Generations",
@@ -111,7 +118,10 @@
         "pinGallery": "Pin Gallery",
         "allImagesLoaded": "All Images Loaded",
         "loadMore": "Load More",
-        "noImagesInGallery": "No Images In Gallery"
+        "noImagesInGallery": "No Images In Gallery",
+        "deleteImage": "Delete Image",
+        "deleteImageBin": "Deleted images will be sent to your operating system's Bin.",
+        "deleteImagePermanent": "Deleted images cannot be restored."
     },
     "hotkeys": {
         "keyboardShortcuts": "Keyboard Shortcuts",
@@ -503,7 +513,6 @@
         "useAll": "Use All",
         "useInitImg": "Use Initial Image",
         "info": "Info",
-        "deleteImage": "Delete Image",
         "initialImage": "Initial Image",
         "showOptionsPanel": "Show Options Panel",
         "hidePreview": "Hide Preview",
@@ -518,12 +527,21 @@
         "useCanvasBeta": "Use Canvas Beta Layout",
         "enableImageDebugging": "Enable Image Debugging",
         "useSlidersForAll": "Use Sliders For All Options",
+        "autoShowProgress": "Auto Show Progress Images",
         "resetWebUI": "Reset Web UI",
         "resetWebUIDesc1": "Resetting the web UI only resets the browser's local cache of your images and remembered settings. It does not delete any images from disk.",
         "resetWebUIDesc2": "If images aren't showing up in the gallery or something else isn't working, please try resetting before submitting an issue on GitHub.",
-        "resetComplete": "Web UI has been reset. Refresh the page to reload."
+        "resetComplete": "Web UI has been reset. Refresh the page to reload.",
+        "consoleLogLevel": "Log Level",
+        "shouldLogToConsole": "Console Logging",
+        "developer": "Developer",
+        "general": "General"
     },
     "toast": {
+        "serverError": "Server Error",
+        "disconnected": "Disconnected from Server",
+        "connected": "Connected to Server",
+        "canceled": "Processing Canceled",
         "tempFoldersEmptied": "Temp Folder Emptied",
         "uploadFailed": "Upload failed",
         "uploadFailedMultipleImagesDesc": "Multiple images pasted, may only upload one image at a time",
@@ -628,5 +646,9 @@
         "betaDarkenOutside": "Darken Outside",
         "betaLimitToBox": "Limit To Box",
         "betaPreserveMasked": "Preserve Masked"
+    },
+    "ui": {
+        "showProgressImages": "Show Progress Images",
+        "hideProgressImages": "Hide Progress Images"
     }
 }

invokeai/frontend/web/public/locales/es.json

@@ -73,7 +73,8 @@
         "postprocessing": "Tratamiento posterior",
         "txt2img": "De texto a imagen",
         "accept": "Aceptar",
-        "cancel": "Cancelar"
+        "cancel": "Cancelar",
+        "linear": "Lineal"
     },
     "gallery": {
         "generations": "Generaciones",
@@ -483,7 +484,9 @@
         "negativePrompts": "Preguntas negativas",
         "imageToImage": "Imagen a imagen",
         "denoisingStrength": "Intensidad de la eliminación del ruido",
-        "hiresStrength": "Alta resistencia"
+        "hiresStrength": "Alta resistencia",
+        "showPreview": "Mostrar la vista previa",
+        "hidePreview": "Ocultar la vista previa"
     },
     "settings": {
         "models": "Modelos",
@@ -529,7 +532,11 @@
         "metadataLoadFailed": "Error al cargar metadatos",
         "initialImageSet": "Imágen inicial establecida",
         "initialImageNotSet": "Imagen inicial no establecida",
-        "initialImageNotSetDesc": "Error al establecer la imágen inicial"
+        "initialImageNotSetDesc": "Error al establecer la imágen inicial",
+        "serverError": "Error en el servidor",
+        "disconnected": "Desconectado del servidor",
+        "canceled": "Procesando la cancelación",
+        "connected": "Conectado al servidor"
     },
     "tooltip": {
         "feature": {
@@ -625,6 +632,7 @@
         "toggleAutoscroll": "Activar el autodesplazamiento",
         "toggleLogViewer": "Alternar el visor de registros",
         "showGallery": "Mostrar galería",
-        "showOptionsPanel": "Mostrar el panel de opciones"
+        "showOptionsPanel": "Mostrar el panel de opciones",
+        "menu": "Menú"
     }
 }

invokeai/frontend/web/public/locales/fi.json

@@ -0,0 +1,122 @@
+{
+    "accessibility": {
+        "reset": "Resetoi",
+        "useThisParameter": "Käytä tätä parametria",
+        "modelSelect": "Mallin Valinta",
+        "exitViewer": "Poistu katselimesta",
+        "uploadImage": "Lataa kuva",
+        "copyMetadataJson": "Kopioi metadata JSON:iin",
+        "invokeProgressBar": "Invoken edistymispalkki",
+        "nextImage": "Seuraava kuva",
+        "previousImage": "Edellinen kuva",
+        "zoomIn": "Lähennä",
+        "flipHorizontally": "Käännä vaakasuoraan",
+        "zoomOut": "Loitonna",
+        "rotateCounterClockwise": "Kierrä vastapäivään",
+        "rotateClockwise": "Kierrä myötäpäivään",
+        "flipVertically": "Käännä pystysuoraan",
+        "showGallery": "Näytä galleria",
+        "modifyConfig": "Muokkaa konfiguraatiota",
+        "toggleAutoscroll": "Kytke automaattinen vieritys",
+        "toggleLogViewer": "Kytke lokin katselutila",
+        "showOptionsPanel": "Näytä asetukset"
+    },
+    "common": {
+        "postProcessDesc2": "Erillinen käyttöliittymä tullaan julkaisemaan helpottaaksemme työnkulkua jälkikäsittelyssä.",
+        "training": "Kouluta",
+        "statusLoadingModel": "Ladataan mallia",
+        "statusModelChanged": "Malli vaihdettu",
+        "statusConvertingModel": "Muunnetaan mallia",
+        "statusModelConverted": "Malli muunnettu",
+        "langFrench": "Ranska",
+        "langItalian": "Italia",
+        "languagePickerLabel": "Kielen valinta",
+        "hotkeysLabel": "Pikanäppäimet",
+        "reportBugLabel": "Raportoi Bugista",
+        "langPolish": "Puola",
+        "themeLabel": "Teema",
+        "langDutch": "Hollanti",
+        "settingsLabel": "Asetukset",
+        "githubLabel": "Github",
+        "darkTheme": "Tumma",
+        "lightTheme": "Vaalea",
+        "greenTheme": "Vihreä",
+        "langGerman": "Saksa",
+        "langPortuguese": "Portugali",
+        "discordLabel": "Discord",
+        "langEnglish": "Englanti",
+        "oceanTheme": "Meren sininen",
+        "langRussian": "Venäjä",
+        "langUkranian": "Ukraina",
+        "langSpanish": "Espanja",
+        "upload": "Lataa",
+        "statusMergedModels": "Mallit yhdistelty",
+        "img2img": "Kuva kuvaksi",
+        "nodes": "Solmut",
+        "nodesDesc": "Solmupohjainen järjestelmä kuvien generoimiseen on parhaillaan kehitteillä. Pysy kuulolla päivityksistä tähän uskomattomaan ominaisuuteen liittyen.",
+        "postProcessDesc1": "Invoke AI tarjoaa monenlaisia jälkikäsittelyominaisuukisa. Kuvan laadun skaalaus sekä kasvojen korjaus ovat jo saatavilla WebUI:ssä. Voit ottaa ne käyttöön lisäasetusten valikosta teksti kuvaksi sekä kuva kuvaksi -välilehdiltä. Voit myös suoraan prosessoida kuvia käyttämällä kuvan toimintapainikkeita nykyisen kuvan yläpuolella tai tarkastelussa.",
+        "postprocessing": "Jälkikäsitellään",
+        "postProcessing": "Jälkikäsitellään",
+        "cancel": "Peruuta",
+        "close": "Sulje",
+        "accept": "Hyväksy",
+        "statusConnected": "Yhdistetty",
+        "statusError": "Virhe",
+        "statusProcessingComplete": "Prosessointi valmis",
+        "load": "Lataa",
+        "back": "Takaisin",
+        "statusGeneratingTextToImage": "Generoidaan tekstiä kuvaksi",
+        "trainingDesc2": "InvokeAI tukee jo mukautettujen upotusten kouluttamista tekstin inversiolla käyttäen pääskriptiä.",
+        "statusDisconnected": "Yhteys katkaistu",
+        "statusPreparing": "Valmistellaan",
+        "statusIterationComplete": "Iteraatio valmis",
+        "statusMergingModels": "Yhdistellään malleja",
+        "statusProcessingCanceled": "Valmistelu peruutettu",
+        "statusSavingImage": "Tallennetaan kuvaa",
+        "statusGeneratingImageToImage": "Generoidaan kuvaa kuvaksi",
+        "statusRestoringFacesGFPGAN": "Korjataan kasvoja (GFPGAN)",
+        "statusRestoringFacesCodeFormer": "Korjataan kasvoja (CodeFormer)",
+        "statusGeneratingInpainting": "Generoidaan sisällemaalausta",
+        "statusGeneratingOutpainting": "Generoidaan ulosmaalausta",
+        "statusRestoringFaces": "Korjataan kasvoja",
+        "pinOptionsPanel": "Kiinnitä asetukset -paneeli",
+        "loadingInvokeAI": "Ladataan Invoke AI:ta",
+        "loading": "Ladataan",
+        "statusGenerating": "Generoidaan",
+        "txt2img": "Teksti kuvaksi",
+        "trainingDesc1": "Erillinen työnkulku omien upotusten ja tarkastuspisteiden kouluttamiseksi käyttäen tekstin inversiota ja dreamboothia selaimen käyttöliittymässä.",
+        "postProcessDesc3": "Invoke AI:n komentorivi tarjoaa paljon muita ominaisuuksia, kuten esimerkiksi Embiggenin.",
+        "unifiedCanvas": "Yhdistetty kanvas",
+        "statusGenerationComplete": "Generointi valmis"
+    },
+    "gallery": {
+        "uploads": "Lataukset",
+        "showUploads": "Näytä lataukset",
+        "galleryImageResetSize": "Resetoi koko",
+        "maintainAspectRatio": "Säilytä kuvasuhde",
+        "galleryImageSize": "Kuvan koko",
+        "pinGallery": "Kiinnitä galleria",
+        "showGenerations": "Näytä generaatiot",
+        "singleColumnLayout": "Yhden sarakkeen asettelu",
+        "generations": "Generoinnit",
+        "gallerySettings": "Gallerian asetukset",
+        "autoSwitchNewImages": "Vaihda uusiin kuviin automaattisesti",
+        "allImagesLoaded": "Kaikki kuvat ladattu",
+        "noImagesInGallery": "Ei kuvia galleriassa",
+        "loadMore": "Lataa lisää"
+    },
+    "hotkeys": {
+        "keyboardShortcuts": "näppäimistön pikavalinnat",
+        "appHotkeys": "Sovelluksen pikanäppäimet",
+        "generalHotkeys": "Yleiset pikanäppäimet",
+        "galleryHotkeys": "Gallerian pikanäppäimet",
+        "unifiedCanvasHotkeys": "Yhdistetyn kanvaan pikanäppäimet",
+        "cancel": {
+            "desc": "Peruuta kuvan luominen",
+            "title": "Peruuta"
+        },
+        "invoke": {
+            "desc": "Luo kuva"
+        }
+    }
+}

invokeai/frontend/web/public/locales/it.json

@@ -73,7 +73,8 @@
         "postprocessing": "Post Elaborazione",
         "txt2img": "Testo a Immagine",
         "accept": "Accetta",
-        "cancel": "Annulla"
+        "cancel": "Annulla",
+        "linear": "Lineare"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -483,7 +484,9 @@
         },
         "hSymmetryStep": "Passi Simmetria Orizzontale",
         "vSymmetryStep": "Passi Simmetria Verticale",
-        "symmetry": "Simmetria"
+        "symmetry": "Simmetria",
+        "hidePreview": "Nascondi l'anteprima",
+        "showPreview": "Mostra l'anteprima"
     },
     "settings": {
         "models": "Modelli",
@@ -529,7 +532,11 @@
         "metadataLoadFailed": "Impossibile caricare i metadati",
         "initialImageSet": "Immagine iniziale impostata",
         "initialImageNotSet": "Immagine iniziale non impostata",
-        "initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale"
+        "initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale",
+        "serverError": "Errore del Server",
+        "disconnected": "Disconnesso dal Server",
+        "connected": "Connesso al Server",
+        "canceled": "Elaborazione annullata"
     },
     "tooltip": {
         "feature": {
@@ -625,6 +632,7 @@
         "showOptionsPanel": "Mostra il pannello opzioni",
         "flipVertically": "Capovolgi verticalmente",
         "toggleAutoscroll": "Attiva/disattiva lo scorrimento automatico",
-        "modifyConfig": "Modifica configurazione"
+        "modifyConfig": "Modifica configurazione",
+        "menu": "Menu"
     }
 }

invokeai/frontend/web/public/locales/ja.json

@@ -37,7 +37,43 @@
         "statusUpscaling": "アップスケーリング",
         "statusUpscalingESRGAN": "アップスケーリング (ESRGAN)",
         "statusLoadingModel": "モデルを読み込む",
-        "statusModelChanged": "モデルを変更"
+        "statusModelChanged": "モデルを変更",
+        "cancel": "キャンセル",
+        "accept": "同意",
+        "langBrPortuguese": "Português do Brasil",
+        "langRussian": "Русский",
+        "langSimplifiedChinese": "简体中文",
+        "langUkranian": "Украї́нська",
+        "langSpanish": "Español",
+        "img2img": "img2img",
+        "unifiedCanvas": "Unified Canvas",
+        "statusMergingModels": "モデルのマージ",
+        "statusModelConverted": "変換済モデル",
+        "statusGeneratingInpainting": "Inpaintingを生成",
+        "statusIterationComplete": "Iteration Complete",
+        "statusGeneratingOutpainting": "Outpaintingを生成",
+        "loading": "ロード中",
+        "loadingInvokeAI": "Invoke AIをロード中",
+        "statusConvertingModel": "モデルの変換",
+        "statusMergedModels": "マージ済モデル",
+        "pinOptionsPanel": "オプションパネルを固定",
+        "githubLabel": "Github",
+        "hotkeysLabel": "ホットキー",
+        "langHebrew": "עברית",
+        "discordLabel": "Discord",
+        "langItalian": "Italiano",
+        "langEnglish": "English",
+        "oceanTheme": "オーシャン",
+        "langArabic": "アラビア語",
+        "langDutch": "Nederlands",
+        "langFrench": "Français",
+        "langGerman": "Deutsch",
+        "langPortuguese": "Português",
+        "nodes": "ノード",
+        "langKorean": "한국어",
+        "langPolish": "Polski",
+        "txt2img": "txt2img",
+        "postprocessing": "Post Processing"
     },
     "gallery": {
         "uploads": "アップロード",
@@ -46,11 +82,14 @@
         "galleryImageResetSize": "サイズをリセット",
         "gallerySettings": "ギャラリーの設定",
         "maintainAspectRatio": "アスペクト比を維持",
-        "singleColumnLayout": "シングルカラムレイアウト",
+        "singleColumnLayout": "1カラムレイアウト",
         "pinGallery": "ギャラリーにピン留め",
         "allImagesLoaded": "すべての画像を読み込む",
         "loadMore": "さらに読み込む",
-        "noImagesInGallery": "ギャラリーに画像がありません"
+        "noImagesInGallery": "ギャラリーに画像がありません",
+        "generations": "生成",
+        "showGenerations": "生成過程を見る",
+        "autoSwitchNewImages": "新しい画像に自動切替"
     },
     "hotkeys": {
         "keyboardShortcuts": "キーボードショートカット",
@@ -59,14 +98,16 @@
         "galleryHotkeys": "ギャラリーのホットキー",
         "unifiedCanvasHotkeys": "Unified Canvasのホットキー",
         "invoke": {
-            "desc": "画像を生成"
+            "desc": "画像を生成",
+            "title": "Invoke"
         },
         "cancel": {
             "title": "キャンセル",
             "desc": "画像の生成をキャンセル"
         },
         "focusPrompt": {
-            "desc": "プロンプトテキストボックスにフォーカス"
+            "desc": "プロンプトテキストボックスにフォーカス",
+            "title": "プロジェクトにフォーカス"
         },
         "toggleOptions": {
             "title": "オプションパネルのトグル",
@@ -410,5 +451,27 @@
         "accept": "同意",
         "showHide": "表示/非表示",
         "discardAll": "すべて破棄"
+    },
+    "accessibility": {
+        "modelSelect": "モデルを選択",
+        "invokeProgressBar": "進捗バー",
+        "reset": "リセット",
+        "uploadImage": "画像をアップロード",
+        "previousImage": "前の画像",
+        "nextImage": "次の画像",
+        "useThisParameter": "このパラメータを使用する",
+        "copyMetadataJson": "メタデータをコピー(JSON)",
+        "zoomIn": "ズームイン",
+        "exitViewer": "ExitViewer",
+        "zoomOut": "ズームアウト",
+        "rotateCounterClockwise": "反時計回りに回転",
+        "rotateClockwise": "時計回りに回転",
+        "flipHorizontally": "水平方向に反転",
+        "flipVertically": "垂直方向に反転",
+        "toggleAutoscroll": "自動スクロールの切替",
+        "modifyConfig": "Modify Config",
+        "toggleLogViewer": "Log Viewerの切替",
+        "showGallery": "ギャラリーを表示",
+        "showOptionsPanel": "オプションパネルを表示"
     }
 }

invokeai/frontend/web/public/locales/mn.json

@@ -0,0 +1 @@
+{}

invokeai/frontend/web/public/locales/nl.json

@@ -62,7 +62,18 @@
         "statusConvertingModel": "Omzetten van model",
         "statusModelConverted": "Model omgezet",
         "statusMergingModels": "Samenvoegen van modellen",
-        "statusMergedModels": "Modellen samengevoegd"
+        "statusMergedModels": "Modellen samengevoegd",
+        "cancel": "Annuleer",
+        "accept": "Akkoord",
+        "langPortuguese": "Português",
+        "pinOptionsPanel": "Zet deelscherm Opties vast",
+        "loading": "Bezig met laden",
+        "loadingInvokeAI": "Bezig met laden van Invoke AI",
+        "oceanTheme": "Oceaan",
+        "langHebrew": "עברית",
+        "langKorean": "한국어",
+        "txt2img": "Tekst naar afbeelding",
+        "postprocessing": "Nabewerking"
     },
     "gallery": {
         "generations": "Gegenereerde afbeeldingen",
@@ -301,7 +312,7 @@
         "name": "Naam",
         "nameValidationMsg": "Geef een naam voor je model",
         "description": "Beschrijving",
-        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model.",
+        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model",
         "config": "Configuratie",
         "configValidationMsg": "Pad naar het configuratiebestand van je model.",
         "modelLocation": "Locatie model",
@@ -391,7 +402,13 @@
         "modelMergeInterpAddDifferenceHelp": "In deze stand wordt model 3 eerst van model 2 afgehaald. Wat daar uitkomt wordt gemengd met model 1, gebruikmakend van de hierboven ingestelde alfawaarde.",
         "inverseSigmoid": "Keer Sigmoid om",
         "sigmoid": "Sigmoid",
-        "weightedSum": "Gewogen som"
+        "weightedSum": "Gewogen som",
+        "v2_base": "v2 (512px)",
+        "v2_768": "v2 (768px)",
+        "none": "geen",
+        "addDifference": "Voeg verschil toe",
+        "scanForModels": "Scan naar modellen",
+        "pickModelType": "Kies modelsoort"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -561,7 +578,7 @@
         "autoSaveToGallery": "Bewaar automatisch naar galerij",
         "saveBoxRegionOnly": "Bewaar alleen tekengebied",
         "limitStrokesToBox": "Beperk streken tot tekenvak",
-        "showCanvasDebugInfo": "Toon foutopsporingsgegevens canvas",
+        "showCanvasDebugInfo": "Toon aanvullende canvasgegevens",
         "clearCanvasHistory": "Wis canvasgeschiedenis",
         "clearHistory": "Wis geschiedenis",
         "clearCanvasHistoryMessage": "Het wissen van de canvasgeschiedenis laat het huidige canvas ongemoeid, maar wist onherstelbaar de geschiedenis voor het ongedaan maken en herhalen.",
@@ -587,5 +604,27 @@
         "betaDarkenOutside": "Verduister buiten tekenvak",
         "betaLimitToBox": "Beperk tot tekenvak",
         "betaPreserveMasked": "Behoud masker"
+    },
+    "accessibility": {
+        "exitViewer": "Stop viewer",
+        "zoomIn": "Zoom in",
+        "rotateCounterClockwise": "Draai tegen de klok in",
+        "modelSelect": "Modelkeuze",
+        "invokeProgressBar": "Voortgangsbalk Invoke",
+        "reset": "Herstel",
+        "uploadImage": "Upload afbeelding",
+        "previousImage": "Vorige afbeelding",
+        "nextImage": "Volgende afbeelding",
+        "useThisParameter": "Gebruik deze parameter",
+        "copyMetadataJson": "Kopieer metagegevens-JSON",
+        "zoomOut": "Zoom uit",
+        "rotateClockwise": "Draai met de klok mee",
+        "flipHorizontally": "Spiegel horizontaal",
+        "flipVertically": "Spiegel verticaal",
+        "modifyConfig": "Wijzig configuratie",
+        "toggleAutoscroll": "Autom. scrollen aan/uit",
+        "toggleLogViewer": "Logboekviewer aan/uit",
+        "showGallery": "Toon galerij",
+        "showOptionsPanel": "Toon deelscherm Opties"
     }
 }

invokeai/frontend/web/public/locales/ru.json

@@ -9,7 +9,7 @@
         "lightTheme": "Светлая",
         "greenTheme": "Зеленая",
         "img2img": "Изображение в изображение (img2img)",
-        "unifiedCanvas": "Универсальный холст",
+        "unifiedCanvas": "Единый холст",
         "nodes": "Ноды",
         "langRussian": "Русский",
         "nodesDesc": "Cистема генерации изображений на основе нодов (узлов) уже разрабатывается. Следите за новостями об этой замечательной функции.",
@@ -53,7 +53,28 @@
         "loading": "Загрузка",
         "loadingInvokeAI": "Загрузка Invoke AI",
         "back": "Назад",
-        "statusConvertingModel": "Конвертация модели"
+        "statusConvertingModel": "Конвертация модели",
+        "cancel": "Отменить",
+        "accept": "Принять",
+        "oceanTheme": "Океан",
+        "langUkranian": "Украинский",
+        "langEnglish": "Английский",
+        "postprocessing": "Постобработка",
+        "langArabic": "Арабский",
+        "langSpanish": "Испанский",
+        "langSimplifiedChinese": "Китайский (упрощенный)",
+        "langDutch": "Нидерландский",
+        "langFrench": "Французский",
+        "langGerman": "Немецкий",
+        "langHebrew": "Иврит",
+        "langItalian": "Итальянский",
+        "langJapanese": "Японский",
+        "langKorean": "Корейский",
+        "langPolish": "Польский",
+        "langPortuguese": "Португальский",
+        "txt2img": "Текст в изображение (txt2img)",
+        "langBrPortuguese": "Португальский (Бразилия)",
+        "linear": "Линейная обработка"
     },
     "gallery": {
         "generations": "Генерации",
@@ -72,11 +93,11 @@
         "noImagesInGallery": "Изображений нет"
     },
     "hotkeys": {
-        "keyboardShortcuts": "Клавиатурные сокращения",
+        "keyboardShortcuts": "Горячие клавиши",
         "appHotkeys": "Горячие клавиши приложения",
         "generalHotkeys": "Общие горячие клавиши",
         "galleryHotkeys": "Горячие клавиши галереи",
-        "unifiedCanvasHotkeys": "Горячие клавиши универсального холста",
+        "unifiedCanvasHotkeys": "Горячие клавиши Единого холста",
         "invoke": {
             "title": "Invoke",
             "desc": "Сгенерировать изображение"
@@ -266,12 +287,12 @@
             "desc": "Сбросить вид холста"
         },
         "previousStagingImage": {
-            "title": "Previous Staging Image",
-            "desc": "Предыдущее изображение"
+            "title": "Предыдущее изображение",
+            "desc": "Предыдущая область изображения"
         },
         "nextStagingImage": {
-            "title": "Next Staging Image",
-            "desc": "Следующее изображение"
+            "title": "Следующее изображение",
+            "desc": "Следующая область изображения"
         },
         "acceptStagingImage": {
             "title": "Принять изображение",
@@ -353,7 +374,42 @@
         "modelConverted": "Модель преобразована",
         "invokeRoot": "Каталог InvokeAI",
         "modelsMerged": "Модели объединены",
-        "mergeModels": "Объединить модели"
+        "mergeModels": "Объединить модели",
+        "scanForModels": "Просканировать модели",
+        "sigmoid": "Сигмоид",
+        "formMessageDiffusersModelLocation": "Расположение Diffusers-модели",
+        "modelThree": "Модель 3",
+        "modelMergeHeaderHelp2": "Только Diffusers-модели доступны для объединения. Если вы хотите объединить checkpoint-модели, сначала преобразуйте их в Diffusers.",
+        "pickModelType": "Выбрать тип модели",
+        "formMessageDiffusersVAELocation": "Расположение VAE",
+        "v1": "v1",
+        "convertToDiffusersSaveLocation": "Путь сохранения",
+        "customSaveLocation": "Пользовательский путь сохранения",
+        "alpha": "Альфа",
+        "diffusersModels": "Diffusers",
+        "customConfig": "Пользовательский конфиг",
+        "pathToCustomConfig": "Путь к пользовательскому конфигу",
+        "inpainting": "v1 Inpainting",
+        "sameFolder": "В ту же папку",
+        "modelOne": "Модель 1",
+        "mergedModelCustomSaveLocation": "Пользовательский путь",
+        "none": "пусто",
+        "addDifference": "Добавить разницу",
+        "vaeRepoIDValidationMsg": "Онлайн репозиторий VAE",
+        "convertToDiffusersHelpText2": "Этот процесс заменит вашу запись в Model Manager на версию той же модели в Diffusers.",
+        "custom": "Пользовательский",
+        "modelTwo": "Модель 2",
+        "mergedModelSaveLocation": "Путь сохранения",
+        "merge": "Объединить",
+        "interpolationType": "Тип интерполяции",
+        "modelMergeInterpAddDifferenceHelp": "В этом режиме Модель 3 сначала вычитается из Модели 2. Результирующая версия смешивается с Моделью 1 с установленным выше коэффициентом Альфа.",
+        "modelMergeHeaderHelp1": "Вы можете объединить до трех разных моделей, чтобы создать смешанную, соответствующую вашим потребностям.",
+        "modelMergeAlphaHelp": "Альфа влияет на силу смешивания моделей. Более низкие значения альфа приводят к меньшему влиянию второй модели.",
+        "inverseSigmoid": "Обратный Сигмоид",
+        "weightedSum": "Взвешенная сумма",
+        "safetensorModels": "SafeTensors",
+        "v2_768": "v2 (768px)",
+        "v2_base": "v2 (512px)"
     },
     "parameters": {
         "images": "Изображения",
@@ -380,7 +436,7 @@
         "scale": "Масштаб",
         "otherOptions": "Другие параметры",
         "seamlessTiling": "Бесшовный узор",
-        "hiresOptim": "Высокое разрешение",
+        "hiresOptim": "Оптимизация High Res",
         "imageFit": "Уместить изображение",
         "codeformerFidelity": "Точность",
         "seamSize": "Размер шва",
@@ -397,11 +453,11 @@
         "infillScalingHeader": "Заполнение и масштабирование",
         "img2imgStrength": "Сила обработки img2img",
         "toggleLoopback": "Зациклить обработку",
-        "invoke": "Вызвать",
+        "invoke": "Invoke",
         "promptPlaceholder": "Введите запрос здесь (на английском). [исключенные токены], (более значимые)++, (менее значимые)--, swap и blend тоже доступны (смотрите Github)",
         "sendTo": "Отправить",
         "sendToImg2Img": "Отправить в img2img",
-        "sendToUnifiedCanvas": "Отправить на холст",
+        "sendToUnifiedCanvas": "Отправить на Единый холст",
         "copyImageToLink": "Скопировать ссылку",
         "downloadImage": "Скачать",
         "openInViewer": "Открыть в просмотрщике",
@@ -413,7 +469,24 @@
         "info": "Метаданные",
         "deleteImage": "Удалить изображение",
         "initialImage": "Исходное изображение",
-        "showOptionsPanel": "Показать панель настроек"
+        "showOptionsPanel": "Показать панель настроек",
+        "vSymmetryStep": "Шаг верт. симметрии",
+        "cancel": {
+            "immediate": "Отменить немедленно",
+            "schedule": "Отменить после текущей итерации",
+            "isScheduled": "Отмена",
+            "setType": "Установить тип отмены"
+        },
+        "general": "Основное",
+        "hiresStrength": "Сила High Res",
+        "symmetry": "Симметрия",
+        "hSymmetryStep": "Шаг гор. симметрии",
+        "hidePreview": "Скрыть предпросмотр",
+        "imageToImage": "Изображение в изображение",
+        "denoisingStrength": "Сила шумоподавления",
+        "copyImage": "Скопировать изображение",
+        "negativePrompts": "Исключающий запрос",
+        "showPreview": "Показать предпросмотр"
     },
     "settings": {
         "models": "Модели",
@@ -423,10 +496,11 @@
         "displayHelpIcons": "Показывать значки подсказок",
         "useCanvasBeta": "Показывать инструменты слева (Beta UI)",
         "enableImageDebugging": "Включить отладку",
-        "resetWebUI": "Вернуть умолчания",
+        "resetWebUI": "Сброс настроек Web UI",
         "resetWebUIDesc1": "Сброс настроек веб-интерфейса удаляет только локальный кэш браузера с вашими изображениями и настройками. Он не удаляет изображения с диска.",
         "resetWebUIDesc2": "Если изображения не отображаются в галерее или не работает что-то еще, пожалуйста, попробуйте сбросить настройки, прежде чем сообщать о проблеме на GitHub.",
-        "resetComplete": "Интерфейс сброшен. Обновите эту страницу."
+        "resetComplete": "Интерфейс сброшен. Обновите эту страницу.",
+        "useSlidersForAll": "Использовать ползунки для всех параметров"
     },
     "toast": {
         "tempFoldersEmptied": "Временная папка очищена",
@@ -441,7 +515,7 @@
         "imageSavedToGallery": "Изображение сохранено в галерею",
         "canvasMerged": "Холст объединен",
         "sentToImageToImage": "Отправить в img2img",
-        "sentToUnifiedCanvas": "Отправить на холст",
+        "sentToUnifiedCanvas": "Отправлено на Единый холст",
         "parametersSet": "Параметры заданы",
         "parametersNotSet": "Параметры не заданы",
         "parametersNotSetDesc": "Не найдены метаданные изображения.",
@@ -458,7 +532,11 @@
         "metadataLoadFailed": "Не удалось загрузить метаданные",
         "initialImageSet": "Исходное изображение задано",
         "initialImageNotSet": "Исходное изображение не задано",
-        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение"
+        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение",
+        "serverError": "Ошибка сервера",
+        "disconnected": "Отключено от сервера",
+        "connected": "Подключено к серверу",
+        "canceled": "Обработка отменена"
     },
     "tooltip": {
         "feature": {
@@ -507,7 +585,7 @@
         "autoSaveToGallery": "Автосохранение в галерее",
         "saveBoxRegionOnly": "Сохранять только выделение",
         "limitStrokesToBox": "Ограничить штрихи выделением",
-        "showCanvasDebugInfo": "Показать отладку холста",
+        "showCanvasDebugInfo": "Показать доп. информацию о холсте",
         "clearCanvasHistory": "Очистить историю холста",
         "clearHistory": "Очистить историю",
         "clearCanvasHistoryMessage": "Очистка истории холста оставляет текущий холст нетронутым, но удаляет историю отмен и повторов.",
@@ -535,6 +613,26 @@
         "betaPreserveMasked": "Сохранять маскируемую область"
     },
     "accessibility": {
-        "modelSelect": "Выбор модели"
+        "modelSelect": "Выбор модели",
+        "uploadImage": "Загрузить изображение",
+        "nextImage": "Следующее изображение",
+        "previousImage": "Предыдущее изображение",
+        "zoomIn": "Приблизить",
+        "zoomOut": "Отдалить",
+        "rotateClockwise": "Повернуть по часовой стрелке",
+        "rotateCounterClockwise": "Повернуть против часовой стрелки",
+        "flipVertically": "Перевернуть вертикально",
+        "flipHorizontally": "Отразить горизонтально",
+        "toggleAutoscroll": "Включить автопрокрутку",
+        "toggleLogViewer": "Показать или скрыть просмотрщик логов",
+        "showOptionsPanel": "Показать опции",
+        "showGallery": "Показать галерею",
+        "invokeProgressBar": "Индикатор выполнения",
+        "reset": "Сброс",
+        "modifyConfig": "Изменить конфиг",
+        "useThisParameter": "Использовать этот параметр",
+        "copyMetadataJson": "Скопировать метаданные JSON",
+        "exitViewer": "Закрыть просмотрщик",
+        "menu": "Меню"
     }
 }

invokeai/frontend/web/public/locales/sv.json

@@ -0,0 +1,254 @@
+{
+    "accessibility": {
+        "copyMetadataJson": "Kopiera metadata JSON",
+        "zoomIn": "Zooma in",
+        "exitViewer": "Avslutningsvisare",
+        "modelSelect": "Välj modell",
+        "uploadImage": "Ladda upp bild",
+        "invokeProgressBar": "Invoke förloppsmätare",
+        "nextImage": "Nästa bild",
+        "toggleAutoscroll": "Växla automatisk rullning",
+        "flipHorizontally": "Vänd vågrätt",
+        "flipVertically": "Vänd lodrätt",
+        "zoomOut": "Zooma ut",
+        "toggleLogViewer": "Växla logvisare",
+        "reset": "Starta om",
+        "previousImage": "Föregående bild",
+        "useThisParameter": "Använd denna parametern",
+        "showGallery": "Visa galleri",
+        "rotateCounterClockwise": "Rotera moturs",
+        "rotateClockwise": "Rotera medurs",
+        "modifyConfig": "Ändra konfiguration",
+        "showOptionsPanel": "Visa inställningspanelen"
+    },
+    "common": {
+        "hotkeysLabel": "Snabbtangenter",
+        "reportBugLabel": "Rapportera bugg",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "settingsLabel": "Inställningar",
+        "darkTheme": "Mörk",
+        "lightTheme": "Ljus",
+        "greenTheme": "Grön",
+        "oceanTheme": "Hav",
+        "langEnglish": "Engelska",
+        "langDutch": "Nederländska",
+        "langFrench": "Franska",
+        "langGerman": "Tyska",
+        "langItalian": "Italienska",
+        "langArabic": "العربية",
+        "langHebrew": "עברית",
+        "langPolish": "Polski",
+        "langPortuguese": "Português",
+        "langBrPortuguese": "Português do Brasil",
+        "langSimplifiedChinese": "简体中文",
+        "langJapanese": "日本語",
+        "langKorean": "한국어",
+        "langRussian": "Русский",
+        "unifiedCanvas": "Förenad kanvas",
+        "nodesDesc": "Ett nodbaserat system för bildgenerering är under utveckling. Håll utkik för uppdateringar om denna fantastiska funktion.",
+        "langUkranian": "Украї́нська",
+        "langSpanish": "Español",
+        "postProcessDesc2": "Ett dedikerat användargränssnitt kommer snart att släppas för att underlätta mer avancerade arbetsflöden av efterbehandling.",
+        "trainingDesc1": "Ett dedikerat arbetsflöde för träning av dina egna inbäddningar och kontrollpunkter genom Textual Inversion eller Dreambooth från webbgränssnittet.",
+        "trainingDesc2": "InvokeAI stöder redan träning av anpassade inbäddningar med hjälp av Textual Inversion genom huvudscriptet.",
+        "upload": "Ladda upp",
+        "close": "Stäng",
+        "cancel": "Avbryt",
+        "accept": "Acceptera",
+        "statusDisconnected": "Frånkopplad",
+        "statusGeneratingTextToImage": "Genererar text till bild",
+        "statusGeneratingImageToImage": "Genererar Bild till bild",
+        "statusGeneratingInpainting": "Genererar Måla i",
+        "statusGenerationComplete": "Generering klar",
+        "statusModelConverted": "Modell konverterad",
+        "statusMergingModels": "Sammanfogar modeller",
+        "pinOptionsPanel": "Nåla fast inställningspanelen",
+        "loading": "Laddar",
+        "loadingInvokeAI": "Laddar Invoke AI",
+        "statusRestoringFaces": "Återskapar ansikten",
+        "languagePickerLabel": "Språkväljare",
+        "themeLabel": "Tema",
+        "txt2img": "Text till bild",
+        "nodes": "Noder",
+        "img2img": "Bild till bild",
+        "postprocessing": "Efterbehandling",
+        "postProcessing": "Efterbehandling",
+        "load": "Ladda",
+        "training": "Träning",
+        "postProcessDesc1": "Invoke AI erbjuder ett brett utbud av efterbehandlingsfunktioner. Uppskalning och ansiktsåterställning finns redan tillgängligt i webbgränssnittet. Du kommer åt dem ifrån Avancerade inställningar-menyn under Bild till bild-fliken. Du kan också behandla bilder direkt genom att använda knappen bildåtgärder ovanför nuvarande bild eller i bildvisaren.",
+        "postProcessDesc3": "Invoke AI's kommandotolk erbjuder många olika funktioner, bland annat \"Förstora\".",
+        "statusGenerating": "Genererar",
+        "statusError": "Fel",
+        "back": "Bakåt",
+        "statusConnected": "Ansluten",
+        "statusPreparing": "Förbereder",
+        "statusProcessingCanceled": "Bearbetning avbruten",
+        "statusProcessingComplete": "Bearbetning färdig",
+        "statusGeneratingOutpainting": "Genererar Fyll ut",
+        "statusIterationComplete": "Itterering klar",
+        "statusSavingImage": "Sparar bild",
+        "statusRestoringFacesGFPGAN": "Återskapar ansikten (GFPGAN)",
+        "statusRestoringFacesCodeFormer": "Återskapar ansikten (CodeFormer)",
+        "statusUpscaling": "Skala upp",
+        "statusUpscalingESRGAN": "Uppskalning (ESRGAN)",
+        "statusModelChanged": "Modell ändrad",
+        "statusLoadingModel": "Laddar modell",
+        "statusConvertingModel": "Konverterar modell",
+        "statusMergedModels": "Modeller sammanfogade"
+    },
+    "gallery": {
+        "generations": "Generationer",
+        "showGenerations": "Visa generationer",
+        "uploads": "Uppladdningar",
+        "showUploads": "Visa uppladdningar",
+        "galleryImageSize": "Bildstorlek",
+        "allImagesLoaded": "Alla bilder laddade",
+        "loadMore": "Ladda mer",
+        "galleryImageResetSize": "Återställ storlek",
+        "gallerySettings": "Galleriinställningar",
+        "maintainAspectRatio": "Behåll bildförhållande",
+        "pinGallery": "Nåla fast galleri",
+        "noImagesInGallery": "Inga bilder i galleriet",
+        "autoSwitchNewImages": "Ändra automatiskt till nya bilder",
+        "singleColumnLayout": "Enkolumnslayout"
+    },
+    "hotkeys": {
+        "generalHotkeys": "Allmänna snabbtangenter",
+        "galleryHotkeys": "Gallerisnabbtangenter",
+        "unifiedCanvasHotkeys": "Snabbtangenter för sammanslagskanvas",
+        "invoke": {
+            "title": "Anropa",
+            "desc": "Genererar en bild"
+        },
+        "cancel": {
+            "title": "Avbryt",
+            "desc": "Avbryt bildgenerering"
+        },
+        "focusPrompt": {
+            "desc": "Fokusera området för promptinmatning",
+            "title": "Fokusprompt"
+        },
+        "pinOptions": {
+            "desc": "Nåla fast alternativpanelen",
+            "title": "Nåla fast alternativ"
+        },
+        "toggleOptions": {
+            "title": "Växla inställningar",
+            "desc": "Öppna och stäng alternativpanelen"
+        },
+        "toggleViewer": {
+            "title": "Växla visaren",
+            "desc": "Öppna och stäng bildvisaren"
+        },
+        "toggleGallery": {
+            "title": "Växla galleri",
+            "desc": "Öppna eller stäng galleribyrån"
+        },
+        "maximizeWorkSpace": {
+            "title": "Maximera arbetsyta",
+            "desc": "Stäng paneler och maximera arbetsyta"
+        },
+        "changeTabs": {
+            "title": "Växla flik",
+            "desc": "Byt till en annan arbetsyta"
+        },
+        "consoleToggle": {
+            "title": "Växla konsol",
+            "desc": "Öppna och stäng konsol"
+        },
+        "setSeed": {
+            "desc": "Använd seed för nuvarande bild",
+            "title": "välj seed"
+        },
+        "setParameters": {
+            "title": "Välj parametrar",
+            "desc": "Använd alla parametrar från nuvarande bild"
+        },
+        "setPrompt": {
+            "desc": "Använd prompt för nuvarande bild",
+            "title": "Välj prompt"
+        },
+        "restoreFaces": {
+            "title": "Återskapa ansikten",
+            "desc": "Återskapa nuvarande bild"
+        },
+        "upscale": {
+            "title": "Skala upp",
+            "desc": "Skala upp nuvarande bild"
+        },
+        "showInfo": {
+            "title": "Visa info",
+            "desc": "Visa metadata för nuvarande bild"
+        },
+        "sendToImageToImage": {
+            "title": "Skicka till Bild till bild",
+            "desc": "Skicka nuvarande bild till Bild till bild"
+        },
+        "deleteImage": {
+            "title": "Radera bild",
+            "desc": "Radera nuvarande bild"
+        },
+        "closePanels": {
+            "title": "Stäng paneler",
+            "desc": "Stäng öppna paneler"
+        },
+        "previousImage": {
+            "title": "Föregående bild",
+            "desc": "Visa föregående bild"
+        },
+        "nextImage": {
+            "title": "Nästa bild",
+            "desc": "Visa nästa bild"
+        },
+        "toggleGalleryPin": {
+            "title": "Växla gallerinål",
+            "desc": "Nålar fast eller nålar av galleriet i gränssnittet"
+        },
+        "increaseGalleryThumbSize": {
+            "title": "Förstora galleriets bildstorlek",
+            "desc": "Förstora miniatyrbildernas storlek"
+        },
+        "decreaseGalleryThumbSize": {
+            "title": "Minska gelleriets bildstorlek",
+            "desc": "Minska miniatyrbildernas storlek i galleriet"
+        },
+        "decreaseBrushSize": {
+            "desc": "Förminska storleken på kanvas- pensel eller suddgummi",
+            "title": "Minska penselstorlek"
+        },
+        "increaseBrushSize": {
+            "title": "Öka penselstorlek",
+            "desc": "Öka stoleken på kanvas- pensel eller suddgummi"
+        },
+        "increaseBrushOpacity": {
+            "title": "Öka penselns opacitet",
+            "desc": "Öka opaciteten för kanvaspensel"
+        },
+        "decreaseBrushOpacity": {
+            "desc": "Minska kanvaspenselns opacitet",
+            "title": "Minska penselns opacitet"
+        },
+        "moveTool": {
+            "title": "Flytta",
+            "desc": "Tillåt kanvasnavigation"
+        },
+        "fillBoundingBox": {
+            "title": "Fyll ram",
+            "desc": "Fyller ramen med pensels färg"
+        },
+        "keyboardShortcuts": "Snabbtangenter",
+        "appHotkeys": "Appsnabbtangenter",
+        "selectBrush": {
+            "desc": "Välj kanvaspensel",
+            "title": "Välj pensel"
+        },
+        "selectEraser": {
+            "desc": "Välj kanvassuddgummi",
+            "title": "Välj suddgummi"
+        },
+        "eraseBoundingBox": {
+            "title": "Ta bort ram"
+        }
+    }
+}

invokeai/frontend/web/public/locales/tr.json

@@ -0,0 +1,64 @@
+{
+    "accessibility": {
+        "invokeProgressBar": "Invoke ilerleme durumu",
+        "nextImage": "Sonraki Resim",
+        "useThisParameter": "Kullanıcı parametreleri",
+        "copyMetadataJson": "Metadata verilerini kopyala (JSON)",
+        "exitViewer": "Görüntüleme Modundan Çık",
+        "zoomIn": "Yakınlaştır",
+        "zoomOut": "Uzaklaştır",
+        "rotateCounterClockwise": "Döndür (Saat yönünün tersine)",
+        "rotateClockwise": "Döndür (Saat yönünde)",
+        "flipHorizontally": "Yatay Çevir",
+        "flipVertically": "Dikey Çevir",
+        "modifyConfig": "Ayarları Değiştir",
+        "toggleAutoscroll": "Otomatik kaydırmayı aç/kapat",
+        "toggleLogViewer": "Günlük Görüntüleyici Aç/Kapa",
+        "showOptionsPanel": "Ayarlar Panelini Göster",
+        "modelSelect": "Model Seçin",
+        "reset": "Sıfırla",
+        "uploadImage": "Resim Yükle",
+        "previousImage": "Önceki Resim",
+        "menu": "Menü",
+        "showGallery": "Galeriyi Göster"
+    },
+    "common": {
+        "hotkeysLabel": "Kısayol Tuşları",
+        "themeLabel": "Tema",
+        "languagePickerLabel": "Dil Seçimi",
+        "reportBugLabel": "Hata Bildir",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "settingsLabel": "Ayarlar",
+        "darkTheme": "Karanlık Tema",
+        "lightTheme": "Aydınlık Tema",
+        "greenTheme": "Yeşil Tema",
+        "oceanTheme": "Okyanus Tema",
+        "langArabic": "Arapça",
+        "langEnglish": "İngilizce",
+        "langDutch": "Hollandaca",
+        "langFrench": "Fransızca",
+        "langGerman": "Almanca",
+        "langItalian": "İtalyanca",
+        "langJapanese": "Japonca",
+        "langPolish": "Lehçe",
+        "langPortuguese": "Portekizce",
+        "langBrPortuguese": "Portekizcr (Brezilya)",
+        "langRussian": "Rusça",
+        "langSimplifiedChinese": "Çince (Basit)",
+        "langUkranian": "Ukraynaca",
+        "langSpanish": "İspanyolca",
+        "txt2img": "Metinden Resime",
+        "img2img": "Resimden Metine",
+        "linear": "Çizgisel",
+        "nodes": "Düğümler",
+        "postprocessing": "İşlem Sonrası",
+        "postProcessing": "İşlem Sonrası",
+        "postProcessDesc2": "Daha gelişmiş özellikler için ve iş akışını kolaylaştırmak için özel bir kullanıcı arayüzü çok yakında yayınlanacaktır.",
+        "postProcessDesc3": "Invoke AI komut satırı arayüzü, bir çok yeni özellik sunmaktadır.",
+        "langKorean": "Korece",
+        "unifiedCanvas": "Akıllı Tuval",
+        "nodesDesc": "Görüntülerin oluşturulmasında hazırladığımız yeni bir sistem geliştirme aşamasındadır. Bu harika özellikler ve çok daha fazlası için bizi takip etmeye devam edin.",
+        "postProcessDesc1": "Invoke AI son kullanıcıya yönelik bir çok özellik sunar. Görüntü kalitesi yükseltme, yüz restorasyonu WebUI üzerinden kullanılabilir. Metinden resime ve resimden metne araçlarına gelişmiş seçenekler menüsünden ulaşabilirsiniz. İsterseniz mevcut görüntü ekranının üzerindeki veya görüntüleyicideki görüntüyü doğrudan düzenleyebilirsiniz."
+    }
+}

invokeai/frontend/web/public/locales/uk.json

@@ -16,9 +16,9 @@
         "postProcessing": "Постобробка",
         "postProcessDesc1": "Invoke AI пропонує широкий спектр функцій постобробки. Збільшення зображення (upscale) та відновлення облич вже доступні в інтерфейсі. Отримайте доступ до них з меню 'Додаткові параметри' на вкладках 'Зображення із тексту' та 'Зображення із зображення'. Обробляйте зображення безпосередньо, використовуючи кнопки дій із зображеннями над поточним зображенням або в режимі перегляду.",
         "postProcessDesc2": "Найближчим часом буде випущено спеціальний інтерфейс для більш сучасних процесів постобробки.",
-        "postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen",
+        "postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen.",
         "training": "Навчання",
-        "trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth",
+        "trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth.",
         "trainingDesc2": "InvokeAI вже підтримує навчання моделей за допомогою TI, через інтерфейс командного рядка.",
         "upload": "Завантажити",
         "close": "Закрити",
@@ -43,7 +43,38 @@
         "statusUpscaling": "Збільшення",
         "statusUpscalingESRGAN": "Збільшення (ESRGAN)",
         "statusLoadingModel": "Завантаження моделі",
-        "statusModelChanged": "Модель змінено"
+        "statusModelChanged": "Модель змінено",
+        "cancel": "Скасувати",
+        "accept": "Підтвердити",
+        "back": "Назад",
+        "postprocessing": "Постобробка",
+        "statusModelConverted": "Модель сконвертована",
+        "statusMergingModels": "Злиття моделей",
+        "loading": "Завантаження",
+        "loadingInvokeAI": "Завантаження Invoke AI",
+        "langHebrew": "Іврит",
+        "langKorean": "Корейська",
+        "langPortuguese": "Португальська",
+        "pinOptionsPanel": "Закріпити панель налаштувань",
+        "oceanTheme": "Океан",
+        "langArabic": "Арабська",
+        "langSimplifiedChinese": "Китайська (спрощена)",
+        "langSpanish": "Іспанська",
+        "langEnglish": "Англійська",
+        "langGerman": "Німецька",
+        "langItalian": "Італійська",
+        "langJapanese": "Японська",
+        "langPolish": "Польська",
+        "langBrPortuguese": "Португальська (Бразилія)",
+        "langRussian": "Російська",
+        "githubLabel": "Github",
+        "txt2img": "Текст в зображення (txt2img)",
+        "discordLabel": "Discord",
+        "langDutch": "Голландська",
+        "langFrench": "Французька",
+        "statusMergedModels": "Моделі об'єднані",
+        "statusConvertingModel": "Конвертація моделі",
+        "linear": "Лінійна обробка"
     },
     "gallery": {
         "generations": "Генерації",
@@ -284,15 +315,15 @@
         "description": "Опис",
         "descriptionValidationMsg": "Введіть опис моделі",
         "config": "Файл конфігурації",
-        "configValidationMsg": "Шлях до файлу конфігурації",
+        "configValidationMsg": "Шлях до файлу конфігурації.",
         "modelLocation": "Розташування моделі",
-        "modelLocationValidationMsg": "Шлях до файлу з моделлю",
+        "modelLocationValidationMsg": "Шлях до файлу з моделлю.",
         "vaeLocation": "Розтышування VAE",
-        "vaeLocationValidationMsg": "Шлях до VAE",
+        "vaeLocationValidationMsg": "Шлях до VAE.",
         "width": "Ширина",
-        "widthValidationMsg": "Початкова ширина зображень",
+        "widthValidationMsg": "Початкова ширина зображень.",
         "height": "Висота",
-        "heightValidationMsg": "Початкова висота зображень",
+        "heightValidationMsg": "Початкова висота зображень.",
         "addModel": "Додати модель",
         "updateModel": "Оновити модель",
         "availableModels": "Доступні моделі",
@@ -319,7 +350,66 @@
         "deleteModel": "Видалити модель",
         "deleteConfig": "Видалити конфігурацію",
         "deleteMsg1": "Ви точно хочете видалити модель із InvokeAI?",
-        "deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову."
+        "deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову.",
+        "allModels": "Усі моделі",
+        "diffusersModels": "Diffusers",
+        "scanForModels": "Сканувати моделі",
+        "convert": "Конвертувати",
+        "convertToDiffusers": "Конвертувати в Diffusers",
+        "formMessageDiffusersVAELocationDesc": "Якщо не надано, InvokeAI буде шукати файл VAE в розташуванні моделі, вказаній вище.",
+        "convertToDiffusersHelpText3": "Файл моделі на диску НЕ буде видалено або змінено. Ви можете знову додати його в Model Manager, якщо потрібно.",
+        "customConfig": "Користувальницький конфіг",
+        "invokeRoot": "Каталог InvokeAI",
+        "custom": "Користувальницький",
+        "modelTwo": "Модель 2",
+        "modelThree": "Модель 3",
+        "mergedModelName": "Назва об'єднаної моделі",
+        "alpha": "Альфа",
+        "interpolationType": "Тип інтерполяції",
+        "mergedModelSaveLocation": "Шлях збереження",
+        "mergedModelCustomSaveLocation": "Користувальницький шлях",
+        "invokeAIFolder": "Каталог InvokeAI",
+        "ignoreMismatch": "Ігнорувати невідповідності між вибраними моделями",
+        "modelMergeHeaderHelp2": "Тільки Diffusers-моделі доступні для об'єднання. Якщо ви хочете об'єднати checkpoint-моделі, спочатку перетворіть їх на Diffusers.",
+        "checkpointModels": "Checkpoints",
+        "repo_id": "ID репозиторію",
+        "v2_base": "v2 (512px)",
+        "repoIDValidationMsg": "Онлайн-репозиторій моделі",
+        "formMessageDiffusersModelLocationDesc": "Вкажіть хоча б одне.",
+        "formMessageDiffusersModelLocation": "Шлях до Diffusers-моделі",
+        "v2_768": "v2 (768px)",
+        "formMessageDiffusersVAELocation": "Шлях до VAE",
+        "convertToDiffusersHelpText5": "Переконайтеся, що у вас достатньо місця на диску. Моделі зазвичай займають від 4 до 7 Гб.",
+        "convertToDiffusersSaveLocation": "Шлях збереження",
+        "v1": "v1",
+        "convertToDiffusersHelpText6": "Ви хочете перетворити цю модель?",
+        "inpainting": "v1 Inpainting",
+        "modelConverted": "Модель перетворено",
+        "sameFolder": "У ту ж папку",
+        "statusConverting": "Перетворення",
+        "merge": "Об'єднати",
+        "mergeModels": "Об'єднати моделі",
+        "modelOne": "Модель 1",
+        "sigmoid": "Сігмоїд",
+        "weightedSum": "Зважена сума",
+        "none": "пусто",
+        "addDifference": "Додати різницю",
+        "pickModelType": "Вибрати тип моделі",
+        "convertToDiffusersHelpText4": "Це одноразова дія. Вона може зайняти від 30 до 60 секунд в залежності від характеристик вашого комп'ютера.",
+        "pathToCustomConfig": "Шлях до конфігу користувача",
+        "safetensorModels": "SafeTensors",
+        "addCheckpointModel": "Додати модель Checkpoint/Safetensor",
+        "addDiffuserModel": "Додати Diffusers",
+        "vaeRepoID": "ID репозиторію VAE",
+        "vaeRepoIDValidationMsg": "Онлайн-репозиторій VAE",
+        "modelMergeInterpAddDifferenceHelp": "У цьому режимі Модель 3 спочатку віднімається з Моделі 2. Результуюча версія змішується з Моделью 1 із встановленим вище коефіцієнтом Альфа.",
+        "customSaveLocation": "Користувальницький шлях збереження",
+        "modelMergeAlphaHelp": "Альфа впливає силу змішування моделей. Нижчі значення альфа призводять до меншого впливу другої моделі.",
+        "convertToDiffusersHelpText1": "Ця модель буде конвертована в формат 🧨 Diffusers.",
+        "convertToDiffusersHelpText2": "Цей процес замінить ваш запис в Model Manager на версію тієї ж моделі в Diffusers.",
+        "modelsMerged": "Моделі об'єднані",
+        "modelMergeHeaderHelp1": "Ви можете об'єднати до трьох різних моделей, щоб створити змішану, що відповідає вашим потребам.",
+        "inverseSigmoid": "Зворотній Сігмоїд"
     },
     "parameters": {
         "images": "Зображення",
@@ -346,7 +436,7 @@
         "scale": "Масштаб",
         "otherOptions": "інші параметри",
         "seamlessTiling": "Безшовний узор",
-        "hiresOptim": "Висока роздільна здатність",
+        "hiresOptim": "Оптимізація High Res",
         "imageFit": "Вмістити зображення",
         "codeformerFidelity": "Точність",
         "seamSize": "Размір шву",
@@ -379,7 +469,24 @@
         "info": "Метадані",
         "deleteImage": "Видалити зображення",
         "initialImage": "Початкове зображення",
-        "showOptionsPanel": "Показати панель налаштувань"
+        "showOptionsPanel": "Показати панель налаштувань",
+        "general": "Основне",
+        "cancel": {
+            "immediate": "Скасувати негайно",
+            "schedule": "Скасувати після поточної ітерації",
+            "isScheduled": "Відміна",
+            "setType": "Встановити тип скасування"
+        },
+        "vSymmetryStep": "Крок верт. симетрії",
+        "hiresStrength": "Сила High Res",
+        "hidePreview": "Сховати попередній перегляд",
+        "showPreview": "Показати попередній перегляд",
+        "imageToImage": "Зображення до зображення",
+        "denoisingStrength": "Сила шумоподавлення",
+        "copyImage": "Копіювати зображення",
+        "symmetry": "Симетрія",
+        "hSymmetryStep": "Крок гор. симетрії",
+        "negativePrompts": "Виключний запит"
     },
     "settings": {
         "models": "Моделі",
@@ -392,7 +499,8 @@
         "resetWebUI": "Повернути початкові",
         "resetWebUIDesc1": "Скидання настройок веб-інтерфейсу видаляє лише локальний кеш браузера з вашими зображеннями та налаштуваннями. Це не призводить до видалення зображень з диску.",
         "resetWebUIDesc2": "Якщо зображення не відображаються в галереї або не працює ще щось, спробуйте скинути налаштування, перш ніж повідомляти про проблему на GitHub.",
-        "resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку."
+        "resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку.",
+        "useSlidersForAll": "Використовувати повзунки для всіх параметрів"
     },
     "toast": {
         "tempFoldersEmptied": "Тимчасова папка очищена",
@@ -410,21 +518,25 @@
         "sentToUnifiedCanvas": "Надіслати на полотно",
         "parametersSet": "Параметри задані",
         "parametersNotSet": "Параметри не задані",
-        "parametersNotSetDesc": "Не знайдені метадані цього зображення",
+        "parametersNotSetDesc": "Не знайдені метадані цього зображення.",
         "parametersFailed": "Проблема із завантаженням параметрів",
-        "parametersFailedDesc": "Неможливо завантажити початкове зображення",
+        "parametersFailedDesc": "Неможливо завантажити початкове зображення.",
         "seedSet": "Сід заданий",
         "seedNotSet": "Сід не заданий",
-        "seedNotSetDesc": "Не вдалося знайти сід для зображення",
+        "seedNotSetDesc": "Не вдалося знайти сід для зображення.",
         "promptSet": "Запит заданий",
         "promptNotSet": "Запит не заданий",
-        "promptNotSetDesc": "Не вдалося знайти запит для зображення",
+        "promptNotSetDesc": "Не вдалося знайти запит для зображення.",
         "upscalingFailed": "Збільшення не вдалося",
         "faceRestoreFailed": "Відновлення облич не вдалося",
         "metadataLoadFailed": "Не вдалося завантажити метадані",
         "initialImageSet": "Початкове зображення задане",
         "initialImageNotSet": "Початкове зображення не задане",
-        "initialImageNotSetDesc": "Не вдалося завантажити початкове зображення"
+        "initialImageNotSetDesc": "Не вдалося завантажити початкове зображення",
+        "serverError": "Помилка сервера",
+        "disconnected": "Відключено від сервера",
+        "connected": "Підключено до сервера",
+        "canceled": "Обробку скасовано"
     },
     "tooltip": {
         "feature": {
@@ -473,10 +585,10 @@
         "autoSaveToGallery": "Автозбереження до галереї",
         "saveBoxRegionOnly": "Зберiгати тiльки видiлення",
         "limitStrokesToBox": "Обмежити штрихи виділенням",
-        "showCanvasDebugInfo": "Показати налаштування полотна",
+        "showCanvasDebugInfo": "Показати дод. інформацію про полотно",
         "clearCanvasHistory": "Очистити iсторiю полотна",
         "clearHistory": "Очистити iсторiю",
-        "clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору",
+        "clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору.",
         "clearCanvasHistoryConfirm": "Ви впевнені, що хочете очистити історію полотна?",
         "emptyTempImageFolder": "Очистити тимчасову папку",
         "emptyFolder": "Очистити папку",
@@ -499,5 +611,28 @@
         "betaDarkenOutside": "Затемнити зовні",
         "betaLimitToBox": "Обмежити виділенням",
         "betaPreserveMasked": "Зберiгати замасковану область"
+    },
+    "accessibility": {
+        "nextImage": "Наступне зображення",
+        "modelSelect": "Вибір моделі",
+        "invokeProgressBar": "Індикатор виконання",
+        "reset": "Скинути",
+        "uploadImage": "Завантажити зображення",
+        "useThisParameter": "Використовувати цей параметр",
+        "exitViewer": "Вийти з переглядача",
+        "zoomIn": "Збільшити",
+        "zoomOut": "Зменшити",
+        "rotateCounterClockwise": "Обертати проти годинникової стрілки",
+        "rotateClockwise": "Обертати за годинниковою стрілкою",
+        "toggleAutoscroll": "Увімкнути автопрокручування",
+        "toggleLogViewer": "Показати або приховати переглядач журналів",
+        "showGallery": "Показати галерею",
+        "previousImage": "Попереднє зображення",
+        "copyMetadataJson": "Скопіювати метадані JSON",
+        "flipVertically": "Перевернути по вертикалі",
+        "flipHorizontally": "Відобразити по горизонталі",
+        "showOptionsPanel": "Показати опції",
+        "modifyConfig": "Змінити конфігурацію",
+        "menu": "Меню"
     }
 }

invokeai/frontend/web/public/locales/vi.json

@@ -0,0 +1 @@
+{}

invokeai/frontend/web/public/locales/zh_CN.json

@@ -481,5 +481,22 @@
         "betaDarkenOutside": "暗化外部区域",
         "betaLimitToBox": "限制在框内",
         "betaPreserveMasked": "保留遮罩层"
+    },
+    "accessibility": {
+        "modelSelect": "模型选择",
+        "invokeProgressBar": "Invoke 进度条",
+        "reset": "重置",
+        "nextImage": "下一张图片",
+        "useThisParameter": "使用此参数",
+        "uploadImage": "上传图片",
+        "previousImage": "上一张图片",
+        "copyMetadataJson": "复制JSON元数据",
+        "exitViewer": "退出视口（ExitViewer）",
+        "zoomIn": "放大",
+        "zoomOut": "缩小",
+        "rotateCounterClockwise": "逆时针旋转",
+        "rotateClockwise": "顺时针旋转",
+        "flipHorizontally": "水平翻转",
+        "flipVertically": "垂直翻转"
     }
 }

invokeai/frontend/web/src/Loading.tsx

@@ -1,39 +0,0 @@
-import { Flex, Spinner, Text } from '@chakra-ui/react';
-import { useTranslation } from 'react-i18next';
-
-interface LoaderProps {
-  showText?: boolean;
-  text?: string;
-}
-
-// This component loads before the theme so we cannot use theme tokens here
-
-const Loading = (props: LoaderProps) => {
-  const { t } = useTranslation();
-  const { showText = false, text = t('common.loadingInvokeAI') } = props;
-
-  return (
-    <Flex
-      width="100vw"
-      height="100vh"
-      alignItems="center"
-      justifyContent="center"
-      bg="#121212"
-      flexDirection="column"
-      rowGap={4}
-    >
-      <Spinner color="grey" w="5rem" h="5rem" />
-      {showText && (
-        <Text
-          color="grey"
-          fontWeight="semibold"
-          fontFamily="'Inter', sans-serif"
-        >
-          {text}
-        </Text>
-      )}
-    </Flex>
-  );
-};
-
-export default Loading;

invokeai/frontend/web/src/app/App.tsx

@@ -1,63 +0,0 @@
-import ImageUploader from 'common/components/ImageUploader';
-import Console from 'features/system/components/Console';
-import ProgressBar from 'features/system/components/ProgressBar';
-import SiteHeader from 'features/system/components/SiteHeader';
-import InvokeTabs from 'features/ui/components/InvokeTabs';
-import { keepGUIAlive } from './utils';
-
-import useToastWatcher from 'features/system/hooks/useToastWatcher';
-
-import FloatingGalleryButton from 'features/ui/components/FloatingGalleryButton';
-import FloatingParametersPanelButtons from 'features/ui/components/FloatingParametersPanelButtons';
-import { Box, Flex, Grid, Portal, useColorMode } from '@chakra-ui/react';
-import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
-import ImageGalleryPanel from 'features/gallery/components/ImageGalleryPanel';
-import Lightbox from 'features/lightbox/components/Lightbox';
-import { useAppSelector } from './storeHooks';
-import { PropsWithChildren, useEffect } from 'react';
-
-keepGUIAlive();
-
-const App = (props: PropsWithChildren) => {
-  useToastWatcher();
-
-  const currentTheme = useAppSelector((state) => state.ui.currentTheme);
-  const { setColorMode } = useColorMode();
-
-  useEffect(() => {
-    setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
-  }, [setColorMode, currentTheme]);
-
-  return (
-    <Grid w="100vw" h="100vh">
-      <Lightbox />
-      <ImageUploader>
-        <ProgressBar />
-        <Grid
-          gap={4}
-          p={4}
-          gridAutoRows="min-content auto"
-          w={APP_WIDTH}
-          h={APP_HEIGHT}
-        >
-          {props.children || <SiteHeader />}
-          <Flex gap={4} w="full" h="full">
-            <InvokeTabs />
-            <ImageGalleryPanel />
-          </Flex>
-        </Grid>
-        <Box>
-          <Console />
-        </Box>
-      </ImageUploader>
-      <Portal>
-        <FloatingParametersPanelButtons />
-      </Portal>
-      <Portal>
-        <FloatingGalleryButton />
-      </Portal>
-    </Grid>
-  );
-};
-
-export default App;

invokeai/frontend/web/src/app/components/App.tsx

@@ -0,0 +1,129 @@
+import ImageUploader from 'common/components/ImageUploader';
+import ProgressBar from 'features/system/components/ProgressBar';
+import SiteHeader from 'features/system/components/SiteHeader';
+import InvokeTabs from 'features/ui/components/InvokeTabs';
+
+import useToastWatcher from 'features/system/hooks/useToastWatcher';
+
+import FloatingGalleryButton from 'features/ui/components/FloatingGalleryButton';
+import FloatingParametersPanelButtons from 'features/ui/components/FloatingParametersPanelButtons';
+import { Box, Flex, Grid, Portal, useColorMode } from '@chakra-ui/react';
+import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
+import ImageGalleryPanel from 'features/gallery/components/ImageGalleryPanel';
+import Lightbox from 'features/lightbox/components/Lightbox';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import {
+  memo,
+  PropsWithChildren,
+  useCallback,
+  useEffect,
+  useState,
+} from 'react';
+import { motion, AnimatePresence } from 'framer-motion';
+import Loading from 'common/components/Loading/Loading';
+import { useIsApplicationReady } from 'features/system/hooks/useIsApplicationReady';
+import { PartialAppConfig } from 'app/types/invokeai';
+import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
+import { configChanged } from 'features/system/store/configSlice';
+import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import { useLogger } from 'app/logging/useLogger';
+import ProgressImagePreview from 'features/parameters/components/ProgressImagePreview';
+
+const DEFAULT_CONFIG = {};
+
+interface Props extends PropsWithChildren {
+  config?: PartialAppConfig;
+}
+
+const App = ({ config = DEFAULT_CONFIG, children }: Props) => {
+  useToastWatcher();
+  useGlobalHotkeys();
+  const log = useLogger();
+
+  const currentTheme = useAppSelector((state) => state.ui.currentTheme);
+
+  const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
+
+  const isApplicationReady = useIsApplicationReady();
+
+  const [loadingOverridden, setLoadingOverridden] = useState(false);
+
+  const { setColorMode } = useColorMode();
+  const dispatch = useAppDispatch();
+
+  useEffect(() => {
+    log.info({ namespace: 'App', data: config }, 'Received config');
+    dispatch(configChanged(config));
+  }, [dispatch, config, log]);
+
+  useEffect(() => {
+    setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
+  }, [setColorMode, currentTheme]);
+
+  const handleOverrideClicked = useCallback(() => {
+    setLoadingOverridden(true);
+  }, []);
+
+  return (
+    <Grid w="100vw" h="100vh" position="relative" overflow="hidden">
+      {isLightboxEnabled && <Lightbox />}
+      <ImageUploader>
+        <ProgressBar />
+        <Grid
+          gap={4}
+          p={4}
+          gridAutoRows="min-content auto"
+          w={APP_WIDTH}
+          h={APP_HEIGHT}
+        >
+          {children || <SiteHeader />}
+          <Flex
+            gap={4}
+            w={{ base: '100vw', xl: 'full' }}
+            h="full"
+            flexDir={{ base: 'column', xl: 'row' }}
+          >
+            <InvokeTabs />
+            <ImageGalleryPanel />
+          </Flex>
+        </Grid>
+      </ImageUploader>
+
+      <AnimatePresence>
+        {!isApplicationReady && !loadingOverridden && (
+          <motion.div
+            key="loading"
+            initial={{ opacity: 1 }}
+            animate={{ opacity: 1 }}
+            exit={{ opacity: 0 }}
+            transition={{ duration: 0.3 }}
+            style={{ zIndex: 3 }}
+          >
+            <Box position="absolute" top={0} left={0} w="100vw" h="100vh">
+              <Loading />
+            </Box>
+            <Box
+              onClick={handleOverrideClicked}
+              position="absolute"
+              top={0}
+              right={0}
+              cursor="pointer"
+              w="2rem"
+              h="2rem"
+            />
+          </motion.div>
+        )}
+      </AnimatePresence>
+
+      <Portal>
+        <FloatingParametersPanelButtons />
+      </Portal>
+      <Portal>
+        <FloatingGalleryButton />
+      </Portal>
+      <ProgressImagePreview />
+    </Grid>
+  );
+};
+
+export default memo(App);

invokeai/frontend/web/src/app/components/InvokeAIUI.tsx

@@ -0,0 +1,72 @@
+import React, { lazy, memo, PropsWithChildren, useEffect } from 'react';
+import { Provider } from 'react-redux';
+import { PersistGate } from 'redux-persist/integration/react';
+import { store } from 'app/store/store';
+import { persistor } from '../store/persistor';
+import { OpenAPI } from 'services/api';
+import '@fontsource/inter/100.css';
+import '@fontsource/inter/200.css';
+import '@fontsource/inter/300.css';
+import '@fontsource/inter/400.css';
+import '@fontsource/inter/500.css';
+import '@fontsource/inter/600.css';
+import '@fontsource/inter/700.css';
+import '@fontsource/inter/800.css';
+import '@fontsource/inter/900.css';
+
+import Loading from '../../common/components/Loading/Loading';
+import { addMiddleware, resetMiddlewares } from 'redux-dynamic-middlewares';
+import { PartialAppConfig } from 'app/types/invokeai';
+
+import '../../i18n';
+import { socketMiddleware } from 'services/events/middleware';
+
+const App = lazy(() => import('./App'));
+const ThemeLocaleProvider = lazy(() => import('./ThemeLocaleProvider'));
+
+interface Props extends PropsWithChildren {
+  apiUrl?: string;
+  token?: string;
+  config?: PartialAppConfig;
+}
+
+const InvokeAIUI = ({ apiUrl, token, config, children }: Props) => {
+  useEffect(() => {
+    // configure API client token
+    if (token) {
+      OpenAPI.TOKEN = token;
+    }
+
+    // configure API client base url
+    if (apiUrl) {
+      OpenAPI.BASE = apiUrl;
+    }
+
+    // reset dynamically added middlewares
+    resetMiddlewares();
+
+    // TODO: at this point, after resetting the middleware, we really ought to clean up the socket
+    // stuff by calling `dispatch(socketReset())`. but we cannot dispatch from here as we are
+    // outside the provider. it's not needed until there is the possibility that we will change
+    // the `apiUrl`/`token` dynamically.
+
+    // rebuild socket middleware with token and apiUrl
+    addMiddleware(socketMiddleware());
+  }, [apiUrl, token]);
+
+  return (
+    <React.StrictMode>
+      <Provider store={store}>
+        <PersistGate loading={<Loading />} persistor={persistor}>
+          <React.Suspense fallback={<Loading />}>
+            <ThemeLocaleProvider>
+              <App config={config}>{children}</App>
+            </ThemeLocaleProvider>
+          </React.Suspense>
+        </PersistGate>
+      </Provider>
+    </React.StrictMode>
+  );
+};
+
+export default memo(InvokeAIUI);

invokeai/frontend/web/src/app/components/ThemeLocaleProvider.tsx

@@ -2,8 +2,8 @@ import { ChakraProvider, extendTheme } from '@chakra-ui/react';
 import { ReactNode, useEffect } from 'react';
 import { useTranslation } from 'react-i18next';
 import { theme as invokeAITheme } from 'theme/theme';
-import { RootState } from './store';
-import { useAppSelector } from './storeHooks';
+import { RootState } from 'app/store/store';
+import { useAppSelector } from 'app/store/storeHooks';
 
 import { greenTeaThemeColors } from 'theme/colors/greenTea';
 import { invokeAIThemeColors } from 'theme/colors/invokeAI';

invokeai/frontend/web/src/app/constants.ts

@@ -1,23 +1,6 @@
 // TODO: use Enums?
 
-import { InProgressImageType } from 'features/system/store/systemSlice';
-
-// Valid samplers
-export const SAMPLERS: Array<string> = [
-  'ddim',
-  'plms',
-  'k_lms',
-  'k_dpm_2',
-  'k_dpm_2_a',
-  'k_dpmpp_2',
-  'k_dpmpp_2_a',
-  'k_euler',
-  'k_euler_a',
-  'k_heun',
-];
-
-// Valid Diffusers Samplers
-export const DIFFUSERS_SAMPLERS: Array<string> = [
+export const DIFFUSERS_SCHEDULERS: Array<string> = [
   'ddim',
   'plms',
   'k_lms',
@@ -31,13 +14,13 @@ export const DIFFUSERS_SAMPLERS: Array<string> = [
 ];
 
 // Valid image widths
-export const WIDTHS: Array<number> = Array.from(Array(65)).map(
-  (_x, i) => i * 64
+export const WIDTHS: Array<number> = Array.from(Array(64)).map(
+  (_x, i) => (i + 1) * 64
 );
 
 // Valid image heights
-export const HEIGHTS: Array<number> = Array.from(Array(65)).map(
-  (_x, i) => i * 64
+export const HEIGHTS: Array<number> = Array.from(Array(64)).map(
+  (_x, i) => (i + 1) * 64
 );
 
 // Valid upscaling levels
@@ -48,15 +31,8 @@ export const UPSCALING_LEVELS: Array<{ key: string; value: number }> = [
 
 export const NUMPY_RAND_MIN = 0;
 
-export const NUMPY_RAND_MAX = 4294967295;
+export const NUMPY_RAND_MAX = 2147483647;
 
 export const FACETOOL_TYPES = ['gfpgan', 'codeformer'] as const;
 
-export const IN_PROGRESS_IMAGE_TYPES: Array<{
-  key: string;
-  value: InProgressImageType;
-}> = [
-  { key: 'None', value: 'none' },
-  { key: 'Fast', value: 'latents' },
-  { key: 'Accurate', value: 'full-res' },
-];
+export const NODE_MIN_WIDTH = 250;

invokeai/frontend/web/src/app/invokeai.d.ts

@@ -1,322 +0,0 @@
-/**
- * Types for images, the things they are made of, and the things
- * they make up.
- *
- * Generated images are txt2img and img2img images. They may have
- * had additional postprocessing done on them when they were first
- * generated.
- *
- * Postprocessed images are images which were not generated here
- * but only postprocessed by the app. They only get postprocessing
- * metadata and have a different image type, e.g. 'esrgan' or
- * 'gfpgan'.
- */
-
-import { InvokeTabName } from 'features/ui/store/tabMap';
-import { IRect } from 'konva/lib/types';
-
-/**
- * TODO:
- * Once an image has been generated, if it is postprocessed again,
- * additional postprocessing steps are added to its postprocessing
- * array.
- *
- * TODO: Better documentation of types.
- */
-
-export declare type PromptItem = {
-  prompt: string;
-  weight: number;
-};
-
-// TECHDEBT: We need to retain compatibility with plain prompt strings and the structure Prompt type
-export declare type Prompt = Array<PromptItem> | string;
-
-export declare type SeedWeightPair = {
-  seed: number;
-  weight: number;
-};
-
-export declare type SeedWeights = Array<SeedWeightPair>;
-
-// All generated images contain these metadata.
-export declare type CommonGeneratedImageMetadata = {
-  postprocessing: null | Array<ESRGANMetadata | GFPGANMetadata>;
-  sampler:
-    | 'ddim'
-    | 'k_dpm_2_a'
-    | 'k_dpm_2'
-    | 'k_dpmpp_2_a'
-    | 'k_dpmpp_2'
-    | 'k_euler_a'
-    | 'k_euler'
-    | 'k_heun'
-    | 'k_lms'
-    | 'plms';
-  prompt: Prompt;
-  seed: number;
-  variations: SeedWeights;
-  steps: number;
-  cfg_scale: number;
-  width: number;
-  height: number;
-  seamless: boolean;
-  hires_fix: boolean;
-  extra: null | Record<string, never>; // Pending development of RFC #266
-};
-
-// txt2img and img2img images have some unique attributes.
-export declare type Txt2ImgMetadata = GeneratedImageMetadata & {
-  type: 'txt2img';
-};
-
-export declare type Img2ImgMetadata = GeneratedImageMetadata & {
-  type: 'img2img';
-  orig_hash: string;
-  strength: number;
-  fit: boolean;
-  init_image_path: string;
-  mask_image_path?: string;
-};
-
-// Superset of  generated image metadata types.
-export declare type GeneratedImageMetadata = Txt2ImgMetadata | Img2ImgMetadata;
-
-// All post processed images contain these metadata.
-export declare type CommonPostProcessedImageMetadata = {
-  orig_path: string;
-  orig_hash: string;
-};
-
-// esrgan and gfpgan images have some unique attributes.
-export declare type ESRGANMetadata = CommonPostProcessedImageMetadata & {
-  type: 'esrgan';
-  scale: 2 | 4;
-  strength: number;
-  denoise_str: number;
-};
-
-export declare type FacetoolMetadata = CommonPostProcessedImageMetadata & {
-  type: 'gfpgan' | 'codeformer';
-  strength: number;
-  fidelity?: number;
-};
-
-// Superset of all postprocessed image metadata types..
-export declare type PostProcessedImageMetadata =
-  | ESRGANMetadata
-  | FacetoolMetadata;
-
-// Metadata includes the system config and image metadata.
-export declare type Metadata = SystemGenerationMetadata & {
-  image: GeneratedImageMetadata | PostProcessedImageMetadata;
-};
-
-// An Image has a UUID, url, modified timestamp, width, height and maybe metadata
-export declare type Image = {
-  uuid: string;
-  url: string;
-  thumbnail: string;
-  mtime: number;
-  metadata?: Metadata;
-  width: number;
-  height: number;
-  category: GalleryCategory;
-  isBase64?: boolean;
-  dreamPrompt?: 'string';
-};
-
-// GalleryImages is an array of Image.
-export declare type GalleryImages = {
-  images: Array<Image>;
-};
-
-/**
- * Types related to the system status.
- */
-
-// This represents the processing status of the backend.
-export declare type SystemStatus = {
-  isProcessing: boolean;
-  currentStep: number;
-  totalSteps: number;
-  currentIteration: number;
-  totalIterations: number;
-  currentStatus: string;
-  currentStatusHasSteps: boolean;
-  hasError: boolean;
-};
-
-export declare type SystemGenerationMetadata = {
-  model: string;
-  model_weights?: string;
-  model_id?: string;
-  model_hash: string;
-  app_id: string;
-  app_version: string;
-};
-
-export declare type SystemConfig = SystemGenerationMetadata & {
-  model_list: ModelList;
-  infill_methods: string[];
-};
-
-export declare type ModelStatus = 'active' | 'cached' | 'not loaded';
-
-export declare type Model = {
-  status: ModelStatus;
-  description: string;
-  weights: string;
-  config?: string;
-  vae?: string;
-  width?: number;
-  height?: number;
-  default?: boolean;
-  format?: string;
-};
-
-export declare type DiffusersModel = {
-  status: ModelStatus;
-  description: string;
-  repo_id?: string;
-  path?: string;
-  vae?: {
-    repo_id?: string;
-    path?: string;
-  };
-  format?: string;
-  default?: boolean;
-};
-
-export declare type ModelList = Record<string, Model & DiffusersModel>;
-
-export declare type FoundModel = {
-  name: string;
-  location: string;
-};
-
-export declare type InvokeModelConfigProps = {
-  name: string | undefined;
-  description: string | undefined;
-  config: string | undefined;
-  weights: string | undefined;
-  vae: string | undefined;
-  width: number | undefined;
-  height: number | undefined;
-  default: boolean | undefined;
-  format: string | undefined;
-};
-
-export declare type InvokeDiffusersModelConfigProps = {
-  name: string | undefined;
-  description: string | undefined;
-  repo_id: string | undefined;
-  path: string | undefined;
-  default: boolean | undefined;
-  format: string | undefined;
-  vae: {
-    repo_id: string | undefined;
-    path: string | undefined;
-  };
-};
-
-export declare type InvokeModelConversionProps = {
-  model_name: string;
-  save_location: string;
-  custom_location: string | null;
-};
-
-export declare type InvokeModelMergingProps = {
-  models_to_merge: string[];
-  alpha: number;
-  interp: 'weighted_sum' | 'sigmoid' | 'inv_sigmoid' | 'add_difference';
-  force: boolean;
-  merged_model_name: string;
-  model_merge_save_path: string | null;
-};
-
-/**
- * These types type data received from the server via socketio.
- */
-
-export declare type ModelChangeResponse = {
-  model_name: string;
-  model_list: ModelList;
-};
-
-export declare type ModelConvertedResponse = {
-  converted_model_name: string;
-  model_list: ModelList;
-};
-
-export declare type ModelsMergedResponse = {
-  merged_models: string[];
-  merged_model_name: string;
-  model_list: ModelList;
-};
-
-export declare type ModelAddedResponse = {
-  new_model_name: string;
-  model_list: ModelList;
-  update: boolean;
-};
-
-export declare type ModelDeletedResponse = {
-  deleted_model_name: string;
-  model_list: ModelList;
-};
-
-export declare type FoundModelResponse = {
-  search_folder: string;
-  found_models: FoundModel[];
-};
-
-export declare type SystemStatusResponse = SystemStatus;
-
-export declare type SystemConfigResponse = SystemConfig;
-
-export declare type ImageResultResponse = Omit<Image, 'uuid'> & {
-  boundingBox?: IRect;
-  generationMode: InvokeTabName;
-};
-
-export declare type ImageUploadResponse = {
-  // image: Omit<Image, 'uuid' | 'metadata' | 'category'>;
-  url: string;
-  mtime: number;
-  width: number;
-  height: number;
-  thumbnail: string;
-  // bbox: [number, number, number, number];
-};
-
-export declare type ErrorResponse = {
-  message: string;
-  additionalData?: string;
-};
-
-export declare type GalleryImagesResponse = {
-  images: Array<Omit<Image, 'uuid'>>;
-  areMoreImagesAvailable: boolean;
-  category: GalleryCategory;
-};
-
-export declare type ImageDeletedResponse = {
-  uuid: string;
-  url: string;
-  category: GalleryCategory;
-};
-
-export declare type ImageUrlResponse = {
-  url: string;
-};
-
-export declare type UploadImagePayload = {
-  file: File;
-  destination?: ImageUploadDestination;
-};
-
-export declare type UploadOutpaintingMergeImagePayload = {
-  dataURL: string;
-  name: string;
-};

invokeai/frontend/web/src/app/logging/useLogger.ts

@@ -0,0 +1,94 @@
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { systemSelector } from 'features/system/store/systemSelectors';
+import { isEqual } from 'lodash-es';
+import { useEffect } from 'react';
+import { LogLevelName, ROARR, Roarr } from 'roarr';
+import { createLogWriter } from '@roarr/browser-log-writer';
+
+// Base logging context includes only the package name
+const baseContext = { package: '@invoke-ai/invoke-ai-ui' };
+
+// Create browser log writer
+ROARR.write = createLogWriter();
+
+// Module-scoped logger - can be imported and used anywhere
+export let log = Roarr.child(baseContext);
+
+// Translate human-readable log levels to numbers, used for log filtering
+export const LOG_LEVEL_MAP: Record<LogLevelName, number> = {
+  trace: 10,
+  debug: 20,
+  info: 30,
+  warn: 40,
+  error: 50,
+  fatal: 60,
+};
+
+export const VALID_LOG_LEVELS = [
+  'trace',
+  'debug',
+  'info',
+  'warn',
+  'error',
+  'fatal',
+] as const;
+
+export type InvokeLogLevel = (typeof VALID_LOG_LEVELS)[number];
+
+const selector = createSelector(
+  systemSelector,
+  (system) => {
+    const { app_version, consoleLogLevel, shouldLogToConsole } = system;
+
+    return {
+      version: app_version,
+      consoleLogLevel,
+      shouldLogToConsole,
+    };
+  },
+  {
+    memoizeOptions: {
+      resultEqualityCheck: isEqual,
+    },
+  }
+);
+
+export const useLogger = () => {
+  const { version, consoleLogLevel, shouldLogToConsole } =
+    useAppSelector(selector);
+
+  // The provided Roarr browser log writer uses localStorage to config logging to console
+  useEffect(() => {
+    if (shouldLogToConsole) {
+      // Enable console log output
+      localStorage.setItem('ROARR_LOG', 'true');
+
+      // Use a filter to show only logs of the given level
+      localStorage.setItem(
+        'ROARR_FILTER',
+        `context.logLevel:>=${LOG_LEVEL_MAP[consoleLogLevel]}`
+      );
+    } else {
+      // Disable console log output
+      localStorage.setItem('ROARR_LOG', 'false');
+    }
+    ROARR.write = createLogWriter();
+  }, [consoleLogLevel, shouldLogToConsole]);
+
+  // Update the module-scoped logger context as needed
+  useEffect(() => {
+    const newContext: Record<string, any> = {
+      ...baseContext,
+    };
+
+    if (version) {
+      newContext.version = version;
+    }
+
+    log = Roarr.child(newContext);
+  }, [version]);
+
+  // Use the logger within components - no different than just importing it directly
+  return log;
+};

invokeai/frontend/web/src/app/selectors/readinessSelector.ts

@@ -4,7 +4,7 @@ import { initialCanvasImageSelector } from 'features/canvas/store/canvasSelector
 import { generationSelector } from 'features/parameters/store/generationSelectors';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { isEqual } from 'lodash';
+import { isEqual } from 'lodash-es';
 
 export const readinessSelector = createSelector(
   [
@@ -20,6 +20,7 @@ export const readinessSelector = createSelector(
       seedWeights,
       initialImage,
       seed,
+      isImageToImageEnabled,
     } = generation;
 
     const { isProcessing, isConnected } = system;
@@ -33,7 +34,7 @@ export const readinessSelector = createSelector(
       reasonsWhyNotReady.push('Missing prompt');
     }
 
-    if (activeTabName === 'img2img' && !initialImage) {
+    if (isImageToImageEnabled && !initialImage) {
       isReady = false;
       reasonsWhyNotReady.push('No initial image selected');
     }

invokeai/frontend/web/src/app/socketio/actions.ts

@@ -1,61 +1,67 @@
-import { createAction } from '@reduxjs/toolkit';
-import * as InvokeAI from 'app/invokeai';
-import { GalleryCategory } from 'features/gallery/store/gallerySlice';
-import { InvokeTabName } from 'features/ui/store/tabMap';
+// import { createAction } from '@reduxjs/toolkit';
+// import * as InvokeAI from 'app/types/invokeai';
+// import { GalleryCategory } from 'features/gallery/store/gallerySlice';
+// import { InvokeTabName } from 'features/ui/store/tabMap';
 
-/**
- * We can't use redux-toolkit's createSlice() to make these actions,
- * because they have no associated reducer. They only exist to dispatch
- * requests to the server via socketio. These actions will be handled
- * by the middleware.
- */
+// /**
+//  * We can't use redux-toolkit's createSlice() to make these actions,
+//  * because they have no associated reducer. They only exist to dispatch
+//  * requests to the server via socketio. These actions will be handled
+//  * by the middleware.
+//  */
 
-export const generateImage = createAction<InvokeTabName>(
-  'socketio/generateImage'
-);
-export const runESRGAN = createAction<InvokeAI.Image>('socketio/runESRGAN');
-export const runFacetool = createAction<InvokeAI.Image>('socketio/runFacetool');
-export const deleteImage = createAction<InvokeAI.Image>('socketio/deleteImage');
-export const requestImages = createAction<GalleryCategory>(
-  'socketio/requestImages'
-);
-export const requestNewImages = createAction<GalleryCategory>(
-  'socketio/requestNewImages'
-);
-export const cancelProcessing = createAction<undefined>(
-  'socketio/cancelProcessing'
-);
+// export const generateImage = createAction<InvokeTabName>(
+//   'socketio/generateImage'
+// );
+// export const runESRGAN = createAction<InvokeAI._Image>('socketio/runESRGAN');
+// export const runFacetool = createAction<InvokeAI._Image>(
+//   'socketio/runFacetool'
+// );
+// export const deleteImage = createAction<InvokeAI._Image>(
+//   'socketio/deleteImage'
+// );
+// export const requestImages = createAction<GalleryCategory>(
+//   'socketio/requestImages'
+// );
+// export const requestNewImages = createAction<GalleryCategory>(
+//   'socketio/requestNewImages'
+// );
+// export const cancelProcessing = createAction<undefined>(
+//   'socketio/cancelProcessing'
+// );
 
-export const requestSystemConfig = createAction<undefined>(
-  'socketio/requestSystemConfig'
-);
+// export const requestSystemConfig = createAction<undefined>(
+//   'socketio/requestSystemConfig'
+// );
 
-export const searchForModels = createAction<string>('socketio/searchForModels');
+// export const searchForModels = createAction<string>('socketio/searchForModels');
 
-export const addNewModel = createAction<
-  InvokeAI.InvokeModelConfigProps | InvokeAI.InvokeDiffusersModelConfigProps
->('socketio/addNewModel');
+// export const addNewModel = createAction<
+//   InvokeAI.InvokeModelConfigProps | InvokeAI.InvokeDiffusersModelConfigProps
+// >('socketio/addNewModel');
 
-export const deleteModel = createAction<string>('socketio/deleteModel');
+// export const deleteModel = createAction<string>('socketio/deleteModel');
 
-export const convertToDiffusers =
-  createAction<InvokeAI.InvokeModelConversionProps>(
-    'socketio/convertToDiffusers'
-  );
+// export const convertToDiffusers =
+//   createAction<InvokeAI.InvokeModelConversionProps>(
+//     'socketio/convertToDiffusers'
+//   );
 
-export const mergeDiffusersModels =
-  createAction<InvokeAI.InvokeModelMergingProps>(
-    'socketio/mergeDiffusersModels'
-  );
+// export const mergeDiffusersModels =
+//   createAction<InvokeAI.InvokeModelMergingProps>(
+//     'socketio/mergeDiffusersModels'
+//   );
 
-export const requestModelChange = createAction<string>(
-  'socketio/requestModelChange'
-);
+// export const requestModelChange = createAction<string>(
+//   'socketio/requestModelChange'
+// );
 
-export const saveStagingAreaImageToGallery = createAction<string>(
-  'socketio/saveStagingAreaImageToGallery'
-);
+// export const saveStagingAreaImageToGallery = createAction<string>(
+//   'socketio/saveStagingAreaImageToGallery'
+// );
 
-export const emptyTempFolder = createAction<undefined>(
-  'socketio/requestEmptyTempFolder'
-);
+// export const emptyTempFolder = createAction<undefined>(
+//   'socketio/requestEmptyTempFolder'
+// );
+
+export default {};

invokeai/frontend/web/src/app/socketio/emitters.ts

@@ -1,208 +1,209 @@
-import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
-import * as InvokeAI from 'app/invokeai';
-import type { RootState } from 'app/store';
-import {
-  frontendToBackendParameters,
-  FrontendToBackendParametersConfig,
-} from 'common/util/parameterTranslation';
-import dateFormat from 'dateformat';
-import {
-  GalleryCategory,
-  GalleryState,
-  removeImage,
-} from 'features/gallery/store/gallerySlice';
-import {
-  addLogEntry,
-  generationRequested,
-  modelChangeRequested,
-  modelConvertRequested,
-  modelMergingRequested,
-  setIsProcessing,
-} from 'features/system/store/systemSlice';
-import { InvokeTabName } from 'features/ui/store/tabMap';
-import { Socket } from 'socket.io-client';
+// import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
+// import * as InvokeAI from 'app/types/invokeai';
+// import type { RootState } from 'app/store/store';
+// import {
+//   frontendToBackendParameters,
+//   FrontendToBackendParametersConfig,
+// } from 'common/util/parameterTranslation';
+// import dateFormat from 'dateformat';
+// import {
+//   GalleryCategory,
+//   GalleryState,
+//   removeImage,
+// } from 'features/gallery/store/gallerySlice';
+// import {
+//   generationRequested,
+//   modelChangeRequested,
+//   modelConvertRequested,
+//   modelMergingRequested,
+//   setIsProcessing,
+// } from 'features/system/store/systemSlice';
+// import { InvokeTabName } from 'features/ui/store/tabMap';
+// import { Socket } from 'socket.io-client';
 
-/**
- * Returns an object containing all functions which use `socketio.emit()`.
- * i.e. those which make server requests.
- */
-const makeSocketIOEmitters = (
-  store: MiddlewareAPI<Dispatch<AnyAction>, RootState>,
-  socketio: Socket
-) => {
-  // We need to dispatch actions to redux and get pieces of state from the store.
-  const { dispatch, getState } = store;
+// /**
+//  * Returns an object containing all functions which use `socketio.emit()`.
+//  * i.e. those which make server requests.
+//  */
+// const makeSocketIOEmitters = (
+//   store: MiddlewareAPI<Dispatch<AnyAction>, RootState>,
+//   socketio: Socket
+// ) => {
+//   // We need to dispatch actions to redux and get pieces of state from the store.
+//   const { dispatch, getState } = store;
 
-  return {
-    emitGenerateImage: (generationMode: InvokeTabName) => {
-      dispatch(setIsProcessing(true));
+//   return {
+//     emitGenerateImage: (generationMode: InvokeTabName) => {
+//       dispatch(setIsProcessing(true));
 
-      const state: RootState = getState();
+//       const state: RootState = getState();
 
-      const {
-        generation: generationState,
-        postprocessing: postprocessingState,
-        system: systemState,
-        canvas: canvasState,
-      } = state;
+//       const {
+//         generation: generationState,
+//         postprocessing: postprocessingState,
+//         system: systemState,
+//         canvas: canvasState,
+//       } = state;
 
-      const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
-        {
-          generationMode,
-          generationState,
-          postprocessingState,
-          canvasState,
-          systemState,
-        };
+//       const frontendToBackendParametersConfig: FrontendToBackendParametersConfig =
+//         {
+//           generationMode,
+//           generationState,
+//           postprocessingState,
+//           canvasState,
+//           systemState,
+//         };
 
-      dispatch(generationRequested());
+//       dispatch(generationRequested());
 
-      const { generationParameters, esrganParameters, facetoolParameters } =
-        frontendToBackendParameters(frontendToBackendParametersConfig);
+//       const { generationParameters, esrganParameters, facetoolParameters } =
+//         frontendToBackendParameters(frontendToBackendParametersConfig);
 
-      socketio.emit(
-        'generateImage',
-        generationParameters,
-        esrganParameters,
-        facetoolParameters
-      );
+//       socketio.emit(
+//         'generateImage',
+//         generationParameters,
+//         esrganParameters,
+//         facetoolParameters
+//       );
 
-      // we need to truncate the init_mask base64 else it takes up the whole log
-      // TODO: handle maintaining masks for reproducibility in future
-      if (generationParameters.init_mask) {
-        generationParameters.init_mask = generationParameters.init_mask
-          .substr(0, 64)
-          .concat('...');
-      }
-      if (generationParameters.init_img) {
-        generationParameters.init_img = generationParameters.init_img
-          .substr(0, 64)
-          .concat('...');
-      }
+//       // we need to truncate the init_mask base64 else it takes up the whole log
+//       // TODO: handle maintaining masks for reproducibility in future
+//       if (generationParameters.init_mask) {
+//         generationParameters.init_mask = generationParameters.init_mask
+//           .substr(0, 64)
+//           .concat('...');
+//       }
+//       if (generationParameters.init_img) {
+//         generationParameters.init_img = generationParameters.init_img
+//           .substr(0, 64)
+//           .concat('...');
+//       }
 
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Image generation requested: ${JSON.stringify({
-            ...generationParameters,
-            ...esrganParameters,
-            ...facetoolParameters,
-          })}`,
-        })
-      );
-    },
-    emitRunESRGAN: (imageToProcess: InvokeAI.Image) => {
-      dispatch(setIsProcessing(true));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Image generation requested: ${JSON.stringify({
+//             ...generationParameters,
+//             ...esrganParameters,
+//             ...facetoolParameters,
+//           })}`,
+//         })
+//       );
+//     },
+//     emitRunESRGAN: (imageToProcess: InvokeAI._Image) => {
+//       dispatch(setIsProcessing(true));
 
-      const {
-        postprocessing: {
-          upscalingLevel,
-          upscalingDenoising,
-          upscalingStrength,
-        },
-      } = getState();
+//       const {
+//         postprocessing: {
+//           upscalingLevel,
+//           upscalingDenoising,
+//           upscalingStrength,
+//         },
+//       } = getState();
 
-      const esrganParameters = {
-        upscale: [upscalingLevel, upscalingDenoising, upscalingStrength],
-      };
-      socketio.emit('runPostprocessing', imageToProcess, {
-        type: 'esrgan',
-        ...esrganParameters,
-      });
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `ESRGAN upscale requested: ${JSON.stringify({
-            file: imageToProcess.url,
-            ...esrganParameters,
-          })}`,
-        })
-      );
-    },
-    emitRunFacetool: (imageToProcess: InvokeAI.Image) => {
-      dispatch(setIsProcessing(true));
+//       const esrganParameters = {
+//         upscale: [upscalingLevel, upscalingDenoising, upscalingStrength],
+//       };
+//       socketio.emit('runPostprocessing', imageToProcess, {
+//         type: 'esrgan',
+//         ...esrganParameters,
+//       });
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `ESRGAN upscale requested: ${JSON.stringify({
+//             file: imageToProcess.url,
+//             ...esrganParameters,
+//           })}`,
+//         })
+//       );
+//     },
+//     emitRunFacetool: (imageToProcess: InvokeAI._Image) => {
+//       dispatch(setIsProcessing(true));
 
-      const {
-        postprocessing: { facetoolType, facetoolStrength, codeformerFidelity },
-      } = getState();
+//       const {
+//         postprocessing: { facetoolType, facetoolStrength, codeformerFidelity },
+//       } = getState();
 
-      const facetoolParameters: Record<string, unknown> = {
-        facetool_strength: facetoolStrength,
-      };
+//       const facetoolParameters: Record<string, unknown> = {
+//         facetool_strength: facetoolStrength,
+//       };
 
-      if (facetoolType === 'codeformer') {
-        facetoolParameters.codeformer_fidelity = codeformerFidelity;
-      }
+//       if (facetoolType === 'codeformer') {
+//         facetoolParameters.codeformer_fidelity = codeformerFidelity;
+//       }
 
-      socketio.emit('runPostprocessing', imageToProcess, {
-        type: facetoolType,
-        ...facetoolParameters,
-      });
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Face restoration (${facetoolType}) requested: ${JSON.stringify(
-            {
-              file: imageToProcess.url,
-              ...facetoolParameters,
-            }
-          )}`,
-        })
-      );
-    },
-    emitDeleteImage: (imageToDelete: InvokeAI.Image) => {
-      const { url, uuid, category, thumbnail } = imageToDelete;
-      dispatch(removeImage(imageToDelete));
-      socketio.emit('deleteImage', url, thumbnail, uuid, category);
-    },
-    emitRequestImages: (category: GalleryCategory) => {
-      const gallery: GalleryState = getState().gallery;
-      const { earliest_mtime } = gallery.categories[category];
-      socketio.emit('requestImages', category, earliest_mtime);
-    },
-    emitRequestNewImages: (category: GalleryCategory) => {
-      const gallery: GalleryState = getState().gallery;
-      const { latest_mtime } = gallery.categories[category];
-      socketio.emit('requestLatestImages', category, latest_mtime);
-    },
-    emitCancelProcessing: () => {
-      socketio.emit('cancel');
-    },
-    emitRequestSystemConfig: () => {
-      socketio.emit('requestSystemConfig');
-    },
-    emitSearchForModels: (modelFolder: string) => {
-      socketio.emit('searchForModels', modelFolder);
-    },
-    emitAddNewModel: (modelConfig: InvokeAI.InvokeModelConfigProps) => {
-      socketio.emit('addNewModel', modelConfig);
-    },
-    emitDeleteModel: (modelName: string) => {
-      socketio.emit('deleteModel', modelName);
-    },
-    emitConvertToDiffusers: (
-      modelToConvert: InvokeAI.InvokeModelConversionProps
-    ) => {
-      dispatch(modelConvertRequested());
-      socketio.emit('convertToDiffusers', modelToConvert);
-    },
-    emitMergeDiffusersModels: (
-      modelMergeInfo: InvokeAI.InvokeModelMergingProps
-    ) => {
-      dispatch(modelMergingRequested());
-      socketio.emit('mergeDiffusersModels', modelMergeInfo);
-    },
-    emitRequestModelChange: (modelName: string) => {
-      dispatch(modelChangeRequested());
-      socketio.emit('requestModelChange', modelName);
-    },
-    emitSaveStagingAreaImageToGallery: (url: string) => {
-      socketio.emit('requestSaveStagingAreaImageToGallery', url);
-    },
-    emitRequestEmptyTempFolder: () => {
-      socketio.emit('requestEmptyTempFolder');
-    },
-  };
-};
+//       socketio.emit('runPostprocessing', imageToProcess, {
+//         type: facetoolType,
+//         ...facetoolParameters,
+//       });
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Face restoration (${facetoolType}) requested: ${JSON.stringify(
+//             {
+//               file: imageToProcess.url,
+//               ...facetoolParameters,
+//             }
+//           )}`,
+//         })
+//       );
+//     },
+//     emitDeleteImage: (imageToDelete: InvokeAI._Image) => {
+//       const { url, uuid, category, thumbnail } = imageToDelete;
+//       dispatch(removeImage(imageToDelete));
+//       socketio.emit('deleteImage', url, thumbnail, uuid, category);
+//     },
+//     emitRequestImages: (category: GalleryCategory) => {
+//       const gallery: GalleryState = getState().gallery;
+//       const { earliest_mtime } = gallery.categories[category];
+//       socketio.emit('requestImages', category, earliest_mtime);
+//     },
+//     emitRequestNewImages: (category: GalleryCategory) => {
+//       const gallery: GalleryState = getState().gallery;
+//       const { latest_mtime } = gallery.categories[category];
+//       socketio.emit('requestLatestImages', category, latest_mtime);
+//     },
+//     emitCancelProcessing: () => {
+//       socketio.emit('cancel');
+//     },
+//     emitRequestSystemConfig: () => {
+//       socketio.emit('requestSystemConfig');
+//     },
+//     emitSearchForModels: (modelFolder: string) => {
+//       socketio.emit('searchForModels', modelFolder);
+//     },
+//     emitAddNewModel: (modelConfig: InvokeAI.InvokeModelConfigProps) => {
+//       socketio.emit('addNewModel', modelConfig);
+//     },
+//     emitDeleteModel: (modelName: string) => {
+//       socketio.emit('deleteModel', modelName);
+//     },
+//     emitConvertToDiffusers: (
+//       modelToConvert: InvokeAI.InvokeModelConversionProps
+//     ) => {
+//       dispatch(modelConvertRequested());
+//       socketio.emit('convertToDiffusers', modelToConvert);
+//     },
+//     emitMergeDiffusersModels: (
+//       modelMergeInfo: InvokeAI.InvokeModelMergingProps
+//     ) => {
+//       dispatch(modelMergingRequested());
+//       socketio.emit('mergeDiffusersModels', modelMergeInfo);
+//     },
+//     emitRequestModelChange: (modelName: string) => {
+//       dispatch(modelChangeRequested());
+//       socketio.emit('requestModelChange', modelName);
+//     },
+//     emitSaveStagingAreaImageToGallery: (url: string) => {
+//       socketio.emit('requestSaveStagingAreaImageToGallery', url);
+//     },
+//     emitRequestEmptyTempFolder: () => {
+//       socketio.emit('requestEmptyTempFolder');
+//     },
+//   };
+// };
 
-export default makeSocketIOEmitters;
+// export default makeSocketIOEmitters;
+
+export default {};

invokeai/frontend/web/src/app/socketio/listeners.ts

@@ -1,498 +1,502 @@
-import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
-import dateFormat from 'dateformat';
-import i18n from 'i18n';
-import { v4 as uuidv4 } from 'uuid';
+// import { AnyAction, Dispatch, MiddlewareAPI } from '@reduxjs/toolkit';
+// import dateFormat from 'dateformat';
+// import i18n from 'i18n';
+// import { v4 as uuidv4 } from 'uuid';
 
-import * as InvokeAI from 'app/invokeai';
+// import * as InvokeAI from 'app/types/invokeai';
 
-import {
-  addLogEntry,
-  addToast,
-  errorOccurred,
-  processingCanceled,
-  setCurrentStatus,
-  setFoundModels,
-  setIsCancelable,
-  setIsConnected,
-  setIsProcessing,
-  setModelList,
-  setSearchFolder,
-  setSystemConfig,
-  setSystemStatus,
-} from 'features/system/store/systemSlice';
+// import {
+//   addToast,
+//   errorOccurred,
+//   processingCanceled,
+//   setCurrentStatus,
+//   setFoundModels,
+//   setIsCancelable,
+//   setIsConnected,
+//   setIsProcessing,
+//   setModelList,
+//   setSearchFolder,
+//   setSystemConfig,
+//   setSystemStatus,
+// } from 'features/system/store/systemSlice';
 
-import {
-  addGalleryImages,
-  addImage,
-  clearIntermediateImage,
-  GalleryState,
-  removeImage,
-  setIntermediateImage,
-} from 'features/gallery/store/gallerySlice';
+// import {
+//   addGalleryImages,
+//   addImage,
+//   clearIntermediateImage,
+//   GalleryState,
+//   removeImage,
+//   setIntermediateImage,
+// } from 'features/gallery/store/gallerySlice';
 
-import type { RootState } from 'app/store';
-import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
-import {
-  clearInitialImage,
-  setInfillMethod,
-  setInitialImage,
-  setMaskPath,
-} from 'features/parameters/store/generationSlice';
-import { tabMap } from 'features/ui/store/tabMap';
-import {
-  requestImages,
-  requestNewImages,
-  requestSystemConfig,
-} from './actions';
+// import type { RootState } from 'app/store/store';
+// import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
+// import {
+//   clearInitialImage,
+//   initialImageSelected,
+//   setInfillMethod,
+//   // setInitialImage,
+//   setMaskPath,
+// } from 'features/parameters/store/generationSlice';
+// import { tabMap } from 'features/ui/store/tabMap';
+// import {
+//   requestImages,
+//   requestNewImages,
+//   requestSystemConfig,
+// } from './actions';
 
-/**
- * Returns an object containing listener callbacks for socketio events.
- * TODO: This file is large, but simple. Should it be split up further?
- */
-const makeSocketIOListeners = (
-  store: MiddlewareAPI<Dispatch<AnyAction>, RootState>
-) => {
-  const { dispatch, getState } = store;
+// /**
+//  * Returns an object containing listener callbacks for socketio events.
+//  * TODO: This file is large, but simple. Should it be split up further?
+//  */
+// const makeSocketIOListeners = (
+//   store: MiddlewareAPI<Dispatch<AnyAction>, RootState>
+// ) => {
+//   const { dispatch, getState } = store;
 
-  return {
-    /**
-     * Callback to run when we receive a 'connect' event.
-     */
-    onConnect: () => {
-      try {
-        dispatch(setIsConnected(true));
-        dispatch(setCurrentStatus(i18n.t('common.statusConnected')));
-        dispatch(requestSystemConfig());
-        const gallery: GalleryState = getState().gallery;
+//   return {
+//     /**
+//      * Callback to run when we receive a 'connect' event.
+//      */
+//     onConnect: () => {
+//       try {
+//         dispatch(setIsConnected(true));
+//         dispatch(setCurrentStatus(i18n.t('common.statusConnected')));
+//         dispatch(requestSystemConfig());
+//         const gallery: GalleryState = getState().gallery;
 
-        if (gallery.categories.result.latest_mtime) {
-          dispatch(requestNewImages('result'));
-        } else {
-          dispatch(requestImages('result'));
-        }
+//         if (gallery.categories.result.latest_mtime) {
+//           dispatch(requestNewImages('result'));
+//         } else {
+//           dispatch(requestImages('result'));
+//         }
 
-        if (gallery.categories.user.latest_mtime) {
-          dispatch(requestNewImages('user'));
-        } else {
-          dispatch(requestImages('user'));
-        }
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'disconnect' event.
-     */
-    onDisconnect: () => {
-      try {
-        dispatch(setIsConnected(false));
-        dispatch(setCurrentStatus(i18n.t('common.statusDisconnected')));
+//         if (gallery.categories.user.latest_mtime) {
+//           dispatch(requestNewImages('user'));
+//         } else {
+//           dispatch(requestImages('user'));
+//         }
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'disconnect' event.
+//      */
+//     onDisconnect: () => {
+//       try {
+//         dispatch(setIsConnected(false));
+//         dispatch(setCurrentStatus(i18n.t('common.statusDisconnected')));
 
-        dispatch(
-          addLogEntry({
-            timestamp: dateFormat(new Date(), 'isoDateTime'),
-            message: `Disconnected from server`,
-            level: 'warning',
-          })
-        );
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'generationResult' event.
-     */
-    onGenerationResult: (data: InvokeAI.ImageResultResponse) => {
-      try {
-        const state = getState();
-        const { activeTab } = state.ui;
-        const { shouldLoopback } = state.postprocessing;
-        const { boundingBox: _, generationMode, ...rest } = data;
+//         dispatch(
+//           addLogEntry({
+//             timestamp: dateFormat(new Date(), 'isoDateTime'),
+//             message: `Disconnected from server`,
+//             level: 'warning',
+//           })
+//         );
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'generationResult' event.
+//      */
+//     onGenerationResult: (data: InvokeAI.ImageResultResponse) => {
+//       try {
+//         const state = getState();
+//         const { activeTab } = state.ui;
+//         const { shouldLoopback } = state.postprocessing;
+//         const { boundingBox: _, generationMode, ...rest } = data;
 
-        const newImage = {
-          uuid: uuidv4(),
-          ...rest,
-        };
+//         const newImage = {
+//           uuid: uuidv4(),
+//           ...rest,
+//         };
 
-        if (['txt2img', 'img2img'].includes(generationMode)) {
-          dispatch(
-            addImage({
-              category: 'result',
-              image: { ...newImage, category: 'result' },
-            })
-          );
-        }
+//         if (['txt2img', 'img2img'].includes(generationMode)) {
+//           dispatch(
+//             addImage({
+//               category: 'result',
+//               image: { ...newImage, category: 'result' },
+//             })
+//           );
+//         }
 
-        if (generationMode === 'unifiedCanvas' && data.boundingBox) {
-          const { boundingBox } = data;
-          dispatch(
-            addImageToStagingArea({
-              image: { ...newImage, category: 'temp' },
-              boundingBox,
-            })
-          );
+//         if (generationMode === 'unifiedCanvas' && data.boundingBox) {
+//           const { boundingBox } = data;
+//           dispatch(
+//             addImageToStagingArea({
+//               image: { ...newImage, category: 'temp' },
+//               boundingBox,
+//             })
+//           );
 
-          if (state.canvas.shouldAutoSave) {
-            dispatch(
-              addImage({
-                image: { ...newImage, category: 'result' },
-                category: 'result',
-              })
-            );
-          }
-        }
+//           if (state.canvas.shouldAutoSave) {
+//             dispatch(
+//               addImage({
+//                 image: { ...newImage, category: 'result' },
+//                 category: 'result',
+//               })
+//             );
+//           }
+//         }
 
-        if (shouldLoopback) {
-          const activeTabName = tabMap[activeTab];
-          switch (activeTabName) {
-            case 'img2img': {
-              dispatch(setInitialImage(newImage));
-              break;
-            }
-          }
-        }
+//         // TODO: fix
+//         // if (shouldLoopback) {
+//         //   const activeTabName = tabMap[activeTab];
+//         //   switch (activeTabName) {
+//         //     case 'img2img': {
+//         //       dispatch(initialImageSelected(newImage.uuid));
+//         //       // dispatch(setInitialImage(newImage));
+//         //       break;
+//         //     }
+//         //   }
+//         // }
 
-        dispatch(clearIntermediateImage());
+//         dispatch(clearIntermediateImage());
 
-        dispatch(
-          addLogEntry({
-            timestamp: dateFormat(new Date(), 'isoDateTime'),
-            message: `Image generated: ${data.url}`,
-          })
-        );
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'intermediateResult' event.
-     */
-    onIntermediateResult: (data: InvokeAI.ImageResultResponse) => {
-      try {
-        dispatch(
-          setIntermediateImage({
-            uuid: uuidv4(),
-            ...data,
-            category: 'result',
-          })
-        );
-        if (!data.isBase64) {
-          dispatch(
-            addLogEntry({
-              timestamp: dateFormat(new Date(), 'isoDateTime'),
-              message: `Intermediate image generated: ${data.url}`,
-            })
-          );
-        }
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive an 'esrganResult' event.
-     */
-    onPostprocessingResult: (data: InvokeAI.ImageResultResponse) => {
-      try {
-        dispatch(
-          addImage({
-            category: 'result',
-            image: {
-              uuid: uuidv4(),
-              ...data,
-              category: 'result',
-            },
-          })
-        );
+//         dispatch(
+//           addLogEntry({
+//             timestamp: dateFormat(new Date(), 'isoDateTime'),
+//             message: `Image generated: ${data.url}`,
+//           })
+//         );
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'intermediateResult' event.
+//      */
+//     onIntermediateResult: (data: InvokeAI.ImageResultResponse) => {
+//       try {
+//         dispatch(
+//           setIntermediateImage({
+//             uuid: uuidv4(),
+//             ...data,
+//             category: 'result',
+//           })
+//         );
+//         if (!data.isBase64) {
+//           dispatch(
+//             addLogEntry({
+//               timestamp: dateFormat(new Date(), 'isoDateTime'),
+//               message: `Intermediate image generated: ${data.url}`,
+//             })
+//           );
+//         }
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive an 'esrganResult' event.
+//      */
+//     onPostprocessingResult: (data: InvokeAI.ImageResultResponse) => {
+//       try {
+//         dispatch(
+//           addImage({
+//             category: 'result',
+//             image: {
+//               uuid: uuidv4(),
+//               ...data,
+//               category: 'result',
+//             },
+//           })
+//         );
 
-        dispatch(
-          addLogEntry({
-            timestamp: dateFormat(new Date(), 'isoDateTime'),
-            message: `Postprocessed: ${data.url}`,
-          })
-        );
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'progressUpdate' event.
-     * TODO: Add additional progress phases
-     */
-    onProgressUpdate: (data: InvokeAI.SystemStatus) => {
-      try {
-        dispatch(setIsProcessing(true));
-        dispatch(setSystemStatus(data));
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'progressUpdate' event.
-     */
-    onError: (data: InvokeAI.ErrorResponse) => {
-      const { message, additionalData } = data;
+//         dispatch(
+//           addLogEntry({
+//             timestamp: dateFormat(new Date(), 'isoDateTime'),
+//             message: `Postprocessed: ${data.url}`,
+//           })
+//         );
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'progressUpdate' event.
+//      * TODO: Add additional progress phases
+//      */
+//     onProgressUpdate: (data: InvokeAI.SystemStatus) => {
+//       try {
+//         dispatch(setIsProcessing(true));
+//         dispatch(setSystemStatus(data));
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'progressUpdate' event.
+//      */
+//     onError: (data: InvokeAI.ErrorResponse) => {
+//       const { message, additionalData } = data;
 
-      if (additionalData) {
-        // TODO: handle more data than short message
-      }
+//       if (additionalData) {
+//         // TODO: handle more data than short message
+//       }
 
-      try {
-        dispatch(
-          addLogEntry({
-            timestamp: dateFormat(new Date(), 'isoDateTime'),
-            message: `Server error: ${message}`,
-            level: 'error',
-          })
-        );
-        dispatch(errorOccurred());
-        dispatch(clearIntermediateImage());
-      } catch (e) {
-        console.error(e);
-      }
-    },
-    /**
-     * Callback to run when we receive a 'galleryImages' event.
-     */
-    onGalleryImages: (data: InvokeAI.GalleryImagesResponse) => {
-      const { images, areMoreImagesAvailable, category } = data;
+//       try {
+//         dispatch(
+//           addLogEntry({
+//             timestamp: dateFormat(new Date(), 'isoDateTime'),
+//             message: `Server error: ${message}`,
+//             level: 'error',
+//           })
+//         );
+//         dispatch(errorOccurred());
+//         dispatch(clearIntermediateImage());
+//       } catch (e) {
+//         console.error(e);
+//       }
+//     },
+//     /**
+//      * Callback to run when we receive a 'galleryImages' event.
+//      */
+//     onGalleryImages: (data: InvokeAI.GalleryImagesResponse) => {
+//       const { images, areMoreImagesAvailable, category } = data;
 
-      /**
-       * the logic here ideally would be in the reducer but we have a side effect:
-       * generating a uuid. so the logic needs to be here, outside redux.
-       */
+//       /**
+//        * the logic here ideally would be in the reducer but we have a side effect:
+//        * generating a uuid. so the logic needs to be here, outside redux.
+//        */
 
-      // Generate a UUID for each image
-      const preparedImages = images.map((image): InvokeAI.Image => {
-        return {
-          uuid: uuidv4(),
-          ...image,
-        };
-      });
+//       // Generate a UUID for each image
+//       const preparedImages = images.map((image): InvokeAI._Image => {
+//         return {
+//           uuid: uuidv4(),
+//           ...image,
+//         };
+//       });
 
-      dispatch(
-        addGalleryImages({
-          images: preparedImages,
-          areMoreImagesAvailable,
-          category,
-        })
-      );
+//       dispatch(
+//         addGalleryImages({
+//           images: preparedImages,
+//           areMoreImagesAvailable,
+//           category,
+//         })
+//       );
 
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Loaded ${images.length} images`,
-        })
-      );
-    },
-    /**
-     * Callback to run when we receive a 'processingCanceled' event.
-     */
-    onProcessingCanceled: () => {
-      dispatch(processingCanceled());
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Loaded ${images.length} images`,
+//         })
+//       );
+//     },
+//     /**
+//      * Callback to run when we receive a 'processingCanceled' event.
+//      */
+//     onProcessingCanceled: () => {
+//       dispatch(processingCanceled());
 
-      const { intermediateImage } = getState().gallery;
+//       const { intermediateImage } = getState().gallery;
 
-      if (intermediateImage) {
-        if (!intermediateImage.isBase64) {
-          dispatch(
-            addImage({
-              category: 'result',
-              image: intermediateImage,
-            })
-          );
-          dispatch(
-            addLogEntry({
-              timestamp: dateFormat(new Date(), 'isoDateTime'),
-              message: `Intermediate image saved: ${intermediateImage.url}`,
-            })
-          );
-        }
-        dispatch(clearIntermediateImage());
-      }
+//       if (intermediateImage) {
+//         if (!intermediateImage.isBase64) {
+//           dispatch(
+//             addImage({
+//               category: 'result',
+//               image: intermediateImage,
+//             })
+//           );
+//           dispatch(
+//             addLogEntry({
+//               timestamp: dateFormat(new Date(), 'isoDateTime'),
+//               message: `Intermediate image saved: ${intermediateImage.url}`,
+//             })
+//           );
+//         }
+//         dispatch(clearIntermediateImage());
+//       }
 
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Processing canceled`,
-          level: 'warning',
-        })
-      );
-    },
-    /**
-     * Callback to run when we receive a 'imageDeleted' event.
-     */
-    onImageDeleted: (data: InvokeAI.ImageDeletedResponse) => {
-      const { url } = data;
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Processing canceled`,
+//           level: 'warning',
+//         })
+//       );
+//     },
+//     /**
+//      * Callback to run when we receive a 'imageDeleted' event.
+//      */
+//     onImageDeleted: (data: InvokeAI.ImageDeletedResponse) => {
+//       const { url } = data;
 
-      // remove image from gallery
-      dispatch(removeImage(data));
+//       // remove image from gallery
+//       dispatch(removeImage(data));
 
-      // remove references to image in options
-      const {
-        generation: { initialImage, maskPath },
-      } = getState();
+//       // remove references to image in options
+//       const {
+//         generation: { initialImage, maskPath },
+//       } = getState();
 
-      if (
-        initialImage === url ||
-        (initialImage as InvokeAI.Image)?.url === url
-      ) {
-        dispatch(clearInitialImage());
-      }
+//       if (
+//         initialImage === url ||
+//         (initialImage as InvokeAI._Image)?.url === url
+//       ) {
+//         dispatch(clearInitialImage());
+//       }
 
-      if (maskPath === url) {
-        dispatch(setMaskPath(''));
-      }
+//       if (maskPath === url) {
+//         dispatch(setMaskPath(''));
+//       }
 
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Image deleted: ${url}`,
-        })
-      );
-    },
-    onSystemConfig: (data: InvokeAI.SystemConfig) => {
-      dispatch(setSystemConfig(data));
-      if (!data.infill_methods.includes('patchmatch')) {
-        dispatch(setInfillMethod(data.infill_methods[0]));
-      }
-    },
-    onFoundModels: (data: InvokeAI.FoundModelResponse) => {
-      const { search_folder, found_models } = data;
-      dispatch(setSearchFolder(search_folder));
-      dispatch(setFoundModels(found_models));
-    },
-    onNewModelAdded: (data: InvokeAI.ModelAddedResponse) => {
-      const { new_model_name, model_list, update } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setIsProcessing(false));
-      dispatch(setCurrentStatus(i18n.t('modelManager.modelAdded')));
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Model Added: ${new_model_name}`,
-          level: 'info',
-        })
-      );
-      dispatch(
-        addToast({
-          title: !update
-            ? `${i18n.t('modelManager.modelAdded')}: ${new_model_name}`
-            : `${i18n.t('modelManager.modelUpdated')}: ${new_model_name}`,
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        })
-      );
-    },
-    onModelDeleted: (data: InvokeAI.ModelDeletedResponse) => {
-      const { deleted_model_name, model_list } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setIsProcessing(false));
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `${i18n.t(
-            'modelManager.modelAdded'
-          )}: ${deleted_model_name}`,
-          level: 'info',
-        })
-      );
-      dispatch(
-        addToast({
-          title: `${i18n.t(
-            'modelManager.modelEntryDeleted'
-          )}: ${deleted_model_name}`,
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        })
-      );
-    },
-    onModelConverted: (data: InvokeAI.ModelConvertedResponse) => {
-      const { converted_model_name, model_list } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setCurrentStatus(i18n.t('common.statusModelConverted')));
-      dispatch(setIsProcessing(false));
-      dispatch(setIsCancelable(true));
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Model converted: ${converted_model_name}`,
-          level: 'info',
-        })
-      );
-      dispatch(
-        addToast({
-          title: `${i18n.t(
-            'modelManager.modelConverted'
-          )}: ${converted_model_name}`,
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        })
-      );
-    },
-    onModelsMerged: (data: InvokeAI.ModelsMergedResponse) => {
-      const { merged_models, merged_model_name, model_list } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setCurrentStatus(i18n.t('common.statusMergedModels')));
-      dispatch(setIsProcessing(false));
-      dispatch(setIsCancelable(true));
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Models merged: ${merged_models}`,
-          level: 'info',
-        })
-      );
-      dispatch(
-        addToast({
-          title: `${i18n.t('modelManager.modelsMerged')}: ${merged_model_name}`,
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        })
-      );
-    },
-    onModelChanged: (data: InvokeAI.ModelChangeResponse) => {
-      const { model_name, model_list } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setCurrentStatus(i18n.t('common.statusModelChanged')));
-      dispatch(setIsProcessing(false));
-      dispatch(setIsCancelable(true));
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Model changed: ${model_name}`,
-          level: 'info',
-        })
-      );
-    },
-    onModelChangeFailed: (data: InvokeAI.ModelChangeResponse) => {
-      const { model_name, model_list } = data;
-      dispatch(setModelList(model_list));
-      dispatch(setIsProcessing(false));
-      dispatch(setIsCancelable(true));
-      dispatch(errorOccurred());
-      dispatch(
-        addLogEntry({
-          timestamp: dateFormat(new Date(), 'isoDateTime'),
-          message: `Model change failed: ${model_name}`,
-          level: 'error',
-        })
-      );
-    },
-    onTempFolderEmptied: () => {
-      dispatch(
-        addToast({
-          title: i18n.t('toast.tempFoldersEmptied'),
-          status: 'success',
-          duration: 2500,
-          isClosable: true,
-        })
-      );
-    },
-  };
-};
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Image deleted: ${url}`,
+//         })
+//       );
+//     },
+//     onSystemConfig: (data: InvokeAI.SystemConfig) => {
+//       dispatch(setSystemConfig(data));
+//       if (!data.infill_methods.includes('patchmatch')) {
+//         dispatch(setInfillMethod(data.infill_methods[0]));
+//       }
+//     },
+//     onFoundModels: (data: InvokeAI.FoundModelResponse) => {
+//       const { search_folder, found_models } = data;
+//       dispatch(setSearchFolder(search_folder));
+//       dispatch(setFoundModels(found_models));
+//     },
+//     onNewModelAdded: (data: InvokeAI.ModelAddedResponse) => {
+//       const { new_model_name, model_list, update } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setIsProcessing(false));
+//       dispatch(setCurrentStatus(i18n.t('modelManager.modelAdded')));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Model Added: ${new_model_name}`,
+//           level: 'info',
+//         })
+//       );
+//       dispatch(
+//         addToast({
+//           title: !update
+//             ? `${i18n.t('modelManager.modelAdded')}: ${new_model_name}`
+//             : `${i18n.t('modelManager.modelUpdated')}: ${new_model_name}`,
+//           status: 'success',
+//           duration: 2500,
+//           isClosable: true,
+//         })
+//       );
+//     },
+//     onModelDeleted: (data: InvokeAI.ModelDeletedResponse) => {
+//       const { deleted_model_name, model_list } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setIsProcessing(false));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `${i18n.t(
+//             'modelManager.modelAdded'
+//           )}: ${deleted_model_name}`,
+//           level: 'info',
+//         })
+//       );
+//       dispatch(
+//         addToast({
+//           title: `${i18n.t(
+//             'modelManager.modelEntryDeleted'
+//           )}: ${deleted_model_name}`,
+//           status: 'success',
+//           duration: 2500,
+//           isClosable: true,
+//         })
+//       );
+//     },
+//     onModelConverted: (data: InvokeAI.ModelConvertedResponse) => {
+//       const { converted_model_name, model_list } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setCurrentStatus(i18n.t('common.statusModelConverted')));
+//       dispatch(setIsProcessing(false));
+//       dispatch(setIsCancelable(true));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Model converted: ${converted_model_name}`,
+//           level: 'info',
+//         })
+//       );
+//       dispatch(
+//         addToast({
+//           title: `${i18n.t(
+//             'modelManager.modelConverted'
+//           )}: ${converted_model_name}`,
+//           status: 'success',
+//           duration: 2500,
+//           isClosable: true,
+//         })
+//       );
+//     },
+//     onModelsMerged: (data: InvokeAI.ModelsMergedResponse) => {
+//       const { merged_models, merged_model_name, model_list } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setCurrentStatus(i18n.t('common.statusMergedModels')));
+//       dispatch(setIsProcessing(false));
+//       dispatch(setIsCancelable(true));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Models merged: ${merged_models}`,
+//           level: 'info',
+//         })
+//       );
+//       dispatch(
+//         addToast({
+//           title: `${i18n.t('modelManager.modelsMerged')}: ${merged_model_name}`,
+//           status: 'success',
+//           duration: 2500,
+//           isClosable: true,
+//         })
+//       );
+//     },
+//     onModelChanged: (data: InvokeAI.ModelChangeResponse) => {
+//       const { model_name, model_list } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setCurrentStatus(i18n.t('common.statusModelChanged')));
+//       dispatch(setIsProcessing(false));
+//       dispatch(setIsCancelable(true));
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Model changed: ${model_name}`,
+//           level: 'info',
+//         })
+//       );
+//     },
+//     onModelChangeFailed: (data: InvokeAI.ModelChangeResponse) => {
+//       const { model_name, model_list } = data;
+//       dispatch(setModelList(model_list));
+//       dispatch(setIsProcessing(false));
+//       dispatch(setIsCancelable(true));
+//       dispatch(errorOccurred());
+//       dispatch(
+//         addLogEntry({
+//           timestamp: dateFormat(new Date(), 'isoDateTime'),
+//           message: `Model change failed: ${model_name}`,
+//           level: 'error',
+//         })
+//       );
+//     },
+//     onTempFolderEmptied: () => {
+//       dispatch(
+//         addToast({
+//           title: i18n.t('toast.tempFoldersEmptied'),
+//           status: 'success',
+//           duration: 2500,
+//           isClosable: true,
+//         })
+//       );
+//     },
+//   };
+// };
 
-export default makeSocketIOListeners;
+// export default makeSocketIOListeners;
+
+export default {};

invokeai/frontend/web/src/app/socketio/middleware.ts

@@ -1,244 +1,248 @@
-import { Middleware } from '@reduxjs/toolkit';
-import { io } from 'socket.io-client';
+// import { Middleware } from '@reduxjs/toolkit';
+// import { io } from 'socket.io-client';
 
-import makeSocketIOEmitters from './emitters';
-import makeSocketIOListeners from './listeners';
+// import makeSocketIOEmitters from './emitters';
+// import makeSocketIOListeners from './listeners';
 
-import * as InvokeAI from 'app/invokeai';
+// import * as InvokeAI from 'app/types/invokeai';
 
-/**
- * Creates a socketio middleware to handle communication with server.
- *
- * Special `socketio/actionName` actions are created in actions.ts and
- * exported for use by the application, which treats them like any old
- * action, using `dispatch` to dispatch them.
- *
- * These actions are intercepted here, where `socketio.emit()` calls are
- * made on their behalf - see `emitters.ts`. The emitter functions
- * are the outbound communication to the server.
- *
- * Listeners are also established here - see `listeners.ts`. The listener
- * functions receive communication from the server and usually dispatch
- * some new action to handle whatever data was sent from the server.
- */
-export const socketioMiddleware = () => {
-  const { origin } = new URL(window.location.href);
+// /**
+//  * Creates a socketio middleware to handle communication with server.
+//  *
+//  * Special `socketio/actionName` actions are created in actions.ts and
+//  * exported for use by the application, which treats them like any old
+//  * action, using `dispatch` to dispatch them.
+//  *
+//  * These actions are intercepted here, where `socketio.emit()` calls are
+//  * made on their behalf - see `emitters.ts`. The emitter functions
+//  * are the outbound communication to the server.
+//  *
+//  * Listeners are also established here - see `listeners.ts`. The listener
+//  * functions receive communication from the server and usually dispatch
+//  * some new action to handle whatever data was sent from the server.
+//  */
+// export const socketioMiddleware = () => {
+//   const { origin } = new URL(window.location.href);
 
-  const socketio = io(origin, {
-    timeout: 60000,
-    path: `${window.location.pathname}socket.io`,
-  });
+//   const socketio = io(origin, {
+//     timeout: 60000,
+//     path: `${window.location.pathname}socket.io`,
+//   });
 
-  let areListenersSet = false;
+//   socketio.disconnect();
 
-  const middleware: Middleware = (store) => (next) => (action) => {
-    const {
-      onConnect,
-      onDisconnect,
-      onError,
-      onPostprocessingResult,
-      onGenerationResult,
-      onIntermediateResult,
-      onProgressUpdate,
-      onGalleryImages,
-      onProcessingCanceled,
-      onImageDeleted,
-      onSystemConfig,
-      onModelChanged,
-      onFoundModels,
-      onNewModelAdded,
-      onModelDeleted,
-      onModelConverted,
-      onModelsMerged,
-      onModelChangeFailed,
-      onTempFolderEmptied,
-    } = makeSocketIOListeners(store);
+//   let areListenersSet = false;
 
-    const {
-      emitGenerateImage,
-      emitRunESRGAN,
-      emitRunFacetool,
-      emitDeleteImage,
-      emitRequestImages,
-      emitRequestNewImages,
-      emitCancelProcessing,
-      emitRequestSystemConfig,
-      emitSearchForModels,
-      emitAddNewModel,
-      emitDeleteModel,
-      emitConvertToDiffusers,
-      emitMergeDiffusersModels,
-      emitRequestModelChange,
-      emitSaveStagingAreaImageToGallery,
-      emitRequestEmptyTempFolder,
-    } = makeSocketIOEmitters(store, socketio);
+//   const middleware: Middleware = (store) => (next) => (action) => {
+//     const {
+//       onConnect,
+//       onDisconnect,
+//       onError,
+//       onPostprocessingResult,
+//       onGenerationResult,
+//       onIntermediateResult,
+//       onProgressUpdate,
+//       onGalleryImages,
+//       onProcessingCanceled,
+//       onImageDeleted,
+//       onSystemConfig,
+//       onModelChanged,
+//       onFoundModels,
+//       onNewModelAdded,
+//       onModelDeleted,
+//       onModelConverted,
+//       onModelsMerged,
+//       onModelChangeFailed,
+//       onTempFolderEmptied,
+//     } = makeSocketIOListeners(store);
 
-    /**
-     * If this is the first time the middleware has been called (e.g. during store setup),
-     * initialize all our socket.io listeners.
-     */
-    if (!areListenersSet) {
-      socketio.on('connect', () => onConnect());
+//     const {
+//       emitGenerateImage,
+//       emitRunESRGAN,
+//       emitRunFacetool,
+//       emitDeleteImage,
+//       emitRequestImages,
+//       emitRequestNewImages,
+//       emitCancelProcessing,
+//       emitRequestSystemConfig,
+//       emitSearchForModels,
+//       emitAddNewModel,
+//       emitDeleteModel,
+//       emitConvertToDiffusers,
+//       emitMergeDiffusersModels,
+//       emitRequestModelChange,
+//       emitSaveStagingAreaImageToGallery,
+//       emitRequestEmptyTempFolder,
+//     } = makeSocketIOEmitters(store, socketio);
 
-      socketio.on('disconnect', () => onDisconnect());
+//     /**
+//      * If this is the first time the middleware has been called (e.g. during store setup),
+//      * initialize all our socket.io listeners.
+//      */
+//     if (!areListenersSet) {
+//       socketio.on('connect', () => onConnect());
 
-      socketio.on('error', (data: InvokeAI.ErrorResponse) => onError(data));
+//       socketio.on('disconnect', () => onDisconnect());
 
-      socketio.on('generationResult', (data: InvokeAI.ImageResultResponse) =>
-        onGenerationResult(data)
-      );
+//       socketio.on('error', (data: InvokeAI.ErrorResponse) => onError(data));
 
-      socketio.on(
-        'postprocessingResult',
-        (data: InvokeAI.ImageResultResponse) => onPostprocessingResult(data)
-      );
+//       socketio.on('generationResult', (data: InvokeAI.ImageResultResponse) =>
+//         onGenerationResult(data)
+//       );
 
-      socketio.on('intermediateResult', (data: InvokeAI.ImageResultResponse) =>
-        onIntermediateResult(data)
-      );
+//       socketio.on(
+//         'postprocessingResult',
+//         (data: InvokeAI.ImageResultResponse) => onPostprocessingResult(data)
+//       );
 
-      socketio.on('progressUpdate', (data: InvokeAI.SystemStatus) =>
-        onProgressUpdate(data)
-      );
+//       socketio.on('intermediateResult', (data: InvokeAI.ImageResultResponse) =>
+//         onIntermediateResult(data)
+//       );
 
-      socketio.on('galleryImages', (data: InvokeAI.GalleryImagesResponse) =>
-        onGalleryImages(data)
-      );
+//       socketio.on('progressUpdate', (data: InvokeAI.SystemStatus) =>
+//         onProgressUpdate(data)
+//       );
 
-      socketio.on('processingCanceled', () => {
-        onProcessingCanceled();
-      });
+//       socketio.on('galleryImages', (data: InvokeAI.GalleryImagesResponse) =>
+//         onGalleryImages(data)
+//       );
 
-      socketio.on('imageDeleted', (data: InvokeAI.ImageDeletedResponse) => {
-        onImageDeleted(data);
-      });
+//       socketio.on('processingCanceled', () => {
+//         onProcessingCanceled();
+//       });
 
-      socketio.on('systemConfig', (data: InvokeAI.SystemConfig) => {
-        onSystemConfig(data);
-      });
+//       socketio.on('imageDeleted', (data: InvokeAI.ImageDeletedResponse) => {
+//         onImageDeleted(data);
+//       });
 
-      socketio.on('foundModels', (data: InvokeAI.FoundModelResponse) => {
-        onFoundModels(data);
-      });
+//       socketio.on('systemConfig', (data: InvokeAI.SystemConfig) => {
+//         onSystemConfig(data);
+//       });
 
-      socketio.on('newModelAdded', (data: InvokeAI.ModelAddedResponse) => {
-        onNewModelAdded(data);
-      });
+//       socketio.on('foundModels', (data: InvokeAI.FoundModelResponse) => {
+//         onFoundModels(data);
+//       });
 
-      socketio.on('modelDeleted', (data: InvokeAI.ModelDeletedResponse) => {
-        onModelDeleted(data);
-      });
+//       socketio.on('newModelAdded', (data: InvokeAI.ModelAddedResponse) => {
+//         onNewModelAdded(data);
+//       });
 
-      socketio.on('modelConverted', (data: InvokeAI.ModelConvertedResponse) => {
-        onModelConverted(data);
-      });
+//       socketio.on('modelDeleted', (data: InvokeAI.ModelDeletedResponse) => {
+//         onModelDeleted(data);
+//       });
 
-      socketio.on('modelsMerged', (data: InvokeAI.ModelsMergedResponse) => {
-        onModelsMerged(data);
-      });
+//       socketio.on('modelConverted', (data: InvokeAI.ModelConvertedResponse) => {
+//         onModelConverted(data);
+//       });
 
-      socketio.on('modelChanged', (data: InvokeAI.ModelChangeResponse) => {
-        onModelChanged(data);
-      });
+//       socketio.on('modelsMerged', (data: InvokeAI.ModelsMergedResponse) => {
+//         onModelsMerged(data);
+//       });
 
-      socketio.on('modelChangeFailed', (data: InvokeAI.ModelChangeResponse) => {
-        onModelChangeFailed(data);
-      });
+//       socketio.on('modelChanged', (data: InvokeAI.ModelChangeResponse) => {
+//         onModelChanged(data);
+//       });
 
-      socketio.on('tempFolderEmptied', () => {
-        onTempFolderEmptied();
-      });
+//       socketio.on('modelChangeFailed', (data: InvokeAI.ModelChangeResponse) => {
+//         onModelChangeFailed(data);
+//       });
 
-      areListenersSet = true;
-    }
+//       socketio.on('tempFolderEmptied', () => {
+//         onTempFolderEmptied();
+//       });
 
-    /**
-     * Handle redux actions caught by middleware.
-     */
-    switch (action.type) {
-      case 'socketio/generateImage': {
-        emitGenerateImage(action.payload);
-        break;
-      }
+//       areListenersSet = true;
+//     }
 
-      case 'socketio/runESRGAN': {
-        emitRunESRGAN(action.payload);
-        break;
-      }
+//     /**
+//      * Handle redux actions caught by middleware.
+//      */
+//     switch (action.type) {
+//       case 'socketio/generateImage': {
+//         emitGenerateImage(action.payload);
+//         break;
+//       }
 
-      case 'socketio/runFacetool': {
-        emitRunFacetool(action.payload);
-        break;
-      }
+//       case 'socketio/runESRGAN': {
+//         emitRunESRGAN(action.payload);
+//         break;
+//       }
 
-      case 'socketio/deleteImage': {
-        emitDeleteImage(action.payload);
-        break;
-      }
+//       case 'socketio/runFacetool': {
+//         emitRunFacetool(action.payload);
+//         break;
+//       }
 
-      case 'socketio/requestImages': {
-        emitRequestImages(action.payload);
-        break;
-      }
+//       case 'socketio/deleteImage': {
+//         emitDeleteImage(action.payload);
+//         break;
+//       }
 
-      case 'socketio/requestNewImages': {
-        emitRequestNewImages(action.payload);
-        break;
-      }
+//       case 'socketio/requestImages': {
+//         emitRequestImages(action.payload);
+//         break;
+//       }
 
-      case 'socketio/cancelProcessing': {
-        emitCancelProcessing();
-        break;
-      }
+//       case 'socketio/requestNewImages': {
+//         emitRequestNewImages(action.payload);
+//         break;
+//       }
 
-      case 'socketio/requestSystemConfig': {
-        emitRequestSystemConfig();
-        break;
-      }
+//       case 'socketio/cancelProcessing': {
+//         emitCancelProcessing();
+//         break;
+//       }
 
-      case 'socketio/searchForModels': {
-        emitSearchForModels(action.payload);
-        break;
-      }
+//       case 'socketio/requestSystemConfig': {
+//         emitRequestSystemConfig();
+//         break;
+//       }
 
-      case 'socketio/addNewModel': {
-        emitAddNewModel(action.payload);
-        break;
-      }
+//       case 'socketio/searchForModels': {
+//         emitSearchForModels(action.payload);
+//         break;
+//       }
 
-      case 'socketio/deleteModel': {
-        emitDeleteModel(action.payload);
-        break;
-      }
+//       case 'socketio/addNewModel': {
+//         emitAddNewModel(action.payload);
+//         break;
+//       }
 
-      case 'socketio/convertToDiffusers': {
-        emitConvertToDiffusers(action.payload);
-        break;
-      }
+//       case 'socketio/deleteModel': {
+//         emitDeleteModel(action.payload);
+//         break;
+//       }
 
-      case 'socketio/mergeDiffusersModels': {
-        emitMergeDiffusersModels(action.payload);
-        break;
-      }
+//       case 'socketio/convertToDiffusers': {
+//         emitConvertToDiffusers(action.payload);
+//         break;
+//       }
 
-      case 'socketio/requestModelChange': {
-        emitRequestModelChange(action.payload);
-        break;
-      }
+//       case 'socketio/mergeDiffusersModels': {
+//         emitMergeDiffusersModels(action.payload);
+//         break;
+//       }
 
-      case 'socketio/saveStagingAreaImageToGallery': {
-        emitSaveStagingAreaImageToGallery(action.payload);
-        break;
-      }
+//       case 'socketio/requestModelChange': {
+//         emitRequestModelChange(action.payload);
+//         break;
+//       }
 
-      case 'socketio/requestEmptyTempFolder': {
-        emitRequestEmptyTempFolder();
-        break;
-      }
-    }
+//       case 'socketio/saveStagingAreaImageToGallery': {
+//         emitSaveStagingAreaImageToGallery(action.payload);
+//         break;
+//       }
 
-    next(action);
-  };
+//       case 'socketio/requestEmptyTempFolder': {
+//         emitRequestEmptyTempFolder();
+//         break;
+//       }
+//     }
 
-  return middleware;
-};
+//     next(action);
+//   };
+
+//   return middleware;
+// };
+
+export default {};

invokeai/frontend/web/src/app/store/persistor.ts

@@ -1,4 +1,4 @@
-import { store } from 'app/store';
+import { store } from 'app/store/store';
 import { persistStore } from 'redux-persist';
 
 export const persistor = persistStore(store);

invokeai/frontend/web/src/app/store/store.ts

@@ -2,18 +2,34 @@ import { combineReducers, configureStore } from '@reduxjs/toolkit';
 
 import { persistReducer } from 'redux-persist';
 import storage from 'redux-persist/lib/storage'; // defaults to localStorage for web
-
+import dynamicMiddlewares from 'redux-dynamic-middlewares';
 import { getPersistConfig } from 'redux-deep-persist';
 
 import canvasReducer from 'features/canvas/store/canvasSlice';
 import galleryReducer from 'features/gallery/store/gallerySlice';
+import resultsReducer from 'features/gallery/store/resultsSlice';
+import uploadsReducer from 'features/gallery/store/uploadsSlice';
 import lightboxReducer from 'features/lightbox/store/lightboxSlice';
 import generationReducer from 'features/parameters/store/generationSlice';
 import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
 import systemReducer from 'features/system/store/systemSlice';
+import configReducer from 'features/system/store/configSlice';
 import uiReducer from 'features/ui/store/uiSlice';
+import hotkeysReducer from 'features/ui/store/hotkeysSlice';
+import modelsReducer from 'features/system/store/modelSlice';
+import nodesReducer from 'features/nodes/store/nodesSlice';
 
-import { socketioMiddleware } from './socketio/middleware';
+import { canvasDenylist } from 'features/canvas/store/canvasPersistDenylist';
+import { galleryDenylist } from 'features/gallery/store/galleryPersistDenylist';
+import { generationDenylist } from 'features/parameters/store/generationPersistDenylist';
+import { lightboxDenylist } from 'features/lightbox/store/lightboxPersistDenylist';
+import { modelsDenylist } from 'features/system/store/modelsPersistDenylist';
+import { nodesDenylist } from 'features/nodes/store/nodesPersistDenylist';
+import { postprocessingDenylist } from 'features/parameters/store/postprocessingPersistDenylist';
+import { systemDenylist } from 'features/system/store/systemPersistDenylist';
+import { uiDenylist } from 'features/ui/store/uiPersistDenylist';
+import { resultsDenylist } from 'features/gallery/store/resultsPersistDenylist';
+import { uploadsDenylist } from 'features/gallery/store/uploadsPersistDenylist';
 
 /**
  * redux-persist provides an easy and reliable way to persist state across reloads.
@@ -24,54 +40,25 @@ import { socketioMiddleware } from './socketio/middleware';
  *   - Connection/processing status
  *   - Availability of external libraries like ESRGAN/GFPGAN
  *
- * These can be blacklisted in redux-persist.
+ * These can be denylisted in redux-persist.
  *
- * The necesssary nested persistors with blacklists are configured below.
+ * The necesssary nested persistors with denylists are configured below.
  */
 
-const canvasBlacklist = [
-  'cursorPosition',
-  'isCanvasInitialized',
-  'doesCanvasNeedScaling',
-].map((blacklistItem) => `canvas.${blacklistItem}`);
-
-const systemBlacklist = [
-  'currentIteration',
-  'currentStatus',
-  'currentStep',
-  'isCancelable',
-  'isConnected',
-  'isESRGANAvailable',
-  'isGFPGANAvailable',
-  'isProcessing',
-  'socketId',
-  'totalIterations',
-  'totalSteps',
-  'openModel',
-  'cancelOptions.cancelAfter',
-].map((blacklistItem) => `system.${blacklistItem}`);
-
-const galleryBlacklist = [
-  'categories',
-  'currentCategory',
-  'currentImage',
-  'currentImageUuid',
-  'shouldAutoSwitchToNewImages',
-  'intermediateImage',
-].map((blacklistItem) => `gallery.${blacklistItem}`);
-
-const lightboxBlacklist = ['isLightboxOpen'].map(
-  (blacklistItem) => `lightbox.${blacklistItem}`
-);
-
 const rootReducer = combineReducers({
-  generation: generationReducer,
-  postprocessing: postprocessingReducer,
-  gallery: galleryReducer,
-  system: systemReducer,
   canvas: canvasReducer,
-  ui: uiReducer,
+  gallery: galleryReducer,
+  generation: generationReducer,
   lightbox: lightboxReducer,
+  models: modelsReducer,
+  nodes: nodesReducer,
+  postprocessing: postprocessingReducer,
+  results: resultsReducer,
+  system: systemReducer,
+  config: configReducer,
+  ui: uiReducer,
+  uploads: uploadsReducer,
+  hotkeys: hotkeysReducer,
 });
 
 const rootPersistConfig = getPersistConfig({
@@ -79,24 +66,40 @@ const rootPersistConfig = getPersistConfig({
   storage,
   rootReducer,
   blacklist: [
-    ...canvasBlacklist,
-    ...systemBlacklist,
-    ...galleryBlacklist,
-    ...lightboxBlacklist,
+    ...canvasDenylist,
+    ...galleryDenylist,
+    ...generationDenylist,
+    ...lightboxDenylist,
+    ...modelsDenylist,
+    ...nodesDenylist,
+    ...postprocessingDenylist,
+    ...resultsDenylist,
+    ...systemDenylist,
+    ...uiDenylist,
+    ...uploadsDenylist,
+    'hotkeys',
+    'config',
   ],
-  debounce: 300,
 });
 
 const persistedReducer = persistReducer(rootPersistConfig, rootReducer);
 
-// Continue with store setup
+// TODO: rip the old middleware out when nodes is complete
+// export function buildMiddleware() {
+//   if (import.meta.env.MODE === 'nodes' || import.meta.env.MODE === 'package') {
+//     return socketMiddleware();
+//   } else {
+//     return socketioMiddleware();
+//   }
+// }
+
 export const store = configureStore({
   reducer: persistedReducer,
   middleware: (getDefaultMiddleware) =>
     getDefaultMiddleware({
       immutableCheck: false,
       serializableCheck: false,
-    }).concat(socketioMiddleware()),
+    }).concat(dynamicMiddlewares),
   devTools: {
     // Uncommenting these very rapidly called actions makes the redux dev tools output much more readable
     actionsDenylist: [
@@ -108,6 +111,7 @@ export const store = configureStore({
       'canvas/setBoundingBoxDimensions',
       'canvas/setIsDrawing',
       'canvas/addPointToCurrentLine',
+      'socket/generatorProgress',
     ],
   },
 });

invokeai/frontend/web/src/app/store/storeHooks.ts

@@ -1,5 +1,5 @@
 import { TypedUseSelectorHook, useDispatch, useSelector } from 'react-redux';
-import { AppDispatch, RootState } from './store';
+import { AppDispatch, RootState } from 'app/store/store';
 
 // Use throughout your app instead of plain `useDispatch` and `useSelector`
 export const useAppDispatch: () => AppDispatch = useDispatch;

invokeai/frontend/web/src/app/store/storeUtils.ts

@@ -0,0 +1,8 @@
+import { createAsyncThunk } from '@reduxjs/toolkit';
+import { AppDispatch, RootState } from 'app/store/store';
+
+// https://redux-toolkit.js.org/usage/usage-with-typescript#defining-a-pre-typed-createasyncthunk
+export const createAppAsyncThunk = createAsyncThunk.withTypes<{
+  state: RootState;
+  dispatch: AppDispatch;
+}>();

invokeai/frontend/web/src/app/types/invokeai.ts

@@ -0,0 +1,393 @@
+/**
+ * Types for images, the things they are made of, and the things
+ * they make up.
+ *
+ * Generated images are txt2img and img2img images. They may have
+ * had additional postprocessing done on them when they were first
+ * generated.
+ *
+ * Postprocessed images are images which were not generated here
+ * but only postprocessed by the app. They only get postprocessing
+ * metadata and have a different image type, e.g. 'esrgan' or
+ * 'gfpgan'.
+ */
+
+import { GalleryCategory } from 'features/gallery/store/gallerySlice';
+import { FacetoolType } from 'features/parameters/store/postprocessingSlice';
+import { InvokeTabName } from 'features/ui/store/tabMap';
+import { IRect } from 'konva/lib/types';
+import { ImageResponseMetadata, ImageType } from 'services/api';
+import { AnyInvocation } from 'services/events/types';
+import { O } from 'ts-toolbelt';
+
+/**
+ * TODO:
+ * Once an image has been generated, if it is postprocessed again,
+ * additional postprocessing steps are added to its postprocessing
+ * array.
+ *
+ * TODO: Better documentation of types.
+ */
+
+export type PromptItem = {
+  prompt: string;
+  weight: number;
+};
+
+// TECHDEBT: We need to retain compatibility with plain prompt strings and the structure Prompt type
+export type Prompt = Array<PromptItem> | string;
+
+export type SeedWeightPair = {
+  seed: number;
+  weight: number;
+};
+
+export type SeedWeights = Array<SeedWeightPair>;
+
+// All generated images contain these metadata.
+export type CommonGeneratedImageMetadata = {
+  postprocessing: null | Array<ESRGANMetadata | FacetoolMetadata>;
+  sampler:
+    | 'ddim'
+    | 'k_dpm_2_a'
+    | 'k_dpm_2'
+    | 'k_dpmpp_2_a'
+    | 'k_dpmpp_2'
+    | 'k_euler_a'
+    | 'k_euler'
+    | 'k_heun'
+    | 'k_lms'
+    | 'plms';
+  prompt: Prompt;
+  seed: number;
+  variations: SeedWeights;
+  steps: number;
+  cfg_scale: number;
+  width: number;
+  height: number;
+  seamless: boolean;
+  hires_fix: boolean;
+  extra: null | Record<string, never>; // Pending development of RFC #266
+};
+
+// txt2img and img2img images have some unique attributes.
+export type Txt2ImgMetadata = CommonGeneratedImageMetadata & {
+  type: 'txt2img';
+};
+
+export type Img2ImgMetadata = CommonGeneratedImageMetadata & {
+  type: 'img2img';
+  orig_hash: string;
+  strength: number;
+  fit: boolean;
+  init_image_path: string;
+  mask_image_path?: string;
+};
+
+// Superset of  generated image metadata types.
+export type GeneratedImageMetadata = Txt2ImgMetadata | Img2ImgMetadata;
+
+// All post processed images contain these metadata.
+export type CommonPostProcessedImageMetadata = {
+  orig_path: string;
+  orig_hash: string;
+};
+
+// esrgan and gfpgan images have some unique attributes.
+export type ESRGANMetadata = CommonPostProcessedImageMetadata & {
+  type: 'esrgan';
+  scale: 2 | 4;
+  strength: number;
+  denoise_str: number;
+};
+
+export type FacetoolMetadata = CommonPostProcessedImageMetadata & {
+  type: 'gfpgan' | 'codeformer';
+  strength: number;
+  fidelity?: number;
+};
+
+// Superset of all postprocessed image metadata types..
+export type PostProcessedImageMetadata = ESRGANMetadata | FacetoolMetadata;
+
+// Metadata includes the system config and image metadata.
+// export type Metadata = SystemGenerationMetadata & {
+//   image: GeneratedImageMetadata | PostProcessedImageMetadata;
+// };
+
+/**
+ * ResultImage
+ */
+export type Image = {
+  name: string;
+  type: ImageType;
+  url: string;
+  thumbnail: string;
+  metadata: ImageResponseMetadata;
+};
+
+/**
+ * Types related to the system status.
+ */
+
+// // This represents the processing status of the backend.
+// export type SystemStatus = {
+//   isProcessing: boolean;
+//   currentStep: number;
+//   totalSteps: number;
+//   currentIteration: number;
+//   totalIterations: number;
+//   currentStatus: string;
+//   currentStatusHasSteps: boolean;
+//   hasError: boolean;
+// };
+
+// export type SystemGenerationMetadata = {
+//   model: string;
+//   model_weights?: string;
+//   model_id?: string;
+//   model_hash: string;
+//   app_id: string;
+//   app_version: string;
+// };
+
+// export type SystemConfig = SystemGenerationMetadata & {
+//   model_list: ModelList;
+//   infill_methods: string[];
+// };
+
+export type ModelStatus = 'active' | 'cached' | 'not loaded';
+
+export type Model = {
+  status: ModelStatus;
+  description: string;
+  weights: string;
+  config?: string;
+  vae?: string;
+  width?: number;
+  height?: number;
+  default?: boolean;
+  format?: string;
+};
+
+export type DiffusersModel = {
+  status: ModelStatus;
+  description: string;
+  repo_id?: string;
+  path?: string;
+  vae?: {
+    repo_id?: string;
+    path?: string;
+  };
+  format?: string;
+  default?: boolean;
+};
+
+export type ModelList = Record<string, Model & DiffusersModel>;
+
+export type FoundModel = {
+  name: string;
+  location: string;
+};
+
+export type InvokeModelConfigProps = {
+  name: string | undefined;
+  description: string | undefined;
+  config: string | undefined;
+  weights: string | undefined;
+  vae: string | undefined;
+  width: number | undefined;
+  height: number | undefined;
+  default: boolean | undefined;
+  format: string | undefined;
+};
+
+export type InvokeDiffusersModelConfigProps = {
+  name: string | undefined;
+  description: string | undefined;
+  repo_id: string | undefined;
+  path: string | undefined;
+  default: boolean | undefined;
+  format: string | undefined;
+  vae: {
+    repo_id: string | undefined;
+    path: string | undefined;
+  };
+};
+
+export type InvokeModelConversionProps = {
+  model_name: string;
+  save_location: string;
+  custom_location: string | null;
+};
+
+export type InvokeModelMergingProps = {
+  models_to_merge: string[];
+  alpha: number;
+  interp: 'weighted_sum' | 'sigmoid' | 'inv_sigmoid' | 'add_difference';
+  force: boolean;
+  merged_model_name: string;
+  model_merge_save_path: string | null;
+};
+
+/**
+ * These types type data received from the server via socketio.
+ */
+
+export type ModelChangeResponse = {
+  model_name: string;
+  model_list: ModelList;
+};
+
+export type ModelConvertedResponse = {
+  converted_model_name: string;
+  model_list: ModelList;
+};
+
+export type ModelsMergedResponse = {
+  merged_models: string[];
+  merged_model_name: string;
+  model_list: ModelList;
+};
+
+export type ModelAddedResponse = {
+  new_model_name: string;
+  model_list: ModelList;
+  update: boolean;
+};
+
+export type ModelDeletedResponse = {
+  deleted_model_name: string;
+  model_list: ModelList;
+};
+
+export type FoundModelResponse = {
+  search_folder: string;
+  found_models: FoundModel[];
+};
+
+// export type SystemStatusResponse = SystemStatus;
+
+// export type SystemConfigResponse = SystemConfig;
+
+export type ImageResultResponse = Omit<_Image, 'uuid'> & {
+  boundingBox?: IRect;
+  generationMode: InvokeTabName;
+};
+
+export type ImageUploadResponse = {
+  // image: Omit<Image, 'uuid' | 'metadata' | 'category'>;
+  url: string;
+  mtime: number;
+  width: number;
+  height: number;
+  thumbnail: string;
+  // bbox: [number, number, number, number];
+};
+
+export type ErrorResponse = {
+  message: string;
+  additionalData?: string;
+};
+
+export type ImageUrlResponse = {
+  url: string;
+};
+
+export type UploadOutpaintingMergeImagePayload = {
+  dataURL: string;
+  name: string;
+};
+
+/**
+ * A disable-able application feature
+ */
+export type AppFeature =
+  | 'faceRestore'
+  | 'upscaling'
+  | 'lightbox'
+  | 'modelManager'
+  | 'githubLink'
+  | 'discordLink'
+  | 'bugLink'
+  | 'localization';
+
+/**
+ * A disable-able Stable Diffusion feature
+ */
+export type StableDiffusionFeature =
+  | 'noiseConfig'
+  | 'variations'
+  | 'symmetry'
+  | 'tiling'
+  | 'hires';
+
+/**
+ * Configuration options for the InvokeAI UI.
+ * Distinct from system settings which may be changed inside the app.
+ */
+export type AppConfig = {
+  /**
+   * Whether or not URLs should be transformed to use a different host
+   */
+  shouldTransformUrls: boolean;
+  /**
+   * Whether or not we need to re-fetch images
+   */
+  shouldFetchImages: boolean;
+  disabledTabs: InvokeTabName[];
+  disabledFeatures: AppFeature[];
+  canRestoreDeletedImagesFromBin: boolean;
+  sd: {
+    iterations: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+    width: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+    height: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+    steps: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+    guidance: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+    img2imgStrength: {
+      initial: number;
+      min: number;
+      sliderMax: number;
+      inputMax: number;
+      fineStep: number;
+      coarseStep: number;
+    };
+  };
+};
+
+export type PartialAppConfig = O.Partial<AppConfig, 'deep'>;

invokeai/frontend/web/src/app/utils.ts

@@ -1,25 +0,0 @@
-export function keepGUIAlive() {
-  async function getRequest(url = '') {
-    const response = await fetch(url, {
-      method: 'GET',
-      cache: 'no-cache',
-    });
-    return response;
-  }
-
-  const keepAliveServer = () => {
-    const url = document.location;
-    const route = '/flaskwebgui-keep-server-alive';
-    getRequest(url + route).then((data) => {
-      return data;
-    });
-  };
-
-  if (!import.meta.env.NODE_ENV || import.meta.env.NODE_ENV === 'production') {
-    document.addEventListener('DOMContentLoaded', () => {
-      const intervalRequest = 3 * 1000;
-      keepAliveServer();
-      setInterval(keepAliveServer, intervalRequest);
-    });
-  }
-}

invokeai/frontend/web/src/common/components/GuidePopover.tsx

@@ -8,7 +8,7 @@ import {
 } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { Feature, useFeatureHelpInfo } from 'app/features';
-import { useAppSelector } from 'app/storeHooks';
+import { useAppSelector } from 'app/store/storeHooks';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { SystemState } from 'features/system/store/systemSlice';
 import { memo, ReactElement } from 'react';

invokeai/frontend/web/src/common/components/IAINumberInput.tsx

@@ -14,7 +14,7 @@ import {
   Tooltip,
   TooltipProps,
 } from '@chakra-ui/react';
-import { clamp } from 'lodash';
+import { clamp } from 'lodash-es';
 
 import { FocusEvent, memo, useEffect, useState } from 'react';
 

invokeai/frontend/web/src/common/components/IAISelect.tsx

@@ -16,13 +16,23 @@ type IAISelectProps = SelectProps & {
   validValues:
     | Array<number | string>
     | Array<{ key: string; value: string | number }>;
+  horizontal?: boolean;
+  spaceEvenly?: boolean;
 };
 /**
  * Customized Chakra FormControl + Select multi-part component.
  */
 const IAISelect = (props: IAISelectProps) => {
-  const { label, isDisabled, validValues, tooltip, tooltipProps, ...rest } =
-    props;
+  const {
+    label,
+    isDisabled,
+    validValues,
+    tooltip,
+    tooltipProps,
+    horizontal,
+    spaceEvenly,
+    ...rest
+  } = props;
   return (
     <FormControl
       isDisabled={isDisabled}
@@ -32,10 +42,28 @@ const IAISelect = (props: IAISelectProps) => {
         e.nativeEvent.stopPropagation();
         e.nativeEvent.cancelBubble = true;
       }}
+      sx={
+        horizontal
+          ? {
+              display: 'flex',
+              flexDirection: 'row',
+              alignItems: 'center',
+              justifyContent: 'space-between',
+              gap: 4,
+            }
+          : {}
+      }
     >
-      {label && <FormLabel>{label}</FormLabel>}
+      {label && (
+        <FormLabel sx={spaceEvenly ? { flexBasis: 0, flexGrow: 1 } : {}}>
+          {label}
+        </FormLabel>
+      )}
       <Tooltip label={tooltip} {...tooltipProps}>
-        <Select {...rest}>
+        <Select
+          {...rest}
+          rootProps={{ sx: spaceEvenly ? { flexBasis: 0, flexGrow: 1 } : {} }}
+        >
           {validValues.map((opt) => {
             return typeof opt === 'string' || typeof opt === 'number' ? (
               <IAIOption key={opt} value={opt}>

invokeai/frontend/web/src/common/components/IAISlider.tsx

@@ -23,12 +23,21 @@ import {
   Tooltip,
   TooltipProps,
 } from '@chakra-ui/react';
-import { clamp } from 'lodash';
+import { clamp } from 'lodash-es';
 
 import { useTranslation } from 'react-i18next';
-import { FocusEvent, memo, useEffect, useMemo, useState } from 'react';
+import {
+  FocusEvent,
+  memo,
+  MouseEvent,
+  useCallback,
+  useEffect,
+  useMemo,
+  useState,
+} from 'react';
 import { BiReset } from 'react-icons/bi';
 import IAIIconButton, { IAIIconButtonProps } from './IAIIconButton';
+import { roundDownToMultiple } from 'common/util/roundDownToMultiple';
 
 export type IAIFullSliderProps = {
   label: string;
@@ -44,12 +53,10 @@ export type IAIFullSliderProps = {
   inputReadOnly?: boolean;
   withReset?: boolean;
   handleReset?: () => void;
-  isResetDisabled?: boolean;
-  isSliderDisabled?: boolean;
-  isInputDisabled?: boolean;
   tooltipSuffix?: string;
   hideTooltip?: boolean;
   isCompact?: boolean;
+  isDisabled?: boolean;
   sliderFormControlProps?: FormControlProps;
   sliderFormLabelProps?: FormLabelProps;
   sliderMarkProps?: Omit<SliderMarkProps, 'value'>;
@@ -80,10 +87,8 @@ const IAISlider = (props: IAIFullSliderProps) => {
     withReset = false,
     hideTooltip = false,
     isCompact = false,
+    isDisabled = false,
     handleReset,
-    isResetDisabled,
-    isSliderDisabled,
-    isInputDisabled,
     sliderFormControlProps,
     sliderFormLabelProps,
     sliderMarkProps,
@@ -112,31 +117,52 @@ const IAISlider = (props: IAIFullSliderProps) => {
     [max, sliderNumberInputProps?.max]
   );
 
-  const handleSliderChange = (v: number) => {
-    onChange(v);
-  };
+  const handleSliderChange = useCallback(
+    (v: number) => {
+      onChange(v);
+    },
+    [onChange]
+  );
 
-  const handleInputBlur = (e: FocusEvent<HTMLInputElement>) => {
-    if (e.target.value === '') e.target.value = String(min);
-    const clamped = clamp(
-      isInteger ? Math.floor(Number(e.target.value)) : Number(localInputValue),
-      min,
-      numberInputMax
-    );
-    onChange(clamped);
-  };
+  const handleInputBlur = useCallback(
+    (e: FocusEvent<HTMLInputElement>) => {
+      if (e.target.value === '') {
+        e.target.value = String(min);
+      }
+      const clamped = clamp(
+        isInteger
+          ? Math.floor(Number(e.target.value))
+          : Number(localInputValue),
+        min,
+        numberInputMax
+      );
+      const quantized = roundDownToMultiple(clamped, step);
+      onChange(quantized);
+      setLocalInputValue(quantized);
+    },
+    [isInteger, localInputValue, min, numberInputMax, onChange, step]
+  );
 
-  const handleInputChange = (v: number | string) => {
+  const handleInputChange = useCallback((v: number | string) => {
     setLocalInputValue(v);
-  };
+  }, []);
 
-  const handleResetDisable = () => {
-    if (!handleReset) return;
+  const handleResetDisable = useCallback(() => {
+    if (!handleReset) {
+      return;
+    }
     handleReset();
-  };
+  }, [handleReset]);
+
+  const forceInputBlur = useCallback((e: MouseEvent) => {
+    if (e.target instanceof HTMLDivElement) {
+      e.target.focus();
+    }
+  }, []);
 
   return (
     <FormControl
+      onClick={forceInputBlur}
       sx={
         isCompact
           ? {
@@ -149,6 +175,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
             }
           : {}
       }
+      isDisabled={isDisabled}
       {...sliderFormControlProps}
     >
       <FormLabel {...sliderFormLabelProps} mb={-1}>
@@ -166,15 +193,13 @@ const IAISlider = (props: IAIFullSliderProps) => {
           onMouseEnter={() => setShowTooltip(true)}
           onMouseLeave={() => setShowTooltip(false)}
           focusThumbOnChange={false}
-          isDisabled={isSliderDisabled}
-          // width={width}
+          isDisabled={isDisabled}
           {...rest}
         >
           {withSliderMarks && (
             <>
               <SliderMark
                 value={min}
-                // insetInlineStart={0}
                 sx={{
                   insetInlineStart: '0 !important',
                   insetInlineEnd: 'unset !important',
@@ -185,7 +210,6 @@ const IAISlider = (props: IAIFullSliderProps) => {
               </SliderMark>
               <SliderMark
                 value={max}
-                // insetInlineEnd={0}
                 sx={{
                   insetInlineStart: 'unset !important',
                   insetInlineEnd: '0 !important',
@@ -209,7 +233,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
             hidden={hideTooltip}
             {...sliderTooltipProps}
           >
-            <SliderThumb {...sliderThumbProps} />
+            <SliderThumb {...sliderThumbProps} zIndex={0} />
           </Tooltip>
         </Slider>
 
@@ -221,7 +245,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
             value={localInputValue}
             onChange={handleInputChange}
             onBlur={handleInputBlur}
-            isDisabled={isInputDisabled}
+            focusInputOnChange={false}
             {...sliderNumberInputProps}
           >
             <NumberInputField
@@ -244,10 +268,10 @@ const IAISlider = (props: IAIFullSliderProps) => {
           <IAIIconButton
             size="sm"
             aria-label={t('accessibility.reset')}
-            tooltip="Reset"
+            tooltip={t('accessibility.reset')}
             icon={<BiReset />}
+            isDisabled={isDisabled}
             onClick={handleResetDisable}
-            isDisabled={isResetDisabled}
             {...sliderIAIIconButtonProps}
           />
         )}

invokeai/frontend/web/src/common/components/IAISwitch.tsx

@@ -34,10 +34,9 @@ const IAISwitch = (props: Props) => {
       display="flex"
       gap={4}
       alignItems="center"
-      justifyContent="space-between"
       {...formControlProps}
     >
-      <FormLabel my={1} {...formLabelProps}>
+      <FormLabel my={1} flexGrow={1} {...formLabelProps}>
         {label}
       </FormLabel>
       <Switch {...rest} />

invokeai/frontend/web/src/common/components/ImageToImageOverlay.tsx

@@ -0,0 +1,36 @@
+import { Badge, Box, Flex } from '@chakra-ui/react';
+import { Image } from 'app/types/invokeai';
+
+type ImageToImageOverlayProps = {
+  image: Image;
+};
+
+const ImageToImageOverlay = ({ image }: ImageToImageOverlayProps) => {
+  return (
+    <Box
+      sx={{
+        top: 0,
+        left: 0,
+        w: 'full',
+        h: 'full',
+        position: 'absolute',
+      }}
+    >
+      <Flex
+        sx={{
+          position: 'absolute',
+          top: 0,
+          right: 0,
+          p: 2,
+          alignItems: 'flex-start',
+        }}
+      >
+        <Badge variant="solid" colorScheme="base">
+          {image.metadata?.width} × {image.metadata?.height}
+        </Badge>
+      </Flex>
+    </Box>
+  );
+};
+
+export default ImageToImageOverlay;

invokeai/frontend/web/src/common/components/ImageToImageSettingsHeader.tsx

@@ -0,0 +1,41 @@
+import { ButtonGroup, Flex, Spacer, Text } from '@chakra-ui/react';
+import IAIIconButton from 'common/components/IAIIconButton';
+
+import { useTranslation } from 'react-i18next';
+import { FaUndo, FaUpload } from 'react-icons/fa';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { useCallback } from 'react';
+import { clearInitialImage } from 'features/parameters/store/generationSlice';
+
+const ImageToImageSettingsHeader = () => {
+  const dispatch = useAppDispatch();
+  const { t } = useTranslation();
+
+  const handleResetInitialImage = useCallback(() => {
+    dispatch(clearInitialImage());
+  }, [dispatch]);
+
+  return (
+    <Flex w="full" alignItems="center">
+      <Text size="sm" fontWeight={500} color="base.300">
+        Image to Image
+      </Text>
+      <Spacer />
+      <ButtonGroup>
+        <IAIIconButton
+          size="sm"
+          icon={<FaUndo />}
+          aria-label={t('accessibility.reset')}
+          onClick={handleResetInitialImage}
+        />
+        <IAIIconButton
+          size="sm"
+          icon={<FaUpload />}
+          aria-label={t('common.upload')}
+        />
+      </ButtonGroup>
+    </Flex>
+  );
+};
+
+export default ImageToImageSettingsHeader;

invokeai/frontend/web/src/common/components/ImageUploader.tsx

@@ -1,8 +1,7 @@
 import { Box, useToast } from '@chakra-ui/react';
 import { ImageUploaderTriggerContext } from 'app/contexts/ImageUploaderTriggerContext';
-import { useAppDispatch, useAppSelector } from 'app/storeHooks';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import useImageUploader from 'common/hooks/useImageUploader';
-import { uploadImage } from 'features/gallery/store/thunks/uploadImage';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { ResourceKey } from 'i18next';
 import {
@@ -15,6 +14,7 @@ import {
 } from 'react';
 import { FileRejection, useDropzone } from 'react-dropzone';
 import { useTranslation } from 'react-i18next';
+import { imageUploaded } from 'services/thunks/image';
 import ImageUploadOverlay from './ImageUploadOverlay';
 
 type ImageUploaderProps = {
@@ -49,7 +49,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
 
   const fileAcceptedCallback = useCallback(
     async (file: File) => {
-      dispatch(uploadImage({ imageFile: file }));
+      dispatch(imageUploaded({ formData: { file } }));
     },
     [dispatch]
   );
@@ -124,7 +124,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
         return;
       }
 
-      dispatch(uploadImage({ imageFile: file }));
+      dispatch(imageUploaded({ formData: { file } }));
     };
     document.addEventListener('paste', pasteImageListener);
     return () => {

invokeai/frontend/web/src/common/components/Loading/Loading.tsx

@@ -0,0 +1,33 @@
+import { Flex, Image, Spinner } from '@chakra-ui/react';
+import InvokeAILogoImage from 'assets/images/logo.png';
+import { memo } from 'react';
+
+// This component loads before the theme so we cannot use theme tokens here
+
+const Loading = () => {
+  return (
+    <Flex
+      position="relative"
+      width="100vw"
+      height="100vh"
+      alignItems="center"
+      justifyContent="center"
+      bg="#151519"
+    >
+      <Image src={InvokeAILogoImage} w="8rem" h="8rem" />
+      <Spinner
+        label="Loading"
+        color="grey"
+        position="absolute"
+        size="sm"
+        width="24px !important"
+        height="24px !important"
+        right="1.5rem"
+        bottom="1.5rem"
+        speed="1.2s"
+      />
+    </Flex>
+  );
+};
+
+export default memo(Loading);

invokeai/frontend/web/src/common/components/SelectImagePlaceholder.tsx

@@ -0,0 +1,22 @@
+import { Flex, Icon } from '@chakra-ui/react';
+import { FaImage } from 'react-icons/fa';
+
+const SelectImagePlaceholder = () => {
+  return (
+    <Flex
+      sx={{
+        w: 'full',
+        h: 'full',
+        bg: 'base.800',
+        borderRadius: 'base',
+        alignItems: 'center',
+        justifyContent: 'center',
+        aspectRatio: '1/1',
+      }}
+    >
+      <Icon color="base.400" boxSize={32} as={FaImage}></Icon>
+    </Flex>
+  );
+};
+
+export default SelectImagePlaceholder;