fix typos

* add code to repopulate model config records after schema update

* reformat for ruff

* migrate model records using db cursor rather than the ModelRecordConfigService

* ruff fixes

* tweak exception reporting

* fix: build frontend in  pypi-release workflow

This was missing, resulting in the 3.5.0rc1 having no frontend.

* fix: use node 18, set working directory

- Node 20 has  a problem with `pnpm`; set it to Node 18
- Set the working directory for the frontend commands

* Don't copy extraneous paths into installer .zip

* feat(installer): delete frontend build after creating installer

This prevents an empty `dist/` from breaking the app on startup.

* feat: add python dist as release artifact, as input to enable publish to pypi

- The release workflow never runs automatically. It must be manually kicked off.
- The release workflow has an input. When running it from the GH actions UI, you will see a "Publish build on PyPi" prompt. If this value is "true", the workflow will upload the build to PyPi, releasing it. If this is anything else (e.g. "false", the default), the workflow will build but not upload to PyPi.
- The `dist/` folder (where the python package is built) is uploaded as a workflow artifact as a zip file. This can be downloaded and inspected. This allows "dry" runs of the workflow.
- The workflow job and some steps have been renamed to clarify what they do

* translationBot(ui): update translation files

Updated by "Cleanup translation files" hook in Weblate.

Co-authored-by: Hosted Weblate <hosted@weblate.org>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/
Translation: InvokeAI/Web UI

* freeze yaml migration logic at upgrade to 3.5

* moved migration code to migration_3

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Co-authored-by: Hosted Weblate <hosted@weblate.org>

.github/pull_request_template.md

@@ -42,6 +42,21 @@ Please provide steps on how to test changes, any hardware or
 software specifications as well as any other pertinent information. 
 -->
 
+## Merge Plan
+
+<!--
+A merge plan describes how this PR should be handled after it is approved.
+
+Example merge plans:
+- "This PR can be merged when approved"
+- "This must be squash-merged when approved"
+- "DO NOT MERGE - I will rebase and tidy commits before merging"
+- "#dev-chat on discord needs to be advised of this change when it is merged"
+
+A merge plan is particularly important for large PRs or PRs that touch the
+database in any way.
+-->
+
 ## Added/updated tests?
 
 - [ ] Yes

.github/workflows/lint-frontend.yml

@@ -21,16 +21,16 @@ jobs:
     if: github.event.pull_request.draft == false
     runs-on: ubuntu-22.04
     steps:
-      - name: Setup Node 20
+      - name: Setup Node 18
         uses: actions/setup-node@v4
         with:
-          node-version: '20'
+          node-version: '18'
       - name: Checkout
         uses: actions/checkout@v4
       - name: Setup pnpm
         uses: pnpm/action-setup@v2
         with:
-          version: 8
+          version: '8.12.1'
       - name: Install dependencies
         run: 'pnpm install --prefer-frozen-lockfile'
       - name: Typescript

.github/workflows/pypi-release.yml

@@ -1,13 +1,15 @@
 name: PyPI Release
 
 on:
-  push:
-    paths:
-      - 'invokeai/version/invokeai_version.py'
   workflow_dispatch:
+    inputs:
+      publish_package:
+        description: 'Publish build on PyPi? [true/false]'
+        required: true
+        default: 'false'
 
 jobs:
-  release:
+  build-and-release:
     if: github.repository == 'invoke-ai/InvokeAI'
     runs-on: ubuntu-22.04
     env:
@@ -15,19 +17,43 @@ jobs:
       TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
       TWINE_NON_INTERACTIVE: 1
     steps:
-      - name: checkout sources
-        uses: actions/checkout@v3
+      - name: Checkout
+        uses: actions/checkout@v4
 
-      - name: install deps
+      - name: Setup Node 18
+        uses: actions/setup-node@v4
+        with:
+          node-version: '18'
+
+      - name: Setup pnpm
+        uses: pnpm/action-setup@v2
+        with:
+          version: '8.12.1'
+
+      - name: Install frontend dependencies
+        run: pnpm install --prefer-frozen-lockfile
+        working-directory: invokeai/frontend/web
+
+      - name: Build frontend
+        run: pnpm run build
+        working-directory: invokeai/frontend/web
+
+      - name: Install python dependencies
         run: pip install --upgrade build twine
 
-      - name: build package
+      - name: Build python package
         run: python3 -m build
 
-      - name: check distribution
+      - name: Upload build as workflow artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: dist
+
+      - name: Check distribution
         run: twine check dist/*
 
-      - name: check PyPI versions
+      - name: Check PyPI versions
         if: github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/heads/release/')
         run: |
           pip install --upgrade requests
@@ -36,6 +62,6 @@ jobs:
           EXISTS=scripts.pypi_helper.local_on_pypi(); \
           print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
 
-      - name: upload package
-        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
+      - name: Publish build on PyPi
+        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != '' && github.event.inputs.publish_package == 'true'
         run: twine upload dist/*

docker/Dockerfile

@@ -59,14 +59,16 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 
 # #### Build the Web UI ------------------------------------
 
-FROM node:18 AS web-builder
+FROM node:18-slim AS web-builder
+ENV PNPM_HOME="/pnpm"
+ENV PATH="$PNPM_HOME:$PATH"
+RUN corepack enable
+
 WORKDIR /build
 COPY invokeai/frontend/web/ ./
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    npm install --include dev
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    yarn vite build
-
+RUN --mount=type=cache,target=/pnpm/store \
+    pnpm install --frozen-lockfile
+RUN pnpm run build
 
 #### Runtime stage ---------------------------------------
 

docker/README.md

@@ -23,7 +23,7 @@ This is done via Docker Desktop preferences
 1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
     a. the desired location of the InvokeAI runtime directory, or
     b. an existing, v3.0.0 compatible runtime directory.
-1. `docker compose up`
+1. Execute `run.sh`
 
 The image will be built automatically if needed.
 
@@ -39,7 +39,7 @@ The Docker daemon on the system must be already set up to use the GPU. In case o
 
 ## Customize
 
-Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `docker compose up`, your custom values will be used.
+Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `run.sh`, your custom values will be used.
 
 You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
 

docker/build.sh

@@ -1,11 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-build_args=""
-
-[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
-
-echo "docker compose build args:"
-echo $build_args
-
-docker compose build $build_args

docker/docker-compose.yml

@@ -2,23 +2,8 @@
 
 version: '3.8'
 
-services:
-  invokeai:
+x-invokeai: &invokeai
     image: "local/invokeai:latest"
-    # edit below to run on a container runtime other than nvidia-container-runtime.
-    # not yet tested with rocm/AMD GPUs
-    # Comment out the "deploy" section to run on CPU only
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - driver: nvidia
-              count: 1
-              capabilities: [gpu]
-    # For AMD support, comment out the deploy section above and uncomment the devices section below:
-    #devices:
-    #  - /dev/kfd:/dev/kfd
-    #  - /dev/dri:/dev/dri
     build:
       context: ..
       dockerfile: docker/Dockerfile
@@ -50,3 +35,27 @@ services:
     #   - |
     #     invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
     #     invokeai-nodes-web --host 0.0.0.0
+
+services:
+  invokeai-nvidia:
+    <<: *invokeai
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+  invokeai-cpu:
+    <<: *invokeai
+    profiles:
+      - cpu
+
+  invokeai-rocm:
+    <<: *invokeai
+    devices:
+      - /dev/kfd:/dev/kfd
+      - /dev/dri:/dev/dri
+    profiles:
+      - rocm

docker/run.sh

@@ -1,11 +1,28 @@
 #!/usr/bin/env bash
 set -e
 
-# This script is provided for backwards compatibility with the old docker setup.
-# it doesn't do much aside from wrapping the usual docker compose CLI.
+run() {
+  local scriptdir=$(dirname "${BASH_SOURCE[0]}")
+  cd "$scriptdir" || exit 1
 
-SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
-cd "$SCRIPTDIR" || exit 1
+  local build_args=""
+  local profile=""
 
-docker compose up -d
-docker compose logs -f
+  [[ -f ".env" ]] &&
+    build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
+    profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+
+  local service_name="invokeai-$profile"
+
+  printf "%s\n" "docker compose build args:"
+  printf "%s\n" "$build_args"
+
+  docker compose build $build_args
+  unset build_args
+
+  printf "%s\n" "starting service $service_name"
+  docker compose --profile "$profile" up -d "$service_name"
+  docker compose logs -f
+}
+
+run

docs/contributing/INVOCATIONS.md

@@ -11,7 +11,7 @@ complex functionality.
 
 InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These can be used as examples to create your own nodes.
 
-New nodes should be added to a subfolder in `nodes` direction found at the root level of the InvokeAI installation location. Nodes added to this folder will be able to be used upon application startup. 
+New nodes should be added to a subfolder in the `nodes` directory found at the root level of the InvokeAI installation location. Nodes added to this folder will be imported upon application startup. 
 
 Example `nodes`  subfolder structure:
 ```py

docs/installation/020_INSTALL_MANUAL.md

@@ -293,6 +293,19 @@ manager, please follow these steps:
 
 ## Developer Install
 
+!!! warning
+
+    InvokeAI uses a SQLite database. By running on `main`, you accept responsibility for your database. This
+    means making regular backups (especially before pulling) and/or fixing it yourself in the event that a
+    PR introduces a schema change.
+    
+    If you don't need persistent backend storage, you can use an ephemeral in-memory database by setting
+    `use_memory_db: true` under `Path:` in your `invokeai.yaml` file.
+
+    If this is untenable, you should run the application via the official installer or a manual install of the
+    python package from pypi. These releases will not break your database.
+
+
 If you have an interest in how InvokeAI works, or you would like to
 add features or bugfixes, you are encouraged to install the source
 code for InvokeAI. For this to work, you will need to install the
@@ -388,3 +401,5 @@ environment variable INVOKEAI_ROOT to point to the installation directory.
 
 Note that if you run into problems with the Conda installation, the InvokeAI
 staff will **not** be able to help you out. Caveat Emptor!
+
+[dev-chat]: https://discord.com/channels/1020123559063990373/1049495067846524939

docs/javascripts/init_kapa_widget.js

@@ -0,0 +1,10 @@
+document.addEventListener("DOMContentLoaded", function () {
+  var script = document.createElement("script");
+  script.src = "https://widget.kapa.ai/kapa-widget.bundle.js";
+  script.setAttribute("data-website-id", "b5973bb1-476b-451e-8cf4-98de86745a10");
+  script.setAttribute("data-project-name", "Invoke.AI");
+  script.setAttribute("data-project-color", "#11213C");
+  script.setAttribute("data-project-logo", "https://avatars.githubusercontent.com/u/113954515?s=280&v=4");
+  script.async = true;
+  document.head.appendChild(script);
+});

installer/create_installer.sh

@@ -91,9 +91,11 @@ rm -rf InvokeAI-Installer
 
 # copy content
 mkdir InvokeAI-Installer
-for f in templates lib *.txt *.reg; do
+for f in templates *.txt *.reg; do
     cp -r ${f} InvokeAI-Installer/
 done
+mkdir InvokeAI-Installer/lib
+cp lib/*.py InvokeAI-Installer/lib
 
 # Move the wheel
 mv dist/*.whl InvokeAI-Installer/lib/
@@ -111,6 +113,6 @@ cp WinLongPathsEnabled.reg InvokeAI-Installer/
 zip -r InvokeAI-installer-$VERSION.zip InvokeAI-Installer
 
 # clean up
-rm -rf InvokeAI-Installer tmp dist
+rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
 
 exit 0

installer/lib/installer.py

@@ -244,9 +244,9 @@ class InvokeAiInstance:
                 "numpy~=1.24.0",  # choose versions that won't be uninstalled during phase 2
                 "urllib3~=1.26.0",
                 "requests~=2.28.0",
-                "torch==2.1.0",
+                "torch==2.1.1",
                 "torchmetrics==0.11.4",
-                "torchvision>=0.14.1",
+                "torchvision>=0.16.1",
                 "--force-reinstall",
                 "--find-links" if find_links is not None else None,
                 find_links,

invokeai/app/api/routers/model_records.py

@@ -26,7 +26,7 @@ from invokeai.backend.model_manager.config import (
 
 from ..dependencies import ApiDependencies
 
-model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2"])
+model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2_unstable"])
 
 
 class ModelsList(BaseModel):
@@ -45,6 +45,9 @@ async def list_model_records(
     base_models: Optional[List[BaseModelType]] = Query(default=None, description="Base models to include"),
     model_type: Optional[ModelType] = Query(default=None, description="The type of model to get"),
     model_name: Optional[str] = Query(default=None, description="Exact match on the name of the model"),
+    model_format: Optional[str] = Query(
+        default=None, description="Exact match on the format of the model (e.g. 'diffusers')"
+    ),
 ) -> ModelsList:
     """Get a list of models."""
     record_store = ApiDependencies.invoker.services.model_records
@@ -52,10 +55,14 @@ async def list_model_records(
     if base_models:
         for base_model in base_models:
             found_models.extend(
-                record_store.search_by_attr(base_model=base_model, model_type=model_type, model_name=model_name)
+                record_store.search_by_attr(
+                    base_model=base_model, model_type=model_type, model_name=model_name, model_format=model_format
+                )
             )
     else:
-        found_models.extend(record_store.search_by_attr(model_type=model_type, model_name=model_name))
+        found_models.extend(
+            record_store.search_by_attr(model_type=model_type, model_name=model_name, model_format=model_format)
+        )
     return ModelsList(models=found_models)
 
 

invokeai/app/invocations/image.py

@@ -13,7 +13,15 @@ from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
-from .baseinvocation import BaseInvocation, Input, InputField, InvocationContext, WithMetadata, invocation
+from .baseinvocation import (
+    BaseInvocation,
+    Classification,
+    Input,
+    InputField,
+    InvocationContext,
+    WithMetadata,
+    invocation,
+)
 
 
 @invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.0")
@@ -421,6 +429,64 @@ class ImageBlurInvocation(BaseInvocation, WithMetadata):
         )
 
 
+@invocation(
+    "unsharp_mask",
+    title="Unsharp Mask",
+    tags=["image", "unsharp_mask"],
+    category="image",
+    version="1.2.0",
+    classification=Classification.Beta,
+)
+class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
+    """Applies an unsharp mask filter to an image"""
+
+    image: ImageField = InputField(description="The image to use")
+    radius: float = InputField(gt=0, description="Unsharp mask radius", default=2)
+    strength: float = InputField(ge=0, description="Unsharp mask strength", default=50)
+
+    def pil_from_array(self, arr):
+        return Image.fromarray((arr * 255).astype("uint8"))
+
+    def array_from_pil(self, img):
+        return numpy.array(img) / 255
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.services.images.get_pil_image(self.image.image_name)
+        mode = image.mode
+
+        alpha_channel = image.getchannel("A") if mode == "RGBA" else None
+        image = image.convert("RGB")
+        image_blurred = self.array_from_pil(image.filter(ImageFilter.GaussianBlur(radius=self.radius)))
+
+        image = self.array_from_pil(image)
+        image += (image - image_blurred) * (self.strength / 100.0)
+        image = numpy.clip(image, 0, 1)
+        image = self.pil_from_array(image)
+
+        image = image.convert(mode)
+
+        # Make the image RGBA if we had a source alpha channel
+        if alpha_channel is not None:
+            image.putalpha(alpha_channel)
+
+        image_dto = context.services.images.create(
+            image=image,
+            image_origin=ResourceOrigin.INTERNAL,
+            image_category=ImageCategory.GENERAL,
+            node_id=self.id,
+            session_id=context.graph_execution_state_id,
+            is_intermediate=self.is_intermediate,
+            metadata=self.metadata,
+            workflow=context.workflow,
+        )
+
+        return ImageOutput(
+            image=ImageField(image_name=image_dto.image_name),
+            width=image.width,
+            height=image.height,
+        )
+
+
 PIL_RESAMPLING_MODES = Literal[
     "nearest",
     "box",

invokeai/app/invocations/tiles.py

@@ -38,7 +38,14 @@ class CalculateImageTilesOutput(BaseInvocationOutput):
     tiles: list[Tile] = OutputField(description="The tiles coordinates that cover a particular image shape.")
 
 
-@invocation("calculate_image_tiles", title="Calculate Image Tiles", tags=["tiles"], category="tiles", version="1.0.0")
+@invocation(
+    "calculate_image_tiles",
+    title="Calculate Image Tiles",
+    tags=["tiles"],
+    category="tiles",
+    version="1.0.0",
+    classification=Classification.Beta,
+)
 class CalculateImageTilesInvocation(BaseInvocation):
     """Calculate the coordinates and overlaps of tiles that cover a target image shape."""
 
@@ -70,7 +77,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
     title="Calculate Image Tiles Even Split",
     tags=["tiles"],
     category="tiles",
-    version="1.0.0",
+    version="1.1.0",
     classification=Classification.Beta,
 )
 class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
@@ -90,11 +97,11 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
         ge=1,
         description="Number of tiles to divide image into on the y axis",
     )
-    overlap_fraction: float = InputField(
-        default=0.25,
+    overlap: int = InputField(
+        default=128,
         ge=0,
-        lt=1,
-        description="Overlap between adjacent tiles as a fraction of the tile's dimensions (0-1)",
+        multiple_of=8,
+        description="The overlap, in pixels, between adjacent tiles.",
     )
 
     def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
@@ -103,7 +110,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
             image_width=self.image_width,
             num_tiles_x=self.num_tiles_x,
             num_tiles_y=self.num_tiles_y,
-            overlap_fraction=self.overlap_fraction,
+            overlap=self.overlap,
         )
         return CalculateImageTilesOutput(tiles=tiles)
 

invokeai/app/services/model_records/model_records_base.py

@@ -7,7 +7,7 @@ from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import List, Optional, Union
 
-from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType
 
 
 class DuplicateModelException(Exception):
@@ -106,6 +106,7 @@ class ModelRecordServiceBase(ABC):
         model_name: Optional[str] = None,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None,
+        model_format: Optional[ModelFormat] = None,
     ) -> List[AnyModelConfig]:
         """
         Return models matching name, base and/or type.
@@ -113,6 +114,7 @@ class ModelRecordServiceBase(ABC):
         :param model_name: Filter by name of model (optional)
         :param base_model: Filter by base model (optional)
         :param model_type: Filter by type of model (optional)
+        :param model_format: Filter by model format (e.g. "diffusers") (optional)
 
         If none of the optional filters are passed, will return all
         models in the database.

invokeai/app/services/model_records/model_records_sql.py

@@ -49,6 +49,7 @@ from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
     ModelConfigFactory,
+    ModelFormat,
     ModelType,
 )
 
@@ -225,6 +226,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         model_name: Optional[str] = None,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None,
+        model_format: Optional[ModelFormat] = None,
     ) -> List[AnyModelConfig]:
         """
         Return models matching name, base and/or type.
@@ -232,6 +234,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         :param model_name: Filter by name of model (optional)
         :param base_model: Filter by base model (optional)
         :param model_type: Filter by type of model (optional)
+        :param model_format: Filter by model format (e.g. "diffusers") (optional)
 
         If none of the optional filters are passed, will return all
         models in the database.
@@ -248,6 +251,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         if model_type:
             where_clause.append("type=?")
             bindings.append(model_type)
+        if model_format:
+            where_clause.append("format=?")
+            bindings.append(model_format)
         where = f"WHERE {' AND '.join(where_clause)}" if where_clause else ""
         with self._db.lock:
             self._cursor.execute(

invokeai/app/services/shared/sqlite/sqlite_util.py

@@ -5,6 +5,7 @@ from invokeai.app.services.image_files.image_files_base import ImageFileStorageB
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_1 import build_migration_1
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_2 import build_migration_2
+from invokeai.app.services.shared.sqlite_migrator.migrations.migration_3 import build_migration_3
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
 
 
@@ -27,6 +28,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
     migrator = SqliteMigrator(db=db)
     migrator.register_migration(build_migration_1())
     migrator.register_migration(build_migration_2(image_files=image_files, logger=logger))
+    migrator.register_migration(build_migration_3())
     migrator.run_migrations()
 
     return db

invokeai/app/services/shared/sqlite_migrator/migrations/migration_2.py

@@ -1,10 +1,17 @@
 import sqlite3
 from logging import Logger
 
+from pydantic import ValidationError
 from tqdm import tqdm
 
 from invokeai.app.services.image_files.image_files_base import ImageFileStorageBase
+from invokeai.app.services.image_files.image_files_common import ImageFileNotFoundException
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
+from invokeai.app.services.workflow_records.workflow_records_common import (
+    UnsafeWorkflowWithVersionValidator,
+)
+
+from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
 
 
 class Migration2Callback:
@@ -19,6 +26,7 @@ class Migration2Callback:
         self._add_workflow_library(cursor)
         self._drop_model_manager_metadata(cursor)
         self._recreate_model_config(cursor)
+        self._migrate_model_config_records(cursor)
         self._migrate_embedded_workflows(cursor)
 
     def _add_images_has_workflow(self, cursor: sqlite3.Cursor) -> None:
@@ -126,6 +134,11 @@ class Migration2Callback:
             """
         )
 
+    def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
+        """After updating the model config table, we repopulate it."""
+        model_record_migrator = MigrateModelYamlToDb1(cursor)
+        model_record_migrator.migrate()
+
     def _migrate_embedded_workflows(self, cursor: sqlite3.Cursor) -> None:
         """
         In the v3.5.0 release, InvokeAI changed how it handles embedded workflows. The `images` table in
@@ -134,7 +147,7 @@ class Migration2Callback:
         This migrate callback checks each image for the presence of an embedded workflow, then updates its entry
         in the database accordingly.
         """
-        # Get the total number of images and chunk it into pages
+        # Get all image names
         cursor.execute("SELECT image_name FROM images")
         image_names: list[str] = [image[0] for image in cursor.fetchall()]
         total_image_names = len(image_names)
@@ -149,8 +162,17 @@ class Migration2Callback:
         pbar = tqdm(image_names)
         for idx, image_name in enumerate(pbar):
             pbar.set_description(f"Checking image {idx + 1}/{total_image_names} for workflow")
-            pil_image = self._image_files.get(image_name)
+            try:
+                pil_image = self._image_files.get(image_name)
+            except ImageFileNotFoundException:
+                self._logger.warning(f"Image {image_name} not found, skipping")
+                continue
             if "invokeai_workflow" in pil_image.info:
+                try:
+                    UnsafeWorkflowWithVersionValidator.validate_json(pil_image.info.get("invokeai_workflow", ""))
+                except ValidationError:
+                    self._logger.warning(f"Image {image_name} has invalid embedded workflow, skipping")
+                    continue
                 to_migrate.append((True, image_name))
 
         self._logger.info(f"Adding {len(to_migrate)} embedded workflows to database")

invokeai/app/services/shared/sqlite_migrator/migrations/migration_3.py

@@ -0,0 +1,75 @@
+import sqlite3
+
+from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
+
+from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
+
+
+class Migration3Callback:
+    def __init__(self) -> None:
+        pass
+
+    def __call__(self, cursor: sqlite3.Cursor) -> None:
+        self._drop_model_manager_metadata(cursor)
+        self._recreate_model_config(cursor)
+        self._migrate_model_config_records(cursor)
+
+    def _drop_model_manager_metadata(self, cursor: sqlite3.Cursor) -> None:
+        """Drops the `model_manager_metadata` table."""
+        cursor.execute("DROP TABLE IF EXISTS model_manager_metadata;")
+
+    def _recreate_model_config(self, cursor: sqlite3.Cursor) -> None:
+        """
+        Drops the `model_config` table, recreating it.
+
+        In 3.4.0, this table used explicit columns but was changed to use json_extract 3.5.0.
+
+        Because this table is not used in production, we are able to simply drop it and recreate it.
+        """
+
+        cursor.execute("DROP TABLE IF EXISTS model_config;")
+
+        cursor.execute(
+            """--sql
+            CREATE TABLE IF NOT EXISTS model_config (
+                id TEXT NOT NULL PRIMARY KEY,
+                -- The next 3 fields are enums in python, unrestricted string here
+                base TEXT GENERATED ALWAYS as (json_extract(config, '$.base')) VIRTUAL NOT NULL,
+                type TEXT GENERATED ALWAYS as (json_extract(config, '$.type')) VIRTUAL NOT NULL,
+                name TEXT GENERATED ALWAYS as (json_extract(config, '$.name')) VIRTUAL NOT NULL,
+                path TEXT GENERATED ALWAYS as (json_extract(config, '$.path')) VIRTUAL NOT NULL,
+                format TEXT GENERATED ALWAYS as (json_extract(config, '$.format')) VIRTUAL NOT NULL,
+                original_hash TEXT, -- could be null
+                -- Serialized JSON representation of the whole config object,
+                -- which will contain additional fields from subclasses
+                config TEXT NOT NULL,
+                created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                -- Updated via trigger
+                updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                -- unique constraint on combo of name, base and type
+                UNIQUE(name, base, type)
+            );
+            """
+        )
+
+    def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
+        """After updating the model config table, we repopulate it."""
+        model_record_migrator = MigrateModelYamlToDb1(cursor)
+        model_record_migrator.migrate()
+
+
+def build_migration_3() -> Migration:
+    """
+    Build the migration from database version 2 to 3.
+
+    This migration does the following:
+    - Drops the `model_config` table, recreating it
+    - Migrates data from `models.yaml` into the `model_config` table
+    """
+    migration_3 = Migration(
+        from_version=2,
+        to_version=3,
+        callback=Migration3Callback(),
+    )
+
+    return migration_3

invokeai/app/services/shared/sqlite_migrator/migrations/util/migrate_yaml_config_1.py

@@ -1,8 +1,12 @@
 # Copyright (c) 2023 Lincoln D. Stein
 """Migrate from the InvokeAI v2 models.yaml format to the v3 sqlite format."""
 
+import json
+import sqlite3
 from hashlib import sha1
 from logging import Logger
+from pathlib import Path
+from typing import Optional
 
 from omegaconf import DictConfig, OmegaConf
 from pydantic import TypeAdapter
@@ -10,13 +14,12 @@ from pydantic import TypeAdapter
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.model_records import (
     DuplicateModelException,
-    ModelRecordServiceSQL,
     UnknownModelException,
 )
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
+    ModelConfigFactory,
     ModelType,
 )
 from invokeai.backend.model_manager.hash import FastModelHash
@@ -25,9 +28,9 @@ from invokeai.backend.util.logging import InvokeAILogger
 ModelsValidator = TypeAdapter(AnyModelConfig)
 
 
-class MigrateModelYamlToDb:
+class MigrateModelYamlToDb1:
     """
-    Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.2.0)
+    Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.5.0).
 
     The class has one externally useful method, migrate(), which scans the
     currently models.yaml file and imports all its entries into invokeai.db.
@@ -41,17 +44,13 @@ class MigrateModelYamlToDb:
 
     config: InvokeAIAppConfig
     logger: Logger
+    cursor: sqlite3.Cursor
 
-    def __init__(self) -> None:
+    def __init__(self, cursor: sqlite3.Cursor = None) -> None:
         self.config = InvokeAIAppConfig.get_config()
         self.config.parse_args()
         self.logger = InvokeAILogger.get_logger()
-
-    def get_db(self) -> ModelRecordServiceSQL:
-        """Fetch the sqlite3 database for this installation."""
-        db_path = None if self.config.use_memory_db else self.config.db_path
-        db = SqliteDatabase(db_path=db_path, logger=self.logger, verbose=self.config.log_sql)
-        return ModelRecordServiceSQL(db)
+        self.cursor = cursor
 
     def get_yaml(self) -> DictConfig:
         """Fetch the models.yaml DictConfig for this installation."""
@@ -62,8 +61,10 @@ class MigrateModelYamlToDb:
 
     def migrate(self) -> None:
         """Do the migration from models.yaml to invokeai.db."""
-        db = self.get_db()
-        yaml = self.get_yaml()
+        try:
+            yaml = self.get_yaml()
+        except OSError:
+            return
 
         for model_key, stanza in yaml.items():
             if model_key == "__metadata__":
@@ -86,22 +87,62 @@ class MigrateModelYamlToDb:
             new_config: AnyModelConfig = ModelsValidator.validate_python(stanza)  # type: ignore # see https://github.com/pydantic/pydantic/discussions/7094
 
             try:
-                if original_record := db.search_by_path(stanza.path):
-                    key = original_record[0].key
+                if original_record := self._search_by_path(stanza.path):
+                    key = original_record.key
                     self.logger.info(f"Updating model {model_name} with information from models.yaml using key {key}")
-                    db.update_model(key, new_config)
+                    self._update_model(key, new_config)
                 else:
                     self.logger.info(f"Adding model {model_name} with key {model_key}")
-                    db.add_model(new_key, new_config)
+                    self._add_model(new_key, new_config)
             except DuplicateModelException:
                 self.logger.warning(f"Model {model_name} is already in the database")
             except UnknownModelException:
                 self.logger.warning(f"Model at {stanza.path} could not be found in database")
 
+    def _search_by_path(self, path: Path) -> Optional[AnyModelConfig]:
+        self.cursor.execute(
+            """--sql
+            SELECT config FROM model_config
+            WHERE path=?;
+            """,
+            (str(path),),
+        )
+        results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self.cursor.fetchall()]
+        return results[0] if results else None
 
-def main():
-    MigrateModelYamlToDb().migrate()
+    def _update_model(self, key: str, config: AnyModelConfig) -> None:
+        record = ModelConfigFactory.make_config(config, key=key)  # ensure it is a valid config obect
+        json_serialized = record.model_dump_json()  # and turn it into a json string.
+        self.cursor.execute(
+            """--sql
+            UPDATE model_config
+            SET
+                config=?
+            WHERE id=?;
+            """,
+            (json_serialized, key),
+        )
+        if self.cursor.rowcount == 0:
+            raise UnknownModelException("model not found")
 
-
-if __name__ == "__main__":
-    main()
+    def _add_model(self, key: str, config: AnyModelConfig) -> None:
+        record = ModelConfigFactory.make_config(config, key=key)  # ensure it is a valid config obect.
+        json_serialized = record.model_dump_json()  # and turn it into a json string.
+        try:
+            self.cursor.execute(
+                """--sql
+                INSERT INTO model_config (
+                   id,
+                   original_hash,
+                   config
+                  )
+                VALUES (?,?,?);
+                """,
+                (
+                    key,
+                    record.original_hash,
+                    json_serialized,
+                ),
+            )
+        except sqlite3.IntegrityError as exc:
+            raise DuplicateModelException(f"{record.name}: model is already in database") from exc

invokeai/app/services/workflow_records/workflow_records_common.py

@@ -65,12 +65,24 @@ class WorkflowWithoutID(BaseModel):
     nodes: list[dict[str, JsonValue]] = Field(description="The nodes of the workflow.")
     edges: list[dict[str, JsonValue]] = Field(description="The edges of the workflow.")
 
-    model_config = ConfigDict(extra="forbid")
+    model_config = ConfigDict(extra="ignore")
 
 
 WorkflowWithoutIDValidator = TypeAdapter(WorkflowWithoutID)
 
 
+class UnsafeWorkflowWithVersion(BaseModel):
+    """
+    This utility model only requires a workflow to have a valid version string.
+    It is used to validate a workflow version without having to validate the entire workflow.
+    """
+
+    meta: WorkflowMeta = Field(description="The meta of the workflow.")
+
+
+UnsafeWorkflowWithVersionValidator = TypeAdapter(UnsafeWorkflowWithVersion)
+
+
 class Workflow(WorkflowWithoutID):
     id: str = Field(description="The id of the workflow.")
 

invokeai/backend/model_management/model_probe.py

@@ -389,7 +389,7 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
         elif "clip_g" in checkpoint:
             token_dim = checkpoint["clip_g"].shape[-1]
         else:
-            token_dim = list(checkpoint.values())[0].shape[0]
+            token_dim = list(checkpoint.values())[0].shape[-1]
         if token_dim == 768:
             return BaseModelType.StableDiffusion1
         elif token_dim == 1024:

invokeai/backend/model_management/util.py

@@ -9,7 +9,7 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     :param checkpoint: The checkpoint
     """
 
-    def _get_shape_1(key, tensor, checkpoint):
+    def _get_shape_1(key: str, tensor, checkpoint) -> int:
         lora_token_vector_length = None
 
         if "." not in key:
@@ -57,6 +57,10 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     for key, tensor in checkpoint.items():
         if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
             lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
+        elif key.startswith("lora_unet_") and (
+            "time_emb_proj.lora_down" in key
+        ):  # recognizes format at https://civitai.com/models/224641
+            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
         elif key.startswith("lora_te") and "_self_attn_" in key:
             tmp_length = _get_shape_1(key, tensor, checkpoint)
             if key.startswith("lora_te_"):

invokeai/backend/model_manager/probe.py

@@ -400,6 +400,8 @@ class LoRACheckpointProbe(CheckpointProbeBase):
             return BaseModelType.StableDiffusion1
         elif token_vector_length == 1024:
             return BaseModelType.StableDiffusion2
+        elif token_vector_length == 1280:
+            return BaseModelType.StableDiffusionXL  # recognizes format at https://civitai.com/models/224641
         elif token_vector_length == 2048:
             return BaseModelType.StableDiffusionXL
         else:

invokeai/backend/tiles/tiles.py

@@ -102,7 +102,7 @@ def calc_tiles_with_overlap(
 
 
 def calc_tiles_even_split(
-    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap_fraction: float = 0
+    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap: int = 0
 ) -> list[Tile]:
     """Calculate the tile coordinates for a given image shape with the number of tiles requested.
 
@@ -111,31 +111,35 @@ def calc_tiles_even_split(
         image_width (int): The image width in px.
         num_x_tiles (int): The number of tile to split the image into on the X-axis.
         num_y_tiles (int): The number of tile to split the image into on the Y-axis.
-        overlap_fraction (float, optional): The target overlap as fraction of the tiles size. Defaults to 0.
+        overlap (int, optional): The overlap between adjacent tiles in pixels. Defaults to 0.
 
     Returns:
         list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
     """
-
-    # Ensure tile size is divisible by 8
+    # Ensure the image is divisible by LATENT_SCALE_FACTOR
     if image_width % LATENT_SCALE_FACTOR != 0 or image_height % LATENT_SCALE_FACTOR != 0:
         raise ValueError(f"image size (({image_width}, {image_height})) must be divisible by {LATENT_SCALE_FACTOR}")
 
-    # Calculate the overlap size based on the percentage and adjust it to be divisible by 8 (rounding up)
-    overlap_x = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_width / num_tiles_x) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-    overlap_y = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_height / num_tiles_y) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-
     # Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
-    tile_size_x = LATENT_SCALE_FACTOR * math.floor(
-        ((image_width + overlap_x * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
-    )
-    tile_size_y = LATENT_SCALE_FACTOR * math.floor(
-        ((image_height + overlap_y * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
-    )
+    if num_tiles_x > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_width - (LATENT_SCALE_FACTOR * (num_tiles_x - 1))
+        tile_size_x = LATENT_SCALE_FACTOR * math.floor(
+            ((image_width + overlap * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
+        )
+        assert overlap < tile_size_x
+    else:
+        tile_size_x = image_width
+
+    if num_tiles_y > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_height - (LATENT_SCALE_FACTOR * (num_tiles_y - 1))
+        tile_size_y = LATENT_SCALE_FACTOR * math.floor(
+            ((image_height + overlap * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
+        )
+        assert overlap < tile_size_y
+    else:
+        tile_size_y = image_height
 
     # tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
     tiles: list[Tile] = []
@@ -143,7 +147,7 @@ def calc_tiles_even_split(
     # Calculate tile coordinates. (Ignore overlap values for now.)
     for tile_idx_y in range(num_tiles_y):
         # Calculate the top and bottom of the row
-        top = tile_idx_y * (tile_size_y - overlap_y)
+        top = tile_idx_y * (tile_size_y - overlap)
         bottom = min(top + tile_size_y, image_height)
         # For the last row adjust bottom to be the height of the image
         if tile_idx_y == num_tiles_y - 1:
@@ -151,7 +155,7 @@ def calc_tiles_even_split(
 
         for tile_idx_x in range(num_tiles_x):
             # Calculate the left & right coordinate of each tile
-            left = tile_idx_x * (tile_size_x - overlap_x)
+            left = tile_idx_x * (tile_size_x - overlap)
             right = min(left + tile_size_x, image_width)
             # For the last tile in the row adjust right to be the width of the image
             if tile_idx_x == num_tiles_x - 1:

invokeai/frontend/install/invokeai_update.py

@@ -4,6 +4,7 @@ pip install <path_to_git_source>.
 """
 import os
 import platform
+from distutils.version import LooseVersion
 
 import pkg_resources
 import psutil
@@ -31,10 +32,6 @@ else:
     console = Console(style=Style(color="grey74", bgcolor="grey19"))
 
 
-def get_versions() -> dict:
-    return requests.get(url=INVOKE_AI_REL).json()
-
-
 def invokeai_is_running() -> bool:
     for p in psutil.process_iter():
         try:
@@ -50,6 +47,20 @@ def invokeai_is_running() -> bool:
     return False
 
 
+def get_pypi_versions():
+    url = "https://pypi.org/pypi/invokeai/json"
+    try:
+        data = requests.get(url).json()
+    except Exception:
+        raise Exception("Unable to fetch version information from PyPi")
+
+    versions = list(data["releases"].keys())
+    versions.sort(key=LooseVersion, reverse=True)
+    latest_version = [v for v in versions if "rc" not in v][0]
+    latest_release_candidate = [v for v in versions if "rc" in v][0]
+    return latest_version, latest_release_candidate, versions
+
+
 def welcome(latest_release: str, latest_prerelease: str):
     @group()
     def text():
@@ -63,8 +74,7 @@ def welcome(latest_release: str, latest_prerelease: str):
         yield "[bold yellow]Options:"
         yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
 [2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
-[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"""
+[3] Manually enter the [bold]version[/bold] you wish to update to"""
 
     console.rule()
     print(
@@ -92,44 +102,35 @@ def get_extras():
 
 
 def main():
-    versions = get_versions()
-    released_versions = [x for x in versions if not (x["draft"] or x["prerelease"])]
-    prerelease_versions = [x for x in versions if not x["draft"] and x["prerelease"]]
-    latest_release = released_versions[0]["tag_name"] if len(released_versions) else None
-    latest_prerelease = prerelease_versions[0]["tag_name"] if len(prerelease_versions) else None
-
     if invokeai_is_running():
         print(":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
         input("Press any key to continue...")
         return
 
+    latest_release, latest_prerelease, versions = get_pypi_versions()
+
     welcome(latest_release, latest_prerelease)
 
-    tag = None
-    branch = None
-    release = None
-    choice = Prompt.ask("Choice:", choices=["1", "2", "3", "4"], default="1")
+    release = latest_release
+    choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
 
     if choice == "1":
         release = latest_release
     elif choice == "2":
         release = latest_prerelease
     elif choice == "3":
-        while not tag:
-            tag = Prompt.ask("Enter an InvokeAI tag name")
-    elif choice == "4":
-        while not branch:
-            branch = Prompt.ask("Enter an InvokeAI branch name")
+        while True:
+            release = Prompt.ask("Enter an InvokeAI version")
+            release.strip()
+            if release in versions:
+                break
+            print(f":exclamation: [bold red]'{release}' is not a recognized InvokeAI release.[/red bold]")
 
     extras = get_extras()
 
-    print(f":crossed_fingers: Upgrading to [yellow]{tag or release or branch}[/yellow]")
-    if release:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_SRC}/{release}.zip" --use-pep517 --upgrade'
-    elif tag:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_TAG}/{tag}.zip" --use-pep517 --upgrade'
-    else:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_BRANCH}/{branch}.zip" --use-pep517 --upgrade'
+    print(f":crossed_fingers: Upgrading to [yellow]{release}[/yellow]")
+    cmd = f'pip install "invokeai{extras}=={release}" --use-pep517 --upgrade'
+
     print("")
     print("")
     if os.system(cmd) == 0:

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

@@ -950,9 +950,9 @@
         "problemSettingTitle": "Problem Setting Title",
         "reloadNodeTemplates": "Reload Node Templates",
         "removeLinearView": "Remove from Linear View",
-        "resetWorkflow": "Reset Workflow Editor",
-        "resetWorkflowDesc": "Are you sure you want to reset the Workflow Editor?",
-        "resetWorkflowDesc2": "Resetting the Workflow Editor will clear all nodes, edges and workflow details. Saved workflows will not be affected.",
+        "newWorkflow": "New Workflow",
+        "newWorkflowDesc": "Create a new workflow?",
+        "newWorkflowDesc2": "Your current workflow has unsaved changes.",
         "scheduler": "Scheduler",
         "schedulerDescription": "TODO",
         "sDXLMainModelField": "SDXL Model",
@@ -1634,10 +1634,10 @@
         "userWorkflows": "My Workflows",
         "defaultWorkflows": "Default Workflows",
         "openWorkflow": "Open Workflow",
-        "uploadWorkflow": "Upload Workflow",
+        "uploadWorkflow": "Load from File",
         "deleteWorkflow": "Delete Workflow",
         "unnamedWorkflow": "Unnamed Workflow",
-        "downloadWorkflow": "Download Workflow",
+        "downloadWorkflow": "Save to File",
         "saveWorkflow": "Save Workflow",
         "saveWorkflowAs": "Save Workflow As",
         "savingWorkflow": "Saving Workflow...",
@@ -1652,7 +1652,7 @@
         "searchWorkflows": "Search Workflows",
         "clearWorkflowSearchFilter": "Clear Workflow Search Filter",
         "workflowName": "Workflow Name",
-        "workflowEditorReset": "Workflow Editor Reset",
+        "newWorkflowCreated": "New Workflow Created",
         "workflowEditorMenu": "Workflow Editor Menu",
         "workflowIsOpen": "Workflow is Open"
     },

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

@@ -727,9 +727,6 @@
         "showMinimapnodes": "Mostrar el minimapa",
         "reloadNodeTemplates": "Recargar las plantillas de nodos",
         "loadWorkflow": "Cargar el flujo de trabajo",
-        "resetWorkflow": "Reiniciar e flujo de trabajo",
-        "resetWorkflowDesc": "¿Está seguro de que deseas restablecer este flujo de trabajo?",
-        "resetWorkflowDesc2": "Al reiniciar el flujo de trabajo se borrarán todos los nodos, aristas y detalles del flujo de trabajo.",
         "downloadWorkflow": "Descargar el flujo de trabajo en un archivo JSON"
     }
 }

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

@@ -104,7 +104,16 @@
         "copyError": "$t(gallery.copy) Errore",
         "input": "Ingresso",
         "notInstalled": "Non $t(common.installed)",
-        "unknownError": "Errore sconosciuto"
+        "unknownError": "Errore sconosciuto",
+        "updated": "Aggiornato",
+        "save": "Salva",
+        "created": "Creato",
+        "prevPage": "Pagina precedente",
+        "delete": "Elimina",
+        "orderBy": "Ordinato per",
+        "nextPage": "Pagina successiva",
+        "saveAs": "Salva come",
+        "unsaved": "Non salvato"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -763,7 +772,10 @@
         "setIPAdapterImage": "Imposta come immagine per l'Adattatore IP",
         "problemSavingMaskDesc": "Impossibile salvare la maschera",
         "setAsCanvasInitialImage": "Imposta come immagine iniziale della tela",
-        "invalidUpload": "Caricamento non valido"
+        "invalidUpload": "Caricamento non valido",
+        "problemDeletingWorkflow": "Problema durante l'eliminazione del flusso di lavoro",
+        "workflowDeleted": "Flusso di lavoro eliminato",
+        "problemRetrievingWorkflow": "Problema nel recupero del flusso di lavoro"
     },
     "tooltip": {
         "feature": {
@@ -886,11 +898,8 @@
         "zoomInNodes": "Ingrandire",
         "fitViewportNodes": "Adatta vista",
         "showGraphNodes": "Mostra sovrapposizione grafico",
-        "resetWorkflowDesc2": "Reimpostare il flusso di lavoro cancellerà tutti i nodi, i bordi e i dettagli del flusso di lavoro.",
         "reloadNodeTemplates": "Ricarica i modelli di nodo",
         "loadWorkflow": "Importa flusso di lavoro JSON",
-        "resetWorkflow": "Reimposta flusso di lavoro",
-        "resetWorkflowDesc": "Sei sicuro di voler reimpostare questo flusso di lavoro?",
         "downloadWorkflow": "Esporta flusso di lavoro JSON",
         "scheduler": "Campionatore",
         "addNode": "Aggiungi nodo",
@@ -1080,25 +1089,30 @@
         "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
         "nodeVersion": "Versione Nodo",
         "inputFieldTypeParseError": "Impossibile analizzare il tipo di campo di input {{node}}.{{field}} ({{message}})",
-        "unsupportedArrayItemType": "tipo di elemento dell'array non supportato \"{{type}}\"",
+        "unsupportedArrayItemType": "Tipo di elemento dell'array non supportato \"{{type}}\"",
         "targetNodeFieldDoesNotExist": "Connessione non valida: il campo di destinazione/input {{node}}.{{field}} non esiste",
         "unsupportedMismatchedUnion": "tipo CollectionOrScalar non corrispondente con tipi di base {{firstType}} e {{secondType}}",
         "allNodesUpdated": "Tutti i nodi sono aggiornati",
         "sourceNodeDoesNotExist": "Connessione non valida: il nodo di origine/output {{node}} non esiste",
-        "unableToExtractEnumOptions": "impossibile estrarre le opzioni enum",
-        "unableToParseFieldType": "impossibile analizzare il tipo di campo",
+        "unableToExtractEnumOptions": "Impossibile estrarre le opzioni enum",
+        "unableToParseFieldType": "Impossibile analizzare il tipo di campo",
         "unrecognizedWorkflowVersion": "Versione dello schema del flusso di lavoro non riconosciuta {{version}}",
         "outputFieldTypeParseError": "Impossibile analizzare il tipo di campo di output {{node}}.{{field}} ({{message}})",
         "sourceNodeFieldDoesNotExist": "Connessione non valida: il campo di origine/output {{node}}.{{field}} non esiste",
         "unableToGetWorkflowVersion": "Impossibile ottenere la versione dello schema del flusso di lavoro",
         "nodePack": "Pacchetto di nodi",
-        "unableToExtractSchemaNameFromRef": "impossibile estrarre il nome dello schema dal riferimento",
+        "unableToExtractSchemaNameFromRef": "Impossibile estrarre il nome dello schema dal riferimento",
         "unknownOutput": "Output sconosciuto: {{name}}",
         "unknownNodeType": "Tipo di nodo sconosciuto",
         "targetNodeDoesNotExist": "Connessione non valida: il nodo di destinazione/input {{node}} non esiste",
         "unknownFieldType": "$t(nodes.unknownField) tipo: {{type}}",
         "deletedInvalidEdge": "Eliminata connessione non valida {{source}} -> {{target}}",
-        "unknownInput": "Input sconosciuto: {{name}}"
+        "unknownInput": "Input sconosciuto: {{name}}",
+        "prototypeDesc": "Questa invocazione è un prototipo. Potrebbe subire modifiche sostanziali durante gli aggiornamenti dell'app e potrebbe essere rimossa in qualsiasi momento.",
+        "betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine.",
+        "newWorkflow": "Nuovo flusso di lavoro",
+        "newWorkflowDesc": "Creare un nuovo flusso di lavoro?",
+        "newWorkflowDesc2": "Il flusso di lavoro attuale presenta modifiche non salvate."
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1594,5 +1608,36 @@
         "hrf": "Correzione Alta Risoluzione",
         "hrfStrength": "Forza della Correzione Alta Risoluzione",
         "strengthTooltip": "Valori più bassi comportano meno dettagli, il che può ridurre potenziali artefatti."
+    },
+    "workflows": {
+        "saveWorkflowAs": "Salva flusso di lavoro come",
+        "workflowEditorMenu": "Menu dell'editor del flusso di lavoro",
+        "noSystemWorkflows": "Nessun flusso di lavoro del sistema",
+        "workflowName": "Nome del flusso di lavoro",
+        "noUserWorkflows": "Nessun flusso di lavoro utente",
+        "defaultWorkflows": "Flussi di lavoro predefiniti",
+        "saveWorkflow": "Salva flusso di lavoro",
+        "openWorkflow": "Apri flusso di lavoro",
+        "clearWorkflowSearchFilter": "Cancella il filtro di ricerca del flusso di lavoro",
+        "workflowLibrary": "Libreria",
+        "noRecentWorkflows": "Nessun flusso di lavoro recente",
+        "workflowSaved": "Flusso di lavoro salvato",
+        "workflowIsOpen": "Il flusso di lavoro è aperto",
+        "unnamedWorkflow": "Flusso di lavoro senza nome",
+        "savingWorkflow": "Salvataggio del flusso di lavoro...",
+        "problemLoading": "Problema durante il caricamento dei flussi di lavoro",
+        "loading": "Caricamento dei flussi di lavoro",
+        "searchWorkflows": "Cerca flussi di lavoro",
+        "problemSavingWorkflow": "Problema durante il salvataggio del flusso di lavoro",
+        "deleteWorkflow": "Elimina flusso di lavoro",
+        "workflows": "Flussi di lavoro",
+        "noDescription": "Nessuna descrizione",
+        "userWorkflows": "I miei flussi di lavoro",
+        "newWorkflowCreated": "Nuovo flusso di lavoro creato",
+        "downloadWorkflow": "Salva su file",
+        "uploadWorkflow": "Carica da file"
+    },
+    "app": {
+        "storeNotInitialized": "Il negozio non è inizializzato"
     }
 }

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

@@ -844,9 +844,6 @@
         "hideLegendNodes": "Typelegende veld verbergen",
         "reloadNodeTemplates": "Herlaad knooppuntsjablonen",
         "loadWorkflow": "Laad werkstroom",
-        "resetWorkflow": "Herstel werkstroom",
-        "resetWorkflowDesc": "Weet je zeker dat je deze werkstroom wilt herstellen?",
-        "resetWorkflowDesc2": "Herstel van een werkstroom haalt alle knooppunten, randen en werkstroomdetails weg.",
         "downloadWorkflow": "Download JSON van werkstroom",
         "booleanPolymorphicDescription": "Een verzameling Booleanse waarden.",
         "scheduler": "Planner",

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

@@ -110,7 +110,17 @@
         "copyError": "$t(gallery.copy) 错误",
         "input": "输入",
         "notInstalled": "非 $t(common.installed)",
-        "delete": "删除"
+        "delete": "删除",
+        "updated": "已上传",
+        "save": "保存",
+        "created": "已创建",
+        "prevPage": "上一页",
+        "unknownError": "未知错误",
+        "direction": "指向",
+        "orderBy": "排序方式：",
+        "nextPage": "下一页",
+        "saveAs": "保存为",
+        "unsaved": "未保存"
     },
     "gallery": {
         "generations": "生成的图像",
@@ -146,7 +156,11 @@
         "image": "图像",
         "drop": "弃用",
         "dropOrUpload": "$t(gallery.drop) 或上传",
-        "dropToUpload": "$t(gallery.drop) 以上传"
+        "dropToUpload": "$t(gallery.drop) 以上传",
+        "problemDeletingImagesDesc": "有一张或多张图像无法被删除",
+        "problemDeletingImages": "删除图像时出现问题",
+        "unstarImage": "取消收藏图像",
+        "starImage": "收藏图像"
     },
     "hotkeys": {
         "keyboardShortcuts": "键盘快捷键",
@@ -724,7 +738,7 @@
         "nodesUnrecognizedTypes": "无法加载。节点图有无法识别的节点类型",
         "nodesNotValidJSON": "无效的 JSON",
         "nodesNotValidGraph": "无效的 InvokeAi 节点图",
-        "nodesLoadedFailed": "节点图加载失败",
+        "nodesLoadedFailed": "节点加载失败",
         "modelAddedSimple": "已添加模型",
         "modelAdded": "已添加模型: {{modelName}}",
         "imageSavingFailed": "图像保存失败",
@@ -760,7 +774,10 @@
         "problemImportingMask": "导入遮罩时出现问题",
         "baseModelChangedCleared_other": "基础模型已更改, 已清除或禁用 {{count}} 个不兼容的子模型",
         "setAsCanvasInitialImage": "设为画布初始图像",
-        "invalidUpload": "无效的上传"
+        "invalidUpload": "无效的上传",
+        "problemDeletingWorkflow": "删除工作流时出现问题",
+        "workflowDeleted": "已删除工作流",
+        "problemRetrievingWorkflow": "检索工作流时发生问题"
     },
     "unifiedCanvas": {
         "layer": "图层",
@@ -875,11 +892,8 @@
     },
     "nodes": {
         "zoomInNodes": "放大",
-        "resetWorkflowDesc": "是否确定要清空节点图?",
-        "resetWorkflow": "清空节点图",
-        "loadWorkflow": "读取节点图",
+        "loadWorkflow": "加载工作流",
         "zoomOutNodes": "缩小",
-        "resetWorkflowDesc2": "重置节点图将清除所有节点、边际和节点图详情.",
         "reloadNodeTemplates": "重载节点模板",
         "hideGraphNodes": "隐藏节点图信息",
         "fitViewportNodes": "自适应视图",
@@ -888,7 +902,7 @@
         "showLegendNodes": "显示字段类型图例",
         "hideLegendNodes": "隐藏字段类型图例",
         "showGraphNodes": "显示节点图信息",
-        "downloadWorkflow": "下载节点图 JSON",
+        "downloadWorkflow": "下载工作流 JSON",
         "workflowDescription": "简述",
         "versionUnknown": " 未知版本",
         "noNodeSelected": "无选中的节点",
@@ -1103,7 +1117,9 @@
         "collectionOrScalarFieldType": "{{name}} 合集 | 标量",
         "nodeVersion": "节点版本",
         "deletedInvalidEdge": "已删除无效的边缘 {{source}} -> {{target}}",
-        "unknownInput": "未知输入：{{name}}"
+        "unknownInput": "未知输入：{{name}}",
+        "prototypeDesc": "此调用是一个原型 (prototype)。它可能会在本项目更新期间发生破坏性更改，并且随时可能被删除。",
+        "betaDesc": "此调用尚处于测试阶段。在稳定之前，它可能会在项目更新期间发生破坏性更改。本项目计划长期支持这种调用。"
     },
     "controlnet": {
         "resize": "直接缩放",
@@ -1607,5 +1623,35 @@
         "hrf": "高分辨率修复",
         "hrfStrength": "高分辨率修复强度",
         "strengthTooltip": "值越低细节越少，但可以减少部分潜在的伪影。"
+    },
+    "workflows": {
+        "saveWorkflowAs": "保存工作流为",
+        "workflowEditorMenu": "工作流编辑器菜单",
+        "noSystemWorkflows": "无系统工作流",
+        "workflowName": "工作流名称",
+        "noUserWorkflows": "无用户工作流",
+        "defaultWorkflows": "默认工作流",
+        "saveWorkflow": "保存工作流",
+        "openWorkflow": "打开工作流",
+        "clearWorkflowSearchFilter": "清除工作流检索过滤器",
+        "workflowLibrary": "工作流库",
+        "downloadWorkflow": "下载工作流",
+        "noRecentWorkflows": "无最近工作流",
+        "workflowSaved": "已保存工作流",
+        "workflowIsOpen": "工作流已打开",
+        "unnamedWorkflow": "未命名的工作流",
+        "savingWorkflow": "保存工作流中...",
+        "problemLoading": "加载工作流时出现问题",
+        "loading": "加载工作流中",
+        "searchWorkflows": "检索工作流",
+        "problemSavingWorkflow": "保存工作流时出现问题",
+        "deleteWorkflow": "删除工作流",
+        "workflows": "工作流",
+        "noDescription": "无描述",
+        "uploadWorkflow": "上传工作流",
+        "userWorkflows": "我的工作流"
+    },
+    "app": {
+        "storeNotInitialized": "商店尚未初始化"
     }
 }

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts

@@ -144,6 +144,7 @@ export const buildCanvasImageToImageGraph = (
         type: 'l2i',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [
@@ -255,6 +256,7 @@ export const buildCanvasImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -295,6 +297,7 @@ export const buildCanvasImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts

@@ -191,6 +191,7 @@ export const buildCanvasInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts

@@ -199,6 +199,7 @@ export const buildCanvasOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts

@@ -266,6 +266,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -306,6 +307,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts

@@ -196,6 +196,7 @@ export const buildCanvasSDXLInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts

@@ -204,6 +204,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts

@@ -258,6 +258,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -288,6 +289,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts

@@ -246,6 +246,7 @@ export const buildCanvasTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -276,6 +277,7 @@ export const buildCanvasTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts

@@ -143,6 +143,7 @@ export const buildLinearImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts

@@ -154,6 +154,7 @@ export const buildLinearSDXLImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts

@@ -127,6 +127,7 @@ export const buildLinearSDXLTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts

@@ -146,6 +146,7 @@ export const buildLinearTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts

@@ -64,7 +64,10 @@ const migrateV1toV2 = (workflowToMigrate: WorkflowV1): WorkflowV2 => {
       const nodePack = invocationTemplate
         ? invocationTemplate.nodePack
         : t('common.unknown');
+
       (node.data as unknown as InvocationNodeData).nodePack = nodePack;
+      // Fallback to 1.0.0 if not specified - this matches the behavior of the backend
+      node.data.version ||= '1.0.0';
     }
   });
   // Bump version

invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem.tsx

@@ -11,44 +11,48 @@ import {
   Text,
   useDisclosure,
 } from '@chakra-ui/react';
-import { useAppDispatch } from 'app/store/storeHooks';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { memo, useCallback, useRef } from 'react';
 import { useTranslation } from 'react-i18next';
-import { FaTrash } from 'react-icons/fa';
+import { FaCircleNodes } from 'react-icons/fa6';
 
-const ResetWorkflowEditorMenuItem = () => {
+const NewWorkflowMenuItem = () => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const { isOpen, onOpen, onClose } = useDisclosure();
   const cancelRef = useRef<HTMLButtonElement | null>(null);
+  const isTouched = useAppSelector((state) => state.workflow.isTouched);
 
-  const handleConfirmClear = useCallback(() => {
+  const handleNewWorkflow = useCallback(() => {
     dispatch(nodeEditorReset());
 
     dispatch(
       addToast(
         makeToast({
-          title: t('workflows.workflowEditorReset'),
+          title: t('workflows.newWorkflowCreated'),
           status: 'success',
         })
       )
     );
 
     onClose();
-  }, [dispatch, t, onClose]);
+  }, [dispatch, onClose, t]);
+
+  const onClick = useCallback(() => {
+    if (!isTouched) {
+      handleNewWorkflow();
+      return;
+    }
+    onOpen();
+  }, [handleNewWorkflow, isTouched, onOpen]);
 
   return (
     <>
-      <MenuItem
-        as="button"
-        icon={<FaTrash />}
-        sx={{ color: 'error.600', _dark: { color: 'error.300' } }}
-        onClick={onOpen}
-      >
-        {t('nodes.resetWorkflow')}
+      <MenuItem as="button" icon={<FaCircleNodes />} onClick={onClick}>
+        {t('nodes.newWorkflow')}
       </MenuItem>
 
       <AlertDialog
@@ -61,13 +65,13 @@ const ResetWorkflowEditorMenuItem = () => {
 
         <AlertDialogContent>
           <AlertDialogHeader fontSize="lg" fontWeight="bold">
-            {t('nodes.resetWorkflow')}
+            {t('nodes.newWorkflow')}
           </AlertDialogHeader>
 
           <AlertDialogBody py={4}>
             <Flex flexDir="column" gap={2}>
-              <Text>{t('nodes.resetWorkflowDesc')}</Text>
-              <Text variant="subtext">{t('nodes.resetWorkflowDesc2')}</Text>
+              <Text>{t('nodes.newWorkflowDesc')}</Text>
+              <Text variant="subtext">{t('nodes.newWorkflowDesc2')}</Text>
             </Flex>
           </AlertDialogBody>
 
@@ -75,7 +79,7 @@ const ResetWorkflowEditorMenuItem = () => {
             <Button ref={cancelRef} onClick={onClose}>
               {t('common.cancel')}
             </Button>
-            <Button colorScheme="error" ml={3} onClick={handleConfirmClear}>
+            <Button colorScheme="error" ml={3} onClick={handleNewWorkflow}>
               {t('common.accept')}
             </Button>
           </AlertDialogFooter>
@@ -85,4 +89,4 @@ const ResetWorkflowEditorMenuItem = () => {
   );
 };
 
-export default memo(ResetWorkflowEditorMenuItem);
+export default memo(NewWorkflowMenuItem);

invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu.tsx

@@ -9,7 +9,7 @@ import IAIIconButton from 'common/components/IAIIconButton';
 import { useGlobalMenuCloseTrigger } from 'common/hooks/useGlobalMenuCloseTrigger';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import DownloadWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/DownloadWorkflowMenuItem';
-import ResetWorkflowEditorMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/ResetWorkflowEditorMenuItem';
+import NewWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem';
 import SaveWorkflowAsMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SaveWorkflowAsMenuItem';
 import SaveWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SaveWorkflowMenuItem';
 import SettingsMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SettingsMenuItem';
@@ -39,7 +39,7 @@ const WorkflowLibraryMenu = () => {
         {isWorkflowLibraryEnabled && <SaveWorkflowAsMenuItem />}
         <DownloadWorkflowMenuItem />
         <UploadWorkflowMenuItem />
-        <ResetWorkflowEditorMenuItem />
+        <NewWorkflowMenuItem />
         <MenuDivider />
         <SettingsMenuItem />
       </MenuList>

mkdocs.yml

@@ -101,6 +101,8 @@ plugins:
 extra_javascript:
   - https://unpkg.com/tablesort@5.3.0/dist/tablesort.min.js
   - javascripts/tablesort.js
+  - https://widget.kapa.ai/kapa-widget.bundle.js
+  - javascript/init_kapa_widget.js
 
 extra:
   analytics:

pyproject.toml

@@ -32,7 +32,7 @@ classifiers = [
   'Topic :: Scientific/Engineering :: Image Processing',
 ]
 dependencies = [
-  "accelerate~=0.24.0",
+  "accelerate~=0.25.0",
   "albumentations",
   "basicsr",
   "click",
@@ -80,11 +80,11 @@ dependencies = [
   "semver~=3.0.1",
   "send2trash",
   "test-tube~=0.7.5",
-  "torch==2.1.0",
-  "torchvision==0.16.0",
+  "torch==2.1.1",
+  "torchvision==0.16.1",
   "torchmetrics~=0.11.0",
   "torchsde~=0.2.5",
-  "transformers~=4.35.0",
+  "transformers~=4.36.0",
   "uvicorn[standard]~=0.21.1",
   "windows-curses; sys_platform=='win32'",
 ]
@@ -107,7 +107,7 @@ dependencies = [
   "pytest-datadir",
 ]
 "xformers" = [
-  "xformers==0.0.22post7; sys_platform!='darwin'",
+  "xformers==0.0.23; sys_platform!='darwin'",
   "triton; sys_platform=='linux'",
 ]
 "onnx" = ["onnxruntime"]
@@ -138,7 +138,6 @@ dependencies = [
 "invokeai-node-web" = "invokeai.app.api_app:invoke_api"
 "invokeai-import-images" = "invokeai.frontend.install.import_images:main"
 "invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main"
-"invokeai-migrate-models-to-db" = "invokeai.backend.model_manager.migrate_to_db:main"
 
 [project.urls]
 "Homepage" = "https://invoke-ai.github.io/InvokeAI/"

tests/backend/tiles/test_tiles.py

@@ -305,9 +305,7 @@ def test_calc_tiles_min_overlap_input_validation(
 
 def test_calc_tiles_even_split_single_tile():
     """Test calc_tiles_even_split() behavior when a single tile covers the image."""
-    tiles = calc_tiles_even_split(
-        image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap=64)
 
     expected_tiles = [
         Tile(
@@ -322,36 +320,34 @@ def test_calc_tiles_even_split_single_tile():
 def test_calc_tiles_even_split_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image is evenly covered by multiple tiles."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=320, left=0, right=624),
-            overlap=TBLR(top=0, bottom=72, left=0, right=136),
+            coords=TBLR(top=0, bottom=320, left=0, right=576),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=488, right=1112),
-            overlap=TBLR(top=0, bottom=72, left=136, right=136),
+            coords=TBLR(top=0, bottom=320, left=512, right=1088),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=976, right=1600),
-            overlap=TBLR(top=0, bottom=72, left=136, right=0),
+            coords=TBLR(top=0, bottom=320, left=1024, right=1600),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=248, bottom=576, left=0, right=624),
-            overlap=TBLR(top=72, bottom=0, left=0, right=136),
+            coords=TBLR(top=256, bottom=576, left=0, right=576),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=488, right=1112),
-            overlap=TBLR(top=72, bottom=0, left=136, right=136),
+            coords=TBLR(top=256, bottom=576, left=512, right=1088),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=976, right=1600),
-            overlap=TBLR(top=72, bottom=0, left=136, right=0),
+            coords=TBLR(top=256, bottom=576, left=1024, right=1600),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
     assert tiles == expected_tiles
@@ -360,36 +356,34 @@ def test_calc_tiles_even_split_evenly_divisible():
 def test_calc_tiles_even_split_not_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image requires 'uneven' overlaps to achieve proper coverage."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=224, left=0, right=464),
-            overlap=TBLR(top=0, bottom=56, left=0, right=104),
+            coords=TBLR(top=0, bottom=232, left=0, right=440),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=360, right=824),
-            overlap=TBLR(top=0, bottom=56, left=104, right=104),
+            coords=TBLR(top=0, bottom=232, left=376, right=816),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=720, right=1200),
-            overlap=TBLR(top=0, bottom=56, left=104, right=0),
+            coords=TBLR(top=0, bottom=232, left=752, right=1200),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=168, bottom=400, left=0, right=464),
-            overlap=TBLR(top=56, bottom=0, left=0, right=104),
+            coords=TBLR(top=168, bottom=400, left=0, right=440),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=360, right=824),
-            overlap=TBLR(top=56, bottom=0, left=104, right=104),
+            coords=TBLR(top=168, bottom=400, left=376, right=816),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=720, right=1200),
-            overlap=TBLR(top=56, bottom=0, left=104, right=0),
+            coords=TBLR(top=168, bottom=400, left=752, right=1200),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -399,28 +393,26 @@ def test_calc_tiles_even_split_not_evenly_divisible():
 def test_calc_tiles_even_split_difficult_size():
     """Test calc_tiles_even_split() behavior when the image is a difficult size to spilt evenly and keep div8."""
     # Parameters are a difficult size for other tile gen routines to calculate
-    tiles = calc_tiles_even_split(
-        image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=560, left=0, right=560),
-            overlap=TBLR(top=0, bottom=128, left=0, right=128),
+            coords=TBLR(top=0, bottom=528, left=0, right=528),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=560, left=432, right=1000),
-            overlap=TBLR(top=0, bottom=128, left=128, right=0),
+            coords=TBLR(top=0, bottom=528, left=464, right=1000),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=0, right=560),
-            overlap=TBLR(top=128, bottom=0, left=0, right=128),
+            coords=TBLR(top=464, bottom=1000, left=0, right=528),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=432, right=1000),
-            overlap=TBLR(top=128, bottom=0, left=128, right=0),
+            coords=TBLR(top=464, bottom=1000, left=464, right=1000),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -428,11 +420,13 @@ def test_calc_tiles_even_split_difficult_size():
 
 
 @pytest.mark.parametrize(
-    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap_fraction", "raises"],
+    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap", "raises"],
     [
-        (128, 128, 1, 1, 0.25, False),  # OK
+        (128, 128, 1, 1, 127, False),  # OK
         (128, 128, 1, 1, 0, False),  # OK
-        (128, 128, 2, 1, 0, False),  # OK
+        (128, 128, 2, 2, 0, False),  # OK
+        (128, 128, 2, 1, 120, True),  # overlap equals tile_height.
+        (128, 128, 1, 2, 120, True),  # overlap equals tile_width.
         (127, 127, 1, 1, 0, True),  # image size must be dividable by 8
     ],
 )
@@ -441,15 +435,15 @@ def test_calc_tiles_even_split_input_validation(
     image_width: int,
     num_tiles_x: int,
     num_tiles_y: int,
-    overlap_fraction: float,
+    overlap: int,
     raises: bool,
 ):
     """Test that calc_tiles_even_split() raises an exception if the inputs are invalid."""
     if raises:
-        with pytest.raises(ValueError):
-            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        with pytest.raises((AssertionError, ValueError)):
+            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
     else:
-        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
 
 
 #############################################