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Merge branch 'main' into pin-timm-for-llava

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Eugene Brodsky 2025-03-31 11:37:29 -04:00 committed by GitHub
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21
.github/workflows/python-checks.yml vendored
View File

@ -34,6 +34,9 @@ on:
jobs:
python-checks:
env:
# uv requires a venv by default - but for this, we can simply use the system python
UV_SYSTEM_PYTHON: 1
runs-on: ubuntu-latest
timeout-minutes: 5 # expected run time: <1 min
steps:
@ -57,25 +60,19 @@ jobs:
- '!invokeai/frontend/web/**'
- 'tests/**'
- name: setup python
- name: setup uv
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
uses: actions/setup-python@v5
uses: astral-sh/setup-uv@v5
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
- name: install ruff
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: pip install ruff==0.9.9
shell: bash
version: '0.6.10'
enable-cache: true
- name: ruff check
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: ruff check --output-format=github .
run: uv tool run ruff@0.11.2 check --output-format=github .
shell: bash
- name: ruff format
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
run: ruff format --check .
run: uv tool run ruff@0.11.2 format --check .
shell: bash

30
.github/workflows/python-tests.yml vendored
View File

@ -39,24 +39,15 @@ jobs:
strategy:
matrix:
python-version:
- '3.10'
- '3.11'
- '3.12'
platform:
- linux-cuda-11_7
- linux-rocm-5_2
- linux-cpu
- macos-default
- windows-cpu
include:
- platform: linux-cuda-11_7
os: ubuntu-22.04
github-env: $GITHUB_ENV
- platform: linux-rocm-5_2
os: ubuntu-22.04
extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
github-env: $GITHUB_ENV
- platform: linux-cpu
os: ubuntu-22.04
os: ubuntu-24.04
extra-index-url: 'https://download.pytorch.org/whl/cpu'
github-env: $GITHUB_ENV
- platform: macos-default
@ -70,6 +61,8 @@ jobs:
timeout-minutes: 15 # expected run time: 2-6 min, depending on platform
env:
PIP_USE_PEP517: '1'
UV_SYSTEM_PYTHON: 1
steps:
- name: checkout
# https://github.com/nschloe/action-cached-lfs-checkout
@ -92,20 +85,25 @@ jobs:
- '!invokeai/frontend/web/**'
- 'tests/**'
- name: setup uv
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
uses: astral-sh/setup-uv@v5
with:
version: '0.6.10'
enable-cache: true
python-version: ${{ matrix.python-version }}
- name: setup python
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: pip
cache-dependency-path: pyproject.toml
- name: install dependencies
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
env:
PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
run: >
pip3 install --editable=".[test]"
UV_INDEX: ${{ matrix.extra-index-url }}
run: uv pip install --editable ".[test]"
- name: run pytest
if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}

20
.github/workflows/typegen-checks.yml vendored
View File

@ -54,17 +54,25 @@ jobs:
- 'pyproject.toml'
- 'invokeai/**'
- name: setup uv
if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
uses: astral-sh/setup-uv@v5
with:
version: '0.6.10'
enable-cache: true
python-version: '3.11'
- name: setup python
if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
uses: actions/setup-python@v5
with:
python-version: '3.10'
cache: pip
cache-dependency-path: pyproject.toml
python-version: '3.11'
- name: install python dependencies
- name: install dependencies
if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
run: pip3 install --use-pep517 --editable="."
env:
UV_INDEX: ${{ matrix.extra-index-url }}
run: uv pip install --editable .
- name: install frontend dependencies
if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
@ -77,7 +85,7 @@ jobs:
- name: generate schema
if: ${{ steps.changed-files.outputs.src_any_changed == 'true' || inputs.always_run == true }}
run: make frontend-typegen
run: cd invokeai/frontend/web && uv run ../../../scripts/generate_openapi_schema.py | pnpm typegen
shell: bash
- name: compare files

16
invokeai/app/api/routers/images.py
View File

@ -96,6 +96,22 @@ async def upload_image(
raise HTTPException(status_code=500, detail="Failed to create image")
class ImageUploadEntry(BaseModel):
image_dto: ImageDTO = Body(description="The image DTO")
presigned_url: str = Body(description="The URL to get the presigned URL for the image upload")
@images_router.post("/", operation_id="create_image_upload_entry")
async def create_image_upload_entry(
width: int = Body(description="The width of the image"),
height: int = Body(description="The height of the image"),
board_id: Optional[str] = Body(default=None, description="The board to add this image to, if any"),
) -> ImageUploadEntry:
"""Uploads an image from a URL, not implemented"""
raise HTTPException(status_code=501, detail="Not implemented")
@images_router.delete("/i/{image_name}", operation_id="delete_image")
async def delete_image(
image_name: str = Path(description="The name of the image to delete"),

203
invokeai/app/invocations/baseinvocation.py
View File

@ -8,6 +8,7 @@ import sys
import warnings
from abc import ABC, abstractmethod
from enum import Enum
from functools import lru_cache
from inspect import signature
from typing import (
TYPE_CHECKING,
@ -27,7 +28,6 @@ import semver
from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, create_model
from pydantic.fields import FieldInfo
from pydantic_core import PydanticUndefined
from typing_extensions import TypeAliasType
from invokeai.app.invocations.fields import (
FieldKind,
@ -100,37 +100,6 @@ class BaseInvocationOutput(BaseModel):
All invocation outputs must use the `@invocation_output` decorator to provide their unique type.
"""
_output_classes: ClassVar[set[BaseInvocationOutput]] = set()
_typeadapter: ClassVar[Optional[TypeAdapter[Any]]] = None
_typeadapter_needs_update: ClassVar[bool] = False
@classmethod
def register_output(cls, output: BaseInvocationOutput) -> None:
"""Registers an invocation output."""
cls._output_classes.add(output)
cls._typeadapter_needs_update = True
@classmethod
def get_outputs(cls) -> Iterable[BaseInvocationOutput]:
"""Gets all invocation outputs."""
return cls._output_classes
@classmethod
def get_typeadapter(cls) -> TypeAdapter[Any]:
"""Gets a pydantc TypeAdapter for the union of all invocation output types."""
if not cls._typeadapter or cls._typeadapter_needs_update:
AnyInvocationOutput = TypeAliasType(
"AnyInvocationOutput", Annotated[Union[tuple(cls._output_classes)], Field(discriminator="type")]
)
cls._typeadapter = TypeAdapter(AnyInvocationOutput)
cls._typeadapter_needs_update = False
return cls._typeadapter
@classmethod
def get_output_types(cls) -> Iterable[str]:
"""Gets all invocation output types."""
return (i.get_type() for i in BaseInvocationOutput.get_outputs())
@staticmethod
def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseInvocationOutput]) -> None:
"""Adds various UI-facing attributes to the invocation output's OpenAPI schema."""
@ -173,76 +142,16 @@ class BaseInvocation(ABC, BaseModel):
All invocations must use the `@invocation` decorator to provide their unique type.
"""
_invocation_classes: ClassVar[set[BaseInvocation]] = set()
_typeadapter: ClassVar[Optional[TypeAdapter[Any]]] = None
_typeadapter_needs_update: ClassVar[bool] = False
@classmethod
def get_type(cls) -> str:
"""Gets the invocation's type, as provided by the `@invocation` decorator."""
return cls.model_fields["type"].default
@classmethod
def register_invocation(cls, invocation: BaseInvocation) -> None:
"""Registers an invocation."""
cls._invocation_classes.add(invocation)
cls._typeadapter_needs_update = True
@classmethod
def get_typeadapter(cls) -> TypeAdapter[Any]:
"""Gets a pydantc TypeAdapter for the union of all invocation types."""
if not cls._typeadapter or cls._typeadapter_needs_update:
AnyInvocation = TypeAliasType(
"AnyInvocation", Annotated[Union[tuple(cls.get_invocations())], Field(discriminator="type")]
)
cls._typeadapter = TypeAdapter(AnyInvocation)
cls._typeadapter_needs_update = False
return cls._typeadapter
@classmethod
def invalidate_typeadapter(cls) -> None:
"""Invalidates the typeadapter, forcing it to be rebuilt on next access. If the invocation allowlist or
denylist is changed, this should be called to ensure the typeadapter is updated and validation respects
the updated allowlist and denylist."""
cls._typeadapter_needs_update = True
@classmethod
def get_invocations(cls) -> Iterable[BaseInvocation]:
"""Gets all invocations, respecting the allowlist and denylist."""
app_config = get_config()
allowed_invocations: set[BaseInvocation] = set()
for sc in cls._invocation_classes:
invocation_type = sc.get_type()
is_in_allowlist = (
invocation_type in app_config.allow_nodes if isinstance(app_config.allow_nodes, list) else True
)
is_in_denylist = (
invocation_type in app_config.deny_nodes if isinstance(app_config.deny_nodes, list) else False
)
if is_in_allowlist and not is_in_denylist:
allowed_invocations.add(sc)
return allowed_invocations
@classmethod
def get_invocations_map(cls) -> dict[str, BaseInvocation]:
"""Gets a map of all invocation types to their invocation classes."""
return {i.get_type(): i for i in BaseInvocation.get_invocations()}
@classmethod
def get_invocation_types(cls) -> Iterable[str]:
"""Gets all invocation types."""
return (i.get_type() for i in BaseInvocation.get_invocations())
@classmethod
def get_output_annotation(cls) -> BaseInvocationOutput:
"""Gets the invocation's output annotation (i.e. the return annotation of its `invoke()` method)."""
return signature(cls.invoke).return_annotation
@classmethod
def get_invocation_for_type(cls, invocation_type: str) -> BaseInvocation | None:
"""Gets the invocation class for a given invocation type."""
return cls.get_invocations_map().get(invocation_type)
@staticmethod
def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseInvocation]) -> None:
"""Adds various UI-facing attributes to the invocation's OpenAPI schema."""
@ -340,6 +249,105 @@ class BaseInvocation(ABC, BaseModel):
TBaseInvocation = TypeVar("TBaseInvocation", bound=BaseInvocation)
class InvocationRegistry:
_invocation_classes: ClassVar[set[type[BaseInvocation]]] = set()
_output_classes: ClassVar[set[type[BaseInvocationOutput]]] = set()
@classmethod
def register_invocation(cls, invocation: type[BaseInvocation]) -> None:
"""Registers an invocation."""
cls._invocation_classes.add(invocation)
cls.invalidate_invocation_typeadapter()
@classmethod
@lru_cache(maxsize=1)
def get_invocation_typeadapter(cls) -> TypeAdapter[Any]:
"""Gets a pydantic TypeAdapter for the union of all invocation types.
This is used to parse serialized invocations into the correct invocation class.
This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
the updated allowlist and denylist.
@see https://docs.pydantic.dev/latest/concepts/type_adapter/
"""
return TypeAdapter(Annotated[Union[tuple(cls.get_invocation_classes())], Field(discriminator="type")])
@classmethod
def invalidate_invocation_typeadapter(cls) -> None:
"""Invalidates the cached invocation type adapter."""
cls.get_invocation_typeadapter.cache_clear()
@classmethod
def get_invocation_classes(cls) -> Iterable[type[BaseInvocation]]:
"""Gets all invocations, respecting the allowlist and denylist."""
app_config = get_config()
allowed_invocations: set[type[BaseInvocation]] = set()
for sc in cls._invocation_classes:
invocation_type = sc.get_type()
is_in_allowlist = (
invocation_type in app_config.allow_nodes if isinstance(app_config.allow_nodes, list) else True
)
is_in_denylist = (
invocation_type in app_config.deny_nodes if isinstance(app_config.deny_nodes, list) else False
)
if is_in_allowlist and not is_in_denylist:
allowed_invocations.add(sc)
return allowed_invocations
@classmethod
def get_invocations_map(cls) -> dict[str, type[BaseInvocation]]:
"""Gets a map of all invocation types to their invocation classes."""
return {i.get_type(): i for i in cls.get_invocation_classes()}
@classmethod
def get_invocation_types(cls) -> Iterable[str]:
"""Gets all invocation types."""
return (i.get_type() for i in cls.get_invocation_classes())
@classmethod
def get_invocation_for_type(cls, invocation_type: str) -> type[BaseInvocation] | None:
"""Gets the invocation class for a given invocation type."""
return cls.get_invocations_map().get(invocation_type)
@classmethod
def register_output(cls, output: "type[TBaseInvocationOutput]") -> None:
"""Registers an invocation output."""
cls._output_classes.add(output)
cls.invalidate_output_typeadapter()
@classmethod
def get_output_classes(cls) -> Iterable[type[BaseInvocationOutput]]:
"""Gets all invocation outputs."""
return cls._output_classes
@classmethod
@lru_cache(maxsize=1)
def get_output_typeadapter(cls) -> TypeAdapter[Any]:
"""Gets a pydantic TypeAdapter for the union of all invocation output types.
This is used to parse serialized invocation outputs into the correct invocation output class.
This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
the updated allowlist and denylist.
@see https://docs.pydantic.dev/latest/concepts/type_adapter/
"""
return TypeAdapter(Annotated[Union[tuple(cls._output_classes)], Field(discriminator="type")])
@classmethod
def invalidate_output_typeadapter(cls) -> None:
"""Invalidates the cached invocation output type adapter."""
cls.get_output_typeadapter.cache_clear()
@classmethod
def get_output_types(cls) -> Iterable[str]:
"""Gets all invocation output types."""
return (i.get_type() for i in cls.get_output_classes())
RESERVED_NODE_ATTRIBUTE_FIELD_NAMES = {
"id",
"is_intermediate",
@ -453,8 +461,8 @@ def invocation(
node_pack = cls.__module__.split(".")[0]
# Handle the case where an existing node is being clobbered by the one we are registering
if invocation_type in BaseInvocation.get_invocation_types():
clobbered_invocation = BaseInvocation.get_invocation_for_type(invocation_type)
if invocation_type in InvocationRegistry.get_invocation_types():
clobbered_invocation = InvocationRegistry.get_invocation_for_type(invocation_type)
# This should always be true - we just checked if the invocation type was in the set
assert clobbered_invocation is not None
@ -539,8 +547,7 @@ def invocation(
)
cls.__doc__ = docstring
# TODO: how to type this correctly? it's typed as ModelMetaclass, a private class in pydantic
BaseInvocation.register_invocation(cls) # type: ignore
InvocationRegistry.register_invocation(cls)
return cls
@ -565,7 +572,7 @@ def invocation_output(
if re.compile(r"^\S+$").match(output_type) is None:
raise ValueError(f'"output_type" must consist of non-whitespace characters, got "{output_type}"')
if output_type in BaseInvocationOutput.get_output_types():
if output_type in InvocationRegistry.get_output_types():
raise ValueError(f'Invocation type "{output_type}" already exists')
validate_fields(cls.model_fields, output_type)
@ -586,7 +593,7 @@ def invocation_output(
)
cls.__doc__ = docstring
BaseInvocationOutput.register_output(cls) # type: ignore # TODO: how to type this correctly?
InvocationRegistry.register_output(cls)
return cls

19
invokeai/app/invocations/image.py
View File

@ -1089,7 +1089,7 @@ class CanvasV2MaskAndCropInvocation(BaseInvocation, WithMetadata, WithBoard):
@invocation(
"expand_mask_with_fade", title="Expand Mask with Fade", tags=["image", "mask"], category="image", version="1.0.0"
"expand_mask_with_fade", title="Expand Mask with Fade", tags=["image", "mask"], category="image", version="1.0.1"
)
class ExpandMaskWithFadeInvocation(BaseInvocation, WithMetadata, WithBoard):
"""Expands a mask with a fade effect. The mask uses black to indicate areas to keep from the generated image and white for areas to discard.
@ -1147,8 +1147,21 @@ class ExpandMaskWithFadeInvocation(BaseInvocation, WithMetadata, WithBoard):
coeffs = numpy.polyfit(x_control, y_control, 3)
poly = numpy.poly1d(coeffs)
# Evaluate and clip the smooth mapping
feather = numpy.clip(poly(d_norm), 0, 1)
# Evaluate the polynomial
feather = poly(d_norm)
# The polynomial fit isn't perfect. Points beyond the fade distance are likely to be slightly less than 1.0,
# even though the control points indicate that they should be exactly 1.0. This is due to the nature of the
# polynomial fit, which is a best approximation of the control points but not an exact match.
# When this occurs, the area outside the mask and fade-out will not be 100% transparent. For example, it may
# have an alpha value of 1 instead of 0. So we must force pixels at or beyond the fade distance to exactly 1.0.
# Force pixels at or beyond the fade distance to exactly 1.0
feather = numpy.where(d_norm >= 1.0, 1.0, feather)
# Clip any other values to ensure they're in the valid range [0,1]
feather = numpy.clip(feather, 0, 1)
# Build final image.
np_result = numpy.where(black_mask == 1, 0, (feather * 255).astype(numpy.uint8))

9
invokeai/app/services/shared/graph.py
View File

@ -21,6 +21,7 @@ from invokeai.app.invocations import * # noqa: F401 F403
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
InvocationRegistry,
invocation,
invocation_output,
)
@ -283,7 +284,7 @@ class AnyInvocation(BaseInvocation):
@classmethod
def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema:
def validate_invocation(v: Any) -> "AnyInvocation":
return BaseInvocation.get_typeadapter().validate_python(v)
return InvocationRegistry.get_invocation_typeadapter().validate_python(v)
return core_schema.no_info_plain_validator_function(validate_invocation)
@ -294,7 +295,7 @@ class AnyInvocation(BaseInvocation):
# Nodes are too powerful, we have to make our own OpenAPI schema manually
# No but really, because the schema is dynamic depending on loaded nodes, we need to generate it manually
oneOf: list[dict[str, str]] = []
names = [i.__name__ for i in BaseInvocation.get_invocations()]
names = [i.__name__ for i in InvocationRegistry.get_invocation_classes()]
for name in sorted(names):
oneOf.append({"$ref": f"#/components/schemas/{name}"})
return {"oneOf": oneOf}
@ -304,7 +305,7 @@ class AnyInvocationOutput(BaseInvocationOutput):
@classmethod
def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler):
def validate_invocation_output(v: Any) -> "AnyInvocationOutput":
return BaseInvocationOutput.get_typeadapter().validate_python(v)
return InvocationRegistry.get_output_typeadapter().validate_python(v)
return core_schema.no_info_plain_validator_function(validate_invocation_output)
@ -316,7 +317,7 @@ class AnyInvocationOutput(BaseInvocationOutput):
# No but really, because the schema is dynamic depending on loaded nodes, we need to generate it manually
oneOf: list[dict[str, str]] = []
names = [i.__name__ for i in BaseInvocationOutput.get_outputs()]
names = [i.__name__ for i in InvocationRegistry.get_output_classes()]
for name in sorted(names):
oneOf.append({"$ref": f"#/components/schemas/{name}"})
return {"oneOf": oneOf}

9
invokeai/app/util/custom_openapi.py
View File

@ -4,7 +4,10 @@ from fastapi import FastAPI
from fastapi.openapi.utils import get_openapi
from pydantic.json_schema import models_json_schema
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, UIConfigBase
from invokeai.app.invocations.baseinvocation import (
InvocationRegistry,
UIConfigBase,
)
from invokeai.app.invocations.fields import InputFieldJSONSchemaExtra, OutputFieldJSONSchemaExtra
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.services.events.events_common import EventBase
@ -56,14 +59,14 @@ def get_openapi_func(
invocation_output_map_required: list[str] = []
# We need to manually add all outputs to the schema - pydantic doesn't add them because they aren't used directly.
for output in BaseInvocationOutput.get_outputs():
for output in InvocationRegistry.get_output_classes():
json_schema = output.model_json_schema(mode="serialization", ref_template="#/components/schemas/{model}")
move_defs_to_top_level(openapi_schema, json_schema)
openapi_schema["components"]["schemas"][output.__name__] = json_schema
# Technically, invocations are added to the schema by pydantic, but we still need to manually set their output
# property, so we'll just do it all manually.
for invocation in BaseInvocation.get_invocations():
for invocation in InvocationRegistry.get_invocation_classes():
json_schema = invocation.model_json_schema(
mode="serialization", ref_template="#/components/schemas/{model}"
)

23
invokeai/backend/flux/flux_state_dict_utils.py Normal file
View File

@ -0,0 +1,23 @@
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from invokeai.backend.model_manager.legacy_probe import CkptType
def get_flux_in_channels_from_state_dict(state_dict: "CkptType") -> int | None:
"""Gets the in channels from the state dict."""
# "Standard" FLUX models use "img_in.weight", but some community fine tunes use
# "model.diffusion_model.img_in.weight". Known models that use the latter key:
# - https://civitai.com/models/885098?modelVersionId=990775
# - https://civitai.com/models/1018060?modelVersionId=1596255
# - https://civitai.com/models/978314/ultrareal-fine-tune?modelVersionId=1413133
keys = {"img_in.weight", "model.diffusion_model.img_in.weight"}
for key in keys:
val = state_dict.get(key)
if val is not None:
return val.shape[1]
return None

10
invokeai/backend/model_manager/legacy_probe.py
View File

@ -14,6 +14,7 @@ from invokeai.backend.flux.controlnet.state_dict_utils import (
is_state_dict_instantx_controlnet,
is_state_dict_xlabs_controlnet,
)
from invokeai.backend.flux.flux_state_dict_utils import get_flux_in_channels_from_state_dict
from invokeai.backend.flux.ip_adapter.state_dict_utils import is_state_dict_xlabs_ip_adapter
from invokeai.backend.flux.redux.flux_redux_state_dict_utils import is_state_dict_likely_flux_redux
from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS, ModelHash
@ -564,7 +565,14 @@ class CheckpointProbeBase(ProbeBase):
state_dict = self.checkpoint.get("state_dict") or self.checkpoint
if base_type == BaseModelType.Flux:
in_channels = state_dict["img_in.weight"].shape[1]
in_channels = get_flux_in_channels_from_state_dict(state_dict)
if in_channels is None:
# If we cannot find the in_channels, we assume that this is a normal variant. Log a warning.
logger.warning(
f"{self.model_path} does not have img_in.weight or model.diffusion_model.img_in.weight key. Assuming normal variant."
)
return ModelVariantType.Normal
# FLUX Model variant types are distinguished by input channels:
# - Unquantized Dev and Schnell have in_channels=64

60
invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts
View File

@ -1,6 +1,8 @@
import { isAnyOf } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { RootState } from 'app/store/store';
import { imageUploadedClientSide } from 'features/gallery/store/actions';
import { selectListBoardsQueryArgs } from 'features/gallery/store/gallerySelectors';
import { boardIdSelected, galleryViewChanged } from 'features/gallery/store/gallerySlice';
import { toast } from 'features/toast/toast';
@ -8,7 +10,8 @@ import { t } from 'i18next';
import { omit } from 'lodash-es';
import { boardsApi } from 'services/api/endpoints/boards';
import { imagesApi } from 'services/api/endpoints/images';
import type { ImageDTO } from 'services/api/types';
import { getCategories, getListImagesUrl } from 'services/api/util';
const log = logger('gallery');
/**
@ -34,19 +37,56 @@ let lastUploadedToastTimeout: number | null = null;
export const addImageUploadedFulfilledListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.uploadImage.matchFulfilled,
matcher: isAnyOf(imagesApi.endpoints.uploadImage.matchFulfilled, imageUploadedClientSide),
effect: (action, { dispatch, getState }) => {
const imageDTO = action.payload;
let imageDTO: ImageDTO;
let silent;
let isFirstUploadOfBatch = true;
if (imageUploadedClientSide.match(action)) {
imageDTO = action.payload.imageDTO;
silent = action.payload.silent;
isFirstUploadOfBatch = action.payload.isFirstUploadOfBatch;
} else if (imagesApi.endpoints.uploadImage.matchFulfilled(action)) {
imageDTO = action.payload;
silent = action.meta.arg.originalArgs.silent;
isFirstUploadOfBatch = action.meta.arg.originalArgs.isFirstUploadOfBatch ?? true;
} else {
return;
}
if (silent || imageDTO.is_intermediate) {
// If the image is silent or intermediate, we don't want to show a toast
return;
}
if (imageUploadedClientSide.match(action)) {
const categories = getCategories(imageDTO);
const boardId = imageDTO.board_id ?? 'none';
dispatch(
imagesApi.util.invalidateTags([
{
type: 'ImageList',
id: getListImagesUrl({
board_id: boardId,
categories,
}),
},
{
type: 'Board',
id: boardId,
},
{
type: 'BoardImagesTotal',
id: boardId,
},
])
);
}
const state = getState();
log.debug({ imageDTO }, 'Image uploaded');
if (action.meta.arg.originalArgs.silent || imageDTO.is_intermediate) {
// When a "silent" upload is requested, or the image is intermediate, we can skip all post-upload actions,
// like toasts and switching the gallery view
return;
}
const boardId = imageDTO.board_id ?? 'none';
const DEFAULT_UPLOADED_TOAST = {
@ -80,7 +120,7 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
*
* Default to true to not require _all_ image upload handlers to set this value
*/
const isFirstUploadOfBatch = action.meta.arg.originalArgs.isFirstUploadOfBatch ?? true;
if (isFirstUploadOfBatch) {
dispatch(boardIdSelected({ boardId }));
dispatch(galleryViewChanged('assets'));

2
invokeai/frontend/web/src/app/types/invokeai.ts
View File

@ -73,6 +73,7 @@ export type AppConfig = {
maxUpscaleDimension?: number;
allowPrivateBoards: boolean;
allowPrivateStylePresets: boolean;
allowClientSideUpload: boolean;
disabledTabs: TabName[];
disabledFeatures: AppFeature[];
disabledSDFeatures: SDFeature[];
@ -81,7 +82,6 @@ export type AppConfig = {
metadataFetchDebounce?: number;
workflowFetchDebounce?: number;
isLocal?: boolean;
maxImageUploadCount?: number;
sd: {
defaultModel?: string;
disabledControlNetModels: string[];

105
invokeai/frontend/web/src/common/hooks/useClientSideUpload.ts Normal file
View File

@ -0,0 +1,105 @@
import { useStore } from '@nanostores/react';
import { $authToken } from 'app/store/nanostores/authToken';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { imageUploadedClientSide } from 'features/gallery/store/actions';
import { selectAutoAddBoardId } from 'features/gallery/store/gallerySelectors';
import { useCallback } from 'react';
import { useCreateImageUploadEntryMutation } from 'services/api/endpoints/images';
import type { ImageDTO } from 'services/api/types';
export const useClientSideUpload = () => {
const dispatch = useAppDispatch();
const autoAddBoardId = useAppSelector(selectAutoAddBoardId);
const authToken = useStore($authToken);
const [createImageUploadEntry] = useCreateImageUploadEntryMutation();
const clientSideUpload = useCallback(
async (file: File, i: number): Promise<ImageDTO> => {
const image = new Image();
const objectURL = URL.createObjectURL(file);
image.src = objectURL;
let width = 0;
let height = 0;
let thumbnail: Blob | undefined;
await new Promise<void>((resolve) => {
image.onload = () => {
width = image.naturalWidth;
height = image.naturalHeight;
// Calculate thumbnail dimensions maintaining aspect ratio
let thumbWidth = width;
let thumbHeight = height;
if (width > height && width > 256) {
thumbWidth = 256;
thumbHeight = Math.round((height * 256) / width);
} else if (height > 256) {
thumbHeight = 256;
thumbWidth = Math.round((width * 256) / height);
}
const canvas = document.createElement('canvas');
canvas.width = thumbWidth;
canvas.height = thumbHeight;
const ctx = canvas.getContext('2d');
ctx?.drawImage(image, 0, 0, thumbWidth, thumbHeight);
canvas.toBlob(
(blob) => {
if (blob) {
thumbnail = blob;
// Clean up resources
URL.revokeObjectURL(objectURL);
image.src = ''; // Clear image source
image.remove(); // Remove the image element
canvas.width = 0; // Clear canvas
canvas.height = 0;
resolve();
}
},
'image/webp',
0.8
);
};
// Handle load errors
image.onerror = () => {
URL.revokeObjectURL(objectURL);
image.remove();
resolve();
};
});
const { presigned_url, image_dto } = await createImageUploadEntry({
width,
height,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
}).unwrap();
await fetch(`${presigned_url}/?type=full`, {
method: 'PUT',
body: file,
...(authToken && {
headers: {
Authorization: `Bearer ${authToken}`,
},
}),
});
await fetch(`${presigned_url}/?type=thumbnail`, {
method: 'PUT',
body: thumbnail,
...(authToken && {
headers: {
Authorization: `Bearer ${authToken}`,
},
}),
});
dispatch(imageUploadedClientSide({ imageDTO: image_dto, silent: false, isFirstUploadOfBatch: i === 0 }));
return image_dto;
},
[autoAddBoardId, authToken, createImageUploadEntry, dispatch]
);
return clientSideUpload;
};

43
invokeai/frontend/web/src/common/hooks/useImageUploadButton.tsx
View File

@ -3,7 +3,7 @@ import { IconButton } from '@invoke-ai/ui-library';
import { logger } from 'app/logging/logger';
import { useAppSelector } from 'app/store/storeHooks';
import { selectAutoAddBoardId } from 'features/gallery/store/gallerySelectors';
import { selectMaxImageUploadCount } from 'features/system/store/configSlice';
import { selectIsClientSideUploadEnabled } from 'features/system/store/configSlice';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import type { FileRejection } from 'react-dropzone';
@ -15,6 +15,7 @@ import type { ImageDTO } from 'services/api/types';
import { assert } from 'tsafe';
import type { SetOptional } from 'type-fest';
import { useClientSideUpload } from './useClientSideUpload';
type UseImageUploadButtonArgs =
| {
isDisabled?: boolean;
@ -50,8 +51,9 @@ const log = logger('gallery');
*/
export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: UseImageUploadButtonArgs) => {
const autoAddBoardId = useAppSelector(selectAutoAddBoardId);
const isClientSideUploadEnabled = useAppSelector(selectIsClientSideUploadEnabled);
const [uploadImage, request] = useUploadImageMutation();
const maxImageUploadCount = useAppSelector(selectMaxImageUploadCount);
const clientSideUpload = useClientSideUpload();
const { t } = useTranslation();
const onDropAccepted = useCallback(
@ -79,22 +81,27 @@ export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: Us
onUpload(imageDTO);
}
} else {
const imageDTOs = await uploadImages(
files.map((file, i) => ({
file,
image_category: 'user',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
silent: false,
isFirstUploadOfBatch: i === 0,
}))
);
let imageDTOs: ImageDTO[] = [];
if (isClientSideUploadEnabled) {
imageDTOs = await Promise.all(files.map((file, i) => clientSideUpload(file, i)));
} else {
imageDTOs = await uploadImages(
files.map((file, i) => ({
file,
image_category: 'user',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
silent: false,
isFirstUploadOfBatch: i === 0,
}))
);
}
if (onUpload) {
onUpload(imageDTOs);
}
}
},
[allowMultiple, autoAddBoardId, onUpload, uploadImage]
[allowMultiple, autoAddBoardId, onUpload, uploadImage, isClientSideUploadEnabled, clientSideUpload]
);
const onDropRejected = useCallback(
@ -105,10 +112,7 @@ export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: Us
file: rejection.file.path,
}));
log.error({ errors }, 'Invalid upload');
const description =
maxImageUploadCount === undefined
? t('toast.uploadFailedInvalidUploadDesc')
: t('toast.uploadFailedInvalidUploadDesc_withCount', { count: maxImageUploadCount });
const description = t('toast.uploadFailedInvalidUploadDesc');
toast({
id: 'UPLOAD_FAILED',
@ -120,7 +124,7 @@ export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: Us
return;
}
},
[maxImageUploadCount, t]
[t]
);
const {
@ -137,8 +141,7 @@ export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: Us
onDropRejected,
disabled: isDisabled,
noDrag: true,
multiple: allowMultiple && (maxImageUploadCount === undefined || maxImageUploadCount > 1),
maxFiles: maxImageUploadCount,
multiple: allowMultiple,
});
return { getUploadButtonProps, getUploadInputProps, openUploader, request };

24
invokeai/frontend/web/src/features/controlLayers/components/ParamDenoisingStrength.tsx
View File

@ -14,8 +14,9 @@ import WavyLine from 'common/components/WavyLine';
import { selectImg2imgStrength, setImg2imgStrength } from 'features/controlLayers/store/paramsSlice';
import { selectActiveRasterLayerEntities } from 'features/controlLayers/store/selectors';
import { selectImg2imgStrengthConfig } from 'features/system/store/configSlice';
import { memo, useCallback } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { useSelectedModelConfig } from 'services/api/hooks/useSelectedModelConfig';
const selectHasRasterLayersWithContent = createSelector(
selectActiveRasterLayerEntities,
@ -26,6 +27,7 @@ export const ParamDenoisingStrength = memo(() => {
const img2imgStrength = useAppSelector(selectImg2imgStrength);
const dispatch = useAppDispatch();
const hasRasterLayersWithContent = useAppSelector(selectHasRasterLayersWithContent);
const selectedModelConfig = useSelectedModelConfig();
const onChange = useCallback(
(v: number) => {
@ -39,8 +41,24 @@ export const ParamDenoisingStrength = memo(() => {
const [invokeBlue300] = useToken('colors', ['invokeBlue.300']);
const isDisabled = useMemo(() => {
if (!hasRasterLayersWithContent) {
// Denoising strength does nothing if there are no raster layers w/ content
return true;
}
if (
selectedModelConfig?.type === 'main' &&
selectedModelConfig?.base === 'flux' &&
selectedModelConfig.variant === 'inpaint'
) {
// Denoising strength is ignored by FLUX Fill, which is indicated by the variant being 'inpaint'
return true;
}
return false;
}, [hasRasterLayersWithContent, selectedModelConfig]);
return (
<FormControl isDisabled={!hasRasterLayersWithContent} p={1} justifyContent="space-between" h={8}>
<FormControl isDisabled={isDisabled} p={1} justifyContent="space-between" h={8}>
<Flex gap={3} alignItems="center">
<InformationalPopover feature="paramDenoisingStrength">
<FormLabel mr={0}>{`${t('parameters.denoisingStrength')}`}</FormLabel>
@ -49,7 +67,7 @@ export const ParamDenoisingStrength = memo(() => {
<WavyLine amplitude={img2imgStrength * 10} stroke={invokeBlue300} strokeWidth={1} width={40} height={14} />
)}
</Flex>
{hasRasterLayersWithContent ? (
{!isDisabled ? (
<>
<CompositeSlider
step={config.coarseStep}

47
invokeai/frontend/web/src/features/dnd/FullscreenDropzone.tsx
View File

@ -8,12 +8,13 @@ import { useStore } from '@nanostores/react';
import { getStore } from 'app/store/nanostores/store';
import { useAppSelector } from 'app/store/storeHooks';
import { $focusedRegion } from 'common/hooks/focus';
import { useClientSideUpload } from 'common/hooks/useClientSideUpload';
import { setFileToPaste } from 'features/controlLayers/components/CanvasPasteModal';
import { DndDropOverlay } from 'features/dnd/DndDropOverlay';
import type { DndTargetState } from 'features/dnd/types';
import { $imageViewer } from 'features/gallery/components/ImageViewer/useImageViewer';
import { selectAutoAddBoardId } from 'features/gallery/store/gallerySelectors';
import { selectMaxImageUploadCount } from 'features/system/store/configSlice';
import { selectIsClientSideUploadEnabled } from 'features/system/store/configSlice';
import { toast } from 'features/toast/toast';
import { selectActiveTab } from 'features/ui/store/uiSelectors';
import { memo, useCallback, useEffect, useRef, useState } from 'react';
@ -53,13 +54,6 @@ const zUploadFile = z
(file) => ({ message: `File extension .${file.name.split('.').at(-1)} is not supported` })
);
const getFilesSchema = (max?: number) => {
if (max === undefined) {
return z.array(zUploadFile);
}
return z.array(zUploadFile).max(max);
};
const sx = {
position: 'absolute',
top: 2,
@ -74,22 +68,19 @@ const sx = {
export const FullscreenDropzone = memo(() => {
const { t } = useTranslation();
const ref = useRef<HTMLDivElement>(null);
const maxImageUploadCount = useAppSelector(selectMaxImageUploadCount);
const [dndState, setDndState] = useState<DndTargetState>('idle');
const activeTab = useAppSelector(selectActiveTab);
const isImageViewerOpen = useStore($imageViewer);
const isClientSideUploadEnabled = useAppSelector(selectIsClientSideUploadEnabled);
const clientSideUpload = useClientSideUpload();
const validateAndUploadFiles = useCallback(
(files: File[]) => {
async (files: File[]) => {
const { getState } = getStore();
const uploadFilesSchema = getFilesSchema(maxImageUploadCount);
const parseResult = uploadFilesSchema.safeParse(files);
const parseResult = z.array(zUploadFile).safeParse(files);
if (!parseResult.success) {
const description =
maxImageUploadCount === undefined
? t('toast.uploadFailedInvalidUploadDesc')
: t('toast.uploadFailedInvalidUploadDesc_withCount', { count: maxImageUploadCount });
const description = t('toast.uploadFailedInvalidUploadDesc');
toast({
id: 'UPLOAD_FAILED',
@ -118,17 +109,23 @@ export const FullscreenDropzone = memo(() => {
const autoAddBoardId = selectAutoAddBoardId(getState());
const uploadArgs: UploadImageArg[] = files.map((file, i) => ({
file,
image_category: 'user',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
isFirstUploadOfBatch: i === 0,
}));
if (isClientSideUploadEnabled) {
for (const [i, file] of files.entries()) {
await clientSideUpload(file, i);
}
} else {
const uploadArgs: UploadImageArg[] = files.map((file, i) => ({
file,
image_category: 'user',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
isFirstUploadOfBatch: i === 0,
}));
uploadImages(uploadArgs);
uploadImages(uploadArgs);
}
},
[activeTab, isImageViewerOpen, maxImageUploadCount, t]
[activeTab, isImageViewerOpen, t, isClientSideUploadEnabled, clientSideUpload]
);
const onPaste = useCallback(

19
invokeai/frontend/web/src/features/gallery/components/GalleryUploadButton.tsx
View File

@ -1,31 +1,18 @@
import { IconButton } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { useImageUploadButton } from 'common/hooks/useImageUploadButton';
import { selectMaxImageUploadCount } from 'features/system/store/configSlice';
import { t } from 'i18next';
import { useMemo } from 'react';
import { PiUploadBold } from 'react-icons/pi';
export const GalleryUploadButton = () => {
const maxImageUploadCount = useAppSelector(selectMaxImageUploadCount);
const uploadOptions = useMemo(() => ({ allowMultiple: maxImageUploadCount !== 1 }), [maxImageUploadCount]);
const uploadApi = useImageUploadButton(uploadOptions);
const uploadApi = useImageUploadButton({ allowMultiple: true });
return (
<>
<IconButton
size="sm"
alignSelf="stretch"
variant="link"
aria-label={
maxImageUploadCount === undefined || maxImageUploadCount > 1
? t('accessibility.uploadImages')
: t('accessibility.uploadImage')
}
tooltip={
maxImageUploadCount === undefined || maxImageUploadCount > 1
? t('accessibility.uploadImages')
: t('accessibility.uploadImage')
}
aria-label={t('accessibility.uploadImages')}
tooltip={t('accessibility.uploadImages')}
icon={<PiUploadBold />}
{...uploadApi.getUploadButtonProps()}
/>

7
invokeai/frontend/web/src/features/gallery/store/actions.ts
View File

@ -1,4 +1,5 @@
import { createAction } from '@reduxjs/toolkit';
import type { ImageDTO } from 'services/api/types';
export const sentImageToCanvas = createAction('gallery/sentImageToCanvas');
@ -7,3 +8,9 @@ export const imageDownloaded = createAction('gallery/imageDownloaded');
export const imageCopiedToClipboard = createAction('gallery/imageCopiedToClipboard');
export const imageOpenedInNewTab = createAction('gallery/imageOpenedInNewTab');
export const imageUploadedClientSide = createAction<{
imageDTO: ImageDTO;
silent: boolean;
isFirstUploadOfBatch: boolean;
}>('gallery/imageUploadedClientSide');

4
invokeai/frontend/web/src/features/system/store/configSlice.ts
View File

@ -20,6 +20,7 @@ const initialConfigState: AppConfig = {
shouldFetchMetadataFromApi: false,
allowPrivateBoards: false,
allowPrivateStylePresets: false,
allowClientSideUpload: false,
disabledTabs: [],
disabledFeatures: ['lightbox', 'faceRestore', 'batches'],
disabledSDFeatures: ['variation', 'symmetry', 'hires', 'perlinNoise', 'noiseThreshold'],
@ -218,6 +219,5 @@ export const selectWorkflowFetchDebounce = createConfigSelector((config) => conf
export const selectMetadataFetchDebounce = createConfigSelector((config) => config.metadataFetchDebounce ?? 300);
export const selectIsModelsTabDisabled = createConfigSelector((config) => config.disabledTabs.includes('models'));
export const selectMaxImageUploadCount = createConfigSelector((config) => config.maxImageUploadCount);
export const selectIsClientSideUploadEnabled = createConfigSelector((config) => config.allowClientSideUpload);
export const selectIsLocal = createSelector(selectConfigSlice, (config) => config.isLocal);

12
invokeai/frontend/web/src/services/api/endpoints/images.ts
View File

@ -7,6 +7,8 @@ import type {
DeleteBoardResult,
GraphAndWorkflowResponse,
ImageDTO,
ImageUploadEntryRequest,
ImageUploadEntryResponse,
ListImagesArgs,
ListImagesResponse,
UploadImageArg,
@ -287,6 +289,7 @@ export const imagesApi = api.injectEndpoints({
},
};
},
invalidatesTags: (result) => {
if (!result || result.is_intermediate) {
// Don't add it to anything
@ -314,7 +317,13 @@ export const imagesApi = api.injectEndpoints({
];
},
}),
createImageUploadEntry: build.mutation<ImageUploadEntryResponse, ImageUploadEntryRequest>({
query: ({ width, height, board_id }) => ({
url: buildImagesUrl(),
method: 'POST',
body: { width, height, board_id },
}),
}),
deleteBoard: build.mutation<DeleteBoardResult, string>({
query: (board_id) => ({ url: buildBoardsUrl(board_id), method: 'DELETE' }),
invalidatesTags: () => [
@ -549,6 +558,7 @@ export const {
useGetImageWorkflowQuery,
useLazyGetImageWorkflowQuery,
useUploadImageMutation,
useCreateImageUploadEntryMutation,
useClearIntermediatesMutation,
useAddImagesToBoardMutation,
useRemoveImagesFromBoardMutation,

201
invokeai/frontend/web/src/services/api/schema.ts
View File

@ -466,6 +466,30 @@ export type paths = {
patch?: never;
trace?: never;
};
"/api/v1/images/": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* List Image Dtos
* @description Gets a list of image DTOs
*/
get: operations["list_image_dtos"];
put?: never;
/**
* Create Image Upload Entry
* @description Uploads an image from a URL, not implemented
*/
post: operations["create_image_upload_entry"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/api/v1/images/i/{image_name}": {
parameters: {
query?: never;
@ -619,26 +643,6 @@ export type paths = {
patch?: never;
trace?: never;
};
"/api/v1/images/": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* List Image Dtos
* @description Gets a list of image DTOs
*/
get: operations["list_image_dtos"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/api/v1/images/delete": {
parameters: {
query?: never;
@ -2358,6 +2362,24 @@ export type components = {
*/
batch_ids: string[];
};
/** Body_create_image_upload_entry */
Body_create_image_upload_entry: {
/**
* Width
* @description The width of the image
*/
width: number;
/**
* Height
* @description The height of the image
*/
height: number;
/**
* Board Id
* @description The board to add this image to, if any
*/
board_id?: string | null;
};
/** Body_create_style_preset */
Body_create_style_preset: {
/**
@ -10754,6 +10776,16 @@ export type components = {
*/
type: "i2l";
};
/** ImageUploadEntry */
ImageUploadEntry: {
/** @description The image DTO */
image_dto: components["schemas"]["ImageDTO"];
/**
* Presigned Url
* @description The URL to get the presigned URL for the image upload
*/
presigned_url: string;
};
/**
* ImageUrlsDTO
* @description The URLs for an image and its thumbnail.
@ -23219,6 +23251,87 @@ export interface operations {
};
};
};
list_image_dtos: {
parameters: {
query?: {
/** @description The origin of images to list. */
image_origin?: components["schemas"]["ResourceOrigin"] | null;
/** @description The categories of image to include. */
categories?: components["schemas"]["ImageCategory"][] | null;
/** @description Whether to list intermediate images. */
is_intermediate?: boolean | null;
/** @description The board id to filter by. Use 'none' to find images without a board. */
board_id?: string | null;
/** @description The page offset */
offset?: number;
/** @description The number of images per page */
limit?: number;
/** @description The order of sort */
order_dir?: components["schemas"]["SQLiteDirection"];
/** @description Whether to sort by starred images first */
starred_first?: boolean;
/** @description The term to search for */
search_term?: string | null;
};
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["OffsetPaginatedResults_ImageDTO_"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
create_image_upload_entry: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["Body_create_image_upload_entry"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["ImageUploadEntry"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
get_image_dto: {
parameters: {
query?: never;
@ -23572,54 +23685,6 @@ export interface operations {
};
};
};
list_image_dtos: {
parameters: {
query?: {
/** @description The origin of images to list. */
image_origin?: components["schemas"]["ResourceOrigin"] | null;
/** @description The categories of image to include. */
categories?: components["schemas"]["ImageCategory"][] | null;
/** @description Whether to list intermediate images. */
is_intermediate?: boolean | null;
/** @description The board id to filter by. Use 'none' to find images without a board. */
board_id?: string | null;
/** @description The page offset */
offset?: number;
/** @description The number of images per page */
limit?: number;
/** @description The order of sort */
order_dir?: components["schemas"]["SQLiteDirection"];
/** @description Whether to sort by starred images first */
starred_first?: boolean;
/** @description The term to search for */
search_term?: string | null;
};
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["OffsetPaginatedResults_ImageDTO_"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
delete_images_from_list: {
parameters: {
query?: never;

3
invokeai/frontend/web/src/services/api/types.ts
View File

@ -354,3 +354,6 @@ export type UploadImageArg = {
*/
isFirstUploadOfBatch?: boolean;
};
export type ImageUploadEntryResponse = S['ImageUploadEntry'];
export type ImageUploadEntryRequest = paths['/api/v1/images/']['post']['requestBody']['content']['application/json'];

2
invokeai/version/invokeai_version.py
View File

@ -1 +1 @@
__version__ = "5.9.0"
__version__ = "5.9.1"

2
pyproject.toml
View File

@ -117,7 +117,7 @@ dependencies = [
]
"dev" = ["jurigged", "pudb", "snakeviz", "gprof2dot"]
"test" = [
"ruff~=0.9.9",
"ruff~=0.11.2",
"ruff-lsp~=0.0.62",
"mypy",
"pre-commit",

4
tests/backend/flux/controlnet/test_state_dict_utils.py
View File

@ -24,7 +24,7 @@ from tests.backend.flux.controlnet.xlabs_flux_controlnet_state_dict import xlabs
],
)
def test_is_state_dict_xlabs_controlnet(sd_shapes: dict[str, list[int]], expected: bool):
sd = {k: None for k in sd_shapes}
sd = dict.fromkeys(sd_shapes)
assert is_state_dict_xlabs_controlnet(sd) == expected
@ -37,7 +37,7 @@ def test_is_state_dict_xlabs_controlnet(sd_shapes: dict[str, list[int]], expecte
],
)
def test_is_state_dict_instantx_controlnet(sd_keys: list[str], expected: bool):
sd = {k: None for k in sd_keys}
sd = dict.fromkeys(sd_keys)
assert is_state_dict_instantx_controlnet(sd) == expected

2
tests/backend/flux/ip_adapter/test_xlabs_ip_adapter_flux.py
View File

@ -19,7 +19,7 @@ from tests.backend.flux.ip_adapter.xlabs_flux_ip_adapter_v2_state_dict import xl
@pytest.mark.parametrize("sd_shapes", [xlabs_flux_ip_adapter_sd_shapes, xlabs_flux_ip_adapter_v2_sd_shapes])
def test_is_state_dict_xlabs_ip_adapter(sd_shapes: dict[str, list[int]]):
# Construct a dummy state_dict.
sd = {k: None for k in sd_shapes}
sd = dict.fromkeys(sd_shapes)
assert is_state_dict_xlabs_ip_adapter(sd)

8
tests/test_config.py
View File

@ -5,7 +5,7 @@ from typing import Any
import pytest
from pydantic import ValidationError
from invokeai.app.invocations.baseinvocation import BaseInvocation
from invokeai.app.invocations.baseinvocation import InvocationRegistry
from invokeai.app.services.config.config_default import (
DefaultInvokeAIAppConfig,
InvokeAIAppConfig,
@ -274,7 +274,7 @@ def test_deny_nodes(patch_rootdir):
# We've changed the config, we need to invalidate the typeadapter cache so that the new config is used for
# subsequent graph validations
BaseInvocation.invalidate_typeadapter()
InvocationRegistry.invalidate_invocation_typeadapter()
# confirm graph validation fails when using denied node
Graph.model_validate({"nodes": {"1": {"id": "1", "type": "integer"}}})
@ -284,7 +284,7 @@ def test_deny_nodes(patch_rootdir):
Graph.model_validate({"nodes": {"1": {"id": "1", "type": "float"}}})
# confirm invocations union will not have denied nodes
all_invocations = BaseInvocation.get_invocations()
all_invocations = InvocationRegistry.get_invocation_classes()
has_integer = len([i for i in all_invocations if i.get_type() == "integer"]) == 1
has_string = len([i for i in all_invocations if i.get_type() == "string"]) == 1
@ -296,4 +296,4 @@ def test_deny_nodes(patch_rootdir):
# Reset the config so that it doesn't affect other tests
get_config.cache_clear()
BaseInvocation.invalidate_typeadapter()
InvocationRegistry.invalidate_invocation_typeadapter()