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Author SHA1 Message Date
Mary Hipp
59bd6b935d wip missing fields prototype 2025-02-19 16:00:33 -05:00
263 changed files with 5838 additions and 11661 deletions

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@@ -76,6 +76,9 @@ jobs:
latest=${{ matrix.gpu-driver == 'cuda' && github.ref == 'refs/heads/main' }}
suffix=-${{ matrix.gpu-driver }},onlatest=false
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
@@ -100,7 +103,7 @@ jobs:
push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' || github.event.inputs.push-to-registry }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
# cache-from: |
# type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
# type=gha,scope=main-${{ matrix.gpu-driver }}
# cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
cache-from: |
type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
type=gha,scope=main-${{ matrix.gpu-driver }}
cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}

View File

@@ -13,63 +13,48 @@ RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
git
# Install `uv` for package management
COPY --from=ghcr.io/astral-sh/uv:0.6.0 /uv /uvx /bin/
COPY --from=ghcr.io/astral-sh/uv:0.5.5 /uv /uvx /bin/
ENV VIRTUAL_ENV=/opt/venv
ENV PATH="$VIRTUAL_ENV/bin:$PATH"
ENV INVOKEAI_SRC=/opt/invokeai
ENV PYTHON_VERSION=3.11
ENV UV_PYTHON=3.11
ENV UV_COMPILE_BYTECODE=1
ENV UV_LINK_MODE=copy
ENV UV_PROJECT_ENVIRONMENT="$VIRTUAL_ENV"
ENV UV_INDEX="https://download.pytorch.org/whl/cu124"
ARG GPU_DRIVER=cuda
ARG TARGETPLATFORM="linux/amd64"
# unused but available
ARG BUILDPLATFORM
# Switch to the `ubuntu` user to work around dependency issues with uv-installed python
RUN mkdir -p ${VIRTUAL_ENV} && \
mkdir -p ${INVOKEAI_SRC} && \
chmod -R a+w /opt && \
mkdir ~ubuntu/.cache && chown ubuntu: ~ubuntu/.cache
chmod -R a+w /opt
USER ubuntu
# Install python
RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \
uv python install ${PYTHON_VERSION}
# Install python and create the venv
RUN uv python install ${PYTHON_VERSION} && \
uv venv --relocatable --prompt "invoke" --python ${PYTHON_VERSION} ${VIRTUAL_ENV}
WORKDIR ${INVOKEAI_SRC}
COPY invokeai ./invokeai
COPY pyproject.toml ./
# Install project's dependencies as a separate layer so they aren't rebuilt every commit.
# bind-mount instead of copy to defer adding sources to the image until next layer.
#
# Editable mode helps use the same image for development:
# the local working copy can be bind-mounted into the image
# at path defined by ${INVOKEAI_SRC}
# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
# x86_64/CUDA is the default
RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
--mount=type=bind,source=invokeai/version,target=invokeai/version \
if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
UV_INDEX="https://download.pytorch.org/whl/cpu"; \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
elif [ "$GPU_DRIVER" = "rocm" ]; then \
UV_INDEX="https://download.pytorch.org/whl/rocm6.1"; \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm6.1"; \
else \
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu124"; \
fi && \
uv sync --no-install-project
# Now that the bulk of the dependencies have been installed, copy in the project files that change more frequently.
COPY invokeai invokeai
COPY pyproject.toml .
RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
UV_INDEX="https://download.pytorch.org/whl/cpu"; \
elif [ "$GPU_DRIVER" = "rocm" ]; then \
UV_INDEX="https://download.pytorch.org/whl/rocm6.1"; \
fi && \
uv sync
uv pip install --python ${PYTHON_VERSION} $extra_index_url_arg -e "."
#### Build the Web UI ------------------------------------
@@ -113,7 +98,6 @@ RUN apt update && apt install -y --no-install-recommends \
ENV INVOKEAI_SRC=/opt/invokeai
ENV VIRTUAL_ENV=/opt/venv
ENV UV_PROJECT_ENVIRONMENT="$VIRTUAL_ENV"
ENV PYTHON_VERSION=3.11
ENV INVOKEAI_ROOT=/invokeai
ENV INVOKEAI_HOST=0.0.0.0
@@ -125,7 +109,7 @@ ENV CONTAINER_GID=${CONTAINER_GID:-1000}
# Install `uv` for package management
# and install python for the ubuntu user (expected to exist on ubuntu >=24.x)
# this is too tiny to optimize with multi-stage builds, but maybe we'll come back to it
COPY --from=ghcr.io/astral-sh/uv:0.6.0 /uv /uvx /bin/
COPY --from=ghcr.io/astral-sh/uv:0.5.5 /uv /uvx /bin/
USER ubuntu
RUN uv python install ${PYTHON_VERSION}
USER root

View File

@@ -1,50 +1,41 @@
# Release Process
The Invoke application is published as a python package on [PyPI]. This includes both a source distribution and built distribution (a wheel).
The app is published in twice, in different build formats.
Most users install it with the [Launcher](https://github.com/invoke-ai/launcher/), others with `pip`.
The launcher uses GitHub as the source of truth for available releases.
## Broad Strokes
- Merge all changes and bump the version in the codebase.
- Tag the release commit.
- Wait for the release workflow to complete.
- Approve the PyPI publish jobs.
- Write GH release notes.
- A [PyPI] distribution. This includes both a source distribution and built distribution (a wheel). Users install with `pip install invokeai`. The updater uses this build.
- An installer on the [InvokeAI Releases Page]. This is a zip file with install scripts and a wheel. This is only used for new installs.
## General Prep
Make a developer call-out for PRs to merge. Merge and test things out. Bump the version by editing `invokeai/version/invokeai_version.py`.
Make a developer call-out for PRs to merge. Merge and test things out.
While the release workflow does not include end-to-end tests, it does pause before publishing so you can download and test the final build.
## Release Workflow
The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
It is triggered on **tag push**, when the tag matches `v*`.
It is triggered on **tag push**, when the tag matches `v*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
> Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch. So long as the tag exists, that commit will exist.
### Triggering the Workflow
Ensure all commits that should be in the release are merged, and you have pulled them locally.
Run `make tag-release` to tag the current commit and kick off the workflow.
Double-check that you have checked out the commit that will represent the release (typically the latest commit on `main`).
Run `make tag-release` to tag the current commit and kick off the workflow. You will be prompted to provide a message - use the version specifier.
If this version's tag already exists for some reason (maybe you had to make a last minute change), the script will overwrite it.
> In case you cannot use the Make target, the release may also be dispatched [manually] via GH.
The release may also be dispatched [manually].
### Workflow Jobs and Process
The workflow consists of a number of concurrently-run checks and tests, then two final publish jobs.
The workflow consists of a number of concurrently-run jobs, and two final publish jobs.
The publish jobs require manual approval and are only run if the other jobs succeed.
#### `check-version` Job
This job ensures that the `invokeai` python package version specifier matches the tag for the release. The version specifier is pulled from the `__version__` variable in `invokeai/version/invokeai_version.py`.
This job checks that the git ref matches the app version. It matches the ref against the `__version__` variable in `invokeai/version/invokeai_version.py`.
When the workflow is triggered by tag push, the ref is the tag. If the workflow is run manually, the ref is the target selected from the **Use workflow from** dropdown.
This job uses [samuelcolvin/check-python-version].
@@ -52,52 +43,62 @@ This job uses [samuelcolvin/check-python-version].
#### Check and Test Jobs
Next, these jobs run and must pass. They are the same jobs that are run for every PR.
- **`python-tests`**: runs `pytest` on matrix of platforms
- **`python-checks`**: runs `ruff` (format and lint)
- **`frontend-tests`**: runs `vitest`
- **`frontend-checks`**: runs `prettier` (format), `eslint` (lint), `dpdm` (circular refs), `tsc` (static type check) and `knip` (unused imports)
- **`typegen-checks`**: ensures the frontend and backend types are synced
> **TODO** We should add `mypy` or `pyright` to the **`check-python`** job.
> **TODO** We should add an end-to-end test job that generates an image.
#### `build-installer` Job
This sets up both python and frontend dependencies and builds the python package. Internally, this runs `installer/create_installer.sh` and uploads two artifacts:
- **`dist`**: the python distribution, to be published on PyPI
- **`InvokeAI-installer-${VERSION}.zip`**: the legacy install scripts
You don't need to download either of these files.
> The legacy install scripts are no longer used, but we haven't updated the workflow to skip building them.
- **`InvokeAI-installer-${VERSION}.zip`**: the installer to be included in the GitHub release
#### Sanity Check & Smoke Test
At this point, the release workflow pauses as the remaining publish jobs require approval.
At this point, the release workflow pauses as the remaining publish jobs require approval. Time to test the installer.
It's possible to test the python package before it gets published to PyPI. We've never had problems with it, so it's not necessary to do this.
Because the installer pulls from PyPI, and we haven't published to PyPI yet, you will need to install from the wheel:
But, if you want to be extra-super careful, here's how to test it:
- Download and unzip `dist.zip` and the installer from the **Summary** tab of the workflow
- Run the installer script using the `--wheel` CLI arg, pointing at the wheel:
- Download the `dist.zip` build artifact from the `build-installer` job
- Unzip it and find the wheel file
- Create a fresh Invoke install by following the [manual install guide](https://invoke-ai.github.io/InvokeAI/installation/manual/) - but instead of installing from PyPI, install from the wheel
- Test the app
```sh
./install.sh --wheel ../InvokeAI-4.0.0rc6-py3-none-any.whl
```
- Install to a temporary directory so you get the new user experience
- Download a model and generate
> The same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the exactly the same installation as if the installer got the wheel from PyPI.
##### Something isn't right
If testing reveals any issues, no worries. Cancel the workflow, which will cancel the pending publish jobs (you didn't approve them prematurely, right?) and start over.
If testing reveals any issues, no worries. Cancel the workflow, which will cancel the pending publish jobs (you didn't approve them prematurely, right?).
Now you can start from the top:
- Fix the issues and PR the fixes per usual
- Get the PR approved and merged per usual
- Switch to `main` and pull in the fixes
- Run `make tag-release` to move the tag to `HEAD` (which has the fixes) and kick off the release workflow again
- Re-do the sanity check
#### PyPI Publish Jobs
The publish jobs will not run if any of the previous jobs fail.
The publish jobs will run if any of the previous jobs fail.
They use [GitHub environments], which are configured as [trusted publishers] on PyPI.
Both jobs require a @hipsterusername or @psychedelicious to approve them from the workflow's **Summary** tab.
Both jobs require a maintainer to approve them from the workflow's **Summary** tab.
- Click the **Review deployments** button
- Select the environment (either `testpypi` or `pypi` - typically you select both)
- Select the environment (either `testpypi` or `pypi`)
- Click **Approve and deploy**
> **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a given version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
@@ -112,33 +113,46 @@ If there are no incidents, contact @hipsterusername or @lstein, who have owner a
Publishes the distribution on the [Test PyPI] index, using the `testpypi` GitHub environment.
This job is not required for the production PyPI publish, but included just in case you want to test the PyPI release for some reason:
This job is not required for the production PyPI publish, but included just in case you want to test the PyPI release.
- Approve this publish job without approving the prod publish
- Let it finish
- Create a fresh Invoke install by following the [manual install guide](https://invoke-ai.github.io/InvokeAI/installation/manual/), making sure to use the Test PyPI index URL: `https://test.pypi.org/simple/`
- Test the app
If approved and successful, you could try out the test release like this:
```sh
# Create a new virtual environment
python -m venv ~/.test-invokeai-dist --prompt test-invokeai-dist
# Install the distribution from Test PyPI
pip install --index-url https://test.pypi.org/simple/ invokeai
# Run and test the app
invokeai-web
# Cleanup
deactivate
rm -rf ~/.test-invokeai-dist
```
#### `publish-pypi` Job
Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
It's a good idea to wait to approve and run this job until you have the release notes ready!
## Publish the GitHub Release with installer
## Prep and publish the GitHub Release
Once the release is published to PyPI, it's time to publish the GitHub release.
1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
2. The **Generate release notes** button automatically inserts the changelog and new contributors. Make sure to select the correct tags for this release and the last stable release. GH often selects the wrong tags - do this manually.
3. Write the release notes, describing important changes. Contributions from community members should be shouted out. Use the GH-generated changelog to see all contributors. If there are Weblate translation updates, open that PR and shout out every person who contributed a translation.
4. Check **Set as a pre-release** if it's a pre-release.
5. Approve and wait for the `publish-pypi` job to finish if you haven't already.
6. Publish the GH release.
7. Post the release in Discord in the [releases](https://discord.com/channels/1020123559063990373/1149260708098359327) channel with abbreviated notes. For example:
> Invoke v5.7.0 (stable): <https://github.com/invoke-ai/InvokeAI/releases/tag/v5.7.0>
>
> It's a pretty big one - Form Builder, Metadata Nodes (thanks @SkunkWorxDark!), and much more.
8. Right click the message in releases and copy the link to it. Then, post that link in the [new-release-discussion](https://discord.com/channels/1020123559063990373/1149506274971631688) channel. For example:
> Invoke v5.7.0 (stable): <https://discord.com/channels/1020123559063990373/1149260708098359327/1344521744916021248>
1. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.
1. Use `scripts/get_external_contributions.py` to get a list of external contributions to shout out in the release notes.
1. Upload the zip file created in **`build`** job into the Assets section of the release notes.
1. Check **Set as a pre-release** if it's a pre-release.
1. Check **Create a discussion for this release**.
1. Publish the release.
1. Announce the release in Discord.
> **TODO** Workflows can create a GitHub release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
## Manual Build
The `build installer` workflow can be dispatched manually. This is useful to test the installer for a given branch or tag.
No checks are run, it just builds.
## Manual Release
@@ -146,10 +160,12 @@ The `release` workflow can be dispatched manually. You must dispatch the workflo
This functionality is available as a fallback in case something goes wonky. Typically, releases should be triggered via tag push as described above.
[InvokeAI Releases Page]: https://github.com/invoke-ai/InvokeAI/releases
[PyPI]: https://pypi.org/
[Draft a new release]: https://github.com/invoke-ai/InvokeAI/releases/new
[Test PyPI]: https://test.pypi.org/
[version specifier]: https://packaging.python.org/en/latest/specifications/version-specifiers/
[ncipollo/release-action]: https://github.com/ncipollo/release-action
[GitHub environments]: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment
[trusted publishers]: https://docs.pypi.org/trusted-publishers/
[samuelcolvin/check-python-version]: https://github.com/samuelcolvin/check-python-version

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@@ -31,7 +31,6 @@ It is possible to fine-tune the settings for best performance or if you still ge
Low-VRAM mode involves 4 features, each of which can be configured or fine-tuned:
- Partial model loading (`enable_partial_loading`)
- PyTorch CUDA allocator config (`pytorch_cuda_alloc_conf`)
- Dynamic RAM and VRAM cache sizes (`max_cache_ram_gb`, `max_cache_vram_gb`)
- Working memory (`device_working_mem_gb`)
- Keeping a RAM weight copy (`keep_ram_copy_of_weights`)
@@ -52,16 +51,6 @@ As described above, you can enable partial model loading by adding this line to
enable_partial_loading: true
```
### PyTorch CUDA allocator config
The PyTorch CUDA allocator's behavior can be configured using the `pytorch_cuda_alloc_conf` config. Tuning the allocator configuration can help to reduce the peak reserved VRAM. The optimal configuration is dependent on many factors (e.g. device type, VRAM, CUDA driver version, etc.), but switching from PyTorch's native allocator to using CUDA's built-in allocator works well on many systems. To try this, add the following line to your `invokeai.yaml` file:
```yaml
pytorch_cuda_alloc_conf: "backend:cudaMallocAsync"
```
A more complete explanation of the available configuration options is [here](https://pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf).
### Dynamic RAM and VRAM cache sizes
Loading models from disk is slow and can be a major bottleneck for performance. Invoke uses two model caches - RAM and VRAM - to reduce loading from disk to a minimum.
@@ -86,26 +75,24 @@ But, if your GPU has enough VRAM to hold models fully, you might get a perf boos
# As an example, if your system has 32GB of RAM and no other heavy processes, setting the `max_cache_ram_gb` to 28GB
# might be a good value to achieve aggressive model caching.
max_cache_ram_gb: 28
# The default max cache VRAM size is adjusted dynamically based on the amount of available VRAM (taking into
# consideration the VRAM used by other processes).
# You can override the default value by setting `max_cache_vram_gb`.
# CAUTION: Most users should not manually set this value. See warning below.
max_cache_vram_gb: 16
# You can override the default value by setting `max_cache_vram_gb`. Note that this value takes precedence over the
# `device_working_mem_gb`.
# It is recommended to set the VRAM cache size to be as large as possible while leaving enough room for the working
# memory of the tasks you will be doing. For example, on a 24GB GPU that will be running unquantized FLUX without any
# auxiliary models, 18GB might be a good value.
max_cache_vram_gb: 18
```
!!! warning "Max safe value for `max_cache_vram_gb`"
!!! tip "Max safe value for `max_cache_vram_gb`"
Most users should not manually configure the `max_cache_vram_gb`. This configuration value takes precedence over the `device_working_mem_gb` and any operations that explicitly reserve additional working memory (e.g. VAE decode). As such, manually configuring it increases the likelihood of encountering out-of-memory errors.
For users who wish to configure `max_cache_vram_gb`, the max safe value can be determined by subtracting `device_working_mem_gb` from your GPU's VRAM. As described below, the default for `device_working_mem_gb` is 3GB.
To determine the max safe value for `max_cache_vram_gb`, subtract `device_working_mem_gb` from your GPU's VRAM. As described below, the default for `device_working_mem_gb` is 3GB.
For example, if you have a 12GB GPU, the max safe value for `max_cache_vram_gb` is `12GB - 3GB = 9GB`.
If you had increased `device_working_mem_gb` to 4GB, then the max safe value for `max_cache_vram_gb` is `12GB - 4GB = 8GB`.
Most users who override `max_cache_vram_gb` are doing so because they wish to use significantly less VRAM, and should be setting `max_cache_vram_gb` to a value significantly less than the 'max safe value'.
### Working memory
Invoke cannot use _all_ of your VRAM for model caching and loading. It requires some VRAM to use as working memory for various operations.

View File

@@ -7,7 +7,6 @@ from pydantic import BaseModel, Field
from invokeai.app.api.dependencies import ApiDependencies
from invokeai.app.services.board_records.board_records_common import BoardChanges, BoardRecordOrderBy
from invokeai.app.services.boards.boards_common import BoardDTO
from invokeai.app.services.image_records.image_records_common import ImageCategory
from invokeai.app.services.shared.pagination import OffsetPaginatedResults
from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
@@ -88,9 +87,7 @@ async def delete_board(
try:
if include_images is True:
deleted_images = ApiDependencies.invoker.services.board_images.get_all_board_image_names_for_board(
board_id=board_id,
categories=None,
is_intermediate=None,
board_id=board_id
)
ApiDependencies.invoker.services.images.delete_images_on_board(board_id=board_id)
ApiDependencies.invoker.services.boards.delete(board_id=board_id)
@@ -101,9 +98,7 @@ async def delete_board(
)
else:
deleted_board_images = ApiDependencies.invoker.services.board_images.get_all_board_image_names_for_board(
board_id=board_id,
categories=None,
is_intermediate=None,
board_id=board_id
)
ApiDependencies.invoker.services.boards.delete(board_id=board_id)
return DeleteBoardResult(
@@ -147,14 +142,10 @@ async def list_boards(
)
async def list_all_board_image_names(
board_id: str = Path(description="The id of the board"),
categories: list[ImageCategory] | None = Query(default=None, description="The categories of image to include."),
is_intermediate: bool | None = Query(default=None, description="Whether to list intermediate images."),
) -> list[str]:
"""Gets a list of images for a board"""
image_names = ApiDependencies.invoker.services.board_images.get_all_board_image_names_for_board(
board_id,
categories,
is_intermediate,
)
return image_names

View File

@@ -48,9 +48,7 @@ async def enqueue_batch(
) -> EnqueueBatchResult:
"""Processes a batch and enqueues the output graphs for execution."""
return await ApiDependencies.invoker.services.session_queue.enqueue_batch(
queue_id=queue_id, batch=batch, prepend=prepend
)
return ApiDependencies.invoker.services.session_queue.enqueue_batch(queue_id=queue_id, batch=batch, prepend=prepend)
@session_queue_router.get(

View File

@@ -1,8 +1,12 @@
import asyncio
import logging
import mimetypes
import socket
from contextlib import asynccontextmanager
from pathlib import Path
import torch
import uvicorn
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
@@ -11,7 +15,11 @@ from fastapi.responses import HTMLResponse, RedirectResponse
from fastapi_events.handlers.local import local_handler
from fastapi_events.middleware import EventHandlerASGIMiddleware
from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint
from torch.backends.mps import is_available as is_mps_available
# for PyCharm:
# noinspection PyUnresolvedReferences
import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
import invokeai.frontend.web as web_dir
from invokeai.app.api.dependencies import ApiDependencies
from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
@@ -30,13 +38,31 @@ from invokeai.app.api.routers import (
from invokeai.app.api.sockets import SocketIO
from invokeai.app.services.config.config_default import get_config
from invokeai.app.util.custom_openapi import get_openapi_func
from invokeai.backend.util.devices import TorchDevice
from invokeai.backend.util.logging import InvokeAILogger
app_config = get_config()
if is_mps_available():
import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
logger = InvokeAILogger.get_logger(config=app_config)
# fix for windows mimetypes registry entries being borked
# see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
mimetypes.add_type("application/javascript", ".js")
mimetypes.add_type("text/css", ".css")
torch_device_name = TorchDevice.get_torch_device_name()
logger.info(f"Using torch device: {torch_device_name}")
loop = asyncio.new_event_loop()
# We may change the port if the default is in use, this global variable is used to store the port so that we can log
# the correct port when the server starts in the lifespan handler.
port = app_config.port
@asynccontextmanager
async def lifespan(app: FastAPI):
@@ -45,7 +71,7 @@ async def lifespan(app: FastAPI):
# Log the server address when it starts - in case the network log level is not high enough to see the startup log
proto = "https" if app_config.ssl_certfile else "http"
msg = f"Invoke running on {proto}://{app_config.host}:{app_config.port} (Press CTRL+C to quit)"
msg = f"Invoke running on {proto}://{app_config.host}:{port} (Press CTRL+C to quit)"
# Logging this way ignores the logger's log level and _always_ logs the message
record = logger.makeRecord(
@@ -160,3 +186,73 @@ except RuntimeError:
app.mount(
"/static", NoCacheStaticFiles(directory=Path(web_root_path, "static/")), name="static"
) # docs favicon is in here
def check_cudnn(logger: logging.Logger) -> None:
"""Check for cuDNN issues that could be causing degraded performance."""
if torch.backends.cudnn.is_available():
try:
# Note: At the time of writing (torch 2.2.1), torch.backends.cudnn.version() only raises an error the first
# time it is called. Subsequent calls will return the version number without complaining about a mismatch.
cudnn_version = torch.backends.cudnn.version()
logger.info(f"cuDNN version: {cudnn_version}")
except RuntimeError as e:
logger.warning(
"Encountered a cuDNN version issue. This may result in degraded performance. This issue is usually "
"caused by an incompatible cuDNN version installed in your python environment, or on the host "
f"system. Full error message:\n{e}"
)
def invoke_api() -> None:
def find_port(port: int) -> int:
"""Find a port not in use starting at given port"""
# Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
# https://github.com/WaylonWalker
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.settimeout(1)
if s.connect_ex(("localhost", port)) == 0:
return find_port(port=port + 1)
else:
return port
if app_config.dev_reload:
try:
import jurigged
except ImportError as e:
logger.error(
'Can\'t start `--dev_reload` because jurigged is not found; `pip install -e ".[dev]"` to include development dependencies.',
exc_info=e,
)
else:
jurigged.watch(logger=InvokeAILogger.get_logger(name="jurigged").info)
global port
port = find_port(app_config.port)
if port != app_config.port:
logger.warn(f"Port {app_config.port} in use, using port {port}")
check_cudnn(logger)
config = uvicorn.Config(
app=app,
host=app_config.host,
port=port,
loop="asyncio",
log_level=app_config.log_level_network,
ssl_certfile=app_config.ssl_certfile,
ssl_keyfile=app_config.ssl_keyfile,
)
server = uvicorn.Server(config)
# replace uvicorn's loggers with InvokeAI's for consistent appearance
uvicorn_logger = InvokeAILogger.get_logger("uvicorn")
uvicorn_logger.handlers.clear()
for hdlr in logger.handlers:
uvicorn_logger.addHandler(hdlr)
loop.run_until_complete(server.serve())
if __name__ == "__main__":
invoke_api()

View File

@@ -1,5 +1,33 @@
import shutil
import sys
from importlib.util import module_from_spec, spec_from_file_location
from pathlib import Path
from invokeai.app.services.config.config_default import get_config
custom_nodes_path = Path(get_config().custom_nodes_path)
custom_nodes_path.mkdir(parents=True, exist_ok=True)
custom_nodes_init_path = str(custom_nodes_path / "__init__.py")
custom_nodes_readme_path = str(custom_nodes_path / "README.md")
# copy our custom nodes __init__.py to the custom nodes directory
shutil.copy(Path(__file__).parent / "custom_nodes/init.py", custom_nodes_init_path)
shutil.copy(Path(__file__).parent / "custom_nodes/README.md", custom_nodes_readme_path)
# set the same permissions as the destination directory, in case our source is read-only,
# so that the files are user-writable
for p in custom_nodes_path.glob("**/*"):
p.chmod(custom_nodes_path.stat().st_mode)
# Import custom nodes, see https://docs.python.org/3/library/importlib.html#importing-programmatically
spec = spec_from_file_location("custom_nodes", custom_nodes_init_path)
if spec is None or spec.loader is None:
raise RuntimeError(f"Could not load custom nodes from {custom_nodes_init_path}")
module = module_from_spec(spec)
sys.modules[spec.name] = module
spec.loader.exec_module(module)
# add core nodes to __all__
python_files = filter(lambda f: not f.name.startswith("_"), Path(__file__).parent.glob("*.py"))
__all__ = [f.stem for f in python_files] # type: ignore

View File

@@ -44,6 +44,8 @@ if TYPE_CHECKING:
logger = InvokeAILogger.get_logger()
CUSTOM_NODE_PACK_SUFFIX = "__invokeai-custom-node"
class InvalidVersionError(ValueError):
pass
@@ -238,11 +240,6 @@ class BaseInvocation(ABC, BaseModel):
"""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."""
@@ -449,27 +446,8 @@ def invocation(
if re.compile(r"^\S+$").match(invocation_type) is None:
raise ValueError(f'"invocation_type" must consist of non-whitespace characters, got "{invocation_type}"')
# The node pack is the module name - will be "invokeai" for built-in nodes
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)
# This should always be true - we just checked if the invocation type was in the set
assert clobbered_invocation is not None
clobbered_node_pack = clobbered_invocation.UIConfig.node_pack
if clobbered_node_pack == "invokeai":
# The node being clobbered is a core node
raise ValueError(
f'Cannot load node "{invocation_type}" from node pack "{node_pack}" - a core node with the same type already exists'
)
else:
# The node being clobbered is a custom node
raise ValueError(
f'Cannot load node "{invocation_type}" from node pack "{node_pack}" - a node with the same type already exists in node pack "{clobbered_node_pack}"'
)
raise ValueError(f'Invocation type "{invocation_type}" already exists')
validate_fields(cls.model_fields, invocation_type)
@@ -479,7 +457,8 @@ def invocation(
uiconfig["tags"] = tags
uiconfig["category"] = category
uiconfig["classification"] = classification
uiconfig["node_pack"] = node_pack
# The node pack is the module name - will be "invokeai" for built-in nodes
uiconfig["node_pack"] = cls.__module__.split(".")[0]
if version is not None:
try:

View File

@@ -64,50 +64,13 @@ class ImageBatchInvocation(BaseBatchInvocation):
"""Create a batched generation, where the workflow is executed once for each image in the batch."""
images: list[ImageField] = InputField(
default=[],
min_length=1,
description="The images to batch over",
default=[], min_length=1, description="The images to batch over", input=Input.Direct
)
def invoke(self, context: InvocationContext) -> ImageOutput:
raise NotExecutableNodeError()
@invocation_output("image_generator_output")
class ImageGeneratorOutput(BaseInvocationOutput):
"""Base class for nodes that output a collection of boards"""
images: list[ImageField] = OutputField(description="The generated images")
class ImageGeneratorField(BaseModel):
pass
@invocation(
"image_generator",
title="Image Generator",
tags=["primitives", "board", "image", "batch", "special"],
category="primitives",
version="1.0.0",
classification=Classification.Special,
)
class ImageGenerator(BaseInvocation):
"""Generated a collection of images for use in a batched generation"""
generator: ImageGeneratorField = InputField(
description="The image generator.",
input=Input.Direct,
title="Generator Type",
)
def __init__(self):
raise NotExecutableNodeError()
def invoke(self, context: InvocationContext) -> ImageGeneratorOutput:
raise NotExecutableNodeError()
@invocation(
"string_batch",
title="String Batch",

View File

@@ -10,12 +10,10 @@ from pathlib import Path
from invokeai.backend.util.logging import InvokeAILogger
logger = InvokeAILogger.get_logger()
loaded_packs: list[str] = []
failed_packs: list[str] = []
loaded_count = 0
custom_nodes_dir = Path(__file__).parent
for d in custom_nodes_dir.iterdir():
for d in Path(__file__).parent.iterdir():
# skip files
if not d.is_dir():
continue
@@ -49,16 +47,12 @@ for d in custom_nodes_dir.iterdir():
sys.modules[spec.name] = module
spec.loader.exec_module(module)
loaded_packs.append(module_name)
loaded_count += 1
except Exception:
failed_packs.append(module_name)
full_error = traceback.format_exc()
logger.error(f"Failed to load node pack {module_name} (may have partially loaded):\n{full_error}")
logger.error(f"Failed to load node pack {module_name}:\n{full_error}")
del init, module_name
loaded_count = len(loaded_packs)
if loaded_count > 0:
logger.info(
f"Loaded {loaded_count} node pack{'s' if loaded_count != 1 else ''} from {custom_nodes_dir}: {', '.join(loaded_packs)}"
)
logger.info(f"Loaded {loaded_count} node packs from {Path(__file__).parent}")

View File

@@ -41,11 +41,16 @@ class FluxVaeDecodeInvocation(BaseInvocation, WithMetadata, WithBoard):
def _estimate_working_memory(self, latents: torch.Tensor, vae: AutoEncoder) -> int:
"""Estimate the working memory required by the invocation in bytes."""
# It was found experimentally that the peak working memory scales linearly with the number of pixels and the
# element size (precision).
out_h = LATENT_SCALE_FACTOR * latents.shape[-2]
out_w = LATENT_SCALE_FACTOR * latents.shape[-1]
element_size = next(vae.parameters()).element_size()
scaling_constant = 2200 # Determined experimentally.
scaling_constant = 1090 # Determined experimentally.
working_memory = out_h * out_w * element_size * scaling_constant
# We add a 20% buffer to the working memory estimate to be safe.
working_memory = working_memory * 1.2
return int(working_memory)
def _vae_decode(self, vae_info: LoadedModel, latents: torch.Tensor) -> Image.Image:

View File

@@ -60,7 +60,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
# It was found experimentally that the peak working memory scales linearly with the number of pixels and the
# element size (precision). This estimate is accurate for both SD1 and SDXL.
element_size = 4 if self.fp32 else 2
scaling_constant = 2200 # Determined experimentally.
scaling_constant = 960 # Determined experimentally.
if use_tiling:
tile_size = self.tile_size
@@ -84,7 +84,9 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
# If we are running in FP32, then we should account for the likely increase in model size (~250MB).
working_memory += 250 * 2**20
return int(working_memory)
# We add 20% to the working memory estimate to be safe.
working_memory = int(working_memory * 1.2)
return working_memory
@torch.no_grad()
def invoke(self, context: InvocationContext) -> ImageOutput:

View File

@@ -1,40 +0,0 @@
import shutil
import sys
from importlib.util import module_from_spec, spec_from_file_location
from pathlib import Path
def load_custom_nodes(custom_nodes_path: Path):
"""
Loads all custom nodes from the custom_nodes_path directory.
This function copies a custom __init__.py file to the custom_nodes_path directory, effectively turning it into a
python module.
The custom __init__.py file itself imports all the custom node packs as python modules from the custom_nodes_path
directory.
Then,the custom __init__.py file is programmatically imported using importlib. As it executes, it imports all the
custom node packs as python modules.
"""
custom_nodes_path.mkdir(parents=True, exist_ok=True)
custom_nodes_init_path = str(custom_nodes_path / "__init__.py")
custom_nodes_readme_path = str(custom_nodes_path / "README.md")
# copy our custom nodes __init__.py to the custom nodes directory
shutil.copy(Path(__file__).parent / "custom_nodes/init.py", custom_nodes_init_path)
shutil.copy(Path(__file__).parent / "custom_nodes/README.md", custom_nodes_readme_path)
# set the same permissions as the destination directory, in case our source is read-only,
# so that the files are user-writable
for p in custom_nodes_path.glob("**/*"):
p.chmod(custom_nodes_path.stat().st_mode)
# Import custom nodes, see https://docs.python.org/3/library/importlib.html#importing-programmatically
spec = spec_from_file_location("custom_nodes", custom_nodes_init_path)
if spec is None or spec.loader is None:
raise RuntimeError(f"Could not load custom nodes from {custom_nodes_init_path}")
module = module_from_spec(spec)
sys.modules[spec.name] = module
spec.loader.exec_module(module)

View File

@@ -284,7 +284,6 @@ class CoreMetadataInvocation(BaseInvocation):
tags=["metadata"],
category="metadata",
version="1.0.0",
classification=Classification.Deprecated,
)
class MetadataFieldExtractorInvocation(BaseInvocation):
"""Extracts the text value from an image's metadata given a key.

File diff suppressed because it is too large Load Diff

View File

@@ -265,9 +265,13 @@ class ImageInvocation(BaseInvocation):
image: ImageField = InputField(description="The image to load")
def invoke(self, context: InvocationContext) -> ImageOutput:
image_dto = context.images.get_dto(self.image.image_name)
image = context.images.get_pil(self.image.image_name)
return ImageOutput.build(image_dto=image_dto)
return ImageOutput(
image=ImageField(image_name=self.image.image_name),
width=image.width,
height=image.height,
)
@invocation(

View File

@@ -43,11 +43,16 @@ class SD3LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
def _estimate_working_memory(self, latents: torch.Tensor, vae: AutoencoderKL) -> int:
"""Estimate the working memory required by the invocation in bytes."""
# It was found experimentally that the peak working memory scales linearly with the number of pixels and the
# element size (precision).
out_h = LATENT_SCALE_FACTOR * latents.shape[-2]
out_w = LATENT_SCALE_FACTOR * latents.shape[-1]
element_size = next(vae.parameters()).element_size()
scaling_constant = 2200 # Determined experimentally.
scaling_constant = 1230 # Determined experimentally.
working_memory = out_h * out_w * element_size * scaling_constant
# We add a 20% buffer to the working memory estimate to be safe.
working_memory = working_memory * 1.2
return int(working_memory)
@torch.no_grad()

View File

@@ -9,6 +9,6 @@ def validate_weights(weights: Union[float, list[float]]) -> None:
def validate_begin_end_step(begin_step_percent: float, end_step_percent: float) -> None:
"""Validate that begin_step_percent is less than or equal to end_step_percent"""
if begin_step_percent > end_step_percent:
"""Validate that begin_step_percent is less than end_step_percent"""
if begin_step_percent >= end_step_percent:
raise ValueError("Begin step percent must be less than or equal to end step percent")

View File

@@ -1,82 +1,12 @@
import uvicorn
from invokeai.app.invocations.load_custom_nodes import load_custom_nodes
from invokeai.app.services.config.config_default import get_config
from invokeai.app.util.torch_cuda_allocator import configure_torch_cuda_allocator
from invokeai.backend.util.logging import InvokeAILogger
from invokeai.frontend.cli.arg_parser import InvokeAIArgs
def get_app():
"""Import the app and event loop. We wrap this in a function to more explicitly control when it happens, because
importing from api_app does a bunch of stuff - it's more like calling a function than importing a module.
"""
from invokeai.app.api_app import app, loop
return app, loop
"""This is a wrapper around the main app entrypoint, to allow for CLI args to be parsed before running the app."""
def run_app() -> None:
"""The main entrypoint for the app."""
# Parse the CLI arguments.
# Before doing _anything_, parse CLI args!
from invokeai.frontend.cli.arg_parser import InvokeAIArgs
InvokeAIArgs.parse_args()
# Load config.
app_config = get_config()
from invokeai.app.api_app import invoke_api
logger = InvokeAILogger.get_logger(config=app_config)
# Configure the torch CUDA memory allocator.
# NOTE: It is important that this happens before torch is imported.
if app_config.pytorch_cuda_alloc_conf:
configure_torch_cuda_allocator(app_config.pytorch_cuda_alloc_conf, logger)
# Import from startup_utils here to avoid importing torch before configure_torch_cuda_allocator() is called.
from invokeai.app.util.startup_utils import (
apply_monkeypatches,
check_cudnn,
enable_dev_reload,
find_open_port,
register_mime_types,
)
# Find an open port, and modify the config accordingly.
orig_config_port = app_config.port
app_config.port = find_open_port(app_config.port)
if orig_config_port != app_config.port:
logger.warning(f"Port {orig_config_port} is already in use. Using port {app_config.port}.")
# Miscellaneous startup tasks.
apply_monkeypatches()
register_mime_types()
if app_config.dev_reload:
enable_dev_reload()
check_cudnn(logger)
# Initialize the app and event loop.
app, loop = get_app()
# Load custom nodes. This must be done after importing the Graph class, which itself imports all modules from the
# invocations module. The ordering here is implicit, but important - we want to load custom nodes after all the
# core nodes have been imported so that we can catch when a custom node clobbers a core node.
load_custom_nodes(custom_nodes_path=app_config.custom_nodes_path)
# Start the server.
config = uvicorn.Config(
app=app,
host=app_config.host,
port=app_config.port,
loop="asyncio",
log_level=app_config.log_level_network,
ssl_certfile=app_config.ssl_certfile,
ssl_keyfile=app_config.ssl_keyfile,
)
server = uvicorn.Server(config)
# replace uvicorn's loggers with InvokeAI's for consistent appearance
uvicorn_logger = InvokeAILogger.get_logger("uvicorn")
uvicorn_logger.handlers.clear()
for hdlr in logger.handlers:
uvicorn_logger.addHandler(hdlr)
loop.run_until_complete(server.serve())
invoke_api()

View File

@@ -1,8 +1,6 @@
from abc import ABC, abstractmethod
from typing import Optional
from invokeai.app.services.image_records.image_records_common import ImageCategory
class BoardImageRecordStorageBase(ABC):
"""Abstract base class for the one-to-many board-image relationship record storage."""
@@ -28,8 +26,6 @@ class BoardImageRecordStorageBase(ABC):
def get_all_board_image_names_for_board(
self,
board_id: str,
categories: list[ImageCategory] | None,
is_intermediate: bool | None,
) -> list[str]:
"""Gets all board images for a board, as a list of the image names."""
pass

View File

@@ -1,20 +1,23 @@
import sqlite3
import threading
from typing import Optional, cast
from invokeai.app.services.board_image_records.board_image_records_base import BoardImageRecordStorageBase
from invokeai.app.services.image_records.image_records_common import (
ImageCategory,
ImageRecord,
deserialize_image_record,
)
from invokeai.app.services.image_records.image_records_common import ImageRecord, deserialize_image_record
from invokeai.app.services.shared.pagination import OffsetPaginatedResults
from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
_conn: sqlite3.Connection
_cursor: sqlite3.Cursor
_lock: threading.RLock
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._lock = db.lock
self._conn = db.conn
self._cursor = self._conn.cursor()
def add_image_to_board(
self,
@@ -22,8 +25,8 @@ class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
image_name: str,
) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
INSERT INTO board_images (board_id, image_name)
VALUES (?, ?)
@@ -35,14 +38,16 @@ class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
def remove_image_from_board(
self,
image_name: str,
) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE FROM board_images
WHERE image_name = ?;
@@ -53,6 +58,8 @@ class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
def get_images_for_board(
self,
@@ -61,108 +68,96 @@ class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
limit: int = 10,
) -> OffsetPaginatedResults[ImageRecord]:
# TODO: this isn't paginated yet?
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT images.*
FROM board_images
INNER JOIN images ON board_images.image_name = images.image_name
WHERE board_images.board_id = ?
ORDER BY board_images.updated_at DESC;
""",
(board_id,),
)
result = cast(list[sqlite3.Row], cursor.fetchall())
images = [deserialize_image_record(dict(r)) for r in result]
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT images.*
FROM board_images
INNER JOIN images ON board_images.image_name = images.image_name
WHERE board_images.board_id = ?
ORDER BY board_images.updated_at DESC;
""",
(board_id,),
)
result = cast(list[sqlite3.Row], self._cursor.fetchall())
images = [deserialize_image_record(dict(r)) for r in result]
cursor.execute(
"""--sql
SELECT COUNT(*) FROM images WHERE 1=1;
"""
)
count = cast(int, cursor.fetchone()[0])
self._cursor.execute(
"""--sql
SELECT COUNT(*) FROM images WHERE 1=1;
"""
)
count = cast(int, self._cursor.fetchone()[0])
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
return OffsetPaginatedResults(items=images, offset=offset, limit=limit, total=count)
def get_all_board_image_names_for_board(
self,
board_id: str,
categories: list[ImageCategory] | None,
is_intermediate: bool | None,
) -> list[str]:
params: list[str | bool] = []
# Base query is a join between images and board_images
stmt = """
SELECT images.image_name
FROM images
LEFT JOIN board_images ON board_images.image_name = images.image_name
WHERE 1=1
AND board_images.board_id = ?
"""
params.append(board_id)
# Add the category filter
if categories is not None:
# Convert the enum values to unique list of strings
category_strings = [c.value for c in set(categories)]
# Create the correct length of placeholders
placeholders = ",".join("?" * len(category_strings))
stmt += f"""--sql
AND images.image_category IN ( {placeholders} )
"""
# Unpack the included categories into the query params
for c in category_strings:
params.append(c)
# Add the is_intermediate filter
if is_intermediate is not None:
stmt += """--sql
AND images.is_intermediate = ?
"""
params.append(is_intermediate)
# Put a ring on it
stmt += ";"
# Execute the query
cursor = self._conn.cursor()
cursor.execute(stmt, params)
result = cast(list[sqlite3.Row], cursor.fetchall())
image_names = [r[0] for r in result]
return image_names
def get_all_board_image_names_for_board(self, board_id: str) -> list[str]:
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT image_name
FROM board_images
WHERE board_id = ?;
""",
(board_id,),
)
result = cast(list[sqlite3.Row], self._cursor.fetchall())
image_names = [r[0] for r in result]
return image_names
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
def get_board_for_image(
self,
image_name: str,
) -> Optional[str]:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT board_id
FROM board_images
WHERE image_name = ?;
""",
(image_name,),
)
result = cursor.fetchone()
if result is None:
return None
return cast(str, result[0])
(image_name,),
)
result = self._cursor.fetchone()
if result is None:
return None
return cast(str, result[0])
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
def get_image_count_for_board(self, board_id: str) -> int:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT COUNT(*)
FROM board_images
INNER JOIN images ON board_images.image_name = images.image_name
WHERE images.is_intermediate = FALSE
AND board_images.board_id = ?;
""",
(board_id,),
)
count = cast(int, cursor.fetchone()[0])
return count
(board_id,),
)
count = cast(int, self._cursor.fetchone()[0])
return count
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()

View File

@@ -1,8 +1,6 @@
from abc import ABC, abstractmethod
from typing import Optional
from invokeai.app.services.image_records.image_records_common import ImageCategory
class BoardImagesServiceABC(ABC):
"""High-level service for board-image relationship management."""
@@ -28,8 +26,6 @@ class BoardImagesServiceABC(ABC):
def get_all_board_image_names_for_board(
self,
board_id: str,
categories: list[ImageCategory] | None,
is_intermediate: bool | None,
) -> list[str]:
"""Gets all board images for a board, as a list of the image names."""
pass

View File

@@ -1,7 +1,6 @@
from typing import Optional
from invokeai.app.services.board_images.board_images_base import BoardImagesServiceABC
from invokeai.app.services.image_records.image_records_common import ImageCategory
from invokeai.app.services.invoker import Invoker
@@ -27,14 +26,8 @@ class BoardImagesService(BoardImagesServiceABC):
def get_all_board_image_names_for_board(
self,
board_id: str,
categories: list[ImageCategory] | None,
is_intermediate: bool | None,
) -> list[str]:
return self.__invoker.services.board_image_records.get_all_board_image_names_for_board(
board_id,
categories,
is_intermediate,
)
return self.__invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
def get_board_for_image(
self,

View File

@@ -1,4 +1,5 @@
import sqlite3
import threading
from typing import Union, cast
from invokeai.app.services.board_records.board_records_base import BoardRecordStorageBase
@@ -18,14 +19,20 @@ from invokeai.app.util.misc import uuid_string
class SqliteBoardRecordStorage(BoardRecordStorageBase):
_conn: sqlite3.Connection
_cursor: sqlite3.Cursor
_lock: threading.RLock
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._lock = db.lock
self._conn = db.conn
self._cursor = self._conn.cursor()
def delete(self, board_id: str) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE FROM boards
WHERE board_id = ?;
@@ -33,9 +40,14 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
(board_id,),
)
self._conn.commit()
except sqlite3.Error as e:
self._conn.rollback()
raise BoardRecordDeleteException from e
except Exception as e:
self._conn.rollback()
raise BoardRecordDeleteException from e
finally:
self._lock.release()
def save(
self,
@@ -43,8 +55,8 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
) -> BoardRecord:
try:
board_id = uuid_string()
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
INSERT OR IGNORE INTO boards (board_id, board_name)
VALUES (?, ?);
@@ -55,6 +67,8 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise BoardRecordSaveException from e
finally:
self._lock.release()
return self.get(board_id)
def get(
@@ -62,8 +76,8 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
board_id: str,
) -> BoardRecord:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT *
FROM boards
@@ -72,9 +86,12 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
(board_id,),
)
result = cast(Union[sqlite3.Row, None], cursor.fetchone())
result = cast(Union[sqlite3.Row, None], self._cursor.fetchone())
except sqlite3.Error as e:
self._conn.rollback()
raise BoardRecordNotFoundException from e
finally:
self._lock.release()
if result is None:
raise BoardRecordNotFoundException
return BoardRecord(**dict(result))
@@ -85,10 +102,11 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
changes: BoardChanges,
) -> BoardRecord:
try:
cursor = self._conn.cursor()
self._lock.acquire()
# Change the name of a board
if changes.board_name is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE boards
SET board_name = ?
@@ -99,7 +117,7 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
# Change the cover image of a board
if changes.cover_image_name is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE boards
SET cover_image_name = ?
@@ -110,7 +128,7 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
# Change the archived status of a board
if changes.archived is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE boards
SET archived = ?
@@ -123,6 +141,8 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise BoardRecordSaveException from e
finally:
self._lock.release()
return self.get(board_id)
def get_many(
@@ -133,10 +153,11 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
limit: int = 10,
include_archived: bool = False,
) -> OffsetPaginatedResults[BoardRecord]:
cursor = self._conn.cursor()
try:
self._lock.acquire()
# Build base query
base_query = """
# Build base query
base_query = """
SELECT *
FROM boards
{archived_filter}
@@ -144,67 +165,81 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
LIMIT ? OFFSET ?;
"""
# Determine archived filter condition
archived_filter = "" if include_archived else "WHERE archived = 0"
# Determine archived filter condition
archived_filter = "" if include_archived else "WHERE archived = 0"
final_query = base_query.format(
archived_filter=archived_filter, order_by=order_by.value, direction=direction.value
)
final_query = base_query.format(
archived_filter=archived_filter, order_by=order_by.value, direction=direction.value
)
# Execute query to fetch boards
cursor.execute(final_query, (limit, offset))
# Execute query to fetch boards
self._cursor.execute(final_query, (limit, offset))
result = cast(list[sqlite3.Row], cursor.fetchall())
boards = [deserialize_board_record(dict(r)) for r in result]
result = cast(list[sqlite3.Row], self._cursor.fetchall())
boards = [deserialize_board_record(dict(r)) for r in result]
# Determine count query
if include_archived:
count_query = """
# Determine count query
if include_archived:
count_query = """
SELECT COUNT(*)
FROM boards;
"""
else:
count_query = """
else:
count_query = """
SELECT COUNT(*)
FROM boards
WHERE archived = 0;
"""
# Execute count query
cursor.execute(count_query)
# Execute count query
self._cursor.execute(count_query)
count = cast(int, cursor.fetchone()[0])
count = cast(int, self._cursor.fetchone()[0])
return OffsetPaginatedResults[BoardRecord](items=boards, offset=offset, limit=limit, total=count)
return OffsetPaginatedResults[BoardRecord](items=boards, offset=offset, limit=limit, total=count)
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
def get_all(
self, order_by: BoardRecordOrderBy, direction: SQLiteDirection, include_archived: bool = False
) -> list[BoardRecord]:
cursor = self._conn.cursor()
if order_by == BoardRecordOrderBy.Name:
base_query = """
try:
self._lock.acquire()
if order_by == BoardRecordOrderBy.Name:
base_query = """
SELECT *
FROM boards
{archived_filter}
ORDER BY LOWER(board_name) {direction}
"""
else:
base_query = """
else:
base_query = """
SELECT *
FROM boards
{archived_filter}
ORDER BY {order_by} {direction}
"""
archived_filter = "" if include_archived else "WHERE archived = 0"
archived_filter = "" if include_archived else "WHERE archived = 0"
final_query = base_query.format(
archived_filter=archived_filter, order_by=order_by.value, direction=direction.value
)
final_query = base_query.format(
archived_filter=archived_filter, order_by=order_by.value, direction=direction.value
)
cursor.execute(final_query)
self._cursor.execute(final_query)
result = cast(list[sqlite3.Row], cursor.fetchall())
boards = [deserialize_board_record(dict(r)) for r in result]
result = cast(list[sqlite3.Row], self._cursor.fetchall())
boards = [deserialize_board_record(dict(r)) for r in result]
return boards
return boards
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()

View File

@@ -63,11 +63,7 @@ class BulkDownloadService(BulkDownloadBase):
return [self._invoker.services.images.get_dto(image_name) for image_name in image_names]
def _board_handler(self, board_id: str) -> list[ImageDTO]:
image_names = self._invoker.services.board_image_records.get_all_board_image_names_for_board(
board_id,
categories=None,
is_intermediate=None,
)
image_names = self._invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
return self._image_handler(image_names)
def generate_item_id(self, board_id: Optional[str]) -> str:

View File

@@ -91,7 +91,6 @@ class InvokeAIAppConfig(BaseSettings):
ram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_ram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.
vram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.
lazy_offload: DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.
pytorch_cuda_alloc_conf: Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to "backend:cudaMallocAsync" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.
device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.<br>Valid values: `auto`, `cpu`, `cuda`, `cuda:1`, `mps`
precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.<br>Valid values: `auto`, `float16`, `bfloat16`, `float32`
sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.
@@ -170,9 +169,6 @@ class InvokeAIAppConfig(BaseSettings):
vram: Optional[float] = Field(default=None, ge=0, description="DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.")
lazy_offload: bool = Field(default=True, description="DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.")
# PyTorch Memory Allocator
pytorch_cuda_alloc_conf: Optional[str] = Field(default=None, description="Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to \"backend:cudaMallocAsync\" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.")
# DEVICE
device: DEVICE = Field(default="auto", description="Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.")
precision: PRECISION = Field(default="auto", description="Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.")

View File

@@ -1,4 +1,5 @@
import sqlite3
import threading
from datetime import datetime
from typing import Optional, Union, cast
@@ -21,14 +22,21 @@ from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
class SqliteImageRecordStorage(ImageRecordStorageBase):
_conn: sqlite3.Connection
_cursor: sqlite3.Cursor
_lock: threading.RLock
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._lock = db.lock
self._conn = db.conn
self._cursor = self._conn.cursor()
def get(self, image_name: str) -> ImageRecord:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
f"""--sql
SELECT {IMAGE_DTO_COLS} FROM images
WHERE image_name = ?;
@@ -36,9 +44,12 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
(image_name,),
)
result = cast(Optional[sqlite3.Row], cursor.fetchone())
result = cast(Optional[sqlite3.Row], self._cursor.fetchone())
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordNotFoundException from e
finally:
self._lock.release()
if not result:
raise ImageRecordNotFoundException
@@ -47,8 +58,9 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
def get_metadata(self, image_name: str) -> Optional[MetadataField]:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT metadata FROM images
WHERE image_name = ?;
@@ -56,7 +68,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
(image_name,),
)
result = cast(Optional[sqlite3.Row], cursor.fetchone())
result = cast(Optional[sqlite3.Row], self._cursor.fetchone())
if not result:
raise ImageRecordNotFoundException
@@ -65,7 +77,10 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
metadata_raw = cast(Optional[str], as_dict.get("metadata", None))
return MetadataFieldValidator.validate_json(metadata_raw) if metadata_raw is not None else None
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordNotFoundException from e
finally:
self._lock.release()
def update(
self,
@@ -73,10 +88,10 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
changes: ImageRecordChanges,
) -> None:
try:
cursor = self._conn.cursor()
self._lock.acquire()
# Change the category of the image
if changes.image_category is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE images
SET image_category = ?
@@ -87,7 +102,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the session associated with the image
if changes.session_id is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE images
SET session_id = ?
@@ -98,7 +113,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the image's `is_intermediate`` flag
if changes.is_intermediate is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE images
SET is_intermediate = ?
@@ -109,7 +124,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the image's `starred`` state
if changes.starred is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE images
SET starred = ?
@@ -122,6 +137,8 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordSaveException from e
finally:
self._lock.release()
def get_many(
self,
@@ -135,104 +152,110 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
board_id: Optional[str] = None,
search_term: Optional[str] = None,
) -> OffsetPaginatedResults[ImageRecord]:
cursor = self._conn.cursor()
try:
self._lock.acquire()
# Manually build two queries - one for the count, one for the records
count_query = """--sql
SELECT COUNT(*)
FROM images
LEFT JOIN board_images ON board_images.image_name = images.image_name
WHERE 1=1
"""
images_query = f"""--sql
SELECT {IMAGE_DTO_COLS}
FROM images
LEFT JOIN board_images ON board_images.image_name = images.image_name
WHERE 1=1
"""
query_conditions = ""
query_params: list[Union[int, str, bool]] = []
if image_origin is not None:
query_conditions += """--sql
AND images.image_origin = ?
"""
query_params.append(image_origin.value)
if categories is not None:
# Convert the enum values to unique list of strings
category_strings = [c.value for c in set(categories)]
# Create the correct length of placeholders
placeholders = ",".join("?" * len(category_strings))
query_conditions += f"""--sql
AND images.image_category IN ( {placeholders} )
# Manually build two queries - one for the count, one for the records
count_query = """--sql
SELECT COUNT(*)
FROM images
LEFT JOIN board_images ON board_images.image_name = images.image_name
WHERE 1=1
"""
# Unpack the included categories into the query params
for c in category_strings:
query_params.append(c)
if is_intermediate is not None:
query_conditions += """--sql
AND images.is_intermediate = ?
images_query = f"""--sql
SELECT {IMAGE_DTO_COLS}
FROM images
LEFT JOIN board_images ON board_images.image_name = images.image_name
WHERE 1=1
"""
query_params.append(is_intermediate)
query_conditions = ""
query_params: list[Union[int, str, bool]] = []
# board_id of "none" is reserved for images without a board
if board_id == "none":
query_conditions += """--sql
AND board_images.board_id IS NULL
"""
elif board_id is not None:
query_conditions += """--sql
AND board_images.board_id = ?
"""
query_params.append(board_id)
if image_origin is not None:
query_conditions += """--sql
AND images.image_origin = ?
"""
query_params.append(image_origin.value)
# Search term condition
if search_term:
query_conditions += """--sql
AND images.metadata LIKE ?
"""
query_params.append(f"%{search_term.lower()}%")
if categories is not None:
# Convert the enum values to unique list of strings
category_strings = [c.value for c in set(categories)]
# Create the correct length of placeholders
placeholders = ",".join("?" * len(category_strings))
if starred_first:
query_pagination = f"""--sql
ORDER BY images.starred DESC, images.created_at {order_dir.value} LIMIT ? OFFSET ?
"""
else:
query_pagination = f"""--sql
ORDER BY images.created_at {order_dir.value} LIMIT ? OFFSET ?
"""
query_conditions += f"""--sql
AND images.image_category IN ( {placeholders} )
"""
# Final images query with pagination
images_query += query_conditions + query_pagination + ";"
# Add all the parameters
images_params = query_params.copy()
# Add the pagination parameters
images_params.extend([limit, offset])
# Unpack the included categories into the query params
for c in category_strings:
query_params.append(c)
# Build the list of images, deserializing each row
cursor.execute(images_query, images_params)
result = cast(list[sqlite3.Row], cursor.fetchall())
images = [deserialize_image_record(dict(r)) for r in result]
if is_intermediate is not None:
query_conditions += """--sql
AND images.is_intermediate = ?
"""
# Set up and execute the count query, without pagination
count_query += query_conditions + ";"
count_params = query_params.copy()
cursor.execute(count_query, count_params)
count = cast(int, cursor.fetchone()[0])
query_params.append(is_intermediate)
# board_id of "none" is reserved for images without a board
if board_id == "none":
query_conditions += """--sql
AND board_images.board_id IS NULL
"""
elif board_id is not None:
query_conditions += """--sql
AND board_images.board_id = ?
"""
query_params.append(board_id)
# Search term condition
if search_term:
query_conditions += """--sql
AND images.metadata LIKE ?
"""
query_params.append(f"%{search_term.lower()}%")
if starred_first:
query_pagination = f"""--sql
ORDER BY images.starred DESC, images.created_at {order_dir.value} LIMIT ? OFFSET ?
"""
else:
query_pagination = f"""--sql
ORDER BY images.created_at {order_dir.value} LIMIT ? OFFSET ?
"""
# Final images query with pagination
images_query += query_conditions + query_pagination + ";"
# Add all the parameters
images_params = query_params.copy()
# Add the pagination parameters
images_params.extend([limit, offset])
# Build the list of images, deserializing each row
self._cursor.execute(images_query, images_params)
result = cast(list[sqlite3.Row], self._cursor.fetchall())
images = [deserialize_image_record(dict(r)) for r in result]
# Set up and execute the count query, without pagination
count_query += query_conditions + ";"
count_params = query_params.copy()
self._cursor.execute(count_query, count_params)
count = cast(int, self._cursor.fetchone()[0])
except sqlite3.Error as e:
self._conn.rollback()
raise e
finally:
self._lock.release()
return OffsetPaginatedResults(items=images, offset=offset, limit=limit, total=count)
def delete(self, image_name: str) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE FROM images
WHERE image_name = ?;
@@ -243,48 +266,58 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordDeleteException from e
finally:
self._lock.release()
def delete_many(self, image_names: list[str]) -> None:
try:
cursor = self._conn.cursor()
placeholders = ",".join("?" for _ in image_names)
self._lock.acquire()
# Construct the SQLite query with the placeholders
query = f"DELETE FROM images WHERE image_name IN ({placeholders})"
# Execute the query with the list of IDs as parameters
cursor.execute(query, image_names)
self._cursor.execute(query, image_names)
self._conn.commit()
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordDeleteException from e
finally:
self._lock.release()
def get_intermediates_count(self) -> int:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT COUNT(*) FROM images
WHERE is_intermediate = TRUE;
"""
)
count = cast(int, cursor.fetchone()[0])
self._conn.commit()
return count
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT COUNT(*) FROM images
WHERE is_intermediate = TRUE;
"""
)
count = cast(int, self._cursor.fetchone()[0])
self._conn.commit()
return count
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordDeleteException from e
finally:
self._lock.release()
def delete_intermediates(self) -> list[str]:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT image_name FROM images
WHERE is_intermediate = TRUE;
"""
)
result = cast(list[sqlite3.Row], cursor.fetchall())
result = cast(list[sqlite3.Row], self._cursor.fetchall())
image_names = [r[0] for r in result]
cursor.execute(
self._cursor.execute(
"""--sql
DELETE FROM images
WHERE is_intermediate = TRUE;
@@ -295,6 +328,8 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordDeleteException from e
finally:
self._lock.release()
def save(
self,
@@ -311,8 +346,8 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
metadata: Optional[str] = None,
) -> datetime:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
INSERT OR IGNORE INTO images (
image_name,
@@ -345,7 +380,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
)
self._conn.commit()
cursor.execute(
self._cursor.execute(
"""--sql
SELECT created_at
FROM images
@@ -354,30 +389,34 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
(image_name,),
)
created_at = datetime.fromisoformat(cursor.fetchone()[0])
created_at = datetime.fromisoformat(self._cursor.fetchone()[0])
return created_at
except sqlite3.Error as e:
self._conn.rollback()
raise ImageRecordSaveException from e
finally:
self._lock.release()
def get_most_recent_image_for_board(self, board_id: str) -> Optional[ImageRecord]:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT images.*
FROM images
JOIN board_images ON images.image_name = board_images.image_name
WHERE board_images.board_id = ?
AND images.is_intermediate = FALSE
ORDER BY images.starred DESC, images.created_at DESC
LIMIT 1;
""",
(board_id,),
)
result = cast(Optional[sqlite3.Row], cursor.fetchone())
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT images.*
FROM images
JOIN board_images ON images.image_name = board_images.image_name
WHERE board_images.board_id = ?
AND images.is_intermediate = FALSE
ORDER BY images.starred DESC, images.created_at DESC
LIMIT 1;
""",
(board_id,),
)
result = cast(Optional[sqlite3.Row], self._cursor.fetchone())
finally:
self._lock.release()
if result is None:
return None

View File

@@ -265,11 +265,7 @@ class ImageService(ImageServiceABC):
def delete_images_on_board(self, board_id: str):
try:
image_names = self.__invoker.services.board_image_records.get_all_board_image_names_for_board(
board_id,
categories=None,
is_intermediate=None,
)
image_names = self.__invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
for image_name in image_names:
self.__invoker.services.image_files.delete(image_name)
self.__invoker.services.image_records.delete_many(image_names)
@@ -282,7 +278,7 @@ class ImageService(ImageServiceABC):
self.__invoker.services.logger.error("Failed to delete image files")
raise
except Exception as e:
self.__invoker.services.logger.error(f"Problem deleting image records and files: {str(e)}")
self.__invoker.services.logger.error("Problem deleting image records and files")
raise e
def delete_intermediates(self) -> int:

View File

@@ -78,6 +78,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
"""
super().__init__()
self._db = db
self._cursor = db.conn.cursor()
self._logger = logger
@property
@@ -95,38 +96,38 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
Can raise DuplicateModelException and InvalidModelConfigException exceptions.
"""
try:
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
INSERT INTO models (
id,
config
)
VALUES (?,?);
""",
(
config.key,
config.model_dump_json(),
),
)
self._db.conn.commit()
with self._db.lock:
try:
self._cursor.execute(
"""--sql
INSERT INTO models (
id,
config
)
VALUES (?,?);
""",
(
config.key,
config.model_dump_json(),
),
)
self._db.conn.commit()
except sqlite3.IntegrityError as e:
self._db.conn.rollback()
if "UNIQUE constraint failed" in str(e):
if "models.path" in str(e):
msg = f"A model with path '{config.path}' is already installed"
elif "models.name" in str(e):
msg = f"A model with name='{config.name}', type='{config.type}', base='{config.base}' is already installed"
except sqlite3.IntegrityError as e:
self._db.conn.rollback()
if "UNIQUE constraint failed" in str(e):
if "models.path" in str(e):
msg = f"A model with path '{config.path}' is already installed"
elif "models.name" in str(e):
msg = f"A model with name='{config.name}', type='{config.type}', base='{config.base}' is already installed"
else:
msg = f"A model with key '{config.key}' is already installed"
raise DuplicateModelException(msg) from e
else:
msg = f"A model with key '{config.key}' is already installed"
raise DuplicateModelException(msg) from e
else:
raise e
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
return self.get_model(config.key)
@@ -138,21 +139,21 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
Can raise an UnknownModelException
"""
try:
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
DELETE FROM models
WHERE id=?;
""",
(key,),
)
if cursor.rowcount == 0:
raise UnknownModelException("model not found")
self._db.conn.commit()
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
with self._db.lock:
try:
self._cursor.execute(
"""--sql
DELETE FROM models
WHERE id=?;
""",
(key,),
)
if self._cursor.rowcount == 0:
raise UnknownModelException("model not found")
self._db.conn.commit()
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
def update_model(self, key: str, changes: ModelRecordChanges) -> AnyModelConfig:
record = self.get_model(key)
@@ -163,23 +164,23 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
json_serialized = record.model_dump_json()
try:
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
UPDATE models
SET
config=?
WHERE id=?;
""",
(json_serialized, key),
)
if cursor.rowcount == 0:
raise UnknownModelException("model not found")
self._db.conn.commit()
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
with self._db.lock:
try:
self._cursor.execute(
"""--sql
UPDATE models
SET
config=?
WHERE id=?;
""",
(json_serialized, key),
)
if self._cursor.rowcount == 0:
raise UnknownModelException("model not found")
self._db.conn.commit()
except sqlite3.Error as e:
self._db.conn.rollback()
raise e
return self.get_model(key)
@@ -191,33 +192,33 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
Exceptions: UnknownModelException
"""
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE id=?;
""",
(key,),
)
rows = cursor.fetchone()
if not rows:
raise UnknownModelException("model not found")
model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
with self._db.lock:
self._cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE id=?;
""",
(key,),
)
rows = self._cursor.fetchone()
if not rows:
raise UnknownModelException("model not found")
model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
return model
def get_model_by_hash(self, hash: str) -> AnyModelConfig:
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE hash=?;
""",
(hash,),
)
rows = cursor.fetchone()
if not rows:
raise UnknownModelException("model not found")
model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
with self._db.lock:
self._cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE hash=?;
""",
(hash,),
)
rows = self._cursor.fetchone()
if not rows:
raise UnknownModelException("model not found")
model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
return model
def exists(self, key: str) -> bool:
@@ -226,15 +227,16 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
:param key: Unique key for the model to be deleted
"""
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
select count(*) FROM models
WHERE id=?;
""",
(key,),
)
count = cursor.fetchone()[0]
count = 0
with self._db.lock:
self._cursor.execute(
"""--sql
select count(*) FROM models
WHERE id=?;
""",
(key,),
)
count = self._cursor.fetchone()[0]
return count > 0
def search_by_attr(
@@ -282,18 +284,17 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
where_clause.append("format=?")
bindings.append(model_format)
where = f"WHERE {' AND '.join(where_clause)}" if where_clause else ""
cursor = self._db.conn.cursor()
cursor.execute(
f"""--sql
SELECT config, strftime('%s',updated_at)
FROM models
{where}
ORDER BY {ordering[order_by]} -- using ? to bind doesn't work here for some reason;
""",
tuple(bindings),
)
result = cursor.fetchall()
with self._db.lock:
self._cursor.execute(
f"""--sql
SELECT config, strftime('%s',updated_at)
FROM models
{where}
ORDER BY {ordering[order_by]} -- using ? to bind doesn't work here for some reason;
""",
tuple(bindings),
)
result = self._cursor.fetchall()
# Parse the model configs.
results: list[AnyModelConfig] = []
@@ -312,28 +313,34 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
def search_by_path(self, path: Union[str, Path]) -> List[AnyModelConfig]:
"""Return models with the indicated path."""
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE path=?;
""",
(str(path),),
)
results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in cursor.fetchall()]
results = []
with self._db.lock:
self._cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE path=?;
""",
(str(path),),
)
results = [
ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()
]
return results
def search_by_hash(self, hash: str) -> List[AnyModelConfig]:
"""Return models with the indicated hash."""
cursor = self._db.conn.cursor()
cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE hash=?;
""",
(hash,),
)
results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in cursor.fetchall()]
results = []
with self._db.lock:
self._cursor.execute(
"""--sql
SELECT config, strftime('%s',updated_at) FROM models
WHERE hash=?;
""",
(hash,),
)
results = [
ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()
]
return results
def list_models(
@@ -349,32 +356,33 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
ModelRecordOrderBy.Format: "format",
}
cursor = self._db.conn.cursor()
# Lock so that the database isn't updated while we're doing the two queries.
# query1: get the total number of model configs
cursor.execute(
"""--sql
select count(*) from models;
""",
(),
)
total = int(cursor.fetchone()[0])
with self._db.lock:
# query1: get the total number of model configs
self._cursor.execute(
"""--sql
select count(*) from models;
""",
(),
)
total = int(self._cursor.fetchone()[0])
# query2: fetch key fields
cursor.execute(
f"""--sql
SELECT config
FROM models
ORDER BY {ordering[order_by]} -- using ? to bind doesn't work here for some reason
LIMIT ?
OFFSET ?;
""",
(
per_page,
page * per_page,
),
)
rows = cursor.fetchall()
items = [ModelSummary.model_validate(dict(x)) for x in rows]
return PaginatedResults(page=page, pages=ceil(total / per_page), per_page=per_page, total=total, items=items)
# query2: fetch key fields
self._cursor.execute(
f"""--sql
SELECT config
FROM models
ORDER BY {ordering[order_by]} -- using ? to bind doesn't work here for some reason
LIMIT ?
OFFSET ?;
""",
(
per_page,
page * per_page,
),
)
rows = self._cursor.fetchall()
items = [ModelSummary.model_validate(dict(x)) for x in rows]
return PaginatedResults(
page=page, pages=ceil(total / per_page), per_page=per_page, total=total, items=items
)

View File

@@ -1,5 +1,5 @@
from abc import ABC, abstractmethod
from typing import Any, Coroutine, Optional
from typing import Optional
from invokeai.app.services.session_queue.session_queue_common import (
QUEUE_ITEM_STATUS,
@@ -33,7 +33,7 @@ class SessionQueueBase(ABC):
pass
@abstractmethod
def enqueue_batch(self, queue_id: str, batch: Batch, prepend: bool) -> Coroutine[Any, Any, EnqueueBatchResult]:
def enqueue_batch(self, queue_id: str, batch: Batch, prepend: bool) -> EnqueueBatchResult:
"""Enqueues all permutations of a batch for execution."""
pass

View File

@@ -1,7 +1,7 @@
import datetime
import json
from itertools import chain, product
from typing import Generator, Literal, Optional, TypeAlias, Union, cast
from typing import Generator, Iterable, Literal, NamedTuple, Optional, TypeAlias, Union, cast
from pydantic import (
AliasChoices,
@@ -406,143 +406,61 @@ class IsFullResult(BaseModel):
# region Util
def create_session_nfv_tuples(batch: Batch, maximum: int) -> Generator[tuple[str, str, str], None, None]:
def populate_graph(graph: Graph, node_field_values: Iterable[NodeFieldValue]) -> Graph:
"""
Given a batch and a maximum number of sessions to create, generate a tuple of session_id, session_json, and
field_values_json for each session.
Populates the given graph with the given batch data items.
"""
graph_clone = graph.model_copy(deep=True)
for item in node_field_values:
node = graph_clone.get_node(item.node_path)
if node is None:
continue
setattr(node, item.field_name, item.value)
graph_clone.update_node(item.node_path, node)
return graph_clone
The batch has a "source" graph and a data property. The data property is a list of lists of BatchDatum objects.
Each BatchDatum has a field identifier (e.g. a node id and field name), and a list of values to substitute into
the field.
This structure allows us to create a new graph for every possible permutation of BatchDatum objects:
- Each BatchDatum can be "expanded" into a dict of node-field-value tuples - one for each item in the BatchDatum.
- Zip each inner list of expanded BatchDatum objects together. Call this a "batch_data_list".
- Take the cartesian product of all zipped batch_data_lists, resulting in a list of permutations of BatchDatum
- Take the cartesian product of all zipped batch_data_lists, resulting in a list of lists of BatchDatum objects.
Each inner list now represents the substitution values for a single permutation (session).
- For each permutation, substitute the values into the graph
This function is optimized for performance, as it is used to generate a large number of sessions at once.
Args:
batch: The batch to generate sessions from
maximum: The maximum number of sessions to generate
Returns:
A generator that yields tuples of session_id, session_json, and field_values_json for each session. The
generator will stop early if the maximum number of sessions is reached.
def create_session_nfv_tuples(
batch: Batch, maximum: int
) -> Generator[tuple[GraphExecutionState, list[NodeFieldValue], Optional[WorkflowWithoutID]], None, None]:
"""
Create all graph permutations from the given batch data and graph. Yields tuples
of the form (graph, batch_data_items) where batch_data_items is the list of BatchDataItems
that was applied to the graph.
"""
# TODO: Should this be a class method on Batch?
data: list[list[tuple[dict]]] = []
data: list[list[tuple[NodeFieldValue]]] = []
batch_data_collection = batch.data if batch.data is not None else []
for batch_datum_list in batch_data_collection:
node_field_values_to_zip: list[list[dict]] = []
# Expand each BatchDatum into a list of dicts - one for each item in the BatchDatum
# each batch_datum_list needs to be convered to NodeFieldValues and then zipped
node_field_values_to_zip: list[list[NodeFieldValue]] = []
for batch_datum in batch_datum_list:
node_field_values = [
# Note: A tuple here is slightly faster than a dict, but we need the object in dict form to be inserted
# in the session_queue table anyways. So, overall creating NFVs as dicts is faster.
{"node_path": batch_datum.node_path, "field_name": batch_datum.field_name, "value": item}
NodeFieldValue(node_path=batch_datum.node_path, field_name=batch_datum.field_name, value=item)
for item in batch_datum.items
]
node_field_values_to_zip.append(node_field_values)
# Zip the dicts together to create a list of dicts for each permutation
data.append(list(zip(*node_field_values_to_zip, strict=True))) # type: ignore [arg-type]
# We serialize the graph and session once, then mutate the graph dict in place for each session.
#
# This sounds scary, but it's actually fine.
#
# The batch prep logic injects field values into the same fields for each generated session.
#
# For example, after the product operation, we'll end up with a list of node-field-value tuples like this:
# [
# (
# {"node_path": "1", "field_name": "a", "value": 1},
# {"node_path": "2", "field_name": "b", "value": 2},
# {"node_path": "3", "field_name": "c", "value": 3},
# ),
# (
# {"node_path": "1", "field_name": "a", "value": 4},
# {"node_path": "2", "field_name": "b", "value": 5},
# {"node_path": "3", "field_name": "c", "value": 6},
# )
# ]
#
# Note that each tuple has the same length, and each tuple substitutes values in for exactly the same node fields.
# No matter the complexity of the batch, this property holds true.
#
# This means each permutation's substitution can be done in-place on the same graph dict, because it overwrites the
# previous mutation. We only need to serialize the graph once, and then we can mutate it in place for each session.
#
# Previously, we had created new Graph objects for each session, but this was very slow for large (1k+ session
# batches). We then tried dumping the graph to dict and using deep-copy to create a new dict for each session,
# but this was also slow.
#
# Overall, we achieved a 100x speedup by mutating the graph dict in place for each session over creating new Graph
# objects for each session.
#
# We will also mutate the session dict in place, setting a new ID for each session and setting the mutated graph
# dict as the session's graph.
# Dump the batch's graph to a dict once
graph_as_dict = batch.graph.model_dump(warnings=False, exclude_none=True)
# We must provide a Graph object when creating the "dummy" session dict, but we don't actually use it. It will be
# overwritten for each session by the mutated graph_as_dict.
session_dict = GraphExecutionState(graph=Graph()).model_dump(warnings=False, exclude_none=True)
# Now we can create a generator that yields the session_id, session_json, and field_values_json for each session.
# create generator to yield session,nfv tuples
count = 0
# Each batch may have multiple runs, so we need to generate the same number of sessions for each run. The total is
# still limited by the maximum number of sessions.
for _ in range(batch.runs):
for d in product(*data):
if count >= maximum:
# We've reached the maximum number of sessions we may generate
return
# Flatten the list of lists of dicts into a single list of dicts
# TODO(psyche): Is the a more efficient way to do this?
flat_node_field_values = list(chain.from_iterable(d))
# Need a fresh ID for each session
session_id = uuid_string()
# Mutate the session dict in place
session_dict["id"] = session_id
# Substitute the values into the graph
for nfv in flat_node_field_values:
graph_as_dict["nodes"][nfv["node_path"]][nfv["field_name"]] = nfv["value"]
# Mutate the session dict in place
session_dict["graph"] = graph_as_dict
# Serialize the session and field values
# Note the use of pydantic's to_jsonable_python to handle serialization of any python object, including sets.
session_json = json.dumps(session_dict, default=to_jsonable_python)
field_values_json = json.dumps(flat_node_field_values, default=to_jsonable_python)
# Yield the session_id, session_json, and field_values_json
yield (session_id, session_json, field_values_json)
# Increment the count so we know when to stop
graph = populate_graph(batch.graph, flat_node_field_values)
yield (GraphExecutionState(graph=graph), flat_node_field_values, batch.workflow)
count += 1
def calc_session_count(batch: Batch) -> int:
"""
Calculates the number of sessions that would be created by the batch, without incurring the overhead of actually
creating them, as is done in `create_session_nfv_tuples()`.
The count is used to communicate to the user how many sessions were _requested_ to be created, as opposed to how
many were _actually_ created (which may be less due to the maximum number of sessions).
Calculates the number of sessions that would be created by the batch, without incurring
the overhead of actually generating them. Adapted from `create_sessions().
"""
# TODO: Should this be a class method on Batch?
if not batch.data:
@@ -558,75 +476,42 @@ def calc_session_count(batch: Batch) -> int:
return len(data_product) * batch.runs
ValueToInsertTuple: TypeAlias = tuple[
str, # queue_id
str, # session (as stringified JSON)
str, # session_id
str, # batch_id
str | None, # field_values (optional, as stringified JSON)
int, # priority
str | None, # workflow (optional, as stringified JSON)
str | None, # origin (optional)
str | None, # destination (optional)
int | None, # retried_from_item_id (optional, this is always None for new items)
]
"""A type alias for the tuple of values to insert into the session queue table."""
class SessionQueueValueToInsert(NamedTuple):
"""A tuple of values to insert into the session_queue table"""
# Careful with the ordering of this - it must match the insert statement
queue_id: str # queue_id
session: str # session json
session_id: str # session_id
batch_id: str # batch_id
field_values: Optional[str] # field_values json
priority: int # priority
workflow: Optional[str] # workflow json
origin: str | None
destination: str | None
retried_from_item_id: int | None = None
def prepare_values_to_insert(
queue_id: str, batch: Batch, priority: int, max_new_queue_items: int
) -> list[ValueToInsertTuple]:
"""
Given a batch, prepare the values to insert into the session queue table. The list of tuples can be used with an
`executemany` statement to insert multiple rows at once.
ValuesToInsert: TypeAlias = list[SessionQueueValueToInsert]
Args:
queue_id: The ID of the queue to insert the items into
batch: The batch to prepare the values for
priority: The priority of the queue items
max_new_queue_items: The maximum number of queue items to insert
Returns:
A list of tuples to insert into the session queue table. Each tuple contains the following values:
- queue_id
- session (as stringified JSON)
- session_id
- batch_id
- field_values (optional, as stringified JSON)
- priority
- workflow (optional, as stringified JSON)
- origin (optional)
- destination (optional)
- retried_from_item_id (optional, this is always None for new items)
"""
# A tuple is a fast and memory-efficient way to store the values to insert. Previously, we used a NamedTuple, but
# measured a ~5% performance improvement by using a normal tuple instead. For very large batches (10k+ items), the
# this difference becomes noticeable.
#
# So, despite the inferior DX with normal tuples, we use one here for performance reasons.
values_to_insert: list[ValueToInsertTuple] = []
# pydantic's to_jsonable_python handles serialization of any python object, including sets, which json.dumps does
# not support by default. Apparently there are sets somewhere in the graph.
# The same workflow is used for all sessions in the batch - serialize it once
workflow_json = json.dumps(batch.workflow, default=to_jsonable_python) if batch.workflow else None
for session_id, session_json, field_values_json in create_session_nfv_tuples(batch, max_new_queue_items):
def prepare_values_to_insert(queue_id: str, batch: Batch, priority: int, max_new_queue_items: int) -> ValuesToInsert:
values_to_insert: ValuesToInsert = []
for session, field_values, workflow in create_session_nfv_tuples(batch, max_new_queue_items):
# sessions must have unique id
session.id = uuid_string()
values_to_insert.append(
(
queue_id,
session_json,
session_id,
batch.batch_id,
field_values_json,
priority,
workflow_json,
batch.origin,
batch.destination,
None,
SessionQueueValueToInsert(
queue_id=queue_id,
session=session.model_dump_json(warnings=False, exclude_none=True), # as json
session_id=session.id,
batch_id=batch.batch_id,
# must use pydantic_encoder bc field_values is a list of models
field_values=json.dumps(field_values, default=to_jsonable_python) if field_values else None, # as json
priority=priority,
workflow=json.dumps(workflow, default=to_jsonable_python) if workflow else None, # as json
origin=batch.origin,
destination=batch.destination,
)
)
return values_to_insert

View File

@@ -1,6 +1,6 @@
import asyncio
import json
import sqlite3
import threading
from typing import Optional, Union, cast
from pydantic_core import to_jsonable_python
@@ -27,6 +27,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
SessionQueueItemDTO,
SessionQueueItemNotFoundError,
SessionQueueStatus,
SessionQueueValueToInsert,
calc_session_count,
prepare_values_to_insert,
)
@@ -37,6 +38,9 @@ from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
class SqliteSessionQueue(SessionQueueBase):
__invoker: Invoker
__conn: sqlite3.Connection
__cursor: sqlite3.Cursor
__lock: threading.RLock
def start(self, invoker: Invoker) -> None:
self.__invoker = invoker
@@ -52,7 +56,9 @@ class SqliteSessionQueue(SessionQueueBase):
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._conn = db.conn
self.__lock = db.lock
self.__conn = db.conn
self.__cursor = self.__conn.cursor()
def _set_in_progress_to_canceled(self) -> None:
"""
@@ -60,8 +66,8 @@ class SqliteSessionQueue(SessionQueueBase):
This is necessary because the invoker may have been killed while processing a queue item.
"""
try:
cursor = self._conn.cursor()
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
"""--sql
UPDATE session_queue
SET status = 'canceled'
@@ -69,13 +75,14 @@ class SqliteSessionQueue(SessionQueueBase):
"""
)
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
def _get_current_queue_size(self, queue_id: str) -> int:
"""Gets the current number of pending queue items"""
cursor = self._conn.cursor()
cursor.execute(
self.__cursor.execute(
"""--sql
SELECT count(*)
FROM session_queue
@@ -85,12 +92,11 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
return cast(int, cursor.fetchone()[0])
return cast(int, self.__cursor.fetchone()[0])
def _get_highest_priority(self, queue_id: str) -> int:
"""Gets the highest priority value in the queue"""
cursor = self._conn.cursor()
cursor.execute(
self.__cursor.execute(
"""--sql
SELECT MAX(priority)
FROM session_queue
@@ -100,14 +106,12 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
return cast(Union[int, None], cursor.fetchone()[0]) or 0
return cast(Union[int, None], self.__cursor.fetchone()[0]) or 0
async def enqueue_batch(self, queue_id: str, batch: Batch, prepend: bool) -> EnqueueBatchResult:
return await asyncio.to_thread(self._enqueue_batch, queue_id, batch, prepend)
def _enqueue_batch(self, queue_id: str, batch: Batch, prepend: bool) -> EnqueueBatchResult:
def enqueue_batch(self, queue_id: str, batch: Batch, prepend: bool) -> EnqueueBatchResult:
try:
cursor = self._conn.cursor()
self.__lock.acquire()
# TODO: how does this work in a multi-user scenario?
current_queue_size = self._get_current_queue_size(queue_id)
max_queue_size = self.__invoker.services.configuration.max_queue_size
@@ -129,17 +133,19 @@ class SqliteSessionQueue(SessionQueueBase):
if requested_count > enqueued_count:
values_to_insert = values_to_insert[:max_new_queue_items]
cursor.executemany(
self.__cursor.executemany(
"""--sql
INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow, origin, destination, retried_from_item_id)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
values_to_insert,
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
enqueue_result = EnqueueBatchResult(
queue_id=queue_id,
requested=requested_count,
@@ -151,19 +157,25 @@ class SqliteSessionQueue(SessionQueueBase):
return enqueue_result
def dequeue(self) -> Optional[SessionQueueItem]:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE status = 'pending'
ORDER BY
priority DESC,
item_id ASC
LIMIT 1
"""
)
result = cast(Union[sqlite3.Row, None], cursor.fetchone())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE status = 'pending'
ORDER BY
priority DESC,
item_id ASC
LIMIT 1
"""
)
result = cast(Union[sqlite3.Row, None], self.__cursor.fetchone())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
if result is None:
return None
queue_item = SessionQueueItem.queue_item_from_dict(dict(result))
@@ -171,40 +183,52 @@ class SqliteSessionQueue(SessionQueueBase):
return queue_item
def get_next(self, queue_id: str) -> Optional[SessionQueueItem]:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE
queue_id = ?
AND status = 'pending'
ORDER BY
priority DESC,
created_at ASC
LIMIT 1
""",
(queue_id,),
)
result = cast(Union[sqlite3.Row, None], cursor.fetchone())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE
queue_id = ?
AND status = 'pending'
ORDER BY
priority DESC,
created_at ASC
LIMIT 1
""",
(queue_id,),
)
result = cast(Union[sqlite3.Row, None], self.__cursor.fetchone())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
if result is None:
return None
return SessionQueueItem.queue_item_from_dict(dict(result))
def get_current(self, queue_id: str) -> Optional[SessionQueueItem]:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE
queue_id = ?
AND status = 'in_progress'
LIMIT 1
""",
(queue_id,),
)
result = cast(Union[sqlite3.Row, None], cursor.fetchone())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT *
FROM session_queue
WHERE
queue_id = ?
AND status = 'in_progress'
LIMIT 1
""",
(queue_id,),
)
result = cast(Union[sqlite3.Row, None], self.__cursor.fetchone())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
if result is None:
return None
return SessionQueueItem.queue_item_from_dict(dict(result))
@@ -218,8 +242,8 @@ class SqliteSessionQueue(SessionQueueBase):
error_traceback: Optional[str] = None,
) -> SessionQueueItem:
try:
cursor = self._conn.cursor()
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
"""--sql
UPDATE session_queue
SET status = ?, error_type = ?, error_message = ?, error_traceback = ?
@@ -227,10 +251,12 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(status, error_type, error_message, error_traceback, item_id),
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
queue_item = self.get_queue_item(item_id)
batch_status = self.get_batch_status(queue_id=queue_item.queue_id, batch_id=queue_item.batch_id)
queue_status = self.get_queue_status(queue_id=queue_item.queue_id)
@@ -238,36 +264,48 @@ class SqliteSessionQueue(SessionQueueBase):
return queue_item
def is_empty(self, queue_id: str) -> IsEmptyResult:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT count(*)
FROM session_queue
WHERE queue_id = ?
""",
(queue_id,),
)
is_empty = cast(int, cursor.fetchone()[0]) == 0
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT count(*)
FROM session_queue
WHERE queue_id = ?
""",
(queue_id,),
)
is_empty = cast(int, self.__cursor.fetchone()[0]) == 0
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
return IsEmptyResult(is_empty=is_empty)
def is_full(self, queue_id: str) -> IsFullResult:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT count(*)
FROM session_queue
WHERE queue_id = ?
""",
(queue_id,),
)
max_queue_size = self.__invoker.services.configuration.max_queue_size
is_full = cast(int, cursor.fetchone()[0]) >= max_queue_size
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT count(*)
FROM session_queue
WHERE queue_id = ?
""",
(queue_id,),
)
max_queue_size = self.__invoker.services.configuration.max_queue_size
is_full = cast(int, self.__cursor.fetchone()[0]) >= max_queue_size
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
return IsFullResult(is_full=is_full)
def clear(self, queue_id: str) -> ClearResult:
try:
cursor = self._conn.cursor()
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -275,8 +313,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
"""--sql
DELETE
FROM session_queue
@@ -284,16 +322,17 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
self.__invoker.services.events.emit_queue_cleared(queue_id)
return ClearResult(deleted=count)
def prune(self, queue_id: str) -> PruneResult:
try:
cursor = self._conn.cursor()
where = """--sql
WHERE
queue_id = ?
@@ -303,7 +342,8 @@ class SqliteSessionQueue(SessionQueueBase):
OR status = 'canceled'
)
"""
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -311,8 +351,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
DELETE
FROM session_queue
@@ -320,10 +360,12 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return PruneResult(deleted=count)
def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
@@ -352,8 +394,8 @@ class SqliteSessionQueue(SessionQueueBase):
def cancel_by_batch_ids(self, queue_id: str, batch_ids: list[str]) -> CancelByBatchIDsResult:
try:
cursor = self._conn.cursor()
current_queue_item = self.get_current(queue_id)
self.__lock.acquire()
placeholders = ", ".join(["?" for _ in batch_ids])
where = f"""--sql
WHERE
@@ -364,7 +406,7 @@ class SqliteSessionQueue(SessionQueueBase):
AND status != 'failed'
"""
params = [queue_id] + batch_ids
cursor.execute(
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -372,8 +414,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
tuple(params),
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
UPDATE session_queue
SET status = 'canceled'
@@ -381,18 +423,20 @@ class SqliteSessionQueue(SessionQueueBase):
""",
tuple(params),
)
self._conn.commit()
self.__conn.commit()
if current_queue_item is not None and current_queue_item.batch_id in batch_ids:
self._set_queue_item_status(current_queue_item.item_id, "canceled")
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CancelByBatchIDsResult(canceled=count)
def cancel_by_destination(self, queue_id: str, destination: str) -> CancelByDestinationResult:
try:
cursor = self._conn.cursor()
current_queue_item = self.get_current(queue_id)
self.__lock.acquire()
where = """--sql
WHERE
queue_id == ?
@@ -402,7 +446,7 @@ class SqliteSessionQueue(SessionQueueBase):
AND status != 'failed'
"""
params = (queue_id, destination)
cursor.execute(
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -410,8 +454,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
params,
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
UPDATE session_queue
SET status = 'canceled'
@@ -419,18 +463,20 @@ class SqliteSessionQueue(SessionQueueBase):
""",
params,
)
self._conn.commit()
self.__conn.commit()
if current_queue_item is not None and current_queue_item.destination == destination:
self._set_queue_item_status(current_queue_item.item_id, "canceled")
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CancelByDestinationResult(canceled=count)
def cancel_by_queue_id(self, queue_id: str) -> CancelByQueueIDResult:
try:
cursor = self._conn.cursor()
current_queue_item = self.get_current(queue_id)
self.__lock.acquire()
where = """--sql
WHERE
queue_id is ?
@@ -439,7 +485,7 @@ class SqliteSessionQueue(SessionQueueBase):
AND status != 'failed'
"""
params = [queue_id]
cursor.execute(
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -447,8 +493,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
tuple(params),
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
UPDATE session_queue
SET status = 'canceled'
@@ -456,7 +502,7 @@ class SqliteSessionQueue(SessionQueueBase):
""",
tuple(params),
)
self._conn.commit()
self.__conn.commit()
if current_queue_item is not None and current_queue_item.queue_id == queue_id:
batch_status = self.get_batch_status(queue_id=queue_id, batch_id=current_queue_item.batch_id)
queue_status = self.get_queue_status(queue_id=queue_id)
@@ -464,19 +510,21 @@ class SqliteSessionQueue(SessionQueueBase):
current_queue_item, batch_status, queue_status
)
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CancelByQueueIDResult(canceled=count)
def cancel_all_except_current(self, queue_id: str) -> CancelAllExceptCurrentResult:
try:
cursor = self._conn.cursor()
where = """--sql
WHERE
queue_id == ?
AND status == 'pending'
"""
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
@@ -484,8 +532,8 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
count = cursor.fetchone()[0]
cursor.execute(
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
UPDATE session_queue
SET status = 'canceled'
@@ -493,35 +541,43 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(queue_id,),
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CancelAllExceptCurrentResult(canceled=count)
def get_queue_item(self, item_id: int) -> SessionQueueItem:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT * FROM session_queue
WHERE
item_id = ?
""",
(item_id,),
)
result = cast(Union[sqlite3.Row, None], cursor.fetchone())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT * FROM session_queue
WHERE
item_id = ?
""",
(item_id,),
)
result = cast(Union[sqlite3.Row, None], self.__cursor.fetchone())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
if result is None:
raise SessionQueueItemNotFoundError(f"No queue item with id {item_id}")
return SessionQueueItem.queue_item_from_dict(dict(result))
def set_queue_item_session(self, item_id: int, session: GraphExecutionState) -> SessionQueueItem:
try:
cursor = self._conn.cursor()
# Use exclude_none so we don't end up with a bunch of nulls in the graph - this can cause validation errors
# when the graph is loaded. Graph execution occurs purely in memory - the session saved here is not referenced
# during execution.
session_json = session.model_dump_json(warnings=False, exclude_none=True)
cursor.execute(
self.__lock.acquire()
self.__cursor.execute(
"""--sql
UPDATE session_queue
SET session = ?
@@ -529,10 +585,12 @@ class SqliteSessionQueue(SessionQueueBase):
""",
(session_json, item_id),
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
return self.get_queue_item(item_id)
def list_queue_items(
@@ -543,71 +601,83 @@ class SqliteSessionQueue(SessionQueueBase):
cursor: Optional[int] = None,
status: Optional[QUEUE_ITEM_STATUS] = None,
) -> CursorPaginatedResults[SessionQueueItemDTO]:
cursor_ = self._conn.cursor()
item_id = cursor
query = """--sql
SELECT item_id,
status,
priority,
field_values,
error_type,
error_message,
error_traceback,
created_at,
updated_at,
completed_at,
started_at,
session_id,
batch_id,
queue_id,
origin,
destination
FROM session_queue
WHERE queue_id = ?
"""
params: list[Union[str, int]] = [queue_id]
if status is not None:
query += """--sql
AND status = ?
"""
params.append(status)
if item_id is not None:
query += """--sql
AND (priority < ?) OR (priority = ? AND item_id > ?)
"""
params.extend([priority, priority, item_id])
query += """--sql
ORDER BY
priority DESC,
item_id ASC
LIMIT ?
try:
item_id = cursor
self.__lock.acquire()
query = """--sql
SELECT item_id,
status,
priority,
field_values,
error_type,
error_message,
error_traceback,
created_at,
updated_at,
completed_at,
started_at,
session_id,
batch_id,
queue_id,
origin,
destination
FROM session_queue
WHERE queue_id = ?
"""
params.append(limit + 1)
cursor_.execute(query, params)
results = cast(list[sqlite3.Row], cursor_.fetchall())
items = [SessionQueueItemDTO.queue_item_dto_from_dict(dict(result)) for result in results]
has_more = False
if len(items) > limit:
# remove the extra item
items.pop()
has_more = True
params: list[Union[str, int]] = [queue_id]
if status is not None:
query += """--sql
AND status = ?
"""
params.append(status)
if item_id is not None:
query += """--sql
AND (priority < ?) OR (priority = ? AND item_id > ?)
"""
params.extend([priority, priority, item_id])
query += """--sql
ORDER BY
priority DESC,
item_id ASC
LIMIT ?
"""
params.append(limit + 1)
self.__cursor.execute(query, params)
results = cast(list[sqlite3.Row], self.__cursor.fetchall())
items = [SessionQueueItemDTO.queue_item_dto_from_dict(dict(result)) for result in results]
has_more = False
if len(items) > limit:
# remove the extra item
items.pop()
has_more = True
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CursorPaginatedResults(items=items, limit=limit, has_more=has_more)
def get_queue_status(self, queue_id: str) -> SessionQueueStatus:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT status, count(*)
FROM session_queue
WHERE queue_id = ?
GROUP BY status
""",
(queue_id,),
)
counts_result = cast(list[sqlite3.Row], cursor.fetchall())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT status, count(*)
FROM session_queue
WHERE queue_id = ?
GROUP BY status
""",
(queue_id,),
)
counts_result = cast(list[sqlite3.Row], self.__cursor.fetchall())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
current_item = self.get_current(queue_id=queue_id)
total = sum(row[1] for row in counts_result)
@@ -626,23 +696,29 @@ class SqliteSessionQueue(SessionQueueBase):
)
def get_batch_status(self, queue_id: str, batch_id: str) -> BatchStatus:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT status, count(*), origin, destination
FROM session_queue
WHERE
queue_id = ?
AND batch_id = ?
GROUP BY status
""",
(queue_id, batch_id),
)
result = cast(list[sqlite3.Row], cursor.fetchall())
total = sum(row[1] for row in result)
counts: dict[str, int] = {row[0]: row[1] for row in result}
origin = result[0]["origin"] if result else None
destination = result[0]["destination"] if result else None
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT status, count(*), origin, destination
FROM session_queue
WHERE
queue_id = ?
AND batch_id = ?
GROUP BY status
""",
(queue_id, batch_id),
)
result = cast(list[sqlite3.Row], self.__cursor.fetchall())
total = sum(row[1] for row in result)
counts: dict[str, int] = {row[0]: row[1] for row in result}
origin = result[0]["origin"] if result else None
destination = result[0]["destination"] if result else None
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
return BatchStatus(
batch_id=batch_id,
@@ -658,18 +734,24 @@ class SqliteSessionQueue(SessionQueueBase):
)
def get_counts_by_destination(self, queue_id: str, destination: str) -> SessionQueueCountsByDestination:
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT status, count(*)
FROM session_queue
WHERE queue_id = ?
AND destination = ?
GROUP BY status
""",
(queue_id, destination),
)
counts_result = cast(list[sqlite3.Row], cursor.fetchall())
try:
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT status, count(*)
FROM session_queue
WHERE queue_id = ?
AND destination = ?
GROUP BY status
""",
(queue_id, destination),
)
counts_result = cast(list[sqlite3.Row], self.__cursor.fetchall())
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
total = sum(row[1] for row in counts_result)
counts: dict[str, int] = {row[0]: row[1] for row in counts_result}
@@ -688,8 +770,9 @@ class SqliteSessionQueue(SessionQueueBase):
def retry_items_by_id(self, queue_id: str, item_ids: list[int]) -> RetryItemsResult:
"""Retries the given queue items"""
try:
cursor = self._conn.cursor()
values_to_insert: list[tuple] = []
self.__lock.acquire()
values_to_insert: list[SessionQueueValueToInsert] = []
retried_item_ids: list[int] = []
for item_id in item_ids:
@@ -715,23 +798,23 @@ class SqliteSessionQueue(SessionQueueBase):
else queue_item.item_id
)
value_to_insert = (
queue_item.queue_id,
queue_item.batch_id,
queue_item.destination,
field_values_json,
queue_item.origin,
queue_item.priority,
workflow_json,
cloned_session_json,
cloned_session.id,
retried_from_item_id,
value_to_insert = SessionQueueValueToInsert(
queue_id=queue_item.queue_id,
batch_id=queue_item.batch_id,
destination=queue_item.destination,
field_values=field_values_json,
origin=queue_item.origin,
priority=queue_item.priority,
workflow=workflow_json,
session=cloned_session_json,
session_id=cloned_session.id,
retried_from_item_id=retried_from_item_id,
)
values_to_insert.append(value_to_insert)
# TODO(psyche): Handle max queue size?
cursor.executemany(
self.__cursor.executemany(
"""--sql
INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow, origin, destination, retried_from_item_id)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
@@ -739,10 +822,12 @@ class SqliteSessionQueue(SessionQueueBase):
values_to_insert,
)
self._conn.commit()
self.__conn.commit()
except Exception:
self._conn.rollback()
self.__conn.rollback()
raise
finally:
self.__lock.release()
retry_result = RetryItemsResult(
queue_id=queue_id,
retried_item_ids=retried_item_ids,

View File

@@ -9,7 +9,6 @@ from torch import Tensor
from invokeai.app.invocations.constants import IMAGE_MODES
from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
from invokeai.app.services.board_records.board_records_common import BoardRecordOrderBy
from invokeai.app.services.boards.boards_common import BoardDTO
from invokeai.app.services.config.config_default import InvokeAIAppConfig
from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
@@ -17,7 +16,6 @@ from invokeai.app.services.images.images_common import ImageDTO
from invokeai.app.services.invocation_services import InvocationServices
from invokeai.app.services.model_records.model_records_base import UnknownModelException
from invokeai.app.services.session_processor.session_processor_common import ProgressImage
from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
from invokeai.app.util.step_callback import flux_step_callback, stable_diffusion_step_callback
from invokeai.backend.model_manager.config import (
AnyModel,
@@ -104,9 +102,7 @@ class BoardsInterface(InvocationContextInterface):
Returns:
A list of all boards.
"""
return self._services.boards.get_all(
order_by=BoardRecordOrderBy.CreatedAt, direction=SQLiteDirection.Descending
)
return self._services.boards.get_all()
def add_image_to_board(self, board_id: str, image_name: str) -> None:
"""Adds an image to a board.
@@ -126,11 +122,7 @@ class BoardsInterface(InvocationContextInterface):
Returns:
A list of all image names for the board.
"""
return self._services.board_images.get_all_board_image_names_for_board(
board_id,
categories=None,
is_intermediate=None,
)
return self._services.board_images.get_all_board_image_names_for_board(board_id)
class LoggerInterface(InvocationContextInterface):
@@ -291,7 +283,7 @@ class ImagesInterface(InvocationContextInterface):
Returns:
The local path of the image or thumbnail.
"""
return Path(self._services.images.get_path(image_name, thumbnail))
return self._services.images.get_path(image_name, thumbnail)
class TensorsInterface(InvocationContextInterface):

View File

@@ -1,4 +1,5 @@
import sqlite3
import threading
from logging import Logger
from pathlib import Path
@@ -37,20 +38,14 @@ class SqliteDatabase:
self.logger.info(f"Initializing database at {self.db_path}")
self.conn = sqlite3.connect(database=self.db_path or sqlite_memory, check_same_thread=False)
self.lock = threading.RLock()
self.conn.row_factory = sqlite3.Row
if self.verbose:
self.conn.set_trace_callback(self.logger.debug)
# Enable foreign key constraints
self.conn.execute("PRAGMA foreign_keys = ON;")
# Enable Write-Ahead Logging (WAL) mode for better concurrency
self.conn.execute("PRAGMA journal_mode = WAL;")
# Set a busy timeout to prevent database lockups during writes
self.conn.execute("PRAGMA busy_timeout = 5000;") # 5 seconds
def clean(self) -> None:
"""
Cleans the database by running the VACUUM command, reporting on the freed space.
@@ -58,14 +53,15 @@ class SqliteDatabase:
# No need to clean in-memory database
if not self.db_path:
return
try:
initial_db_size = Path(self.db_path).stat().st_size
self.conn.execute("VACUUM;")
self.conn.commit()
final_db_size = Path(self.db_path).stat().st_size
freed_space_in_mb = round((initial_db_size - final_db_size) / 1024 / 1024, 2)
if freed_space_in_mb > 0:
self.logger.info(f"Cleaned database (freed {freed_space_in_mb}MB)")
except Exception as e:
self.logger.error(f"Error cleaning database: {e}")
raise
with self.lock:
try:
initial_db_size = Path(self.db_path).stat().st_size
self.conn.execute("VACUUM;")
self.conn.commit()
final_db_size = Path(self.db_path).stat().st_size
freed_space_in_mb = round((initial_db_size - final_db_size) / 1024 / 1024, 2)
if freed_space_in_mb > 0:
self.logger.info(f"Cleaned database (freed {freed_space_in_mb}MB)")
except Exception as e:
self.logger.error(f"Error cleaning database: {e}")
raise

View File

@@ -43,45 +43,46 @@ class SqliteMigrator:
def run_migrations(self) -> bool:
"""Migrates the database to the latest version."""
# This throws if there is a problem.
self._migration_set.validate_migration_chain()
cursor = self._db.conn.cursor()
self._create_migrations_table(cursor=cursor)
with self._db.lock:
# This throws if there is a problem.
self._migration_set.validate_migration_chain()
cursor = self._db.conn.cursor()
self._create_migrations_table(cursor=cursor)
if self._migration_set.count == 0:
self._logger.debug("No migrations registered")
return False
if self._migration_set.count == 0:
self._logger.debug("No migrations registered")
return False
if self._get_current_version(cursor=cursor) == self._migration_set.latest_version:
self._logger.debug("Database is up to date, no migrations to run")
return False
if self._get_current_version(cursor=cursor) == self._migration_set.latest_version:
self._logger.debug("Database is up to date, no migrations to run")
return False
self._logger.info("Database update needed")
self._logger.info("Database update needed")
# Make a backup of the db if it needs to be updated and is a file db
if self._db.db_path is not None:
timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
self._backup_path = self._db.db_path.parent / f"{self._db.db_path.stem}_backup_{timestamp}.db"
self._logger.info(f"Backing up database to {str(self._backup_path)}")
# Use SQLite to do the backup
with closing(sqlite3.connect(self._backup_path)) as backup_conn:
self._db.conn.backup(backup_conn)
else:
self._logger.info("Using in-memory database, no backup needed")
# Make a backup of the db if it needs to be updated and is a file db
if self._db.db_path is not None:
timestamp = datetime.now().strftime("%Y%m%d-%H%M%S")
self._backup_path = self._db.db_path.parent / f"{self._db.db_path.stem}_backup_{timestamp}.db"
self._logger.info(f"Backing up database to {str(self._backup_path)}")
# Use SQLite to do the backup
with closing(sqlite3.connect(self._backup_path)) as backup_conn:
self._db.conn.backup(backup_conn)
else:
self._logger.info("Using in-memory database, no backup needed")
next_migration = self._migration_set.get(from_version=self._get_current_version(cursor))
while next_migration is not None:
self._run_migration(next_migration)
next_migration = self._migration_set.get(self._get_current_version(cursor))
self._logger.info("Database updated successfully")
return True
next_migration = self._migration_set.get(from_version=self._get_current_version(cursor))
while next_migration is not None:
self._run_migration(next_migration)
next_migration = self._migration_set.get(self._get_current_version(cursor))
self._logger.info("Database updated successfully")
return True
def _run_migration(self, migration: Migration) -> None:
"""Runs a single migration."""
try:
# Using sqlite3.Connection as a context manager commits a the transaction on exit, or rolls it back if an
# exception is raised.
with self._db.conn as conn:
with self._db.lock, self._db.conn as conn:
cursor = conn.cursor()
if self._get_current_version(cursor) != migration.from_version:
raise MigrationError(
@@ -107,26 +108,27 @@ class SqliteMigrator:
def _create_migrations_table(self, cursor: sqlite3.Cursor) -> None:
"""Creates the migrations table for the database, if one does not already exist."""
try:
cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='migrations';")
if cursor.fetchone() is not None:
return
cursor.execute(
"""--sql
CREATE TABLE migrations (
version INTEGER PRIMARY KEY,
migrated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW'))
);
"""
)
cursor.execute("INSERT INTO migrations (version) VALUES (0);")
cursor.connection.commit()
self._logger.debug("Created migrations table")
except sqlite3.Error as e:
msg = f"Problem creating migrations table: {e}"
self._logger.error(msg)
cursor.connection.rollback()
raise MigrationError(msg) from e
with self._db.lock:
try:
cursor.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='migrations';")
if cursor.fetchone() is not None:
return
cursor.execute(
"""--sql
CREATE TABLE migrations (
version INTEGER PRIMARY KEY,
migrated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW'))
);
"""
)
cursor.execute("INSERT INTO migrations (version) VALUES (0);")
cursor.connection.commit()
self._logger.debug("Created migrations table")
except sqlite3.Error as e:
msg = f"Problem creating migrations table: {e}"
self._logger.error(msg)
cursor.connection.rollback()
raise MigrationError(msg) from e
@classmethod
def _get_current_version(cls, cursor: sqlite3.Cursor) -> int:

View File

@@ -17,7 +17,9 @@ from invokeai.app.util.misc import uuid_string
class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._lock = db.lock
self._conn = db.conn
self._cursor = self._conn.cursor()
def start(self, invoker: Invoker) -> None:
self._invoker = invoker
@@ -25,25 +27,31 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
def get(self, style_preset_id: str) -> StylePresetRecordDTO:
"""Gets a style preset by ID."""
cursor = self._conn.cursor()
cursor.execute(
"""--sql
SELECT *
FROM style_presets
WHERE id = ?;
""",
(style_preset_id,),
)
row = cursor.fetchone()
if row is None:
raise StylePresetNotFoundError(f"Style preset with id {style_preset_id} not found")
return StylePresetRecordDTO.from_dict(dict(row))
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
SELECT *
FROM style_presets
WHERE id = ?;
""",
(style_preset_id,),
)
row = self._cursor.fetchone()
if row is None:
raise StylePresetNotFoundError(f"Style preset with id {style_preset_id} not found")
return StylePresetRecordDTO.from_dict(dict(row))
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
def create(self, style_preset: StylePresetWithoutId) -> StylePresetRecordDTO:
style_preset_id = uuid_string()
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
INSERT OR IGNORE INTO style_presets (
id,
@@ -64,16 +72,18 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return self.get(style_preset_id)
def create_many(self, style_presets: list[StylePresetWithoutId]) -> None:
style_preset_ids = []
try:
cursor = self._conn.cursor()
self._lock.acquire()
for style_preset in style_presets:
style_preset_id = uuid_string()
style_preset_ids.append(style_preset_id)
cursor.execute(
self._cursor.execute(
"""--sql
INSERT OR IGNORE INTO style_presets (
id,
@@ -94,15 +104,17 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return None
def update(self, style_preset_id: str, changes: StylePresetChanges) -> StylePresetRecordDTO:
try:
cursor = self._conn.cursor()
self._lock.acquire()
# Change the name of a style preset
if changes.name is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE style_presets
SET name = ?
@@ -113,7 +125,7 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
# Change the preset data for a style preset
if changes.preset_data is not None:
cursor.execute(
self._cursor.execute(
"""--sql
UPDATE style_presets
SET preset_data = ?
@@ -126,12 +138,14 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return self.get(style_preset_id)
def delete(self, style_preset_id: str) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE from style_presets
WHERE id = ?;
@@ -142,38 +156,46 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return None
def get_many(self, type: PresetType | None = None) -> list[StylePresetRecordDTO]:
main_query = """
SELECT
*
FROM style_presets
"""
try:
self._lock.acquire()
main_query = """
SELECT
*
FROM style_presets
"""
if type is not None:
main_query += "WHERE type = ? "
if type is not None:
main_query += "WHERE type = ? "
main_query += "ORDER BY LOWER(name) ASC"
main_query += "ORDER BY LOWER(name) ASC"
cursor = self._conn.cursor()
if type is not None:
cursor.execute(main_query, (type,))
else:
cursor.execute(main_query)
if type is not None:
self._cursor.execute(main_query, (type,))
else:
self._cursor.execute(main_query)
rows = cursor.fetchall()
style_presets = [StylePresetRecordDTO.from_dict(dict(row)) for row in rows]
rows = self._cursor.fetchall()
style_presets = [StylePresetRecordDTO.from_dict(dict(row)) for row in rows]
return style_presets
return style_presets
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
def _sync_default_style_presets(self) -> None:
"""Syncs default style presets to the database. Internal use only."""
# First delete all existing default style presets
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE FROM style_presets
WHERE type = "default";
@@ -183,8 +205,10 @@ class SqliteStylePresetRecordsStorage(StylePresetRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
# Next, parse and create the default style presets
with open(Path(__file__).parent / Path("default_style_presets.json"), "r") as file:
with self._lock, open(Path(__file__).parent / Path("default_style_presets.json"), "r") as file:
presets = json.load(file)
for preset in presets:
style_preset = StylePresetWithoutId.model_validate(preset)

View File

@@ -62,13 +62,9 @@ class WorkflowWithoutID(BaseModel):
notes: str = Field(description="The notes of the workflow.")
exposedFields: list[ExposedField] = Field(description="The exposed fields of the workflow.")
meta: WorkflowMeta = Field(description="The meta of the workflow.")
# TODO(psyche): nodes, edges and form are very loosely typed - they are strictly modeled and checked on the frontend.
# TODO: nodes and edges are very loosely typed
nodes: list[dict[str, JsonValue]] = Field(description="The nodes of the workflow.")
edges: list[dict[str, JsonValue]] = Field(description="The edges of the workflow.")
# TODO(psyche): We have a crapload of workflows that have no form, bc it was added after we introduced workflows.
# This is typed as optional to prevent errors when pulling workflows from the DB. The frontend adds a default form if
# it is None.
form: dict[str, JsonValue] | None = Field(default=None, description="The form of the workflow.")
model_config = ConfigDict(extra="ignore")

View File

@@ -23,7 +23,9 @@ from invokeai.app.util.misc import uuid_string
class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
def __init__(self, db: SqliteDatabase) -> None:
super().__init__()
self._lock = db.lock
self._conn = db.conn
self._cursor = self._conn.cursor()
def start(self, invoker: Invoker) -> None:
self._invoker = invoker
@@ -31,36 +33,42 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
def get(self, workflow_id: str) -> WorkflowRecordDTO:
"""Gets a workflow by ID. Updates the opened_at column."""
cursor = self._conn.cursor()
cursor.execute(
"""--sql
UPDATE workflow_library
SET opened_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
WHERE workflow_id = ?;
""",
(workflow_id,),
)
self._conn.commit()
cursor.execute(
"""--sql
SELECT workflow_id, workflow, name, created_at, updated_at, opened_at
FROM workflow_library
WHERE workflow_id = ?;
""",
(workflow_id,),
)
row = cursor.fetchone()
if row is None:
raise WorkflowNotFoundError(f"Workflow with id {workflow_id} not found")
return WorkflowRecordDTO.from_dict(dict(row))
try:
self._lock.acquire()
self._cursor.execute(
"""--sql
UPDATE workflow_library
SET opened_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
WHERE workflow_id = ?;
""",
(workflow_id,),
)
self._conn.commit()
self._cursor.execute(
"""--sql
SELECT workflow_id, workflow, name, created_at, updated_at, opened_at
FROM workflow_library
WHERE workflow_id = ?;
""",
(workflow_id,),
)
row = self._cursor.fetchone()
if row is None:
raise WorkflowNotFoundError(f"Workflow with id {workflow_id} not found")
return WorkflowRecordDTO.from_dict(dict(row))
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
def create(self, workflow: WorkflowWithoutID) -> WorkflowRecordDTO:
try:
# Only user workflows may be created by this method
assert workflow.meta.category is WorkflowCategory.User
workflow_with_id = Workflow(**workflow.model_dump(), id=uuid_string())
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
INSERT OR IGNORE INTO workflow_library (
workflow_id,
@@ -74,12 +82,14 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return self.get(workflow_with_id.id)
def update(self, workflow: Workflow) -> WorkflowRecordDTO:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
UPDATE workflow_library
SET workflow = ?
@@ -91,12 +101,14 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return self.get(workflow.id)
def delete(self, workflow_id: str) -> None:
try:
cursor = self._conn.cursor()
cursor.execute(
self._lock.acquire()
self._cursor.execute(
"""--sql
DELETE from workflow_library
WHERE workflow_id = ? AND category = 'user';
@@ -107,6 +119,8 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
return None
def get_many(
@@ -118,60 +132,66 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
per_page: Optional[int] = None,
query: Optional[str] = None,
) -> PaginatedResults[WorkflowRecordListItemDTO]:
# sanitize!
assert order_by in WorkflowRecordOrderBy
assert direction in SQLiteDirection
assert category in WorkflowCategory
count_query = "SELECT COUNT(*) FROM workflow_library WHERE category = ?"
main_query = """
SELECT
workflow_id,
category,
name,
description,
created_at,
updated_at,
opened_at
FROM workflow_library
WHERE category = ?
"""
main_params: list[int | str] = [category.value]
count_params: list[int | str] = [category.value]
try:
self._lock.acquire()
# sanitize!
assert order_by in WorkflowRecordOrderBy
assert direction in SQLiteDirection
assert category in WorkflowCategory
count_query = "SELECT COUNT(*) FROM workflow_library WHERE category = ?"
main_query = """
SELECT
workflow_id,
category,
name,
description,
created_at,
updated_at,
opened_at
FROM workflow_library
WHERE category = ?
"""
main_params: list[int | str] = [category.value]
count_params: list[int | str] = [category.value]
stripped_query = query.strip() if query else None
if stripped_query:
wildcard_query = "%" + stripped_query + "%"
main_query += " AND name LIKE ? OR description LIKE ? "
count_query += " AND name LIKE ? OR description LIKE ?;"
main_params.extend([wildcard_query, wildcard_query])
count_params.extend([wildcard_query, wildcard_query])
stripped_query = query.strip() if query else None
if stripped_query:
wildcard_query = "%" + stripped_query + "%"
main_query += " AND name LIKE ? OR description LIKE ? "
count_query += " AND name LIKE ? OR description LIKE ?;"
main_params.extend([wildcard_query, wildcard_query])
count_params.extend([wildcard_query, wildcard_query])
main_query += f" ORDER BY {order_by.value} {direction.value}"
main_query += f" ORDER BY {order_by.value} {direction.value}"
if per_page:
main_query += " LIMIT ? OFFSET ?"
main_params.extend([per_page, page * per_page])
if per_page:
main_query += " LIMIT ? OFFSET ?"
main_params.extend([per_page, page * per_page])
cursor = self._conn.cursor()
cursor.execute(main_query, main_params)
rows = cursor.fetchall()
workflows = [WorkflowRecordListItemDTOValidator.validate_python(dict(row)) for row in rows]
self._cursor.execute(main_query, main_params)
rows = self._cursor.fetchall()
workflows = [WorkflowRecordListItemDTOValidator.validate_python(dict(row)) for row in rows]
cursor.execute(count_query, count_params)
total = cursor.fetchone()[0]
self._cursor.execute(count_query, count_params)
total = self._cursor.fetchone()[0]
if per_page:
pages = total // per_page + (total % per_page > 0)
else:
pages = 1 # If no pagination, there is only one page
if per_page:
pages = total // per_page + (total % per_page > 0)
else:
pages = 1 # If no pagination, there is only one page
return PaginatedResults(
items=workflows,
page=page,
per_page=per_page if per_page else total,
pages=pages,
total=total,
)
return PaginatedResults(
items=workflows,
page=page,
per_page=per_page if per_page else total,
pages=pages,
total=total,
)
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()
def _sync_default_workflows(self) -> None:
"""Syncs default workflows to the database. Internal use only."""
@@ -187,6 +207,7 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
"""
try:
self._lock.acquire()
workflows: list[Workflow] = []
workflows_dir = Path(__file__).parent / Path("default_workflows")
workflow_paths = workflows_dir.glob("*.json")
@@ -197,15 +218,14 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
workflows.append(workflow)
# Only default workflows may be managed by this method
assert all(w.meta.category is WorkflowCategory.Default for w in workflows)
cursor = self._conn.cursor()
cursor.execute(
self._cursor.execute(
"""--sql
DELETE FROM workflow_library
WHERE category = 'default';
"""
)
for w in workflows:
cursor.execute(
self._cursor.execute(
"""--sql
INSERT OR REPLACE INTO workflow_library (
workflow_id,
@@ -219,3 +239,5 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
except Exception:
self._conn.rollback()
raise
finally:
self._lock.release()

View File

@@ -1,64 +0,0 @@
import logging
import mimetypes
import socket
import torch
def find_open_port(port: int) -> int:
"""Find a port not in use starting at given port"""
# Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
# https://github.com/WaylonWalker
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.settimeout(1)
if s.connect_ex(("localhost", port)) == 0:
return find_open_port(port=port + 1)
else:
return port
def check_cudnn(logger: logging.Logger) -> None:
"""Check for cuDNN issues that could be causing degraded performance."""
if torch.backends.cudnn.is_available():
try:
# Note: At the time of writing (torch 2.2.1), torch.backends.cudnn.version() only raises an error the first
# time it is called. Subsequent calls will return the version number without complaining about a mismatch.
cudnn_version = torch.backends.cudnn.version()
logger.info(f"cuDNN version: {cudnn_version}")
except RuntimeError as e:
logger.warning(
"Encountered a cuDNN version issue. This may result in degraded performance. This issue is usually "
"caused by an incompatible cuDNN version installed in your python environment, or on the host "
f"system. Full error message:\n{e}"
)
def enable_dev_reload() -> None:
"""Enable hot reloading on python file changes during development."""
from invokeai.backend.util.logging import InvokeAILogger
try:
import jurigged
except ImportError as e:
raise RuntimeError(
'Can\'t start `--dev_reload` because jurigged is not found; `pip install -e ".[dev]"` to include development dependencies.'
) from e
else:
jurigged.watch(logger=InvokeAILogger.get_logger(name="jurigged").info)
def apply_monkeypatches() -> None:
"""Apply monkeypatches to fix issues with third-party libraries."""
import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
if torch.backends.mps.is_available():
import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
def register_mime_types() -> None:
"""Register additional mime types for windows."""
# Fix for windows mimetypes registry entries being borked.
# see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
mimetypes.add_type("application/javascript", ".js")
mimetypes.add_type("text/css", ".css")

View File

@@ -1,52 +0,0 @@
import logging
import os
import sys
def configure_torch_cuda_allocator(pytorch_cuda_alloc_conf: str, logger: logging.Logger):
"""Configure the PyTorch CUDA memory allocator. See
https://pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf for supported
configurations.
"""
if "torch" in sys.modules:
raise RuntimeError("configure_torch_cuda_allocator() must be called before importing torch.")
# Log a warning if the PYTORCH_CUDA_ALLOC_CONF environment variable is already set.
prev_cuda_alloc_conf = os.environ.get("PYTORCH_CUDA_ALLOC_CONF", None)
if prev_cuda_alloc_conf is not None:
if prev_cuda_alloc_conf == pytorch_cuda_alloc_conf:
logger.info(
f"PYTORCH_CUDA_ALLOC_CONF is already set to '{pytorch_cuda_alloc_conf}'. Skipping configuration."
)
return
else:
logger.warning(
f"Attempted to configure the PyTorch CUDA memory allocator with '{pytorch_cuda_alloc_conf}', but PYTORCH_CUDA_ALLOC_CONF is already set to "
f"'{prev_cuda_alloc_conf}'. Skipping configuration."
)
return
# Configure the PyTorch CUDA memory allocator.
# NOTE: It is important that this happens before torch is imported.
os.environ["PYTORCH_CUDA_ALLOC_CONF"] = pytorch_cuda_alloc_conf
import torch
# Relevant docs: https://pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf
if not torch.cuda.is_available():
raise RuntimeError(
"Attempted to configure the PyTorch CUDA memory allocator, but no CUDA devices are available."
)
# Verify that the torch allocator was properly configured.
allocator_backend = torch.cuda.get_allocator_backend()
expected_backend = "cudaMallocAsync" if "cudaMallocAsync" in pytorch_cuda_alloc_conf else "native"
if allocator_backend != expected_backend:
raise RuntimeError(
f"Failed to configure the PyTorch CUDA memory allocator. Expected backend: '{expected_backend}', but got "
f"'{allocator_backend}'. Verify that 1) the pytorch_cuda_alloc_conf is set correctly, and 2) that torch is "
"not imported before calling configure_torch_cuda_allocator()."
)
logger.info(f"PyTorch CUDA memory allocator: {torch.cuda.get_allocator_backend()}")

View File

@@ -75,8 +75,6 @@
"idb-keyval": "^6.2.1",
"jsondiffpatch": "^0.6.0",
"konva": "^9.3.15",
"linkify-react": "^4.2.0",
"linkifyjs": "^4.2.0",
"lodash-es": "^4.17.21",
"lru-cache": "^11.0.1",
"mtwist": "^1.0.2",
@@ -138,8 +136,8 @@
"@types/react-dom": "^18.3.0",
"@types/uuid": "^10.0.0",
"@vitejs/plugin-react-swc": "^3.8.0",
"@vitest/coverage-v8": "^3.0.6",
"@vitest/ui": "^3.0.6",
"@vitest/coverage-v8": "^3.0.5",
"@vitest/ui": "^3.0.5",
"concurrently": "^8.2.2",
"csstype": "^3.1.3",
"dpdm": "^3.14.0",
@@ -160,7 +158,7 @@
"vite-plugin-dts": "^4.5.0",
"vite-plugin-eslint": "^1.8.1",
"vite-tsconfig-paths": "^5.1.4",
"vitest": "^3.0.6"
"vitest": "^1.6.0"
},
"engines": {
"pnpm": "8"

File diff suppressed because it is too large Load Diff

View File

@@ -107,13 +107,7 @@
"min": "Min",
"max": "Max",
"resetToDefaults": "Auf Standard zurücksetzen",
"seed": "Seed",
"row": "Reihe",
"column": "Spalte",
"end": "Ende",
"layout": "Layout",
"board": "Ordner",
"combinatorial": "Kombinatorisch"
"seed": "Seed"
},
"gallery": {
"galleryImageSize": "Bildgröße",
@@ -622,9 +616,7 @@
"hfTokenUnableToVerify": "HF-Token kann nicht überprüft werden",
"hfTokenUnableToVerifyErrorMessage": "HuggingFace-Token kann nicht überprüft werden. Dies ist wahrscheinlich auf einen Netzwerkfehler zurückzuführen. Bitte versuchen Sie es später erneut.",
"hfTokenSaved": "HF-Token gespeichert",
"hfTokenRequired": "Sie versuchen, ein Modell herunterzuladen, für das ein gültiges HuggingFace-Token erforderlich ist.",
"urlUnauthorizedErrorMessage2": "Hier erfahren wie.",
"urlForbidden": "Sie haben keinen Zugriff auf dieses Modell"
"hfTokenRequired": "Sie versuchen, ein Modell herunterzuladen, für das ein gültiges HuggingFace-Token erforderlich ist."
},
"parameters": {
"images": "Bilder",
@@ -691,8 +683,7 @@
"iterations": "Iterationen",
"guidance": "Führung",
"coherenceMode": "Modus",
"recallMetadata": "Metadaten abrufen",
"gaussianBlur": "Gaußsche Unschärfe"
"recallMetadata": "Metadaten abrufen"
},
"settings": {
"displayInProgress": "Zwischenbilder anzeigen",
@@ -892,8 +883,7 @@
"canvas": "Leinwand",
"prompts_one": "Prompt",
"prompts_other": "Prompts",
"batchSize": "Stapelgröße",
"confirm": "Bestätigen"
"batchSize": "Stapelgröße"
},
"metadata": {
"negativePrompt": "Negativ Beschreibung",
@@ -1308,13 +1298,7 @@
"noBatchGroup": "keine Gruppe",
"generatorNoValues": "leer",
"generatorLoading": "wird geladen",
"generatorLoadFromFile": "Aus Datei laden",
"showEdgeLabels": "Kantenbeschriftungen anzeigen",
"downloadWorkflowError": "Fehler beim Herunterladen des Arbeitsablaufs",
"nodeName": "Knotenname",
"description": "Beschreibung",
"loadWorkflowDesc": "Arbeitsablauf laden?",
"loadWorkflowDesc2": "Ihr aktueller Arbeitsablauf enthält nicht gespeicherte Änderungen."
"generatorLoadFromFile": "Aus Datei laden"
},
"hrf": {
"enableHrf": "Korrektur für hohe Auflösungen",

View File

@@ -90,7 +90,6 @@
"back": "Back",
"batch": "Batch Manager",
"beta": "Beta",
"board": "Board",
"cancel": "Cancel",
"close": "Close",
"copy": "Copy",
@@ -312,7 +311,6 @@
},
"gallery": {
"gallery": "Gallery",
"images": "Images",
"assets": "Assets",
"alwaysShowImageSizeBadge": "Always Show Image Size Badge",
"assetsTab": "Files youve uploaded for use in your projects.",
@@ -883,15 +881,11 @@
"parseString": "Parse String",
"splitOn": "Split On",
"noBatchGroup": "no group",
"generatorImagesCategory": "Category",
"generatorImages_one": "{{count}} image",
"generatorImages_other": "{{count}} images",
"generatorNRandomValues_one": "{{count}} random value",
"generatorNRandomValues_other": "{{count}} random values",
"generatorNoValues": "empty",
"generatorLoading": "loading",
"generatorLoadFromFile": "Load from File",
"generatorImagesFromBoard": "Images from Board",
"dynamicPromptsRandom": "Dynamic Prompts (Random)",
"dynamicPromptsCombinatorial": "Dynamic Prompts (Combinatorial)",
"addNode": "Add Node",
@@ -908,8 +902,6 @@
"missingNode": "Missing invocation node",
"missingInvocationTemplate": "Missing invocation template",
"missingFieldTemplate": "Missing field template",
"missingSourceOrTargetNode": "Missing source or target node",
"missingSourceOrTargetHandle": "Missing source or target handle",
"nodePack": "Node pack",
"collection": "Collection",
"singleFieldType": "{{name}} (Single)",
@@ -921,7 +913,6 @@
"currentImage": "Current Image",
"currentImageDescription": "Displays the current image in the Node Editor",
"downloadWorkflow": "Download Workflow JSON",
"downloadWorkflowError": "Error downloading workflow",
"edge": "Edge",
"edit": "Edit",
"editMode": "Edit in Workflow Editor",
@@ -961,7 +952,6 @@
"nodeSearch": "Search for nodes",
"nodeTemplate": "Node Template",
"nodeType": "Node Type",
"nodeName": "Node Name",
"noFieldsLinearview": "No fields added to Linear View",
"noFieldsViewMode": "This workflow has no selected fields to display. View the full workflow to configure values.",
"workflowHelpText": "Need Help? Check out our guide to <LinkComponent>Getting Started with Workflows</LinkComponent>.",
@@ -980,8 +970,6 @@
"newWorkflow": "New Workflow",
"newWorkflowDesc": "Create a new workflow?",
"newWorkflowDesc2": "Your current workflow has unsaved changes.",
"loadWorkflowDesc": "Load workflow?",
"loadWorkflowDesc2": "Your current workflow has unsaved changes.",
"clearWorkflow": "Clear Workflow",
"clearWorkflowDesc": "Clear this workflow and start a new one?",
"clearWorkflowDesc2": "Your current workflow has unsaved changes.",
@@ -1011,7 +999,6 @@
"unknownOutput": "Unknown output: {{name}}",
"updateNode": "Update Node",
"updateApp": "Update App",
"loadingTemplates": "Loading {{name}}",
"updateAllNodes": "Update Nodes",
"allNodesUpdated": "All Nodes Updated",
"unableToUpdateNodes_one": "Unable to update {{count}} node",
@@ -1087,7 +1074,7 @@
"emptyBatches": "empty batches",
"batchNodeNotConnected": "Batch node not connected: {{label}}",
"batchNodeEmptyCollection": "Some batch nodes have empty collections",
"collectionEmpty": "empty collection",
"invalidBatchConfigurationCannotCalculate": "Invalid batch configuration; cannot calculate",
"collectionTooFewItems": "too few items, minimum {{minItems}}",
"collectionTooManyItems": "too many items, maximum {{maxItems}}",
"collectionStringTooLong": "too long, max {{maxLength}}",
@@ -1097,7 +1084,6 @@
"collectionNumberGTExclusiveMax": "{{value}} >= {{exclusiveMaximum}} (exc max)",
"collectionNumberLTExclusiveMin": "{{value}} <= {{exclusiveMinimum}} (exc min)",
"collectionNumberNotMultipleOf": "{{value}} not multiple of {{multipleOf}}",
"batchNodeCollectionSizeMismatchNoGroupId": "Batch group collection size mismatch",
"batchNodeCollectionSizeMismatch": "Collection size mismatch on Batch {{batchGroupId}}",
"noModelSelected": "No model selected",
"noT5EncoderModelSelected": "No T5 Encoder model selected for FLUX generation",
@@ -1718,33 +1704,21 @@
"copyShareLink": "Copy Share Link",
"copyShareLinkForWorkflow": "Copy Share Link for Workflow",
"delete": "Delete",
"openLibrary": "Open Library",
"builder": {
"deleteAllElements": "Delete All Form Elements",
"resetAllNodeFields": "Reset All Node Fields",
"builder": "Form Builder",
"builder": "Builder",
"layout": "Layout",
"row": "Row",
"column": "Column",
"container": "Container",
"heading": "Heading",
"text": "Text",
"divider": "Divider",
"nodeField": "Node Field",
"zoomToNode": "Zoom to Node",
"nodeFieldTooltip": "To add a node field, click the small plus sign button on the field in the Workflow Editor, or drag the field by its name into the form.",
"addToForm": "Add to Form",
"label": "Label",
"showDescription": "Show Description",
"description": "Description",
"component": "Component",
"numberInput": "Number Input",
"singleLine": "Single Line",
"multiLine": "Multi Line",
"slider": "Slider",
"both": "Both",
"emptyRootPlaceholderViewMode": "Click Edit to start building a form for this workflow.",
"emptyRootPlaceholderEditMode": "Drag a form element or node field here to get started.",
"containerPlaceholder": "Empty Container",
"containerPlaceholderDesc": "Drag a form element or node field into this container.",
"headingPlaceholder": "Empty Heading",
"textPlaceholder": "Empty Text",
"workflowBuilderAlphaWarning": "The workflow builder is currently in alpha. There may be breaking changes before the stable release."
@@ -1911,7 +1885,7 @@
"resetGenerationSettings": "Reset Generation Settings",
"replaceCurrent": "Replace Current",
"controlLayerEmptyState": "<UploadButton>Upload an image</UploadButton>, drag an image from the <GalleryButton>gallery</GalleryButton> onto this layer, or draw on the canvas to get started.",
"referenceImageEmptyState": "<UploadButton>Upload an image</UploadButton>, drag an image from the <GalleryButton>gallery</GalleryButton> onto this layer, or <PullBboxButton>pull the bounding box into this layer</PullBboxButton> to get started.",
"referenceImageEmptyState": "<UploadButton>Upload an image</UploadButton> or drag an image from the <GalleryButton>gallery</GalleryButton> onto this layer to get started.",
"warnings": {
"problemsFound": "Problems found",
"unsupportedModel": "layer not supported for selected base model",
@@ -2306,8 +2280,12 @@
"whatsNew": {
"whatsNewInInvoke": "What's New in Invoke",
"items": [
"Memory Management: New setting for users with Nvidia GPUs to reduce VRAM usage.",
"Performance: Continued improvements to overall application performance and responsiveness."
"Improved VRAM setting defaults",
"On-demand model cache clearing",
"Expanded FLUX LoRA compatibility",
"Canvas Adjust Image filter",
"Cancel all but current queue item",
"Copy from and paste to Canvas"
],
"readReleaseNotes": "Read Release Notes",
"watchRecentReleaseVideos": "Watch Recent Release Videos",

View File

@@ -98,22 +98,7 @@
"close": "Fermer",
"clipboard": "Presse-papier",
"loadingModel": "Chargement du modèle",
"generating": "En Génération",
"warnings": "Alertes",
"layout": "Disposition",
"row": "Ligne",
"column": "Colonne",
"start": "Commencer",
"board": "Planche",
"count": "Quantité",
"step": "Étape",
"end": "Fin",
"min": "Min",
"max": "Max",
"values": "Valeurs",
"resetToDefaults": "Réinitialiser par défaut",
"seed": "Graine",
"combinatorial": "Combinatoire"
"generating": "En Génération"
},
"gallery": {
"galleryImageSize": "Taille de l'image",
@@ -180,9 +165,7 @@
"imagesSettings": "Paramètres des images de la galerie",
"assetsTab": "Fichiers que vous avez importés pour vos projets.",
"imagesTab": "Images que vous avez créées et enregistrées dans Invoke.",
"boardsSettings": "Paramètres des planches",
"assets": "Ressources",
"images": "Images"
"boardsSettings": "Paramètres des planches"
},
"modelManager": {
"modelManager": "Gestionnaire de modèle",
@@ -306,7 +289,7 @@
"usingDefaultSettings": "Utilisation des paramètres par défaut du modèle",
"defaultSettingsOutOfSync": "Certain paramètres ne correspondent pas aux valeurs par défaut du modèle :",
"restoreDefaultSettings": "Cliquez pour utiliser les paramètres par défaut du modèle.",
"hfForbiddenErrorMessage": "Nous vous recommandons de visiter la page du modèle. Le propriétaire peut exiger l'acceptation des conditions pour pouvoir télécharger.",
"hfForbiddenErrorMessage": "Nous vous recommandons de visiter la page du modèle sur HuggingFace.com. Le propriétaire peut exiger l'acceptation des conditions pour pouvoir télécharger.",
"hfTokenRequired": "Vous essayez de télécharger un modèle qui nécessite un token HuggingFace valide.",
"clipLEmbed": "CLIP-L Embed",
"hfTokenSaved": "Token HF enregistré",
@@ -320,10 +303,7 @@
"hfForbidden": "Vous n'avez pas accès à ce modèle HF.",
"hfTokenInvalidErrorMessage2": "Mettre à jour dans le ",
"controlLora": "Controle LoRA",
"urlUnauthorizedErrorMessage2": "Découvrir comment ici.",
"urlUnauthorizedErrorMessage": "Vous devrez peut-être configurer un jeton API pour accéder à ce modèle.",
"urlForbidden": "Vous n'avez pas accès à ce modèle",
"urlForbiddenErrorMessage": "Vous devrez peut-être demander l'autorisation du site qui distribue le modèle."
"urlUnauthorizedErrorMessage2": "Découvrir comment ici."
},
"parameters": {
"images": "Images",
@@ -365,31 +345,19 @@
"fluxModelIncompatibleBboxHeight": "$t(parameters.invoke.fluxRequiresDimensionsToBeMultipleOf16), la hauteur de la bounding box est {{height}}",
"fluxModelIncompatibleScaledBboxHeight": "$t(parameters.invoke.fluxRequiresDimensionsToBeMultipleOf16), la hauteur de la bounding box est {{height}}",
"noFLUXVAEModelSelected": "Aucun modèle VAE sélectionné pour la génération FLUX",
"canvasIsTransforming": "La Toile est occupée (en transformation)",
"canvasIsRasterizing": "La Toile est occupée (en rastérisation)",
"canvasIsTransforming": "La Toile se transforme",
"canvasIsRasterizing": "La Toile se rastérise",
"noCLIPEmbedModelSelected": "Aucun modèle CLIP Embed sélectionné pour la génération FLUX",
"canvasIsFiltering": "La Toile est occupée (en filtration)",
"canvasIsFiltering": "La Toile est en train de filtrer",
"fluxModelIncompatibleBboxWidth": "$t(parameters.invoke.fluxRequiresDimensionsToBeMultipleOf16), la largeur de la bounding box est {{width}}",
"noT5EncoderModelSelected": "Aucun modèle T5 Encoder sélectionné pour la génération FLUX",
"fluxModelIncompatibleScaledBboxWidth": "$t(parameters.invoke.fluxRequiresDimensionsToBeMultipleOf16), la largeur de la bounding box mise à l'échelle est {{width}}",
"canvasIsCompositing": "La Toile est occupée (en composition)",
"collectionTooFewItems": "trop peu d'éléments, minimum {{minItems}}",
"collectionTooManyItems": "trop d'éléments, maximum {{maxItems}}",
"canvasIsCompositing": "La toile est en train de composer",
"collectionTooFewItems": "{{nodeLabel}} -> {{fieldLabel}} : trop peu d'éléments, minimum {{minItems}}",
"collectionTooManyItems": "{{nodeLabel}} -> {{fieldLabel}} : trop d'éléments, maximum {{maxItems}}",
"canvasIsSelectingObject": "La toile est occupée (sélection d'objet)",
"emptyBatches": "lots vides",
"batchNodeNotConnected": "Noeud de lots non connecté : {{label}}",
"fluxModelMultipleControlLoRAs": "Vous ne pouvez utiliser qu'un seul Control LoRA à la fois",
"collectionNumberLTMin": "{{value}} < {{minimum}} (incl. min)",
"collectionNumberGTMax": "{{value}} > {{maximum}} (incl. max)",
"collectionNumberGTExclusiveMax": "{{value}} >= {{exclusiveMaximum}} (max exc)",
"batchNodeEmptyCollection": "Certains nœuds de lot ont des collections vides",
"batchNodeCollectionSizeMismatch": "Non-concordance de taille de collection sur le lot {{batchGroupId}}",
"collectionStringTooLong": "trop long, max {{maxLength}}",
"collectionNumberNotMultipleOf": "{{value}} n'est pas un multiple de {{multipleOf}}",
"collectionEmpty": "collection vide",
"collectionStringTooShort": "trop court, min {{minLength}}",
"collectionNumberLTExclusiveMin": "{{value}} <= {{exclusiveMinimum}} (min exc)",
"batchNodeCollectionSizeMismatchNoGroupId": "Taille de collection de groupe par lot non conforme"
"batchNodeNotConnected": "Noeud de lots non connecté : {{label}}"
},
"negativePromptPlaceholder": "Prompt Négatif",
"positivePromptPlaceholder": "Prompt Positif",
@@ -533,13 +501,7 @@
"uploadFailedInvalidUploadDesc_withCount_one": "Doit être au maximum une image PNG ou JPEG.",
"uploadFailedInvalidUploadDesc_withCount_many": "Doit être au maximum {{count}} images PNG ou JPEG.",
"uploadFailedInvalidUploadDesc_withCount_other": "Doit être au maximum {{count}} images PNG ou JPEG.",
"addedToUncategorized": "Ajouté aux ressources de la planche $t(boards.uncategorized)",
"pasteSuccess": "Collé à {{destination}}",
"pasteFailed": "Échec du collage",
"outOfMemoryErrorDescLocal": "Suivez notre <LinkComponent>guide Low VRAM</LinkComponent> pour réduire les OOMs.",
"unableToCopy": "Incapable de Copier",
"unableToCopyDesc": "Votre navigateur ne prend pas en charge l'accès au presse-papiers. Les utilisateurs de Firefox peuvent peut-être résoudre ce problème en suivant ",
"unableToCopyDesc_theseSteps": "ces étapes"
"addedToUncategorized": "Ajouté aux ressources de la planche $t(boards.uncategorized)"
},
"accessibility": {
"uploadImage": "Importer une image",
@@ -697,14 +659,7 @@
"iterations_many": "Itérations",
"iterations_other": "Itérations",
"back": "fin",
"batchSize": "Taille de lot",
"retryFailed": "Problème de nouvelle tentative de l'élément",
"retrySucceeded": "Élément Retenté",
"retryItem": "Réessayer l'élement",
"cancelAllExceptCurrentQueueItemAlertDialog": "Annuler tous les éléments de la file d'attente, sauf celui en cours, arrêtera les éléments en attente mais permettra à celui en cours de se terminer.",
"cancelAllExceptCurrentQueueItemAlertDialog2": "Êtes-vous sûr de vouloir annuler tous les éléments en attente dans la file d'attente?",
"cancelAllExceptCurrentTooltip": "Annuler tout sauf l'élément actuel",
"confirm": "Confirmer"
"batchSize": "Taille de lot"
},
"prompt": {
"noMatchingTriggers": "Pas de déclancheurs correspondants",
@@ -1076,9 +1031,7 @@
"controlNetWeight": {
"heading": "Poids",
"paragraphs": [
"Poids du Control Adapter. Un poids plus élevé aura un impact plus important sur l'image finale.",
"• Poids plus élevé (.75-2) : Crée un impact plus significatif sur le résultat final.",
"• Poids inférieur (0-.75) : Crée un impact plus faible sur le résultat final."
"Poids du Control Adapter. Un poids plus élevé aura un impact plus important sur l'image finale."
]
},
"compositingMaskAdjustments": {
@@ -1123,9 +1076,8 @@
"controlNetBeginEnd": {
"heading": "Pourcentage de début / de fin d'étape",
"paragraphs": [
"Ce paramètre détérmine quelle portion du processus de débruitage (génération) utilisera cette couche comme guide.",
"En général, les Control Adapter appliqués au début du processus guident la composition, tandis que les Control Adapter appliqués à la fin guident les détails.",
"• Étape de fin (%): Spécifie quand arrêter d'appliquer le guide de cette couche et revenir aux guides généraux du modèle et aux autres paramètres."
"La partie du processus de débruitage à laquelle le Control Adapter sera appliqué.",
"En général, les Control Adapter appliqués au début du processus guident la composition, tandis que les Control Adapter appliqués à la fin guident les détails."
]
},
"controlNetControlMode": {
@@ -1490,8 +1442,7 @@
"showDynamicPrompts": "Afficher les Prompts dynamiques",
"dynamicPrompts": "Prompts Dynamiques",
"promptsPreview": "Prévisualisation des Prompts",
"loading": "Génération des Pompts Dynamiques...",
"promptsToGenerate": "Prompts à générer"
"loading": "Génération des Pompts Dynamiques..."
},
"metadata": {
"positivePrompt": "Prompt Positif",
@@ -1702,22 +1653,7 @@
"internalDesc": "Cette invocation est utilisée internalement par Invoke. En fonction des mises à jours il est possible que des changements y soit effectués ou qu'elle soit supprimé sans prévention.",
"splitOn": "Diviser sur",
"generatorNoValues": "vide",
"addItem": "Ajouter un élément",
"specialDesc": "Cette invocation nécessite un traitement spécial dans l'application. Par exemple, les nœuds Batch sont utilisés pour mettre en file d'attente plusieurs graphes à partir d'un seul workflow.",
"unableToUpdateNode": "La mise à jour du nœud a échoué : nœud {{node}} de type {{type}} (peut nécessiter la suppression et la recréation).",
"deletedMissingNodeFieldFormElement": "Champ de formulaire manquant supprimé : nœud {{nodeId}} champ {{fieldName}}",
"nodeName": "Nom du nœud",
"description": "Description",
"loadWorkflowDesc": "Charger le workflow?",
"missingSourceOrTargetNode": "Nœud source ou cible manquant",
"generatorImagesCategory": "Catégorie",
"generatorImagesFromBoard": "Images de la Planche",
"missingSourceOrTargetHandle": "Manque de gestionnaire source ou cible",
"loadingTemplates": "Chargement de {{name}}",
"loadWorkflowDesc2": "Votre workflow actuel contient des modifications non enregistrées.",
"generatorImages_one": "{{count}} image",
"generatorImages_many": "{{count}} images",
"generatorImages_other": "{{count}} images"
"addItem": "Ajouter un élément"
},
"models": {
"noMatchingModels": "Aucun modèle correspondant",
@@ -1776,41 +1712,13 @@
"deleteWorkflow2": "Êtes-vous sûr de vouloir supprimer ce Workflow? Cette action ne peut pas être annulé.",
"download": "Télécharger",
"copyShareLinkForWorkflow": "Copier le lien de partage pour le Workflow",
"delete": "Supprimer",
"builder": {
"component": "Composant",
"numberInput": "Entrée de nombre",
"slider": "Curseur",
"both": "Les deux",
"singleLine": "Ligne unique",
"multiLine": "Multi Ligne",
"headingPlaceholder": "En-tête vide",
"emptyRootPlaceholderEditMode": "Faites glisser un élément de formulaire ou un champ de nœud ici pour commencer.",
"emptyRootPlaceholderViewMode": "Cliquez sur Modifier pour commencer à créer un formulaire pour ce workflow.",
"containerPlaceholder": "Conteneur Vide",
"row": "Ligne",
"column": "Colonne",
"layout": "Mise en page",
"nodeField": "Champ de nœud",
"zoomToNode": "Zoomer sur le nœud",
"nodeFieldTooltip": "Pour ajouter un champ de nœud, cliquez sur le petit bouton plus sur le champ dans l'Éditeur de Workflow, ou faites glisser le champ par son nom dans le formulaire.",
"addToForm": "Ajouter au formulaire",
"label": "Étiquette",
"textPlaceholder": "Texte vide",
"builder": "Constructeur de Formulaire",
"resetAllNodeFields": "Réinitialiser tous les champs de nœud",
"deleteAllElements": "Supprimer tous les éléments de formulaire",
"workflowBuilderAlphaWarning": "Le constructeur de workflow est actuellement en version alpha. Il peut y avoir des changements majeurs avant la version stable.",
"showDescription": "Afficher la description"
},
"openLibrary": "Ouvrir la Bibliothèque"
"delete": "Supprimer"
},
"whatsNew": {
"whatsNewInInvoke": "Quoi de neuf dans Invoke",
"watchRecentReleaseVideos": "Regarder les vidéos des dernières versions",
"items": [
"<StrongComponent>FLUX Guidage Régional (bêta)</StrongComponent> : Notre version bêta de FLUX Guidage Régional est en ligne pour le contrôle des prompt régionaux.",
"Autres améliorations : mise en file d'attente par lots plus rapide, meilleur redimensionnement, sélecteur de couleurs amélioré et nœuds de métadonnées."
"<StrongComponent>FLUX Guidage Régional (bêta)</StrongComponent> : Notre version bêta de FLUX Guidage Régional est en ligne pour le contrôle des prompt régionaux."
],
"readReleaseNotes": "Notes de version",
"watchUiUpdatesOverview": "Aperçu des mises à jour de l'interface utilisateur"
@@ -1924,49 +1832,7 @@
"cancel": "Annuler",
"advanced": "Avancé",
"processingLayerWith": "Calque de traitement avec le filtre {{type}}.",
"forMoreControl": "Pour plus de contrôle, cliquez sur Avancé ci-dessous.",
"adjust_image": {
"b": "B (LAB)",
"blue": "Bleu (RGBA)",
"alpha": "Alpha (RGBA)",
"magenta": "Magenta (CMJN)",
"yellow": "Jaune (CMJN)",
"cb": "Cb (YCbCr)",
"cr": "Cr (YCbCr)",
"cyan": "Cyan (CMJN)",
"label": "Ajuster l'image",
"description": "Ajuste le canal sélectionné d'une image.",
"channel": "Canal",
"value_setting": "Valeur",
"scale_values": "Valeurs d'échelle",
"red": "Rouge (RGBA)",
"green": "Vert (RGBA)",
"black": "Noir (CMJN)",
"hue": "Teinte (HSV)",
"saturation": "Saturation (HSV)",
"value": "Valeur (HSV)",
"luminosity": "Luminosité (LAB)",
"a": "A (LAB)",
"y": "Y (YCbCr)"
},
"img_blur": {
"label": "Flou de l'image",
"blur_type": "Type de flou",
"box_type": "Boîte",
"description": "Floute la couche sélectionnée.",
"blur_radius": "Rayon",
"gaussian_type": "Gaussien"
},
"img_noise": {
"label": "Image de bruit",
"description": "Ajoute du bruit à la couche sélectionnée.",
"gaussian_type": "Gaussien",
"size": "Taille du bruit",
"noise_amount": "Quantité",
"noise_type": "Type de bruit",
"salt_and_pepper_type": "Sel et Poivre",
"noise_color": "Bruit coloré"
}
"forMoreControl": "Pour plus de contrôle, cliquez sur Avancé ci-dessous."
},
"canvasContextMenu": {
"saveToGalleryGroup": "Enregistrer dans la galerie",
@@ -1980,10 +1846,7 @@
"newGlobalReferenceImage": "Nouvelle image de référence globale",
"newControlLayer": "Nouveau couche de contrôle",
"newInpaintMask": "Nouveau Masque Inpaint",
"newRegionalGuidance": "Nouveau Guide Régional",
"copyToClipboard": "Copier dans le presse-papiers",
"copyBboxToClipboard": "Copier Bbox dans le presse-papiers",
"copyCanvasToClipboard": "Copier la Toile dans le presse-papiers"
"newRegionalGuidance": "Nouveau Guide Régional"
},
"bookmark": "Marque-page pour Changement Rapide",
"saveLayerToAssets": "Enregistrer la couche dans les ressources",
@@ -2149,10 +2012,7 @@
"ipAdapterMethod": "Méthode d'IP Adapter",
"full": "Complet",
"style": "Style uniquement",
"composition": "Composition uniquement",
"fullDesc": "Applique le style visuel (couleurs, textures) et la composition (mise en page, structure).",
"styleDesc": "Applique un style visuel (couleurs, textures) sans tenir compte de sa mise en page.",
"compositionDesc": "Réplique la mise en page et la structure tout en ignorant le style de la référence."
"composition": "Composition uniquement"
},
"fitBboxToLayers": "Ajuster la bounding box aux calques",
"regionIsEmpty": "La zone sélectionnée est vide",
@@ -2235,40 +2095,7 @@
"asRasterLayerResize": "En tant que $t(controlLayers.rasterLayer) (Redimensionner)",
"asControlLayer": "En tant que $t(controlLayers.controlLayer)",
"asControlLayerResize": "En $t(controlLayers.controlLayer) (Redimensionner)",
"newSession": "Nouvelle session",
"warnings": {
"controlAdapterIncompatibleBaseModel": "modèle de base de la couche de contrôle incompatible",
"controlAdapterNoControl": "aucun contrôle sélectionné/dessiné",
"rgNoPromptsOrIPAdapters": "pas de textes d'instructions ni d'images de référence",
"rgAutoNegativeNotSupported": "Auto-négatif non pris en charge pour le modèle de base sélectionné",
"rgNoRegion": "aucune région dessinée",
"ipAdapterNoModelSelected": "aucun modèle d'image de référence sélectionné",
"rgReferenceImagesNotSupported": "Les images de référence régionales ne sont pas prises en charge pour le modèle de base sélectionné",
"problemsFound": "Problèmes trouvés",
"unsupportedModel": "couche non prise en charge pour le modèle de base sélectionné",
"rgNegativePromptNotSupported": "Prompt négatif non pris en charge pour le modèle de base sélectionné",
"ipAdapterIncompatibleBaseModel": "modèle de base d'image de référence incompatible",
"controlAdapterNoModelSelected": "aucun modèle de couche de contrôle sélectionné",
"ipAdapterNoImageSelected": "Aucune image de référence sélectionnée."
},
"pasteTo": "Coller vers",
"pasteToAssets": "Ressources",
"pasteToAssetsDesc": "Coller dans les ressources",
"pasteToBbox": "Bbox",
"regionCopiedToClipboard": "{{region}} Copié dans le presse-papiers",
"copyRegionError": "Erreur de copie {{region}}",
"pasteToCanvas": "Toile",
"errors": {
"unableToFindImage": "Impossible de trouver l'image",
"unableToLoadImage": "Impossible de charger l'image"
},
"referenceImageRegional": "Image de référence (régionale)",
"pasteToBboxDesc": "Nouvelle couche (dans Bbox)",
"pasteToCanvasDesc": "Nouvelle couche (dans la Toile)",
"useImage": "Utiliser l'image",
"pastedTo": "Collé à {{destination}}",
"referenceImageEmptyState": "<UploadButton>Séléctionner une image</UploadButton> ou faites glisser une image depuis la <GalleryButton>galerie</GalleryButton> sur cette couche pour commencer.",
"referenceImageGlobal": "Image de référence (Globale)"
"newSession": "Nouvelle session"
},
"upscaling": {
"exceedsMaxSizeDetails": "La limite maximale d'agrandissement est de {{maxUpscaleDimension}}x{{maxUpscaleDimension}} pixels. Veuillez essayer une image plus petite ou réduire votre sélection d'échelle.",
@@ -2348,8 +2175,7 @@
"queue": "File d'attente",
"events": "Événements",
"metadata": "Métadonnées",
"gallery": "Galerie",
"dnd": "Glisser et déposer"
"gallery": "Galerie"
},
"logLevel": {
"trace": "Trace",
@@ -2366,8 +2192,7 @@
"toGetStarted": "Pour commencer, saisissez un prompt dans la boîte et cliquez sur <StrongComponent>Invoke</StrongComponent> pour générer votre première image. Sélectionnez un template de prompt pour améliorer les résultats. Vous pouvez choisir de sauvegarder vos images directement dans la <StrongComponent>Galerie</StrongComponent> ou de les modifier sur la <StrongComponent>Toile</StrongComponent>.",
"gettingStartedSeries": "Vous souhaitez plus de conseils? Consultez notre <LinkComponent>Série de démarrage</LinkComponent> pour des astuces sur l'exploitation du plein potentiel de l'Invoke Studio.",
"noModelsInstalled": "Il semble qu'aucun modèle ne soit installé",
"toGetStartedLocal": "Pour commencer, assurez-vous de télécharger ou d'importer des modèles nécessaires pour exécuter Invoke. Ensuite, saisissez le prompt dans la boîte et cliquez sur <StrongComponent>Invoke</StrongComponent> pour générer votre première image. Sélectionnez un template de prompt pour améliorer les résultats. Vous pouvez choisir de sauvegarder vos images directement sur <StrongComponent>Galerie</StrongComponent> ou les modifier sur la <StrongComponent>Toile</StrongComponent>.",
"lowVRAMMode": "Pour de meilleures performances, suivez notre <LinkComponent>guide Low VRAM</LinkComponent>."
"toGetStartedLocal": "Pour commencer, assurez-vous de télécharger ou d'importer des modèles nécessaires pour exécuter Invoke. Ensuite, saisissez le prompt dans la boîte et cliquez sur <StrongComponent>Invoke</StrongComponent> pour générer votre première image. Sélectionnez un template de prompt pour améliorer les résultats. Vous pouvez choisir de sauvegarder vos images directement sur <StrongComponent>Galerie</StrongComponent> ou les modifier sur la <StrongComponent>Toile</StrongComponent>."
},
"upsell": {
"shareAccess": "Partager l'accès",
@@ -2415,8 +2240,7 @@
"description": "Introduction à l'ajout d'images de référence et IP Adapters globaux."
},
"howDoIUseInpaintMasks": {
"title": "Comment utiliser les masques d'inpainting?",
"description": "Comment appliquer des masques de retourche pour la correction et la variation d'image."
"title": "Comment utiliser les masques d'inpainting?"
},
"creatingYourFirstImage": {
"title": "Créer votre première image",
@@ -2436,10 +2260,5 @@
"studioSessionsDesc2": "Rejoignez notre <DiscordLink /> pour participer aux sessions en direct et poser vos questions. Les sessions sont ajoutée dans la playlist la semaine suivante.",
"supportVideos": "Vidéos d'assistance",
"controlCanvas": "Contrôler la toile"
},
"modelCache": {
"clear": "Effacer le cache du modèle",
"clearSucceeded": "Cache du modèle effacée",
"clearFailed": "Problème de nettoyage du cache du modèle"
}
}

View File

@@ -105,11 +105,7 @@
"resetToDefaults": "Ripristina le impostazioni predefinite",
"seed": "Seme",
"combinatorial": "Combinatorio",
"count": "Quantità",
"board": "Bacheca",
"layout": "Schema",
"row": "Riga",
"column": "Colonna"
"count": "Quantità"
},
"gallery": {
"galleryImageSize": "Dimensione dell'immagine",
@@ -177,8 +173,7 @@
"assetsTab": "File che hai caricato per usarli nei tuoi progetti.",
"boardsSettings": "Impostazioni Bacheche",
"imagesSettings": "Impostazioni Immagini Galleria",
"assets": "Risorse",
"images": "Immagini"
"assets": "Risorse"
},
"hotkeys": {
"searchHotkeys": "Cerca tasti di scelta rapida",
@@ -704,12 +699,12 @@
"batchNodeEmptyCollection": "Alcuni nodi lotto hanno raccolte vuote",
"emptyBatches": "lotti vuoti",
"batchNodeCollectionSizeMismatch": "Le dimensioni della raccolta nel Lotto {{batchGroupId}} non corrispondono",
"invalidBatchConfigurationCannotCalculate": "Configurazione lotto non valida; impossibile calcolare",
"collectionStringTooShort": "troppo corto, minimo {{minLength}}",
"collectionNumberNotMultipleOf": "{{value}} non è multiplo di {{multipleOf}}",
"collectionNumberLTMin": "{{value}} < {{minimum}} (incr min)",
"collectionNumberGTExclusiveMax": "{{value}} >= {{exclusiveMaximum}} (excl max)",
"collectionNumberLTExclusiveMin": "{{value}} <= {{exclusiveMinimum}} (excl min)",
"collectionEmpty": "raccolta vuota"
"collectionNumberLTExclusiveMin": "{{value}} <= {{exclusiveMinimum}} (excl min)"
},
"useCpuNoise": "Usa la CPU per generare rumore",
"iterations": "Iterazioni",
@@ -926,8 +921,8 @@
"boolean": "Booleani",
"node": "Nodo",
"collection": "Raccolta",
"cannotConnectInputToInput": "Impossibile collegare ingresso a ingresso",
"cannotConnectOutputToOutput": "Impossibile collegare uscita ad uscita",
"cannotConnectInputToInput": "Impossibile collegare Input a Input",
"cannotConnectOutputToOutput": "Impossibile collegare Output ad Output",
"cannotConnectToSelf": "Impossibile connettersi a se stesso",
"mismatchedVersion": "Nodo non valido: il nodo {{node}} di tipo {{type}} ha una versione non corrispondente (provare ad aggiornare?)",
"loadingNodes": "Caricamento nodi...",
@@ -1020,21 +1015,7 @@
"generatorNRandomValues_one": "{{count}} valore casuale",
"generatorNRandomValues_many": "{{count}} valori casuali",
"generatorNRandomValues_other": "{{count}} valori casuali",
"arithmeticSequence": "Sequenza aritmetica",
"nodeName": "Nome del nodo",
"loadWorkflowDesc": "Caricare il flusso di lavoro?",
"loadWorkflowDesc2": "Il flusso di lavoro corrente presenta modifiche non salvate.",
"downloadWorkflowError": "Errore durante lo scaricamento del flusso di lavoro",
"deletedMissingNodeFieldFormElement": "Campo modulo mancante eliminato: nodo {{nodeId}} campo {{fieldName}}",
"loadingTemplates": "Caricamento {{name}}",
"unableToUpdateNode": "Aggiornamento del nodo non riuscito: nodo {{node}} di tipo {{type}} (potrebbe essere necessario eliminarlo e ricrearlo)",
"description": "Descrizione",
"generatorImagesCategory": "Categoria",
"generatorImages_one": "{{count}} immagine",
"generatorImages_many": "{{count}} immagini",
"generatorImages_other": "{{count}} immagini",
"generatorImagesFromBoard": "Immagini dalla Bacheca",
"missingSourceOrTargetNode": "Nodo sorgente o di destinazione mancante"
"arithmeticSequence": "Sequenza aritmetica"
},
"boards": {
"autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1160,10 +1141,7 @@
"cancelAllExceptCurrentQueueItemAlertDialog2": "Vuoi davvero annullare tutti gli elementi in coda in sospeso?",
"confirm": "Conferma",
"cancelAllExceptCurrentQueueItemAlertDialog": "L'annullamento di tutti gli elementi della coda, eccetto quello corrente, interromperà gli elementi in sospeso ma consentirà il completamento di quello in corso.",
"cancelAllExceptCurrentTooltip": "Annulla tutto tranne l'elemento corrente",
"retrySucceeded": "Elemento rieseguito",
"retryItem": "Riesegui elemento",
"retryFailed": "Problema riesecuzione elemento"
"cancelAllExceptCurrentTooltip": "Annulla tutto tranne l'elemento corrente"
},
"models": {
"noMatchingModels": "Nessun modello corrispondente",
@@ -1741,38 +1719,7 @@
"download": "Scarica",
"copyShareLink": "Copia Condividi Link",
"copyShareLinkForWorkflow": "Copia Condividi Link del Flusso di lavoro",
"delete": "Elimina",
"openLibrary": "Apri la libreria",
"builder": {
"resetAllNodeFields": "Reimposta tutti i campi del nodo",
"row": "Riga",
"nodeField": "Campo del nodo",
"slider": "Cursore",
"emptyRootPlaceholderEditMode": "Per iniziare, trascina qui un elemento del modulo o un campo nodo.",
"containerPlaceholder": "Contenitore vuoto",
"headingPlaceholder": "Titolo vuoto",
"column": "Colonna",
"nodeFieldTooltip": "Per aggiungere un campo nodo, fare clic sul piccolo pulsante con il segno più sul campo nell'editor del flusso di lavoro, oppure trascinare il campo in base al suo nome nel modulo.",
"label": "Etichetta",
"deleteAllElements": "Elimina tutti gli elementi del modulo",
"addToForm": "Aggiungi al Modulo",
"layout": "Schema",
"builder": "Generatore Modulo",
"zoomToNode": "Zoom sul nodo",
"component": "Componente",
"showDescription": "Mostra Descrizione",
"singleLine": "Linea singola",
"multiLine": "Linea Multipla",
"both": "Entrambi",
"emptyRootPlaceholderViewMode": "Fare clic su Modifica per iniziare a creare un modulo per questo flusso di lavoro.",
"textPlaceholder": "Testo vuoto",
"workflowBuilderAlphaWarning": "Il generatore di flussi di lavoro è attualmente in versione alpha. Potrebbero esserci cambiamenti radicali prima della versione stabile.",
"heading": "Intestazione",
"divider": "Divisore",
"container": "Contenitore",
"text": "Testo",
"numberInput": "Ingresso numerico"
}
"delete": "Elimina"
},
"accordions": {
"compositing": {
@@ -2194,7 +2141,7 @@
"controlLayerEmptyState": "<UploadButton>Carica un'immagine</UploadButton>, trascina un'immagine dalla <GalleryButton>galleria</GalleryButton> su questo livello oppure disegna sulla tela per iniziare.",
"useImage": "Usa immagine",
"resetGenerationSettings": "Ripristina impostazioni di generazione",
"referenceImageEmptyState": "Per iniziare, <UploadButton>carica un'immagine</UploadButton>, trascina un'immagine dalla <GalleryButton>galleria</GalleryButton>, oppure <PullBboxButton>trascina il riquadro di delimitazione in questo livello</PullBboxButton> su questo livello.",
"referenceImageEmptyState": "Per iniziare, <UploadButton>carica un'immagine</UploadButton> oppure trascina un'immagine dalla <GalleryButton>galleria</GalleryButton> su questo livello.",
"asRasterLayer": "Come $t(controlLayers.rasterLayer)",
"asRasterLayerResize": "Come $t(controlLayers.rasterLayer) (Ridimensiona)",
"asControlLayer": "Come $t(controlLayers.controlLayer)",
@@ -2227,11 +2174,7 @@
"pasteToCanvas": "Tela",
"pasteToCanvasDesc": "Nuovo livello (nella Tela)",
"pastedTo": "Incollato su {{destination}}",
"regionCopiedToClipboard": "{{region}} Copiato negli appunti",
"errors": {
"unableToFindImage": "Impossibile trovare l'immagine",
"unableToLoadImage": "Impossibile caricare l'immagine"
}
"regionCopiedToClipboard": "{{region}} Copiato negli appunti"
},
"ui": {
"tabs": {
@@ -2330,8 +2273,12 @@
"watchRecentReleaseVideos": "Guarda i video su questa versione",
"watchUiUpdatesOverview": "Guarda le novità dell'interfaccia",
"items": [
"Editor del flusso di lavoro: nuovo generatore di moduli trascina-e-rilascia per una creazione più facile del flusso di lavoro.",
"Altri miglioramenti: messa in coda dei lotti più rapida, migliore ampliamento, selettore colore migliorato e nodi metadati."
"Impostazioni predefinite VRAM migliorate",
"Cancellazione della cache del modello su richiesta",
"Compatibilità estesa FLUX LoRA",
"Filtro Regola Immagine su Tela",
"Annulla tutto tranne l'elemento della coda corrente",
"Copia da e incolla sulla Tela"
]
},
"system": {

View File

@@ -32,29 +32,29 @@
"learnMore": "もっと学ぶ",
"random": "ランダム",
"batch": "バッチマネージャー",
"advanced": "高度",
"advanced": "高度な設定",
"created": "作成済",
"green": "緑",
"blue": "青",
"alpha": "アルファ",
"outpaint": "outpaint",
"outpaint": "アウトペイント",
"unknown": "不明",
"updated": "更新済",
"add": "追加",
"ai": "ai",
"ai": "AI",
"copyError": "$t(gallery.copy) エラー",
"data": "データ",
"template": "テンプレート",
"red": "赤",
"or": "または",
"checkpoint": "Checkpoint",
"checkpoint": "チェックポイント",
"direction": "方向",
"simple": "シンプル",
"save": "保存",
"saveAs": "名前をつけて保存",
"somethingWentWrong": "何かの問題が発生しました",
"details": "詳細",
"inpaint": "inpaint",
"inpaint": "インペイント",
"delete": "削除",
"nextPage": "次のページ",
"copy": "コピー",
@@ -70,12 +70,12 @@
"unknownError": "未知のエラー",
"orderBy": "並び順:",
"enabled": "有効",
"notInstalled": "未 $t(common.installed)",
"notInstalled": "未インストール",
"positivePrompt": "ポジティブプロンプト",
"negativePrompt": "ネガティブプロンプト",
"selected": "選択済み",
"aboutDesc": "Invokeを業務で利用する場合はマークしてください:",
"beta": "Beta",
"beta": "ベータ",
"disabled": "無効",
"editor": "エディタ",
"safetensors": "Safetensors",
@@ -93,27 +93,7 @@
"reset": "リセット",
"none": "なし",
"new": "新規",
"close": "閉じる",
"warnings": "警告",
"dontShowMeThese": "次回から表示しない",
"goTo": "移動",
"generating": "生成中",
"loadingModel": "モデルをロード中",
"layout": "レイアウト",
"step": "ステップ",
"start": "開始",
"count": "回数",
"end": "終了",
"min": "最小",
"max": "最大",
"values": "値",
"resetToDefaults": "デフォルトに戻す",
"row": "行",
"column": "列",
"board": "ボード",
"seed": "シード",
"combinatorial": "組み合わせ",
"aboutHeading": "想像力をこの手に"
"close": "閉じる"
},
"gallery": {
"galleryImageSize": "画像のサイズ",
@@ -129,7 +109,7 @@
"currentlyInUse": "この画像は現在下記の機能を使用しています:",
"drop": "ドロップ",
"dropOrUpload": "$t(gallery.drop) またはアップロード",
"deleteImage_other": "画像 {{count}} 枚を削除",
"deleteImage_other": "画像を削除",
"deleteImagePermanent": "削除された画像は復元できません。",
"download": "ダウンロード",
"unableToLoad": "ギャラリーをロードできません",
@@ -175,12 +155,7 @@
"displayBoardSearch": "ボード検索",
"displaySearch": "画像を検索",
"boardsSettings": "ボード設定",
"imagesSettings": "ギャラリー画像設定",
"selectAllOnPage": "ページ上のすべてを選択",
"images": "画像",
"assetsTab": "プロジェクトで使用するためにアップロードされたファイル。",
"imagesTab": "Invoke内で作成および保存された画像。",
"assets": "アセット"
"imagesSettings": "ギャラリー画像設定"
},
"hotkeys": {
"searchHotkeys": "ホットキーを検索",
@@ -205,121 +180,44 @@
},
"canvas": {
"redo": {
"title": "やり直し",
"desc": "最後のキャンバス操作をやり直します。"
"title": "やり直し"
},
"transformSelected": {
"title": "変形",
"desc": "選択したレイヤーを変形します。"
"title": "変形"
},
"undo": {
"title": "取り消し",
"desc": "最後のキャンバス操作を取り消します。"
"title": "取り消し"
},
"selectEraserTool": {
"title": "消しゴムツール",
"desc": "消しゴムツールを選択します。"
"title": "消しゴムツール"
},
"cancelTransform": {
"title": "変形をキャンセル",
"desc": "保留中の変形をキャンセルします。"
"title": "変形をキャンセル"
},
"resetSelected": {
"title": "レイヤーをリセット",
"desc": "選択したレイヤーをリセットします。この操作はInpaint MaskおよびRegional Guidanceにのみ適用されます。"
"title": "レイヤーをリセット"
},
"applyTransform": {
"title": "変形を適用",
"desc": "保留中の変形を選択したレイヤーに適用します。"
"title": "変形を適用"
},
"selectColorPickerTool": {
"title": "スポイトツール",
"desc": "スポイトツールを選択します。"
"title": "スポイトツール"
},
"fitBboxToCanvas": {
"title": "バウンディングボックスをキャンバスにフィット",
"desc": "バウンディングボックスがキャンバスに収まるように表示を拡大、位置調整します。"
"title": "バウンディングボックスをキャンバスにフィット"
},
"selectBrushTool": {
"title": "ブラシツール",
"desc": "ブラシツールを選択します。"
"title": "ブラシツール"
},
"selectMoveTool": {
"title": "移動ツール",
"desc": "移動ツールを選択します。"
"title": "移動ツール"
},
"selectBboxTool": {
"title": "バウンディングボックスツール",
"desc": "バウンディングボックスツールを選択します。"
"title": "バウンディングボックスツール"
},
"title": "キャンバス",
"fitLayersToCanvas": {
"title": "レイヤーをキャンバスにフィット",
"desc": "すべての表示レイヤーがキャンバスに収まるように表示を拡大、位置調整します。"
},
"setZoomTo400Percent": {
"desc": "キャンバスのズームを400%に設定します。",
"title": "400%にズーム"
},
"setZoomTo800Percent": {
"title": "800%にズーム",
"desc": "キャンバスのズームを800%に設定します。"
},
"quickSwitch": {
"title": "レイヤーのクイックスイッチ",
"desc": "最後に選択した2つのレイヤー間を切り替えます。レイヤーがブックマークされている場合、常にそのレイヤーと最後に選択したブックマークされていないレイヤーの間を切り替えます。"
},
"nextEntity": {
"title": "次のレイヤー",
"desc": "リスト内の次のレイヤーを選択します。"
},
"filterSelected": {
"title": "フィルター",
"desc": "選択したレイヤーをフィルターします。RasterおよびControlレイヤーにのみ適用されます。"
},
"prevEntity": {
"desc": "リスト内の前のレイヤーを選択します。",
"title": "前のレイヤー"
},
"setFillToWhite": {
"title": "ツール色を白に設定",
"desc": "現在のツールの色を白色に設定します。"
},
"selectViewTool": {
"title": "表示ツール",
"desc": "表示ツールを選択します。"
},
"setZoomTo100Percent": {
"title": "100%にズーム",
"desc": "キャンバスのズームを100%に設定します。"
},
"deleteSelected": {
"desc": "選択したレイヤーを削除します。",
"title": "レイヤーを削除"
},
"cancelFilter": {
"desc": "保留中のフィルターをキャンセルします。",
"title": "フィルターをキャンセル"
},
"applyFilter": {
"title": "フィルターを適用",
"desc": "保留中のフィルターを選択したレイヤーに適用します。"
},
"setZoomTo200Percent": {
"title": "200%にズーム",
"desc": "キャンバスのズームを200%に設定します。"
},
"decrementToolWidth": {
"title": "ツール幅を縮小する",
"desc": "選択中のブラシまたは消しゴムツールの幅を減少させます。"
},
"incrementToolWidth": {
"desc": "選択中のブラシまたは消しゴムツールの幅を増加させます。",
"title": "ツール幅を増加する"
},
"selectRectTool": {
"title": "矩形ツール",
"desc": "矩形ツールを選択します。"
"title": "レイヤーをキャンバスにフィット"
}
},
"workflows": {
@@ -328,13 +226,6 @@
},
"redo": {
"title": "やり直し"
},
"title": "ワークフロー",
"pasteSelection": {
"title": "ペースト"
},
"copySelection": {
"title": "コピー"
}
},
"app": {
@@ -344,62 +235,16 @@
},
"title": "アプリケーション",
"invoke": {
"title": "生成",
"desc": "生成をキューに追加し、キューの末尾に加えます。"
"title": "Invoke"
},
"cancelQueueItem": {
"title": "キャンセル",
"desc": "現在処理中のキュー項目をキャンセルします。"
"title": "キャンセル"
},
"clearQueue": {
"title": "キューをクリア",
"desc": "すべてのキュー項目をキャンセルして消去します。"
},
"selectCanvasTab": {
"desc": "キャンバスタブを選択します。",
"title": "キャンバスタブを選択"
},
"selectUpscalingTab": {
"desc": "アップスケーリングタブを選択します。",
"title": "アップスケーリングタブを選択"
},
"toggleRightPanel": {
"desc": "右パネルを表示または非表示。",
"title": "右パネルをトグル"
},
"selectModelsTab": {
"title": "モデルタブを選択",
"desc": "モデルタブを選択します。"
},
"invokeFront": {
"desc": "生成をキューに追加し、キューの先頭に加えます。",
"title": "生成(先頭)"
},
"resetPanelLayout": {
"title": "パネルレイアウトをリセット",
"desc": "左パネルと右パネルをデフォルトのサイズとレイアウトにリセットします。"
},
"togglePanels": {
"desc": "左パネルと右パネルを合わせて表示または非表示。",
"title": "パネルをトグル"
},
"selectWorkflowsTab": {
"desc": "ワークフロータブを選択します。",
"title": "ワークフロータブを選択"
},
"selectQueueTab": {
"title": "キュータブを選択",
"desc": "キュータブを選択します。"
},
"focusPrompt": {
"title": "プロンプトにフォーカス",
"desc": "カーソルをポジティブプロンプト欄に移動します。"
"title": "キューをクリア"
}
},
"hotkeys": "ホットキー",
"gallery": {
"title": "ギャラリー"
}
"hotkeys": "ホットキー"
},
"modelManager": {
"modelManager": "モデルマネージャ",
@@ -410,13 +255,13 @@
"name": "名前",
"description": "概要",
"config": "コンフィグ",
"repo_id": "リポジトリID",
"repo_id": "Repo ID",
"width": "幅",
"height": "高さ",
"addModel": "モデルを追加",
"availableModels": "モデルを有効化",
"search": "検索",
"load": "ロード",
"load": "Load",
"active": "active",
"selected": "選択済",
"delete": "削除",
@@ -436,7 +281,7 @@
"modelConverted": "モデル変換が完了しました",
"predictionType": "予測タイプSD 2.x モデルおよび一部のSD 1.x モデル用)",
"selectModel": "モデルを選択",
"advanced": "高度",
"advanced": "高度な設定",
"modelDeleted": "モデルが削除されました",
"convertToDiffusersHelpText2": "このプロセスでは、モデルマネージャーのエントリーを同じモデルのディフューザーバージョンに置き換えます。",
"modelUpdateFailed": "モデル更新が失敗しました",
@@ -449,20 +294,7 @@
"convertToDiffusersHelpText4": "これは一回限りのプロセスです。コンピュータの仕様によっては、約30秒から60秒かかる可能性があります。",
"cancel": "キャンセル",
"uploadImage": "画像をアップロード",
"addModels": "モデルを追加",
"modelName": "モデル名",
"source": "ソース",
"path": "パス",
"modelSettings": "モデル設定",
"vae": "VAE",
"huggingFace": "HuggingFace",
"huggingFaceRepoID": "HuggingFace リポジトリID",
"metadata": "メタデータ",
"loraModels": "LoRA",
"edit": "編集",
"install": "インストール",
"huggingFacePlaceholder": "owner/model-name",
"variant": "Variant"
"addModels": "モデルを追加"
},
"parameters": {
"images": "画像",
@@ -473,7 +305,7 @@
"shuffle": "シャッフル",
"strength": "強度",
"upscaling": "アップスケーリング",
"scale": "スケール",
"scale": "Scale",
"scaleBeforeProcessing": "処理前のスケール",
"scaledWidth": "幅のスケール",
"scaledHeight": "高さのスケール",
@@ -482,7 +314,7 @@
"useSeed": "シード値を使用",
"useAll": "すべてを使用",
"info": "情報",
"showOptionsPanel": "サイドパネルを表示 (O or T)",
"showOptionsPanel": "オプションパネルを表示",
"iterations": "生成回数",
"general": "基本設定",
"setToOptimalSize": "サイズをモデルに最適化",
@@ -496,29 +328,16 @@
"useSize": "サイズを使用",
"postProcessing": "ポストプロセス (Shift + U)",
"denoisingStrength": "ノイズ除去強度",
"recallMetadata": "メタデータを再使用",
"copyImage": "画像をコピー",
"positivePromptPlaceholder": "ポジティブプロンプト",
"negativePromptPlaceholder": "ネガティブプロンプト",
"type": "タイプ",
"cancel": {
"cancel": "キャンセル"
},
"cfgScale": "CFGスケール",
"tileSize": "タイルサイズ",
"coherenceMode": "モード"
"recallMetadata": "メタデータを再使用"
},
"settings": {
"models": "モデル",
"displayInProgress": "生成中の画像を表示",
"displayInProgress": "生成中の画像を表示する",
"confirmOnDelete": "削除時に確認",
"resetWebUI": "WebUIをリセット",
"resetWebUIDesc1": "WebUIのリセットは、画像と保存された設定のキャッシュをリセットするだけです。画像を削除するわけではありません。",
"resetWebUIDesc2": "もしギャラリーに画像が表示されないなど、何か問題が発生した場合はGitHubにissueを提出する前にリセットを試してください。",
"resetComplete": "WebUIはリセットされました。",
"ui": "ユーザーインターフェイス",
"beta": "ベータ",
"developer": "開発者"
"resetComplete": "WebUIはリセットされました。F5を押して再読み込みしてください。"
},
"toast": {
"uploadFailed": "アップロード失敗",
@@ -526,8 +345,7 @@
"imageUploadFailed": "画像のアップロードに失敗しました",
"uploadFailedInvalidUploadDesc": "画像はPNGかJPGである必要があります。",
"sentToUpscale": "アップスケーラーに転送しました",
"imageUploaded": "画像をアップロードしました",
"serverError": "サーバーエラー"
"imageUploaded": "画像をアップロードしました"
},
"accessibility": {
"invokeProgressBar": "進捗バー",
@@ -538,7 +356,7 @@
"menu": "メニュー",
"createIssue": "問題を報告",
"resetUI": "$t(accessibility.reset) UI",
"mode": "モード",
"mode": "モード:",
"about": "Invoke について",
"submitSupportTicket": "サポート依頼を送信する",
"uploadImages": "画像をアップロード",
@@ -555,20 +373,7 @@
"positivePrompt": "ポジティブプロンプト",
"strength": "Image to Image 強度",
"recallParameters": "パラメータを再使用",
"recallParameter": "{{label}} を再使用",
"imageDimensions": "画像サイズ",
"imageDetails": "画像の詳細",
"model": "モデル",
"allPrompts": "すべてのプロンプト",
"cfgScale": "CFGスケール",
"createdBy": "作成:",
"metadata": "メタデータ",
"height": "高さ",
"negativePrompt": "ネガティブプロンプト",
"generationMode": "生成モード",
"vae": "VAE",
"cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)",
"canvasV2Metadata": "キャンバス"
"recallParameter": "{{label}} を再使用"
},
"queue": {
"queueEmpty": "キューが空です",
@@ -600,7 +405,7 @@
"batchQueuedDesc_other": "{{count}} セッションをキューの{{direction}}に追加しました",
"graphQueued": "グラフをキューに追加しました",
"batch": "バッチ",
"clearQueueAlertDialog": "キューをクリアすると、処理中の項目は直ちにキャンセルされ、キューは完全にクリアされます。保留中のフィルターもキャンセルされます。",
"clearQueueAlertDialog": "キューをクリアすると、処理中のアイテムは直ちにキャンセルされ、キューは完全にクリアされます。",
"pending": "保留中",
"resumeFailed": "処理の再開に問題があります",
"clear": "クリア",
@@ -618,7 +423,7 @@
"enqueueing": "バッチをキューに追加",
"cancelBatchFailed": "バッチのキャンセルに問題があります",
"clearQueueAlertDialog2": "キューをクリアしてもよろしいですか?",
"item": "項目",
"item": "アイテム",
"graphFailedToQueue": "グラフをキューに追加できませんでした",
"batchFieldValues": "バッチの詳細",
"openQueue": "キューを開く",
@@ -634,17 +439,7 @@
"upscaling": "アップスケール",
"generation": "生成",
"other": "その他",
"gallery": "ギャラリー",
"cancelAllExceptCurrentQueueItemAlertDialog2": "すべての保留中のキュー項目をキャンセルしてもよいですか?",
"cancelAllExceptCurrentTooltip": "現在の項目を除いてすべてキャンセル",
"origin": "先頭",
"destination": "宛先",
"confirm": "確認",
"retryItem": "項目をリトライ",
"batchSize": "バッチサイズ",
"retryFailed": "項目のリトライに問題があります",
"cancelAllExceptCurrentQueueItemAlertDialog": "現在の項目を除くすべてのキュー項目をキャンセルすると、保留中の項目は停止しますが、進行中の項目は完了します。",
"retrySucceeded": "項目がリトライされました"
"gallery": "ギャラリー"
},
"models": {
"noMatchingModels": "一致するモデルがありません",
@@ -653,14 +448,13 @@
"noModelsAvailable": "使用可能なモデルがありません",
"selectModel": "モデルを選択してください",
"concepts": "コンセプト",
"addLora": "LoRAを追加",
"lora": "LoRA"
"addLora": "LoRAを追加"
},
"nodes": {
"addNode": "ノードを追加",
"boolean": "ブーリアン",
"addNodeToolTip": "ノードを追加 (Shift+A, Space)",
"missingTemplate": "Invalid node: タイプ {{type}} のノード {{node}} にテンプレートがりません(未インストール?)",
"missingTemplate": "テンプレートが見つかりません",
"loadWorkflow": "ワークフローを読み込み",
"hideLegendNodes": "フィールドタイプの凡例を非表示",
"float": "浮動小数点",
@@ -671,7 +465,7 @@
"currentImageDescription": "ノードエディタ内の現在の画像を表示",
"downloadWorkflow": "ワークフローのJSONをダウンロード",
"fieldTypesMustMatch": "フィールドタイプが一致している必要があります",
"edge": "エッジ",
"edge": "輪郭",
"animatedEdgesHelp": "選択したエッジおよび選択したノードに接続されたエッジをアニメーション化します",
"cannotDuplicateConnection": "重複した接続は作れません",
"noWorkflow": "ワークフローがありません",
@@ -690,20 +484,7 @@
"cannotConnectToSelf": "自身のノードには接続できません",
"colorCodeEdges": "カラー-Code Edges",
"loadingNodes": "ノードを読み込み中...",
"scheduler": "スケジューラー",
"version": "バージョン",
"edit": "編集",
"nodeVersion": "ノードバージョン",
"workflowTags": "タグ",
"string": "文字列",
"workflowVersion": "バージョン",
"workflowAuthor": "作者",
"ipAdapter": "IP-Adapter",
"notes": "ノート",
"workflow": "ワークフロー",
"workflowName": "名前",
"workflowNotes": "ノート",
"enum": "Enum"
"scheduler": "スケジューラー"
},
"boards": {
"autoAddBoard": "自動追加するボード",
@@ -725,7 +506,7 @@
"deleteBoard": "ボードの削除",
"deleteBoardAndImages": "ボードと画像の削除",
"deleteBoardOnly": "ボードのみ削除",
"deletedBoardsCannotbeRestored": "削除されたボードは復元できません。\"ボードのみ削除\"を選択すると画像は未分類に移動されます。",
"deletedBoardsCannotbeRestored": "削除されたボードは復元できません",
"movingImagesToBoard_other": "{{count}} の画像をボードに移動:",
"hideBoards": "ボードを隠す",
"assetsWithCount_other": "{{count}} のアセット",
@@ -737,12 +518,7 @@
"archiveBoard": "ボードをアーカイブ",
"archived": "アーカイブ完了",
"unarchiveBoard": "アーカイブされていないボード",
"imagesWithCount_other": "{{count}} の画像",
"updateBoardError": "ボード更新エラー",
"selectedForAutoAdd": "自動追加に選択済み",
"deletedPrivateBoardsCannotbeRestored": "削除されたボードは復元できません。\"ボードのみ削除\"を選択すると画像はその作成者のプライベートな未分類に移動されます。",
"noBoards": "{{boardType}} ボードがありません",
"viewBoards": "ボードを表示"
"imagesWithCount_other": "{{count}} の画像"
},
"invocationCache": {
"invocationCache": "呼び出しキャッシュ",
@@ -794,57 +570,6 @@
},
"paramAspect": {
"heading": "縦横比"
},
"refinerSteps": {
"heading": "ステップ"
},
"paramVAE": {
"heading": "VAE"
},
"scale": {
"heading": "スケール"
},
"refinerScheduler": {
"heading": "スケジューラー"
},
"compositingCoherenceMode": {
"heading": "モード"
},
"paramModel": {
"heading": "モデル"
},
"paramHeight": {
"heading": "高さ"
},
"paramSteps": {
"heading": "ステップ"
},
"ipAdapterMethod": {
"heading": "モード"
},
"paramSeed": {
"heading": "シード"
},
"paramIterations": {
"heading": "生成回数"
},
"controlNet": {
"heading": "ControlNet"
},
"paramWidth": {
"heading": "幅"
},
"lora": {
"heading": "LoRA"
},
"loraWeight": {
"heading": "重み"
},
"patchmatchDownScaleSize": {
"heading": "Downscale"
},
"controlNetWeight": {
"heading": "重み"
}
},
"accordions": {
@@ -854,8 +579,7 @@
"coherenceTab": "コヒーレンスパス"
},
"advanced": {
"title": "高度",
"options": "$t(accordions.advanced.title) オプション"
"title": "高度な設定"
},
"control": {
"title": "コントロール"
@@ -884,11 +608,7 @@
},
"ui": {
"tabs": {
"queue": "キュー",
"canvas": "キャンバス",
"workflows": "ワークフロー",
"models": "モデル",
"gallery": "ギャラリー"
"queue": "キュー"
}
},
"controlLayers": {
@@ -903,8 +623,7 @@
"bboxGroup": "バウンディングボックスから作成",
"cropCanvasToBbox": "キャンバスをバウンディングボックスでクロップ",
"newGlobalReferenceImage": "新規全域参照画像",
"newRegionalReferenceImage": "新規領域参照画像",
"canvasGroup": "キャンバス"
"newRegionalReferenceImage": "新規領域参照画像"
},
"regionalGuidance": "領域ガイダンス",
"globalReferenceImage": "全域参照画像",
@@ -925,8 +644,7 @@
"brush": "ブラシ",
"rectangle": "矩形",
"move": "移動",
"eraser": "消しゴム",
"bbox": "Bbox"
"eraser": "消しゴム"
},
"saveCanvasToGallery": "キャンバスをギャラリーに保存",
"saveBboxToGallery": "バウンディングボックスをギャラリーへ保存",
@@ -944,27 +662,7 @@
"canvas": "キャンバス",
"fitBboxToLayers": "バウンディングボックスをレイヤーにフィット",
"removeBookmark": "ブックマークを外す",
"savedToGalleryOk": "ギャラリーに保存しました",
"controlMode": {
"prompt": "プロンプト"
},
"prompt": "プロンプト",
"settings": {
"snapToGrid": {
"off": "オフ",
"on": "オン"
}
},
"filter": {
"filter": "フィルター",
"spandrel_filter": {
"model": "モデル"
},
"apply": "適用",
"reset": "リセット",
"cancel": "キャンセル"
},
"weight": "重み"
"savedToGalleryOk": "ギャラリーに保存しました"
},
"stylePresets": {
"clearTemplateSelection": "選択したテンプレートをクリア",
@@ -976,54 +674,15 @@
"createPromptTemplate": "プロンプトテンプレートを作成",
"promptTemplateCleared": "プロンプトテンプレートをクリアしました",
"searchByName": "名前で検索",
"toggleViewMode": "表示モードを切り替え",
"negativePromptColumn": "'negative_prompt'",
"preview": "プレビュー",
"nameColumn": "'name'",
"type": "タイプ",
"private": "プライベート",
"name": "名称"
"toggleViewMode": "表示モードを切り替え"
},
"upscaling": {
"upscaleModel": "アップスケールモデル",
"postProcessingModel": "ポストプロセスモデル",
"upscale": "アップスケール",
"scale": "スケール"
"upscale": "アップスケール"
},
"sdxl": {
"denoisingStrength": "ノイズ除去強度",
"scheduler": "スケジューラー",
"loading": "ロード中...",
"steps": "ステップ",
"refiner": "Refiner"
},
"modelCache": {
"clear": "モデルキャッシュを消去",
"clearSucceeded": "モデルキャッシュを消去しました",
"clearFailed": "モデルキャッシュの消去中に問題が発生"
},
"workflows": {
"workflows": "ワークフロー",
"ascending": "昇順",
"name": "名前",
"descending": "降順"
},
"system": {
"logNamespaces": {
"system": "システム",
"gallery": "ギャラリー",
"workflows": "ワークフロー",
"models": "モデル",
"canvas": "キャンバス",
"metadata": "メタデータ",
"queue": "キュー"
},
"logLevel": {
"debug": "Debug",
"info": "Info",
"error": "Error",
"fatal": "Fatal",
"warn": "Warn"
}
"scheduler": "スケジューラー"
}
}

View File

@@ -63,7 +63,7 @@
"compareImage": "So Sánh Ảnh",
"compareHelp4": "Nhấn <Kbd>Z</Kbd> hoặc <Kbd>Esc</Kbd> để thoát.",
"compareHelp3": "Nhấn <Kbd>C</Kbd> để đổi ảnh được so sánh.",
"compareHelp1": "Giữ <Kbd>Alt</Kbd> khi bấm vào ảnh trong thư viện ảnh hoặc dùng phím mũi tên để đổi ảnh dùng cho so sánh.",
"compareHelp1": "Giữ <Kbd>Alt</Kbd> khi bấm vào ảnh trong thư viện hoặc dùng phím mũi tên để đổi ảnh dùng cho so sánh.",
"showArchivedBoards": "Hiển Thị Bảng Được Lưu Trữ",
"drop": "Thả",
"copy": "Sao Chép",
@@ -76,11 +76,11 @@
"deleteImagePermanent": "Ảnh đã xoá không thể phục hồi.",
"exitSearch": "Thoát Tìm Kiếm Hình Ảnh",
"exitBoardSearch": "Thoát Tìm Kiểm Bảng",
"gallery": "Thư Viện Ảnh",
"gallery": "Thư Viện",
"galleryImageSize": "Kích Thước Ảnh",
"downloadSelection": "Tải xuống Phần Được Lựa Chọn",
"bulkDownloadRequested": "Chuẩn Bị Tải Xuống",
"unableToLoad": "Không Thể Tải Thư viện Ảnh",
"unableToLoad": "Không Thể Tải Thư viện",
"newestFirst": "Mới Nhất Trước",
"showStarredImagesFirst": "Hiển Thị Ảnh Gắn Sao Trước",
"bulkDownloadRequestedDesc": "Yêu cầu tải xuống đang được chuẩn bị. Vui lòng chờ trong giây lát.",
@@ -103,7 +103,7 @@
"displaySearch": "Tìm Kiếm Hình Ảnh",
"selectAnImageToCompare": "Chọn Ảnh Để So Sánh",
"slider": "Thanh Trượt",
"gallerySettings": "Cài Đặt Thư Viện Ảnh",
"gallerySettings": "Cài Đặt Thư Viện",
"image": "hình ảnh",
"noImageSelected": "Không Có Ảnh Được Chọn",
"noImagesInGallery": "Không Có Ảnh Để Hiển Thị",
@@ -117,9 +117,8 @@
"unstarImage": "Ngừng Gắn Sao Cho Ảnh",
"compareHelp2": "Nhấn <Kbd>M</Kbd> để tuần hoàn trong chế độ so sánh.",
"boardsSettings": "Thiết Lập Bảng",
"imagesSettings": "Cài Đặt Ảnh Trong Thư Viện Ảnh",
"assets": "Tài Nguyên",
"images": "Hình Ảnh"
"imagesSettings": "Cài Đặt Thư Viện Ảnh",
"assets": "Tài Nguyên"
},
"common": {
"ipAdapter": "IP Adapter",
@@ -231,11 +230,7 @@
"max": "Tối Đa",
"resetToDefaults": "Đặt Lại Về Mặc Định",
"seed": "Hạt Giống",
"combinatorial": "Tổ Hợp",
"column": "Cột",
"layout": "Bố Cục",
"row": "Hàng",
"board": "Bảng"
"combinatorial": "Tổ Hợp"
},
"prompt": {
"addPromptTrigger": "Thêm Prompt Trigger",
@@ -290,7 +285,7 @@
"cancelBatch": "Huỷ Bỏ Lô",
"status": "Trạng Thái",
"pending": "Đang Chờ",
"gallery": "Thư Viện Ảnh",
"gallery": "Thư Viện",
"front": "trước",
"batch": "Lô",
"origin": "Nguồn Gốc",
@@ -310,13 +305,10 @@
"graphQueued": "Đồ Thị Đã Vào Hàng",
"batchQueuedDesc_other": "Thêm {{count}} phiên vào {{direction}} của hàng",
"batchSize": "Kích Thước Lô",
"cancelAllExceptCurrentQueueItemAlertDialog": "Huỷ tất cả mục đang xếp hàng ngoại trừ việc nó sẽ dừng các mục đang chờ nhưng cho phép các mục đang chạy được hoàn tất.",
"cancelAllExceptCurrentQueueItemAlertDialog": "Huỷ tất cả mục đang xếp hàng ngoại trừ mục hiện tại, sẽ dừng các mục đang chờ nhưng cho phép các mục đang chạy được hoàn tất.",
"cancelAllExceptCurrentQueueItemAlertDialog2": "Bạn có chắc muốn huỷ tất cả mục đang chờ?",
"cancelAllExceptCurrentTooltip": "Huỷ Bỏ Tất Cả Ngoại Trừ Mục Hiện Tại",
"confirm": "Đồng Ý",
"retrySucceeded": "Mục Đã Thử Lại",
"retryFailed": "Có Vấn Đề Khi Thử Lại Mục",
"retryItem": "Thử Lại Mục"
"confirm": "Đồng Ý"
},
"hotkeys": {
"canvas": {
@@ -522,16 +514,16 @@
},
"gallery": {
"galleryNavRight": {
"desc": "Sang phải theo mạng lưới thư viện ảnh, chọn hình ảnh đó. Nếu đến cuối hàng, qua hàng tiếp theo. Nếu đến hình ảnh cuối cùng, qua trang tiếp theo.",
"desc": "Sang phải theo mạng lưới thư viện, chọn hình ảnh đó. Nếu đến cuối hàng, qua hàng tiếp theo. Nếu đến hình ảnh cuối cùng, qua trang tiếp theo.",
"title": "Sang Phải"
},
"galleryNavDown": {
"title": "Đi Xuống",
"desc": "Đi xuống theo mạng lưới thư viện ảnh, chọn hình ảnh đó. Nếu xuống cuối cùng trang, sang trang tiếp theo."
"desc": "Đi xuống theo mạng lưới thư viện, chọn hình ảnh đó. Nếu xuống cuối cùng trang, sang trang tiếp theo."
},
"galleryNavLeft": {
"title": "Sang Trái",
"desc": "Sang trái theo mạng lưới thư viện ảnh, chọn hình ảnh đó. Nếu đến đầu hàng, về lại hàng trước đó. Nếu đến hình ảnh đầu tiên, về lại trang trước đó."
"desc": "Sang trái theo mạng lưới thư viện, chọn hình ảnh đó. Nếu đến đầu hàng, về lại hàng trước đó. Nếu đến hình ảnh đầu tiên, về lại trang trước đó."
},
"galleryNavUpAlt": {
"title": "Đi Lên (So Sánh Ảnh)",
@@ -543,7 +535,7 @@
},
"galleryNavUp": {
"title": "Đi Lên",
"desc": "Đi lên theo mạng lưới thư viện ảnh, chọn hình ảnh đó. Nếu lên trên cùng trang, về lại trang trước đó."
"desc": "Đi lên theo mạng lưới thư viện, chọn hình ảnh đó. Nếu lên trên cùng trang, về lại trang trước đó."
},
"galleryNavRightAlt": {
"title": "Sang Phải (So Sánh Ảnh)",
@@ -553,7 +545,7 @@
"title": "Chọn Tất Cả Trên Trang",
"desc": "Chọn tất cả ảnh trên trang hiện tại."
},
"title": "Thư Viện Ảnh",
"title": "Thư Viện",
"galleryNavDownAlt": {
"title": "Đi Xuống (So Sánh Ảnh)",
"desc": "Giống với \"Đi Xuống\", nhưng là chọn ảnh được so sánh, mở chế độ so sánh nếu chưa được mở."
@@ -875,7 +867,7 @@
"removeLinearView": "Xoá Khỏi Chế Độ Xem Tuyến Tính",
"unknownErrorValidatingWorkflow": "Lỗi không rõ khi xác thực workflow",
"unableToLoadWorkflow": "Không Thể Tải Workflow",
"workflowSettings": "Cài Đặt Biên Tập Workflow",
"workflowSettings": "Cài Đặt Trình Biên Tập Viên Workflow",
"workflowVersion": "Phiên Bản",
"unableToGetWorkflowVersion": "Không thể tìm phiên bản của lược đồ workflow",
"collection": "Đa tài nguyên",
@@ -972,7 +964,7 @@
"versionUnknown": " Phiên Bản Không Rõ",
"workflowContact": "Thông Tin Liên Lạc",
"workflowName": "Tên",
"saveToGallery": "Lưu Vào Thư Viện Ảnh",
"saveToGallery": "Lưu Vào Thư Viện",
"connectionWouldCreateCycle": "Kết nối này sẽ tạo ra vòng lặp",
"addNode": "Thêm Node",
"unsupportedAnyOfLength": "quá nhiều dữ liệu hợp nhất: {{count}}",
@@ -1003,20 +995,7 @@
"generatorLoading": "đang tải",
"generatorLoadFromFile": "Tải Từ Tệp",
"dynamicPromptsRandom": "Dynamic Prompts (Ngẫu Nhiên)",
"dynamicPromptsCombinatorial": "Dynamic Prompts (Tổ Hợp)",
"missingSourceOrTargetNode": "Thiếu nguồn hoặc node mục tiêu",
"missingSourceOrTargetHandle": "Thiếu nguồn hoặc mục tiêu xử lý",
"deletedMissingNodeFieldFormElement": "Xóa vùng nhập bị thiếu: vùng {{fieldName}} của node {{nodeId}}",
"description": "Mô Tả",
"loadWorkflowDesc": "Tải workflow?",
"loadWorkflowDesc2": "Workflow hiện tại của bạn có những điều chỉnh chưa được lưu.",
"loadingTemplates": "Đang Tải {{name}}",
"nodeName": "Tên Node",
"unableToUpdateNode": "Cập nhật node thất bại: node {{node}} thuộc dạng {{type}} (có thể cần xóa và tạo lại)",
"downloadWorkflowError": "Lỗi tải xuống workflow",
"generatorImagesFromBoard": "Ảnh Từ Bảng",
"generatorImagesCategory": "Phân Loại",
"generatorImages_other": "{{count}} ảnh"
"dynamicPromptsCombinatorial": "Dynamic Prompts (Tổ Hợp)"
},
"popovers": {
"paramCFGRescaleMultiplier": {
@@ -1501,8 +1480,7 @@
"emptyBatches": "lô trống",
"batchNodeNotConnected": "Node Hàng Loạt chưa được kết nối: {{label}}",
"batchNodeEmptyCollection": "Một vài node hàng loạt có tài nguyên rỗng",
"collectionEmpty": "tài nguyên trống",
"batchNodeCollectionSizeMismatchNoGroupId": "tài nguyên theo nhóm có kích thước sai lệch"
"invalidBatchConfigurationCannotCalculate": "Thiết lập lô không hợp lệ; không thể tính toán"
},
"cfgScale": "Thang CFG",
"useSeed": "Dùng Hạt Giống",
@@ -1604,14 +1582,14 @@
"clearIntermediates": "Dọn Sạch Sản Phẩm Trung Gian",
"clearIntermediatesDisabled": "Hàng đợi phải trống để dọn dẹp các sản phẩm trung gian",
"clearIntermediatesDesc1": "Dọn dẹp các sản phẩm trung gian sẽ làm mới trạng thái của Canvas và ControlNet.",
"clearIntermediatesDesc2": "Các sản phẩm ảnh trung gian là sản phẩm phụ trong quá trình tạo sinh, khác với ảnh trong thư viện ảnh. Xoá sản phẩm trung gian sẽ giúp làm trống ổ đĩa.",
"clearIntermediatesDesc2": "Các sản phẩm ảnh trung gian là sản phẩm phụ trong quá trình tạo sinh, khác với ảnh trong thư viện. Xoá sản phẩm trung gian sẽ giúp làm trống ổ đĩa.",
"resetWebUI": "Khởi Động Lại Giao Diện Web",
"showProgressInViewer": "Hiển Thị Hình Ảnh Đang Xử Lý Trong Trình Xem",
"ui": "Giao Diện Người Dùng",
"clearIntermediatesDesc3": "Ảnh trong thư viện ảnh sẽ không bị xoá.",
"clearIntermediatesDesc3": "Ảnh trong thư viện sẽ không bị xoá.",
"informationalPopoversDisabled": "Hộp Thoại Hỗ Trợ Thông Tin Đã Tắt",
"resetComplete": "Giao diện web đã được khởi động lại.",
"resetWebUIDesc2": "Nếu ảnh không được xuất hiện trong thư viện ảnh hoặc điều gì đó không ổn đang diễn ra, hãy thử khởi động lại trước khi báo lỗi trên Github.",
"resetWebUIDesc2": "Nếu ảnh không được xuất hiện trong thư viện hoặc điều gì đó không ổn đang diễn ra, hãy thử khởi động lại trước khi báo lỗi trên Github.",
"displayInProgress": "Hiển Thị Hình Ảnh Đang Xử Lý",
"intermediatesClearedFailed": "Có Vấn Đề Khi Dọn Sạch Sản Phẩm Trung Gian",
"enableInvisibleWatermark": "Bật Chế Độ Ẩn Watermark",
@@ -1639,7 +1617,7 @@
"width": "Chiều Rộng",
"negativePrompt": "Lệnh Tiêu Cực",
"removeBookmark": "Bỏ Đánh Dấu",
"saveBboxToGallery": "Lưu Hộp Giới Hạn Vào Thư Viện Ảnh",
"saveBboxToGallery": "Lưu Hộp Giới Hạn Vào Thư Viện",
"global": "Toàn Vùng",
"pullBboxIntoReferenceImageError": "Có Vấn Đề Khi Chuyển Hộp Giới Hạn Thành Ảnh Mẫu",
"clearHistory": "Xoá Lịch Sử",
@@ -1647,12 +1625,12 @@
"mergeVisibleOk": "Đã gộp layer",
"saveLayerToAssets": "Lưu Layer Vào Khu Tài Nguyên",
"canvas": "Canvas",
"savedToGalleryOk": "Đã Lưu Vào Thư Viện Ảnh",
"savedToGalleryOk": "Đã Lưu Vào Thư Viện",
"addGlobalReferenceImage": "Thêm $t(controlLayers.globalReferenceImage)",
"clipToBbox": "Chuyển Nét Thành Hộp Giới Hạn",
"moveToFront": "Chuyển Lên Trước",
"mergeVisible": "Gộp Layer Đang Hiển Thị",
"savedToGalleryError": "Lỗi khi lưu vào thư viện ảnh",
"savedToGalleryError": "Lỗi khi lưu vào thư viện",
"moveToBack": "Chuyển Về Sau",
"moveBackward": "Chuyển Xuống Cuối",
"newGlobalReferenceImageError": "Có Vấn Đề Khi Tạo Ảnh Mẫu Toàn Vùng",
@@ -1672,7 +1650,7 @@
"regional": "Khu Vực",
"regionIsEmpty": "Vùng được chọn trống",
"bookmark": "Đánh Dấu Để Đổi Nhanh",
"saveCanvasToGallery": "Lưu Canvas Vào Thư Viện Ảnh",
"saveCanvasToGallery": "Lưu Canvas Vào Thư Viện",
"cropLayerToBbox": "Xén Layer Vào Hộp Giới Hạn",
"mergeDown": "Gộp Xuống",
"mergeVisibleError": "Lỗi khi gộp layer",
@@ -1740,11 +1718,11 @@
"pullBboxIntoLayer": "Chuyển Hộp Giới Hạn Vào Layer",
"addInpaintMask": "Thêm $t(controlLayers.inpaintMask)",
"addRegionalGuidance": "Thêm $t(controlLayers.regionalGuidance)",
"sendToGallery": "Đã Chuyển Tới Thư Viện Ảnh",
"sendToGallery": "Chuyển Tới Thư Viện",
"unlocked": "Mở Khoá",
"addReferenceImage": "Thêm $t(controlLayers.referenceImage)",
"sendingToCanvas": "Chuyển Ảnh Tạo Sinh Vào Canvas",
"sendingToGallery": "Chuyển Ảnh Tạo Sinh Vào Thư Viện Ảnh",
"sendingToGallery": "Chuyển Ảnh Tạo Sinh Vào Thư Viện",
"viewProgressOnCanvas": "Xem quá trình xử lý và ảnh đầu ra trong <Btn>Canvas</Btn>.",
"inpaintMask_withCount_other": "Lớp Phủ Inpaint",
"regionalGuidance_withCount_other": "Chỉ Dẫn Khu Vực",
@@ -1755,7 +1733,7 @@
"copyRasterLayerTo": "Sao Chép $t(controlLayers.rasterLayer) Tới",
"copyControlLayerTo": "Sao Chép $t(controlLayers.controlLayer) Tới",
"newRegionalGuidance": "$t(controlLayers.regionalGuidance) Mới",
"newGallerySessionDesc": "Nó sẽ dọn sạch canvas và các thiết lập trừ model được chọn. Các ảnh được tạo sinh sẽ được chuyển đến thư viện ảnh.",
"newGallerySessionDesc": "Nó sẽ dọn sạch canvas và các thiết lập trừ model được chọn. Các ảnh được tạo sinh sẽ được chuyển đến thư viện.",
"stagingOnCanvas": "Hiển thị hình ảnh lên",
"pullBboxIntoReferenceImage": "Chuyển Hộp Giới Hạn Vào Ảnh Mẫu",
"maskFill": "Lấp Đầy Lớp Phủ",
@@ -1777,8 +1755,8 @@
"deleteReferenceImage": "Xoá Ảnh Mẫu",
"inpaintMasks_withCount_visible": "Lớp Phủ Inpaint ({{count}})",
"disableTransparencyEffect": "Tắt Hiệu Ứng Trong Suốt",
"newGallerySession": "Phiên Thư Viện Ảnh Mới",
"sendToGalleryDesc": "Bấm 'Kích Hoạt' sẽ tiến hành tạo sinh và lưu ảnh vào thư viện ảnh.",
"newGallerySession": "Phiên Thư Viện Mới",
"sendToGalleryDesc": "Bấm 'Kích Hoạt' sẽ tiến hành tạo sinh và lưu ảnh vào thư viện.",
"opacity": "Độ Mờ Đục",
"rectangle": "Hình Chữ Nhật",
"addNegativePrompt": "Thêm $t(controlLayers.negativePrompt)",
@@ -1813,13 +1791,13 @@
"process": "Xử Lý"
},
"canvasContextMenu": {
"saveBboxToGallery": "Lưu Hộp Giới Hạn Vào Thư Viện Ảnh",
"saveBboxToGallery": "Lưu Hộp Giới Hạn Vào Thư Viện",
"newGlobalReferenceImage": "Ảnh Mẫu Toàn Vùng Mới",
"cropCanvasToBbox": "Xén Canvas Vào Hộp Giới Hạn",
"newRegionalGuidance": "Chỉ Dẫn Khu Vực Mới",
"saveToGalleryGroup": "Lưu Vào Thư Viện Ảnh",
"saveToGalleryGroup": "Lưu Vào Thư Viện",
"newInpaintMask": "Lớp Phủ Inpaint Mới",
"saveCanvasToGallery": "Lưu Canvas Vào Thư Viện Ảnh",
"saveCanvasToGallery": "Lưu Canvas Vào Thư Viện",
"newRegionalReferenceImage": "Ảnh Mẫu Khu Vực Mới",
"newControlLayer": "Layer Điều Khiển Được Mới",
"newRasterLayer": "Layer Dạng Raster Mới",
@@ -1830,7 +1808,7 @@
"copyBboxToClipboard": "Sao Chép Hộp Giới Hạn Vào Clipboard"
},
"stagingArea": {
"saveToGallery": "Lưu Vào Thư Viện Ảnh",
"saveToGallery": "Lưu Vào Thư Viện",
"accept": "Chấp Nhận",
"discard": "Bỏ Đi",
"previous": "Trước",
@@ -2112,7 +2090,7 @@
"enableLogging": "Bật Chế Độ Ghi Log",
"logNamespaces": {
"models": "Models",
"gallery": "Thư Viện Ảnh",
"gallery": "Thư Viện",
"config": "Cấu Hình",
"queue": "Queue",
"workflows": "Workflow",
@@ -2167,7 +2145,7 @@
"parameterSetDesc": "Gợi lại {{parameter}}",
"loadedWithWarnings": "Đã Tải Workflow Với Cảnh Báo",
"outOfMemoryErrorDesc": "Thiết lập tạo sinh hiện tại đã vượt mức cho phép của thiết bị. Hãy điều chỉnh thiết lập và thử lại.",
"setNodeField": "Đặt làm vùng node",
"setNodeField": "Đặt làm vùng cho node",
"problemRetrievingWorkflow": "Có Vấn Đề Khi Lấy Lại Workflow",
"somethingWentWrong": "Có Vấn Đề Phát Sinh",
"problemDeletingWorkflow": "Có Vấn Đề Khi Xoá Workflow",
@@ -2200,7 +2178,7 @@
},
"ui": {
"tabs": {
"gallery": "Thư Viện Ảnh",
"gallery": "Thư Viện",
"models": "Models",
"generation": "Generation (Máy Tạo Sinh)",
"upscaling": "Upscale (Nâng Cấp Chất Lượng Hình Ảnh)",
@@ -2232,7 +2210,7 @@
"savingWorkflow": "Đang Lưu Workflow...",
"ascending": "Tăng Dần",
"loading": "Đang Tải Workflow",
"chooseWorkflowFromLibrary": "Chọn Workflow Từ Thư Viện",
"chooseWorkflowFromLibrary": "Chọn Workflow Từ Túi Đồ",
"workflows": "Workflow",
"copyShareLinkForWorkflow": "Sao Chép Liên Kết Chia Sẻ Cho Workflow",
"openWorkflow": "Mở Workflow",
@@ -2252,42 +2230,11 @@
"convertGraph": "Chuyển Đổi Đồ Thị",
"saveWorkflowToProject": "Lưu Workflow Vào Dự Án",
"workflowName": "Tên Workflow",
"workflowLibrary": "Thư Viện",
"workflowLibrary": "Túi Đồ",
"opened": "Ngày Mở",
"deleteWorkflow": "Xoá Workflow",
"workflowEditorMenu": "Menu Biên Tập Workflow",
"uploadAndSaveWorkflow": "Tải Lên Thư Viện",
"openLibrary": "Mở Thư Viện",
"builder": {
"resetAllNodeFields": "Tải Lại Các Vùng Node",
"builder": "Trình Tạo Vùng Nhập",
"layout": "Bố Cục",
"row": "Hàng",
"zoomToNode": "Phóng To Vào Node",
"addToForm": "Thêm Vào Vùng Nhập",
"label": "Nhãn Tên",
"showDescription": "Hiện Dòng Mô Tả",
"component": "Thành Phần",
"numberInput": "Nhập Số",
"singleLine": "Một Dòng",
"multiLine": "Nhiều Dòng",
"slider": "Thanh Trượt",
"both": "Cả Hai",
"emptyRootPlaceholderViewMode": "Chọn Chỉnh Sửa để bắt đầu tạo nên một vùng nhập cho workflow này.",
"emptyRootPlaceholderEditMode": "Kéo thành phần vùng nhập hoặc vùng node vào đây để bắt đầu.",
"containerPlaceholder": "Hộp Chứa Trống",
"headingPlaceholder": "Đầu Dòng Trống",
"textPlaceholder": "Văn Bản Trống",
"column": "Cột",
"deleteAllElements": "Xóa Tất Cả Thành Phần",
"nodeField": "Vùng Node",
"nodeFieldTooltip": "Để thêm vùng node, bấm vào dấu cộng nhỏ trên vùng trong Trình Biên Tập Workflow, hoặc kéo vùng theo tên của nó vào vùng nhập.",
"workflowBuilderAlphaWarning": "Trình tạo vùng nhập đang trong giai đoạn alpha. Nó có thể xuất hiện những thay đổi đột ngột trước khi chính thức được phát hành.",
"container": "Hộp Chứa",
"heading": "Đầu Dòng",
"text": "Văn Bản",
"divider": "Gạch Chia"
}
"workflowEditorMenu": "Menu Biên Tập Viên Workflow",
"uploadAndSaveWorkflow": "Tải Lên Túi Đồ"
},
"upscaling": {
"missingUpscaleInitialImage": "Thiếu ảnh dùng để upscale",
@@ -2310,9 +2257,9 @@
"incompatibleBaseModelDesc": "Upscale chỉ hỗ trợ cho model phiên bản SD1.5 và SDXL. Đổi model chính để bật lại tính năng upscale."
},
"newUserExperience": {
"toGetStartedLocal": "Để bắt đầu, hãy chắc chắn đã tải xuống hoặc thêm vào model cần để chạy Invoke. Sau đó, nhập lệnh vào hộp và nhấp chuột vào <StrongComponent>Kích Hoạt</StrongComponent> để tạo ra bức ảnh đầu tiên. Chọn một mẫu trình bày cho lệnh để cải thiện kết quả. Bạn có thể chọn để lưu ảnh trực tiếp vào <StrongComponent>Thư Viện Ảnh</StrongComponent> hoặc chỉnh sửa chúng ở <StrongComponent>Canvas</StrongComponent>.",
"toGetStartedLocal": "Để bắt đầu, hãy chắc chắn đã tải xuống hoặc thêm vào model cần để chạy Invoke. Sau đó, nhập lệnh vào hộp và nhấp chuột vào <StrongComponent>Kích Hoạt</StrongComponent> để tạo ra bức ảnh đầu tiên. Chọn một mẫu trình bày cho lệnh để cải thiện kết quả. Bạn có thể chọn để lưu ảnh trực tiếp vào <StrongComponent>Thư Viện</StrongComponent> hoặc chỉnh sửa chúng ở <StrongComponent>Canvas</StrongComponent>.",
"gettingStartedSeries": "Cần thêm hướng dẫn? Xem thử <LinkComponent>Bắt Đầu Làm Quen</LinkComponent> để biết thêm mẹo khai thác toàn bộ tiềm năng của Invoke Studio.",
"toGetStarted": "Để bắt đầu, hãy nhập lệnh vào hộp và nhấp chuột vào <StrongComponent>Kích Hoạt</StrongComponent> để tạo ra bức ảnh đầu tiên. Chọn một mẫu trình bày cho lệnh để cải thiện kết quả. Bạn có thể chọn để lưu ảnh trực tiếp vào <StrongComponent>Thư Viện Ảnh</StrongComponent> hoặc chỉnh sửa chúng ở <StrongComponent>Canvas</StrongComponent>.",
"toGetStarted": "Để bắt đầu, hãy nhập lệnh vào hộp và nhấp chuột vào <StrongComponent>Kích Hoạt</StrongComponent> để tạo ra bức ảnh đầu tiên. Chọn một mẫu trình bày cho lệnh để cải thiện kết quả. Bạn có thể chọn để lưu ảnh trực tiếp vào <StrongComponent>Thư Viện</StrongComponent> hoặc chỉnh sửa chúng ở <StrongComponent>Canvas</StrongComponent>.",
"noModelsInstalled": "Dường như bạn chưa tải model nào cả! Bạn có thể <DownloadStarterModelsButton>tải xuống các model khởi đầu</DownloadStarterModelsButton> hoặc <ImportModelsButton>nhập vào thêm model</ImportModelsButton>.",
"lowVRAMMode": "Cho hiệu suất tốt nhất, hãy làm theo <LinkComponent>hướng dẫn VRAM Thấp</LinkComponent> của chúng tôi."
},
@@ -2322,8 +2269,12 @@
"watchRecentReleaseVideos": "Xem Video Phát Hành Mới Nhất",
"watchUiUpdatesOverview": "Xem Tổng Quan Về Những Cập Nhật Cho Giao Diện Người Dùng",
"items": [
"Trình Biên Tập Workflow: trình tạo vùng nhập dưới dạng kéo thả nhằm tạo dựng workflow dễ dàng hơn.",
"Các nâng cấp khác: Xếp hàng tạo sinh theo nhóm nhanh hơn, upscale tốt hơn, trình chọn màu được cải thiện, và node chứa metadata."
"Cải thiện các thiết lập mặc định của VRAM",
"Xoá bộ nhớ đệm của model theo yêu cầu",
"Mở rộng khả năng tương thích LoRA trên FLUX",
"Bộ lọc điều chỉnh ảnh trên Canvas",
"Huỷ tất cả trừ mục đang xếp hàng hiện tại",
"Sao chép và dán trên Canvas"
]
},
"upsell": {
@@ -2355,8 +2306,8 @@
"title": "Upscale (Nâng Cấp Chất Lượng Hình Ảnh)"
},
"howDoIGenerateAndSaveToTheGallery": {
"title": "Làm Sao Để Tôi Tạo Sinh Và Lưu Vào Thư Viện Ảnh?",
"description": "Các bước để tạo sinh và lưu ảnh vào thư viện ảnh."
"title": "Làm Sao Để Tôi Tạo Sinh Và Lưu Vào Thư Viện?",
"description": "Các bước để tạo sinh và lưu ảnh vào thư viện."
},
"howDoIEditOnTheCanvas": {
"description": "Hướng dẫn chỉnh sửa ảnh trực tiếp trên canvas.",

View File

@@ -1,15 +1,13 @@
import { Box, useGlobalModifiersInit } from '@invoke-ai/ui-library';
import { useStore } from '@nanostores/react';
import { GlobalImageHotkeys } from 'app/components/GlobalImageHotkeys';
import type { StudioInitAction } from 'app/hooks/useStudioInitAction';
import { $didStudioInit, useStudioInitAction } from 'app/hooks/useStudioInitAction';
import { useStudioInitAction } from 'app/hooks/useStudioInitAction';
import { useSyncQueueStatus } from 'app/hooks/useSyncQueueStatus';
import { useLogger } from 'app/logging/useLogger';
import { useSyncLoggingConfig } from 'app/logging/useSyncLoggingConfig';
import { appStarted } from 'app/store/middleware/listenerMiddleware/listeners/appStarted';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import type { PartialAppConfig } from 'app/types/invokeai';
import Loading from 'common/components/Loading/Loading';
import { useFocusRegionWatcher } from 'common/hooks/focus';
import { useClearStorage } from 'common/hooks/useClearStorage';
import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
@@ -38,7 +36,6 @@ import { configChanged } from 'features/system/store/configSlice';
import { selectLanguage } from 'features/system/store/systemSelectors';
import { AppContent } from 'features/ui/components/AppContent';
import { DeleteWorkflowDialog } from 'features/workflowLibrary/components/DeleteLibraryWorkflowConfirmationAlertDialog';
import { LoadWorkflowConfirmationAlertDialog } from 'features/workflowLibrary/components/LoadWorkflowConfirmationAlertDialog';
import { NewWorkflowConfirmationAlertDialog } from 'features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog';
import i18n from 'i18n';
import { size } from 'lodash-es';
@@ -57,7 +54,6 @@ interface Props {
}
const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
const didStudioInit = useStore($didStudioInit);
const clearStorage = useClearStorage();
const handleReset = useCallback(() => {
@@ -70,7 +66,6 @@ const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
<ErrorBoundary onReset={handleReset} FallbackComponent={AppErrorBoundaryFallback}>
<Box id="invoke-app-wrapper" w="100dvw" h="100dvh" position="relative" overflow="hidden">
<AppContent />
{!didStudioInit && <Loading />}
</Box>
<HookIsolator config={config} studioInitAction={studioInitAction} />
<DeleteImageModal />
@@ -80,7 +75,6 @@ const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
<CancelAllExceptCurrentQueueItemConfirmationAlertDialog />
<ClearQueueConfirmationsAlertDialog />
<NewWorkflowConfirmationAlertDialog />
<LoadWorkflowConfirmationAlertDialog />
<DeleteStylePresetDialog />
<DeleteWorkflowDialog />
<ShareWorkflowModal />

View File

@@ -2,7 +2,6 @@ import 'i18n';
import type { Middleware } from '@reduxjs/toolkit';
import type { StudioInitAction } from 'app/hooks/useStudioInitAction';
import { $didStudioInit } from 'app/hooks/useStudioInitAction';
import type { LoggingOverrides } from 'app/logging/logger';
import { $loggingOverrides, configureLogging } from 'app/logging/logger';
import { $authToken } from 'app/store/nanostores/authToken';
@@ -88,12 +87,6 @@ const InvokeAIUI = ({
);
}, [loggingOverrides]);
useLayoutEffect(() => {
if (studioInitAction) {
$didStudioInit.set(false);
}
}, [studioInitAction]);
useEffect(() => {
// configure API client token
if (token) {

View File

@@ -16,8 +16,7 @@ import { $isStylePresetsMenuOpen, activeStylePresetIdChanged } from 'features/st
import { toast } from 'features/toast/toast';
import { activeTabCanvasRightPanelChanged, setActiveTab } from 'features/ui/store/uiSlice';
import { useGetAndLoadLibraryWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadLibraryWorkflow';
import { atom } from 'nanostores';
import { useCallback, useEffect } from 'react';
import { useCallback, useEffect, useRef } from 'react';
import { useTranslation } from 'react-i18next';
import { getImageDTO, getImageMetadata } from 'services/api/endpoints/images';
import { getStylePreset } from 'services/api/endpoints/stylePresets';
@@ -33,9 +32,6 @@ type StudioDestinationAction = _StudioInitAction<
{ destination: 'generation' | 'canvas' | 'workflows' | 'upscaling' | 'viewAllWorkflows' | 'viewAllStylePresets' }
>;
// Use global state to show loader until we are ready to render the studio.
export const $didStudioInit = atom(false);
export type StudioInitAction =
| LoadWorkflowAction
| SelectStylePresetAction
@@ -55,6 +51,8 @@ export type StudioInitAction =
export const useStudioInitAction = (action?: StudioInitAction) => {
useAssertSingleton('useStudioInitAction');
const { t } = useTranslation();
// Use a ref to ensure that we only perform the action once
const didInit = useRef(false);
const didParseOpenAPISchema = useStore($hasTemplates);
const store = useAppStore();
const { getAndLoadWorkflow } = useGetAndLoadLibraryWorkflow();
@@ -104,16 +102,16 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
}
const metadata = getImageMetadataResult.value;
// This shows a toast
await parseAndRecallAllMetadata(metadata, true);
parseAndRecallAllMetadata(metadata, true);
store.dispatch(setActiveTab('canvas'));
},
[store, t]
);
const handleLoadWorkflow = useCallback(
async (workflowId: string) => {
(workflowId: string) => {
// This shows a toast
await getAndLoadWorkflow(workflowId);
getAndLoadWorkflow(workflowId);
store.dispatch(setActiveTab('workflows'));
},
[getAndLoadWorkflow, store]
@@ -178,48 +176,36 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
[store]
);
const handleStudioInitAction = useCallback(
async (action: StudioInitAction) => {
// This cannot be in the useEffect below because we need to await some of the actions before setting didStudioInit.
switch (action.type) {
case 'loadWorkflow':
await handleLoadWorkflow(action.data.workflowId);
break;
case 'selectStylePreset':
await handleSelectStylePreset(action.data.stylePresetId);
break;
case 'sendToCanvas':
await handleSendToCanvas(action.data.imageName);
break;
case 'useAllParameters':
await handleUseAllMetadata(action.data.imageName);
break;
case 'goToDestination':
handleGoToDestination(action.data.destination);
break;
default:
break;
}
$didStudioInit.set(true);
},
[handleGoToDestination, handleLoadWorkflow, handleSelectStylePreset, handleSendToCanvas, handleUseAllMetadata]
);
useEffect(() => {
if ($didStudioInit.get() || !didParseOpenAPISchema) {
if (didInit.current || !action || !didParseOpenAPISchema) {
return;
}
if (!action) {
$didStudioInit.set(true);
return;
}
didInit.current = true;
handleStudioInitAction(action);
switch (action.type) {
case 'loadWorkflow':
handleLoadWorkflow(action.data.workflowId);
break;
case 'selectStylePreset':
handleSelectStylePreset(action.data.stylePresetId);
break;
case 'sendToCanvas':
handleSendToCanvas(action.data.imageName);
break;
case 'useAllParameters':
handleUseAllMetadata(action.data.imageName);
break;
case 'goToDestination':
handleGoToDestination(action.data.destination);
break;
default:
break;
}
}, [
handleSendToCanvas,
handleUseAllMetadata,
@@ -228,6 +214,5 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
handleGoToDestination,
handleLoadWorkflow,
didParseOpenAPISchema,
handleStudioInitAction,
]);
};

View File

@@ -3,7 +3,6 @@ import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { extractMessageFromAssertionError } from 'common/util/extractMessageFromAssertionError';
import { withResult, withResultAsync } from 'common/util/result';
import { parseify } from 'common/util/serialize';
import { $canvasManager } from 'features/controlLayers/store/ephemeral';
import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
import { buildFLUXGraph } from 'features/nodes/util/graph/generation/buildFLUXGraph';
@@ -14,6 +13,7 @@ import { toast } from 'features/toast/toast';
import { serializeError } from 'serialize-error';
import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
import { assert, AssertionError } from 'tsafe';
import type { JsonObject } from 'type-fest';
const log = logger('generation');
@@ -80,15 +80,16 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(prepareBatchResult.value, enqueueMutationFixedCacheKeyOptions)
);
req.reset();
try {
await req.unwrap();
log.debug(parseify({ batchConfig: prepareBatchResult.value }), 'Enqueued batch');
} catch (error) {
log.error({ error: serializeError(error) }, 'Failed to enqueue batch');
} finally {
req.reset();
const enqueueResult = await withResultAsync(() => req.unwrap());
if (enqueueResult.isErr()) {
log.error({ error: serializeError(enqueueResult.error) }, 'Failed to enqueue batch');
return;
}
log.debug({ batchConfig: prepareBatchResult.value } as JsonObject, 'Enqueued batch');
},
});
};

View File

@@ -1,33 +1,26 @@
import { logger } from 'app/logging/logger';
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { parseify } from 'common/util/serialize';
import { $templates } from 'features/nodes/store/nodesSlice';
import { selectNodesSlice } from 'features/nodes/store/selectors';
import { isBatchNode, isInvocationNode } from 'features/nodes/types/invocation';
import { buildNodesGraph } from 'features/nodes/util/graph/buildNodesGraph';
import { resolveBatchValue } from 'features/nodes/util/node/resolveBatchValue';
import { buildWorkflowWithValidation } from 'features/nodes/util/workflow/buildWorkflow';
import { resolveBatchValue } from 'features/queue/store/readiness';
import { groupBy } from 'lodash-es';
import { serializeError } from 'serialize-error';
import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
import type { Batch, BatchConfig } from 'services/api/types';
const log = logger('generation');
export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) => {
startAppListening({
predicate: (action): action is ReturnType<typeof enqueueRequested> =>
enqueueRequested.match(action) && action.payload.tabName === 'workflows',
effect: async (action, { getState, dispatch }) => {
const state = getState();
const nodesState = selectNodesSlice(state);
const nodes = selectNodesSlice(state);
const workflow = state.workflow;
const templates = $templates.get();
const graph = buildNodesGraph(state, templates);
const graph = buildNodesGraph(nodes);
const builtWorkflow = buildWorkflowWithValidation({
nodes: nodesState.nodes,
edges: nodesState.edges,
nodes: nodes.nodes,
edges: nodes.edges,
workflow,
});
@@ -38,7 +31,7 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
const data: Batch['data'] = [];
const invocationNodes = nodesState.nodes.filter(isInvocationNode);
const invocationNodes = nodes.nodes.filter(isInvocationNode);
const batchNodes = invocationNodes.filter(isBatchNode);
// Handle zipping batch nodes. First group the batch nodes by their batch_group_id
@@ -49,11 +42,9 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
const zippedBatchDataCollectionItems: NonNullable<Batch['data']>[number] = [];
for (const node of batchNodes) {
const value = await resolveBatchValue({ nodesState, node, dispatch });
const value = resolveBatchValue(node, invocationNodes, nodes.edges);
const sourceHandle = node.data.type === 'image_batch' ? 'image' : 'value';
const edgesFromBatch = nodesState.edges.filter(
(e) => e.source === node.id && e.sourceHandle === sourceHandle
);
const edgesFromBatch = nodes.edges.filter((e) => e.source === node.id && e.sourceHandle === sourceHandle);
if (batchGroupId !== 'None') {
// If this batch node has a batch_group_id, we will zip the data collection items
for (const edge of edgesFromBatch) {
@@ -106,9 +97,6 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
const req = dispatch(queueApi.endpoints.enqueueBatch.initiate(batchConfig, enqueueMutationFixedCacheKeyOptions));
try {
await req.unwrap();
log.debug(parseify({ batchConfig }), 'Enqueued batch');
} catch (error) {
log.error({ error: serializeError(error) }, 'Failed to enqueue batch');
} finally {
req.reset();
}

View File

@@ -1,14 +1,9 @@
import { logger } from 'app/logging/logger';
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { parseify } from 'common/util/serialize';
import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
import { buildMultidiffusionUpscaleGraph } from 'features/nodes/util/graph/buildMultidiffusionUpscaleGraph';
import { serializeError } from 'serialize-error';
import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
const log = logger('generation');
export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening) => {
startAppListening({
predicate: (action): action is ReturnType<typeof enqueueRequested> =>
@@ -24,9 +19,6 @@ export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening)
const req = dispatch(queueApi.endpoints.enqueueBatch.initiate(batchConfig, enqueueMutationFixedCacheKeyOptions));
try {
await req.unwrap();
log.debug(parseify({ batchConfig }), 'Enqueued batch');
} catch (error) {
log.error({ error: serializeError(error) }, 'Failed to enqueue batch');
} finally {
req.reset();
}

View File

@@ -22,18 +22,12 @@ const getWorkflow = async (data: GraphAndWorkflowResponse, templates: Templates)
if (data.workflow) {
// Prefer to load the workflow if it's available - it has more information
const parsed = JSON.parse(data.workflow);
return await validateWorkflow({
workflow: parsed,
templates,
checkImageAccess,
checkBoardAccess,
checkModelAccess,
});
return await validateWorkflow(parsed, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
} else if (data.graph) {
// Else we fall back on the graph, using the graphToWorkflow function to convert and do layout
const parsed = JSON.parse(data.graph);
const workflow = graphToWorkflow(parsed as NonNullableGraph, true);
return await validateWorkflow({ workflow, templates, checkImageAccess, checkBoardAccess, checkModelAccess });
return await validateWorkflow(workflow, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
} else {
throw new Error('No workflow or graph provided');
}

View File

@@ -6,18 +6,7 @@ import { memo } from 'react';
const Loading = () => {
return (
<Flex
position="absolute"
width="100dvw"
height="100dvh"
alignItems="center"
justifyContent="center"
bg="#151519"
top={0}
right={0}
bottom={0}
left={0}
>
<Flex position="relative" width="100dvw" height="100dvh" alignItems="center" justifyContent="center" bg="#151519">
<Image src={InvokeLogoWhite} w="8rem" h="8rem" />
<Spinner
label="Loading"

View File

@@ -1,17 +0,0 @@
import type { SystemStyleObject } from '@invoke-ai/ui-library';
import type { Opts as LinkifyOpts } from 'linkifyjs';
export const linkifySx: SystemStyleObject = {
a: {
fontWeight: 'semibold',
},
'a:hover': {
textDecoration: 'underline',
},
};
export const linkifyOptions: LinkifyOpts = {
target: '_blank',
rel: 'noopener noreferrer',
validate: (value) => /^https?:\/\//.test(value),
};

View File

@@ -1,7 +1,5 @@
import { useAppDispatch } from 'app/store/storeHooks';
import { useClipboard } from 'common/hooks/useClipboard';
import { convertImageUrlToBlob } from 'common/util/convertImageUrlToBlob';
import { imageCopiedToClipboard } from 'features/gallery/store/actions';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import { useTranslation } from 'react-i18next';
@@ -9,7 +7,6 @@ import { useTranslation } from 'react-i18next';
export const useCopyImageToClipboard = () => {
const { t } = useTranslation();
const clipboard = useClipboard();
const dispatch = useAppDispatch();
const copyImageToClipboard = useCallback(
async (image_url: string) => {
@@ -26,7 +23,6 @@ export const useCopyImageToClipboard = () => {
title: t('toast.imageCopied'),
status: 'success',
});
dispatch(imageCopiedToClipboard());
});
} catch (err) {
toast({
@@ -37,7 +33,7 @@ export const useCopyImageToClipboard = () => {
});
}
},
[clipboard, t, dispatch]
[clipboard, t]
);
return copyImageToClipboard;

View File

@@ -128,11 +128,7 @@ export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: Us
getInputProps: getUploadInputProps,
open: openUploader,
} = useDropzone({
accept: {
'image/png': ['.png'],
'image/jpeg': ['.jpg', '.jpeg', '.png'],
'image/webp': ['.webp'],
},
accept: { 'image/png': ['.png'], 'image/jpeg': ['.jpg', '.jpeg', '.png'] },
onDropAccepted,
onDropRejected,
disabled: isDisabled,

View File

@@ -2,7 +2,6 @@ import { Button, Flex, Text } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { useImageUploadButton } from 'common/hooks/useImageUploadButton';
import { useEntityIdentifierContext } from 'features/controlLayers/contexts/EntityIdentifierContext';
import { usePullBboxIntoGlobalReferenceImage } from 'features/controlLayers/hooks/saveCanvasHooks';
import { useCanvasIsBusy } from 'features/controlLayers/hooks/useCanvasIsBusy';
import type { SetGlobalReferenceImageDndTargetData } from 'features/dnd/dnd';
import { setGlobalReferenceImageDndTarget } from 'features/dnd/dnd';
@@ -28,7 +27,6 @@ export const IPAdapterSettingsEmptyState = memo(() => {
const onClickGalleryButton = useCallback(() => {
dispatch(activeTabCanvasRightPanelChanged('gallery'));
}, [dispatch]);
const pullBboxIntoIPAdapter = usePullBboxIntoGlobalReferenceImage(entityIdentifier);
const dndTargetData = useMemo<SetGlobalReferenceImageDndTargetData>(
() => setGlobalReferenceImageDndTarget.getData({ entityIdentifier }),
@@ -43,11 +41,8 @@ export const IPAdapterSettingsEmptyState = memo(() => {
GalleryButton: (
<Button onClick={onClickGalleryButton} isDisabled={isBusy} size="sm" variant="link" color="base.300" />
),
PullBboxButton: (
<Button onClick={pullBboxIntoIPAdapter} isDisabled={isBusy} size="sm" variant="link" color="base.300" />
),
}),
[isBusy, onClickGalleryButton, pullBboxIntoIPAdapter, uploadApi]
[isBusy, onClickGalleryButton, uploadApi]
);
return (

View File

@@ -2,7 +2,6 @@ import { Button, Flex, IconButton, Spacer, Text } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { useImageUploadButton } from 'common/hooks/useImageUploadButton';
import { useEntityIdentifierContext } from 'features/controlLayers/contexts/EntityIdentifierContext';
import { usePullBboxIntoRegionalGuidanceReferenceImage } from 'features/controlLayers/hooks/saveCanvasHooks';
import { useCanvasIsBusy } from 'features/controlLayers/hooks/useCanvasIsBusy';
import { rgIPAdapterDeleted } from 'features/controlLayers/store/canvasSlice';
import type { SetRegionalGuidanceReferenceImageDndTargetData } from 'features/dnd/dnd';
@@ -37,7 +36,6 @@ export const RegionalGuidanceIPAdapterSettingsEmptyState = memo(({ referenceImag
const onDeleteIPAdapter = useCallback(() => {
dispatch(rgIPAdapterDeleted({ entityIdentifier, referenceImageId }));
}, [dispatch, entityIdentifier, referenceImageId]);
const pullBboxIntoIPAdapter = usePullBboxIntoRegionalGuidanceReferenceImage(entityIdentifier, referenceImageId);
const dndTargetData = useMemo<SetRegionalGuidanceReferenceImageDndTargetData>(
() =>
@@ -48,21 +46,6 @@ export const RegionalGuidanceIPAdapterSettingsEmptyState = memo(({ referenceImag
[entityIdentifier, referenceImageId]
);
const components = useMemo(
() => ({
UploadButton: (
<Button isDisabled={isBusy} size="sm" variant="link" color="base.300" {...uploadApi.getUploadButtonProps()} />
),
GalleryButton: (
<Button onClick={onClickGalleryButton} isDisabled={isBusy} size="sm" variant="link" color="base.300" />
),
PullBboxButton: (
<Button onClick={pullBboxIntoIPAdapter} isDisabled={isBusy} size="sm" variant="link" color="base.300" />
),
}),
[isBusy, onClickGalleryButton, pullBboxIntoIPAdapter, uploadApi]
);
return (
<Flex flexDir="column" gap={2} position="relative" w="full">
<Flex alignItems="center" gap={2}>
@@ -83,7 +66,23 @@ export const RegionalGuidanceIPAdapterSettingsEmptyState = memo(({ referenceImag
</Flex>
<Flex alignItems="center" gap={2} p={4}>
<Text textAlign="center" color="base.300">
<Trans i18nKey="controlLayers.referenceImageEmptyState" components={components} />
<Trans
i18nKey="controlLayers.referenceImageEmptyState"
components={{
UploadButton: (
<Button
isDisabled={isBusy}
size="sm"
variant="link"
color="base.300"
{...uploadApi.getUploadButtonProps()}
/>
),
GalleryButton: (
<Button onClick={onClickGalleryButton} isDisabled={isBusy} size="sm" variant="link" color="base.300" />
),
}}
/>
</Text>
</Flex>
<input {...uploadApi.getUploadInputProps()} />

View File

@@ -4,7 +4,7 @@ import type { CanvasState } from 'features/controlLayers/store/types';
import { selectDeleteImageModalSlice } from 'features/deleteImageModal/store/slice';
import { selectNodesSlice } from 'features/nodes/store/selectors';
import type { NodesState } from 'features/nodes/store/types';
import { isImageFieldCollectionInputInstance, isImageFieldInputInstance } from 'features/nodes/types/field';
import { isImageFieldInputInstance } from 'features/nodes/types/field';
import { isInvocationNode } from 'features/nodes/types/invocation';
import type { UpscaleState } from 'features/parameters/store/upscaleSlice';
import { selectUpscaleSlice } from 'features/parameters/store/upscaleSlice';
@@ -13,23 +13,11 @@ import { some } from 'lodash-es';
import type { ImageUsage } from './types';
// TODO(psyche): handle image deletion (canvas staging area?)
export const getImageUsage = (nodes: NodesState, canvas: CanvasState, upscale: UpscaleState, image_name: string) => {
const isNodesImage = nodes.nodes.filter(isInvocationNode).some((node) =>
some(node.data.inputs, (input) => {
if (isImageFieldInputInstance(input)) {
if (input.value?.image_name === image_name) {
return true;
}
}
if (isImageFieldCollectionInputInstance(input)) {
if (input.value?.some((value) => value?.image_name === image_name)) {
return true;
}
}
return false;
})
);
const isNodesImage = nodes.nodes
.filter(isInvocationNode)
.some((node) =>
some(node.data.inputs, (input) => isImageFieldInputInstance(input) && input.value?.image_name === image_name)
);
const isUpscaleImage = upscale.upscaleInitialImage?.image_name === image_name;

View File

@@ -22,8 +22,8 @@ import { useBoardName } from 'services/api/hooks/useBoardName';
import type { UploadImageArg } from 'services/api/types';
import { z } from 'zod';
const ACCEPTED_IMAGE_TYPES = ['image/png', 'image/jpg', 'image/jpeg', 'image/webp'];
const ACCEPTED_FILE_EXTENSIONS = ['.png', '.jpg', '.jpeg', '.webp'];
const ACCEPTED_IMAGE_TYPES = ['image/png', 'image/jpg', 'image/jpeg'];
const ACCEPTED_FILE_EXTENSIONS = ['.png', '.jpg', '.jpeg'];
// const MAX_IMAGE_SIZE = 4; //In MegaBytes
// const sizeInMB = (sizeInBytes: number, decimalsNum = 2) => {

View File

@@ -20,7 +20,7 @@ import {
setUpscaleInitialImage,
} from 'features/imageActions/actions';
import { fieldImageCollectionValueChanged } from 'features/nodes/store/nodesSlice';
import { selectFieldInputInstanceSafe, selectNodesSlice } from 'features/nodes/store/selectors';
import { selectFieldInputInstance, selectNodesSlice } from 'features/nodes/store/selectors';
import { type FieldIdentifier, isImageFieldCollectionInputInstance } from 'features/nodes/types/field';
import type { ImageDTO } from 'services/api/types';
import type { JsonObject } from 'type-fest';
@@ -261,7 +261,7 @@ export const addImagesToNodeImageFieldCollectionDndTarget: DndTarget<
const { fieldIdentifier } = targetData.payload;
const fieldInputInstance = selectFieldInputInstanceSafe(
const fieldInputInstance = selectFieldInputInstance(
selectNodesSlice(getState()),
fieldIdentifier.nodeId,
fieldIdentifier.fieldName

View File

@@ -36,13 +36,7 @@ const DeleteBoardModal = () => {
const boardToDelete = useStore($boardToDelete);
const { t } = useTranslation();
const { currentData: boardImageNames, isFetching: isFetchingBoardNames } = useListAllImageNamesForBoardQuery(
boardToDelete?.board_id
? {
board_id: boardToDelete?.board_id,
categories: undefined,
is_intermediate: undefined,
}
: skipToken
boardToDelete?.board_id ?? skipToken
);
const selectImageUsageSummary = useMemo(

View File

@@ -4,7 +4,7 @@ import { useFocusRegion } from 'common/hooks/focus';
import { GalleryHeader } from 'features/gallery/components/GalleryHeader';
import { selectBoardSearchText } from 'features/gallery/store/gallerySelectors';
import { boardSearchTextChanged } from 'features/gallery/store/gallerySlice';
import { HorizontalResizeHandle } from 'features/ui/components/tabs/ResizeHandle';
import ResizeHandle from 'features/ui/components/tabs/ResizeHandle';
import { usePanel, type UsePanelOptions } from 'features/ui/hooks/usePanel';
import type { CSSProperties } from 'react';
import { memo, useCallback, useMemo, useRef } from 'react';
@@ -94,7 +94,7 @@ const GalleryPanelContent = () => {
<BoardsListWrapper />
</Flex>
</Panel>
<HorizontalResizeHandle id="gallery-panel-handle" {...boardsListPanel.resizeHandleProps} />
<ResizeHandle id="gallery-panel-handle" {...boardsListPanel.resizeHandleProps} />
<Panel id="gallery-wrapper-panel" minSize={20}>
<Gallery />
</Panel>

View File

@@ -1,7 +1,5 @@
import { useAppDispatch } from 'app/store/storeHooks';
import { IconMenuItem } from 'common/components/IconMenuItem';
import { useImageDTOContext } from 'features/gallery/contexts/ImageDTOContext';
import { imageOpenedInNewTab } from 'features/gallery/store/actions';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiArrowSquareOutBold } from 'react-icons/pi';
@@ -9,11 +7,9 @@ import { PiArrowSquareOutBold } from 'react-icons/pi';
export const ImageMenuItemOpenInNewTab = memo(() => {
const { t } = useTranslation();
const imageDTO = useImageDTOContext();
const dispatch = useAppDispatch();
const onClick = useCallback(() => {
window.open(imageDTO.image_url, '_blank');
dispatch(imageOpenedInNewTab());
}, [imageDTO.image_url, dispatch]);
}, [imageDTO.image_url]);
return (
<IconMenuItem

View File

@@ -18,6 +18,7 @@ import { getGalleryImageDataTestId } from 'features/gallery/components/ImageGrid
import { SizedSkeletonLoader } from 'features/gallery/components/ImageGrid/SizedSkeletonLoader';
import { $imageViewer } from 'features/gallery/components/ImageViewer/useImageViewer';
import { imageToCompareChanged, selectGallerySlice } from 'features/gallery/store/gallerySlice';
import { atom } from 'nanostores';
import type { MouseEventHandler } from 'react';
import { memo, useCallback, useEffect, useId, useMemo, useState } from 'react';
import type { ImageDTO } from 'services/api/types';
@@ -177,15 +178,20 @@ export const GalleryImage = memo(({ imageDTO }: Props) => {
);
}, [imageDTO, element, store, dndId]);
const [isHovered, setIsHovered] = useState(false);
// Perf optimization:
// The gallery image component can be heavy and re-render often. We want to track hovering state without causing
// unnecessary re-renders. To do this, we use a local atom - which has a stable reference - in the image component -
// and then pass the atom to the hover icons component, which subscribes to the atom and re-renders when the atom
// changes.
const $isHovered = useMemo(() => atom(false), []);
const onMouseOver = useCallback(() => {
setIsHovered(true);
}, []);
$isHovered.set(true);
}, [$isHovered]);
const onMouseOut = useCallback(() => {
setIsHovered(false);
}, []);
$isHovered.set(false);
}, [$isHovered]);
const onClick = useCallback<MouseEventHandler<HTMLDivElement>>(
(e) => {
@@ -241,7 +247,7 @@ export const GalleryImage = memo(({ imageDTO }: Props) => {
maxH="full"
borderRadius="base"
/>
<GalleryImageHoverIcons imageDTO={imageDTO} isHovered={isHovered} />
<GalleryImageHoverIcons imageDTO={imageDTO} $isHovered={$isHovered} />
</Flex>
</Box>
{dragPreviewState?.type === 'multiple-image' ? createMultipleImageDragPreview(dragPreviewState) : null}

View File

@@ -1,19 +1,22 @@
import { useStore } from '@nanostores/react';
import { useAppSelector } from 'app/store/storeHooks';
import { GalleryImageDeleteIconButton } from 'features/gallery/components/ImageGrid/GalleryImageDeleteIconButton';
import { GalleryImageOpenInViewerIconButton } from 'features/gallery/components/ImageGrid/GalleryImageOpenInViewerIconButton';
import { GalleryImageSizeBadge } from 'features/gallery/components/ImageGrid/GalleryImageSizeBadge';
import { GalleryImageStarIconButton } from 'features/gallery/components/ImageGrid/GalleryImageStarIconButton';
import { selectAlwaysShouldImageSizeBadge } from 'features/gallery/store/gallerySelectors';
import type { Atom } from 'nanostores';
import { memo } from 'react';
import type { ImageDTO } from 'services/api/types';
type Props = {
imageDTO: ImageDTO;
isHovered: boolean;
$isHovered: Atom<boolean>;
};
export const GalleryImageHoverIcons = memo(({ imageDTO, isHovered }: Props) => {
export const GalleryImageHoverIcons = memo(({ imageDTO, $isHovered }: Props) => {
const alwaysShowImageSizeBadge = useAppSelector(selectAlwaysShouldImageSizeBadge);
const isHovered = useStore($isHovered);
return (
<>

View File

@@ -1,4 +1,3 @@
import type { FlexProps } from '@invoke-ai/ui-library';
import { Box, Flex, IconButton, Tooltip, useShiftModifier } from '@invoke-ai/ui-library';
import { getOverlayScrollbarsParams } from 'common/components/OverlayScrollbars/constants';
import { useClipboard } from 'common/hooks/useClipboard';
@@ -19,12 +18,12 @@ type Props = {
withDownload?: boolean;
withCopy?: boolean;
extraCopyActions?: { label: string; getData: (data: unknown) => unknown }[];
} & FlexProps;
};
const overlayscrollbarsOptions = getOverlayScrollbarsParams('scroll', 'scroll').options;
const DataViewer = (props: Props) => {
const { label, data, fileName, withDownload = true, withCopy = true, extraCopyActions, ...rest } = props;
const { label, data, fileName, withDownload = true, withCopy = true, extraCopyActions } = props;
const dataString = useMemo(() => (isString(data) ? data : formatter.Serialize(data)) ?? '', [data]);
const shift = useShiftModifier();
const clipboard = useClipboard();
@@ -45,8 +44,8 @@ const DataViewer = (props: Props) => {
const { t } = useTranslation();
return (
<Flex bg="base.800" borderRadius="base" flexGrow={1} w="full" h="full" position="relative" {...rest}>
<Box position="absolute" top={0} left={0} right={0} bottom={0} overflow="auto" p={2} fontSize="sm">
<Flex layerStyle="second" borderRadius="base" flexGrow={1} w="full" h="full" position="relative">
<Box position="absolute" top={0} left={0} right={0} bottom={0} overflow="auto" p={4} fontSize="sm">
<OverlayScrollbarsComponent defer style={overlayScrollbarsStyles} options={overlayscrollbarsOptions}>
<pre>{dataString}</pre>
</OverlayScrollbarsComponent>

View File

@@ -1,7 +1,7 @@
import { Flex, Image } from '@invoke-ai/ui-library';
import type { ComparisonProps } from 'features/gallery/components/ImageViewer/common';
import { ImageComparisonLabel } from 'features/gallery/components/ImageViewer/ImageComparisonLabel';
import { VerticalResizeHandle } from 'features/ui/components/tabs/ResizeHandle';
import ResizeHandle from 'features/ui/components/tabs/ResizeHandle';
import { memo, useCallback, useRef } from 'react';
import type { ImperativePanelGroupHandle } from 'react-resizable-panels';
import { Panel, PanelGroup } from 'react-resizable-panels';
@@ -42,7 +42,7 @@ export const ImageComparisonSideBySide = memo(({ firstImage, secondImage }: Comp
</Flex>
</Flex>
</Panel>
<VerticalResizeHandle id="image-comparison-side-by-side-handle" onDoubleClick={onDoubleClickHandle} />
<ResizeHandle id="image-comparison-side-by-side-handle" onDoubleClick={onDoubleClickHandle} />
<Panel minSize={20}>
<Flex position="relative" w="full" h="full" alignItems="center" justifyContent="center">

View File

@@ -3,7 +3,3 @@ import { createAction } from '@reduxjs/toolkit';
export const sentImageToCanvas = createAction('gallery/sentImageToCanvas');
export const imageDownloaded = createAction('gallery/imageDownloaded');
export const imageCopiedToClipboard = createAction('gallery/imageCopiedToClipboard');
export const imageOpenedInNewTab = createAction('gallery/imageOpenedInNewTab');

View File

@@ -72,11 +72,7 @@ const ModelImageUpload = ({ model_key, model_image }: Props) => {
}, [model_key, t, deleteModelImage]);
const { getInputProps, getRootProps } = useDropzone({
accept: {
'image/png': ['.png'],
'image/jpeg': ['.jpg', '.jpeg', '.png'],
'image/webp': ['.webp'],
},
accept: { 'image/png': ['.png'], 'image/jpeg': ['.jpg', '.jpeg', '.png'] },
onDropAccepted,
noDrag: true,
multiple: false,

View File

@@ -44,7 +44,6 @@ import {
} from 'features/nodes/store/selectors';
import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
import { selectSelectionMode, selectShouldSnapToGrid } from 'features/nodes/store/workflowSettingsSlice';
import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
import type { AnyEdge, AnyNode } from 'features/nodes/types/invocation';
import { useRegisteredHotkeys } from 'features/system/components/HotkeysModal/useHotkeyData';
import type { CSSProperties, MouseEvent } from 'react';
@@ -357,9 +356,6 @@ export const Flow = memo(() => {
selectionMode={selectionMode}
elevateEdgesOnSelect
nodeDragThreshold={1}
noDragClassName={NO_DRAG_CLASS}
noWheelClassName={NO_WHEEL_CLASS}
noPanClassName={NO_PAN_CLASS}
>
<Background />
</ReactFlow>

View File

@@ -5,7 +5,6 @@ import { BaseEdge, EdgeLabelRenderer, getBezierPath } from '@xyflow/react';
import { useAppSelector } from 'app/store/storeHooks';
import { buildSelectAreConnectedNodesSelected } from 'features/nodes/components/flow/edges/util/buildEdgeSelectors';
import { selectShouldAnimateEdges } from 'features/nodes/store/workflowSettingsSlice';
import { NO_DRAG_CLASS, NO_PAN_CLASS } from 'features/nodes/types/constants';
import type { CollapsedInvocationNodeEdge } from 'features/nodes/types/invocation';
import { memo, useMemo } from 'react';
@@ -81,7 +80,7 @@ const InvocationCollapsedEdge = ({
<Box
position="absolute"
transform={`translate(-50%, -50%) translate(${labelX}px,${labelY}px)`}
className={`edge-label-renderer__custom-edge ${NO_DRAG_CLASS} ${NO_PAN_CLASS}`} // Unfortunately edge labels do not get the same zIndex treatment as edges do, so we need to manage this ourselves
className="edge-label-renderer__custom-edge nodrag nopan" // Unfortunately edge labels do not get the same zIndex treatment as edges do, so we need to manage this ourselves
// See: https://github.com/xyflow/xyflow/issues/3658
zIndex={1001}
>

View File

@@ -6,7 +6,6 @@ import { BaseEdge, EdgeLabelRenderer, getBezierPath } from '@xyflow/react';
import { useAppSelector } from 'app/store/storeHooks';
import { $templates } from 'features/nodes/store/nodesSlice';
import { selectShouldAnimateEdges, selectShouldShowEdgeLabels } from 'features/nodes/store/workflowSettingsSlice';
import { NO_DRAG_CLASS, NO_PAN_CLASS } from 'features/nodes/types/constants';
import type { DefaultInvocationNodeEdge } from 'features/nodes/types/invocation';
import { memo, useMemo } from 'react';
@@ -115,7 +114,7 @@ const InvocationDefaultEdge = ({
{label && shouldShowEdgeLabels && (
<EdgeLabelRenderer>
<Flex
className={`${NO_DRAG_CLASS} ${NO_PAN_CLASS}`}
className="nodrag nopan"
transform={`translate(-50%, -50%) translate(${labelX}px,${labelY}px)`}
data-selected={selected}
sx={edgeLabelWrapperSx}

View File

@@ -31,9 +31,6 @@ const sx: SystemStyleObject = {
'&[data-with-footer="true"]': {
borderBottomRadius: 0,
},
'&[data-with-footer="false"]': {
pb: 4,
},
};
const InvocationNode = ({ nodeId, isOpen }: Props) => {

View File

@@ -1,6 +1,5 @@
import type { ChakraProps } from '@invoke-ai/ui-library';
import { Flex, FormControlGroup } from '@invoke-ai/ui-library';
import { useIsExecutableNode } from 'features/nodes/hooks/useIsBatchNode';
import { useNodeHasImageOutput } from 'features/nodes/hooks/useNodeHasImageOutput';
import { DRAG_HANDLE_CLASSNAME } from 'features/nodes/types/constants';
import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
@@ -17,7 +16,6 @@ const props: ChakraProps = { w: 'unset' };
const InvocationNodeFooter = ({ nodeId }: Props) => {
const hasImageOutput = useNodeHasImageOutput(nodeId);
const isExecutableNode = useIsExecutableNode(nodeId);
const isCacheEnabled = useFeatureStatus('invocationCache');
return (
<Flex
@@ -32,8 +30,8 @@ const InvocationNodeFooter = ({ nodeId }: Props) => {
justifyContent="space-between"
>
<FormControlGroup formControlProps={props} formLabelProps={props}>
{isExecutableNode && isCacheEnabled && <UseCacheCheckbox nodeId={nodeId} />}
{isExecutableNode && hasImageOutput && <SaveToGalleryCheckbox nodeId={nodeId} />}
{isCacheEnabled && <UseCacheCheckbox nodeId={nodeId} />}
{hasImageOutput && <SaveToGalleryCheckbox nodeId={nodeId} />}
</FormControlGroup>
</Flex>
);

View File

@@ -3,7 +3,6 @@ import { Flex } from '@invoke-ai/ui-library';
import NodeCollapseButton from 'features/nodes/components/flow/nodes/common/NodeCollapseButton';
import NodeTitle from 'features/nodes/components/flow/nodes/common/NodeTitle';
import InvocationNodeClassificationIcon from 'features/nodes/components/flow/nodes/Invocation/InvocationNodeClassificationIcon';
import { useNodeIsInvalid } from 'features/nodes/hooks/useNodeIsInvalid';
import { memo } from 'react';
import InvocationNodeCollapsedHandles from './InvocationNodeCollapsedHandles';
@@ -26,16 +25,11 @@ const sx: SystemStyleObject = {
'&[data-is-open="true"]': {
borderBottomRadius: 0,
},
'&[data-is-invalid="true"]': {
color: 'error.300',
},
};
const InvocationNodeHeader = ({ nodeId, isOpen }: Props) => {
const isInvalid = useNodeIsInvalid(nodeId);
return (
<Flex layerStyle="nodeHeader" sx={sx} data-is-open={isOpen} data-is-invalid={isInvalid}>
<Flex layerStyle="nodeHeader" sx={sx} data-is-open={isOpen}>
<NodeCollapseButton nodeId={nodeId} isOpen={isOpen} />
<InvocationNodeClassificationIcon nodeId={nodeId} />
<NodeTitle nodeId={nodeId} />

View File

@@ -23,7 +23,7 @@ export const InvocationNodeNotesTextarea = memo(({ nodeId }: Props) => {
return (
<FormControl orientation="vertical" h="full">
<FormLabel>{t('nodes.notes')}</FormLabel>
<Textarea value={notes} onChange={handleNotesChanged} rows={10} resize="none" variant="darkFilled" />
<Textarea value={notes} onChange={handleNotesChanged} rows={10} resize="none" />
</FormControl>
);
});

View File

@@ -3,7 +3,6 @@ import { useAppDispatch } from 'app/store/storeHooks';
import { useNodeHasImageOutput } from 'features/nodes/hooks/useNodeHasImageOutput';
import { useNodeIsIntermediate } from 'features/nodes/hooks/useNodeIsIntermediate';
import { nodeIsIntermediateChanged } from 'features/nodes/store/nodesSlice';
import { NO_PAN_CLASS } from 'features/nodes/types/constants';
import type { ChangeEvent } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
@@ -30,7 +29,7 @@ const SaveToGalleryCheckbox = ({ nodeId }: { nodeId: string }) => {
}
return (
<FormControl className={NO_PAN_CLASS}>
<FormControl className="nopan">
<FormLabel m={0}>{t('nodes.saveToGallery')} </FormLabel>
<Checkbox onChange={handleChange} isChecked={!isIntermediate} />
</FormControl>

View File

@@ -2,7 +2,6 @@ import { Checkbox, FormControl, FormLabel } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { useUseCache } from 'features/nodes/hooks/useUseCache';
import { nodeUseCacheChanged } from 'features/nodes/store/nodesSlice';
import { NO_FIT_ON_DOUBLE_CLICK_CLASS, NO_PAN_CLASS } from 'features/nodes/types/constants';
import type { ChangeEvent } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
@@ -23,9 +22,9 @@ const UseCacheCheckbox = ({ nodeId }: { nodeId: string }) => {
);
const { t } = useTranslation();
return (
<FormControl className={NO_FIT_ON_DOUBLE_CLICK_CLASS}>
<FormControl>
<FormLabel m={0}>{t('invocationCache.useCache')}</FormLabel>
<Checkbox className={NO_PAN_CLASS} onChange={handleChange} isChecked={useCache} />
<Checkbox className="nopan" onChange={handleChange} isChecked={useCache} />
</FormControl>
);
};

View File

@@ -1,7 +1,6 @@
import { CompositeNumberInput } from '@invoke-ai/ui-library';
import { useFloatField } from 'features/nodes/components/flow/nodes/Invocation/fields/FloatField/useFloatField';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { FloatFieldInputInstance, FloatFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -17,7 +16,7 @@ export const FloatFieldInput = memo((props: FieldComponentProps<FloatFieldInputI
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
flex="1 1 0"
/>
);

View File

@@ -1,7 +1,6 @@
import { CompositeNumberInput, CompositeSlider } from '@invoke-ai/ui-library';
import { useFloatField } from 'features/nodes/components/flow/nodes/Invocation/fields/FloatField/useFloatField';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { FloatFieldInputInstance, FloatFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -19,7 +18,7 @@ export const FloatFieldInputAndSlider = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
marks
withThumbTooltip
flex="1 1 0"
@@ -32,7 +31,7 @@ export const FloatFieldInputAndSlider = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
flex="1 1 0"
/>
</>

View File

@@ -1,7 +1,6 @@
import { CompositeSlider } from '@invoke-ai/ui-library';
import { useFloatField } from 'features/nodes/components/flow/nodes/Invocation/fields/FloatField/useFloatField';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { FloatFieldInputInstance, FloatFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -17,7 +16,7 @@ export const FloatFieldSlider = memo((props: FieldComponentProps<FloatFieldInput
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
marks
withThumbTooltip
flex="1 1 0"

View File

@@ -1,29 +0,0 @@
import { IconButton } from '@invoke-ai/ui-library';
import { useAddNodeFieldToRoot } from 'features/nodes/components/sidePanel/builder/use-add-node-field-to-root';
import { memo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
type Props = {
nodeId: string;
fieldName: string;
};
export const InputFieldAddToFormRoot = memo(({ nodeId, fieldName }: Props) => {
const { t } = useTranslation();
const addToRoot = useAddNodeFieldToRoot(nodeId, fieldName);
return (
<IconButton
variant="ghost"
tooltip={t('workflows.builder.addToForm')}
aria-label={t('workflows.builder.addToForm')}
icon={<PiPlusBold />}
pointerEvents="auto"
size="xs"
onClick={addToRoot}
/>
);
});
InputFieldAddToFormRoot.displayName = 'InputFieldAddToFormRoot';

View File

@@ -10,7 +10,6 @@ import {
import { useAppDispatch } from 'app/store/storeHooks';
import { useInputFieldDescription } from 'features/nodes/hooks/useInputFieldDescription';
import { fieldDescriptionChanged } from 'features/nodes/store/nodesSlice';
import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
import type { ChangeEvent } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
@@ -60,7 +59,7 @@ const Content = memo(({ nodeId, fieldName }: Props) => {
<FormControl orientation="vertical">
<FormLabel>{t('nodes.description')}</FormLabel>
<Textarea
className={`${NO_DRAG_CLASS} ${NO_PAN_CLASS} ${NO_WHEEL_CLASS}`}
className="nodrag nopan nowheel"
fontSize="sm"
value={description ?? ''}
onChange={onChange}

View File

@@ -1,16 +1,14 @@
import type { SystemStyleObject } from '@invoke-ai/ui-library';
import { Flex, Spacer } from '@invoke-ai/ui-library';
import { InputFieldAddToFormRoot } from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldAddToFormRoot';
import { Flex, FormControl, Spacer } from '@invoke-ai/ui-library';
import { InputFieldDescriptionPopover } from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldDescriptionPopover';
import { InputFieldHandle } from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldHandle';
import { InputFieldResetToDefaultValueIconButton } from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldResetToDefaultValueIconButton';
import { useNodeFieldDnd } from 'features/nodes/components/sidePanel/builder/dnd-hooks';
import { useNodeFieldDnd } from 'features/nodes/components/sidePanel/builder/dnd';
import { useInputFieldIsConnected } from 'features/nodes/hooks/useInputFieldIsConnected';
import { useInputFieldIsInvalid } from 'features/nodes/hooks/useInputFieldIsInvalid';
import { useInputFieldTemplate } from 'features/nodes/hooks/useInputFieldTemplate';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { FieldInputTemplate } from 'features/nodes/types/field';
import { memo, useRef } from 'react';
import { memo, useCallback, useRef, useState } from 'react';
import { InputFieldRenderer } from './InputFieldRenderer';
import { InputFieldTitle } from './InputFieldTitle';
@@ -59,12 +57,12 @@ type CommonProps = {
fieldTemplate: FieldInputTemplate;
};
const ConnectedOrConnectionField = memo(({ nodeId, fieldName, isInvalid }: CommonProps) => {
const ConnectedOrConnectionField = memo(({ nodeId, fieldName, isInvalid, isConnected }: CommonProps) => {
return (
<InputFieldWrapper>
<Flex px={2}>
<FormControl isInvalid={isInvalid} isDisabled={isConnected} px={2}>
<InputFieldTitle nodeId={nodeId} fieldName={fieldName} isInvalid={isInvalid} />
</Flex>
</FormControl>
<InputFieldHandle nodeId={nodeId} fieldName={fieldName} />
</InputFieldWrapper>
);
@@ -72,10 +70,8 @@ const ConnectedOrConnectionField = memo(({ nodeId, fieldName, isInvalid }: Commo
ConnectedOrConnectionField.displayName = 'ConnectedOrConnectionField';
const directFieldSx: SystemStyleObject = {
w: 'full',
orientation: 'vertical',
px: 2,
flexDir: 'column',
gap: 1,
'&[data-is-dragging="true"]': {
opacity: 0.3,
},
@@ -85,39 +81,48 @@ const directFieldSx: SystemStyleObject = {
'&[data-is-connected="true"]': {
pointerEvents: 'none',
},
// The action buttons are hidden by default and shown on hover
'& .direct-field-action-buttons': {
display: 'none',
},
_hover: {
'& .direct-field-action-buttons': {
display: 'inline-flex',
},
},
};
const DirectField = memo(({ nodeId, fieldName, isInvalid, isConnected, fieldTemplate }: CommonProps) => {
const draggableRef = useRef<HTMLDivElement>(null);
const dragHandleRef = useRef<HTMLDivElement>(null);
const [isHovered, setIsHovered] = useState(false);
const onMouseEnter = useCallback(() => {
setIsHovered(true);
}, []);
const onMouseLeave = useCallback(() => {
setIsHovered(false);
}, []);
const isDragging = useNodeFieldDnd({ nodeId, fieldName }, fieldTemplate, draggableRef, dragHandleRef);
return (
<InputFieldWrapper>
<Flex ref={draggableRef} sx={directFieldSx} data-is-connected={isConnected} data-is-dragging={isDragging}>
<Flex gap={1}>
<Flex className={NO_DRAG_CLASS} ref={dragHandleRef}>
<InputFieldTitle nodeId={nodeId} fieldName={fieldName} isInvalid={isInvalid} isDragging={isDragging} />
</Flex>
<Spacer />
<Flex className="direct-field-action-buttons">
<InputFieldDescriptionPopover nodeId={nodeId} fieldName={fieldName} />
<InputFieldResetToDefaultValueIconButton nodeId={nodeId} fieldName={fieldName} />
<InputFieldAddToFormRoot nodeId={nodeId} fieldName={fieldName} />
<FormControl
ref={draggableRef}
isInvalid={isInvalid}
isDisabled={isConnected}
sx={directFieldSx}
data-is-connected={isConnected}
data-is-dragging={isDragging}
>
<Flex flexDir="column" w="full" gap={1} onMouseEnter={onMouseEnter} onMouseLeave={onMouseLeave}>
<Flex className="nodrag" ref={dragHandleRef} gap={1}>
<InputFieldTitle nodeId={nodeId} fieldName={fieldName} isInvalid={isInvalid} />
<Spacer />
{isHovered && (
<>
<InputFieldDescriptionPopover nodeId={nodeId} fieldName={fieldName} />
<InputFieldResetToDefaultValueIconButton nodeId={nodeId} fieldName={fieldName} />
</>
)}
</Flex>
<InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
</Flex>
<InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
</Flex>
</FormControl>
{fieldTemplate.input !== 'direct' && <InputFieldHandle nodeId={nodeId} fieldName={fieldName} />}
</InputFieldWrapper>
);

View File

@@ -9,9 +9,8 @@ import {
} from 'features/nodes/hooks/useFieldConnectionState';
import { useInputFieldTemplate } from 'features/nodes/hooks/useInputFieldTemplate';
import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
import { HANDLE_TOOLTIP_OPEN_DELAY, MODEL_TYPES } from 'features/nodes/types/constants';
import type { FieldInputTemplate } from 'features/nodes/types/field';
import { isModelFieldType } from 'features/nodes/types/field';
import type { CSSProperties } from 'react';
import { memo, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@@ -65,7 +64,7 @@ export const InputFieldHandle = memo(({ nodeId, fieldName }: Props) => {
const fieldTemplate = useInputFieldTemplate(nodeId, fieldName);
const fieldTypeName = useFieldTypeName(fieldTemplate.type);
const fieldColor = useMemo(() => getFieldColor(fieldTemplate.type), [fieldTemplate.type]);
const isModelField = useMemo(() => isModelFieldType(fieldTemplate.type), [fieldTemplate.type]);
const isModelField = useMemo(() => MODEL_TYPES.some((t) => t === fieldTemplate.type.name), [fieldTemplate.type]);
const isConnectionInProgress = useIsConnectionInProgress();
if (isConnectionInProgress) {

View File

@@ -4,7 +4,6 @@ import { FloatFieldSlider } from 'features/nodes/components/flow/nodes/Invocatio
import { FloatFieldCollectionInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/FloatFieldCollectionInputComponent';
import { FloatGeneratorFieldInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/FloatGeneratorFieldComponent';
import { ImageFieldCollectionInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/ImageFieldCollectionInputComponent';
import { ImageGeneratorFieldInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/ImageGeneratorFieldComponent';
import { IntegerFieldCollectionInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/IntegerFieldCollectionInputComponent';
import { IntegerGeneratorFieldInputComponent } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/IntegerGeneratorFieldComponent';
import ModelIdentifierFieldInputComponent from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/ModelIdentifierFieldInputComponent';
@@ -50,8 +49,6 @@ import {
isImageFieldCollectionInputTemplate,
isImageFieldInputInstance,
isImageFieldInputTemplate,
isImageGeneratorFieldInputInstance,
isImageGeneratorFieldInputTemplate,
isIntegerFieldCollectionInputInstance,
isIntegerFieldCollectionInputTemplate,
isIntegerFieldInputInstance,
@@ -395,13 +392,6 @@ export const InputFieldRenderer = memo(({ nodeId, fieldName, settings }: Props)
return <StringGeneratorFieldInputComponent nodeId={nodeId} field={field} fieldTemplate={template} />;
}
if (isImageGeneratorFieldInputTemplate(template)) {
if (!isImageGeneratorFieldInputInstance(field)) {
return null;
}
return <ImageGeneratorFieldInputComponent nodeId={nodeId} field={field} fieldTemplate={template} />;
}
return null;
});

View File

@@ -12,8 +12,7 @@ import { useInputFieldIsConnected } from 'features/nodes/hooks/useInputFieldIsCo
import { useInputFieldLabel } from 'features/nodes/hooks/useInputFieldLabel';
import { useInputFieldTemplateTitle } from 'features/nodes/hooks/useInputFieldTemplateTitle';
import { fieldLabelChanged } from 'features/nodes/store/nodesSlice';
import { HANDLE_TOOLTIP_OPEN_DELAY, NO_FIT_ON_DOUBLE_CLICK_CLASS } from 'features/nodes/types/constants';
import type { MouseEvent } from 'react';
import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
import { memo, useCallback, useMemo, useRef } from 'react';
import { useTranslation } from 'react-i18next';
@@ -37,11 +36,10 @@ interface Props {
nodeId: string;
fieldName: string;
isInvalid?: boolean;
isDragging?: boolean;
}
export const InputFieldTitle = memo((props: Props) => {
const { nodeId, fieldName, isInvalid, isDragging } = props;
const { nodeId, fieldName, isInvalid } = props;
const inputRef = useRef<HTMLInputElement>(null);
const label = useInputFieldLabel(nodeId, fieldName);
const fieldTemplateTitle = useInputFieldTemplateTitle(nodeId, fieldName);
@@ -66,34 +64,21 @@ export const InputFieldTitle = memo((props: Props) => {
inputRef,
});
const isDisabled = useMemo(
() => (isConnectionInProgress && connectionError !== null && !isConnectionStartField) || isConnected,
[isConnectionInProgress, connectionError, isConnectionStartField, isConnected]
);
const onDoubleClick = useCallback(
(e: MouseEvent<HTMLParagraphElement>) => {
e.stopPropagation();
editable.startEditing();
},
[editable]
);
if (!editable.isEditing) {
return (
<Tooltip
label={<InputFieldTooltipContent nodeId={nodeId} fieldName={fieldName} />}
openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
placement="top"
isDisabled={isDragging}
>
<Text
className={NO_FIT_ON_DOUBLE_CLICK_CLASS}
sx={labelSx}
noOfLines={1}
data-is-invalid={isInvalid}
data-is-disabled={isDisabled}
onDoubleClick={onDoubleClick}
data-is-disabled={
(isConnectionInProgress && connectionError !== null && !isConnectionStartField) || isConnected
}
onDoubleClick={editable.startEditing}
>
{editable.value}
</Text>
@@ -101,14 +86,7 @@ export const InputFieldTitle = memo((props: Props) => {
);
}
return (
<Input
ref={inputRef}
variant="outline"
{...editable.inputProps}
_focusVisible={{ borderRadius: 'base', h: 'unset', px: 2 }}
/>
);
return <Input ref={inputRef} variant="outline" {...editable.inputProps} />;
});
InputFieldTitle.displayName = 'InputFieldTitle';

View File

@@ -1,7 +1,6 @@
import { CompositeNumberInput } from '@invoke-ai/ui-library';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { useIntegerField } from 'features/nodes/components/flow/nodes/Invocation/fields/IntegerField/useIntegerField';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { IntegerFieldInputInstance, IntegerFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -18,7 +17,7 @@ export const IntegerFieldInput = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
flex="1 1 0"
/>
);

View File

@@ -1,7 +1,6 @@
import { CompositeNumberInput, CompositeSlider } from '@invoke-ai/ui-library';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { useIntegerField } from 'features/nodes/components/flow/nodes/Invocation/fields/IntegerField/useIntegerField';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { IntegerFieldInputInstance, IntegerFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -19,7 +18,7 @@ export const IntegerFieldInputAndSlider = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
marks
withThumbTooltip
flex="1 1 0"
@@ -32,7 +31,7 @@ export const IntegerFieldInputAndSlider = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
flex="1 1 0"
/>
</>

View File

@@ -1,7 +1,6 @@
import { CompositeSlider } from '@invoke-ai/ui-library';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { useIntegerField } from 'features/nodes/components/flow/nodes/Invocation/fields/IntegerField/useIntegerField';
import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
import type { IntegerFieldInputInstance, IntegerFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -18,7 +17,7 @@ export const IntegerFieldSlider = memo(
max={max}
step={step}
fineStep={fineStep}
className={NO_DRAG_CLASS}
className="nodrag"
marks
withThumbTooltip
flex="1 1 0"

View File

@@ -15,10 +15,6 @@ export const NodeFieldElementResetToInitialValueIconButton = memo(({ element }:
const { nodeId, fieldName } = data.fieldIdentifier;
const { isValueChanged, resetToInitialValue } = useInputFieldInitialFormValue(id, nodeId, fieldName);
if (!isValueChanged) {
return null;
}
return (
<IconButton
variant="link"

View File

@@ -9,9 +9,8 @@ import {
} from 'features/nodes/hooks/useFieldConnectionState';
import { useOutputFieldTemplate } from 'features/nodes/hooks/useOutputFieldTemplate';
import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
import { HANDLE_TOOLTIP_OPEN_DELAY, MODEL_TYPES } from 'features/nodes/types/constants';
import type { FieldOutputTemplate } from 'features/nodes/types/field';
import { isModelFieldType } from 'features/nodes/types/field';
import type { CSSProperties } from 'react';
import { memo, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@@ -65,7 +64,7 @@ export const OutputFieldHandle = memo(({ nodeId, fieldName }: Props) => {
const fieldTemplate = useOutputFieldTemplate(nodeId, fieldName);
const fieldTypeName = useFieldTypeName(fieldTemplate.type);
const fieldColor = useMemo(() => getFieldColor(fieldTemplate.type), [fieldTemplate.type]);
const isModelField = useMemo(() => isModelFieldType(fieldTemplate.type), [fieldTemplate.type]);
const isModelField = useMemo(() => MODEL_TYPES.some((t) => t === fieldTemplate.type.name), [fieldTemplate.type]);
const isConnectionInProgress = useIsConnectionInProgress();
if (isConnectionInProgress) {

View File

@@ -1,7 +1,6 @@
import { Input } from '@invoke-ai/ui-library';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { useStringField } from 'features/nodes/components/flow/nodes/Invocation/fields/StringField/useStringField';
import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
import type { StringFieldInputInstance, StringFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -9,7 +8,7 @@ export const StringFieldInput = memo(
(props: FieldComponentProps<StringFieldInputInstance, StringFieldInputTemplate>) => {
const { value, onChange } = useStringField(props);
return <Input className={`${NO_DRAG_CLASS} ${NO_PAN_CLASS} ${NO_WHEEL_CLASS}`} value={value} onChange={onChange} />;
return <Input className="nodrag nowheel nopan" value={value} onChange={onChange} />;
}
);

View File

@@ -1,7 +1,6 @@
import { Textarea } from '@invoke-ai/ui-library';
import type { FieldComponentProps } from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/types';
import { useStringField } from 'features/nodes/components/flow/nodes/Invocation/fields/StringField/useStringField';
import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
import type { StringFieldInputInstance, StringFieldInputTemplate } from 'features/nodes/types/field';
import { memo } from 'react';
@@ -11,10 +10,11 @@ export const StringFieldTextarea = memo(
return (
<Textarea
className={`${NO_DRAG_CLASS} ${NO_PAN_CLASS} ${NO_WHEEL_CLASS}`}
className="nodrag nowheel nopan"
value={value}
onChange={onChange}
h="full"
resize="none"
fontSize="sm"
p={2}
/>

View File

@@ -2,7 +2,6 @@ import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
import { Combobox } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { fieldBoardValueChanged } from 'features/nodes/store/nodesSlice';
import { NO_DRAG_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
import type { BoardFieldInputInstance, BoardFieldInputTemplate } from 'features/nodes/types/field';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@@ -10,110 +9,62 @@ import { useListAllBoardsQuery } from 'services/api/endpoints/boards';
import type { FieldComponentProps } from './types';
/**
* The board field values in the UI do not map 1-to-1 to the values the graph expects.
*
* The graph value is either an object in the shape of `{board_id: string}` or undefined.
*
* But in the UI, we have the following options:
* - auto: Use the "auto add" board. During graph building, we pull the auto add board ID from the state and use it.
* - none: Do not assign a board. In the graph, this is represented as undefined.
* - board_id: Assign the specified board. In the graph, this is represented as `{board_id: string}`.
*
* It's also possible that the UI value is undefined, which may be the case for some older workflows. In this case, we
* map it to the "auto" option.
*
* So there is some translation that needs to happen in both directions - when the user selects a board in the UI, and
* when we build the graph. The former is handled in this component, the latter in the `buildNodesGraph` function.
*/
const listAllBoardsQueryArg = { include_archived: true };
const getBoardValue = (val: string) => {
if (val === 'auto' || val === 'none') {
return val;
}
return {
board_id: val,
};
};
const BoardFieldInputComponent = (props: FieldComponentProps<BoardFieldInputInstance, BoardFieldInputTemplate>) => {
const { nodeId, field } = props;
const dispatch = useAppDispatch();
const { t } = useTranslation();
const listAllBoardsQuery = useListAllBoardsQuery(listAllBoardsQueryArg);
const autoOption = useMemo<ComboboxOption>(() => {
return {
label: t('common.auto'),
value: 'auto',
};
}, [t]);
const noneOption = useMemo<ComboboxOption>(() => {
return {
label: `${t('common.none')} (${t('boards.uncategorized')})`,
value: 'none',
};
}, [t]);
const options = useMemo<ComboboxOption[]>(() => {
const _options: ComboboxOption[] = [autoOption, noneOption];
if (listAllBoardsQuery.data) {
for (const board of listAllBoardsQuery.data) {
_options.push({
label: board.board_name,
value: board.board_id,
});
}
const { options, hasBoards } = useListAllBoardsQuery(
{ include_archived: true },
{
selectFromResult: ({ data }) => {
const options: ComboboxOption[] = [
{
label: 'None',
value: 'none',
},
].concat(
(data ?? []).map(({ board_id, board_name }) => ({
label: board_name,
value: board_id,
}))
);
return {
options,
hasBoards: options.length > 1,
};
},
}
return _options;
}, [autoOption, listAllBoardsQuery.data, noneOption]);
);
const onChange = useCallback<ComboboxOnChange>(
(v) => {
if (!v) {
// This should never happen
return;
}
const value = getBoardValue(v.value);
dispatch(
fieldBoardValueChanged({
nodeId,
fieldName: field.name,
value,
value: v.value !== 'none' ? { board_id: v.value } : undefined,
})
);
},
[dispatch, field.name, nodeId]
);
const value = useMemo(() => {
const _value = field.value;
if (!_value || _value === 'auto') {
return autoOption;
}
if (_value === 'none') {
return noneOption;
}
const boardOption = options.find((o) => o.value === _value.board_id);
return boardOption ?? autoOption;
}, [field.value, options, autoOption, noneOption]);
const value = useMemo(() => options.find((o) => o.value === field.value?.board_id), [options, field.value]);
const noOptionsMessage = useCallback(() => t('boards.noMatching'), [t]);
return (
<Combobox
className={`${NO_WHEEL_CLASS} ${NO_DRAG_CLASS}`}
className="nowheel nodrag"
value={value}
options={options}
onChange={onChange}
placeholder={t('boards.selectBoard')}
noOptionsMessage={noOptionsMessage}
isDisabled={!hasBoards}
/>
);
};

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