Release version 2.1.1

.comfyignore

@@ -1,6 +1,3 @@
 .github/
-preview/
 tests/
 registry/
-VERIFICATION.md
-ROLLBACK.md

.github/workflows/ci.yml

@@ -16,6 +16,9 @@ jobs:
       - uses: actions/setup-python@v7.0.0
         with:
           python-version: '3.12'
+      - uses: actions/setup-node@v7.1.0
+        with:
+          node-version: '22'
       - name: Install CPU test dependencies
         run: |
           python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
@@ -32,17 +35,11 @@ jobs:
           for source in pathlib.Path('web').glob('*.js'):
               subprocess.run(['node', '--input-type=module', '--check'], input=source.read_bytes(), check=True)
           PY
-      - name: Check exclusive routing behavior
-        run: node --experimental-default-type=module tests/test_exclusive_routes.mjs
-      - name: Check comparison result history
-        run: node --experimental-default-type=module tests/test_compare_history.mjs
-
-      - name: Check upload transport
-        run: node --experimental-default-type=module tests/test_upload_transport.mjs
-
-      - name: Check crop geometry
+      - name: Run all frontend regression tests
         run: |
-          node --experimental-default-type=module tests/test_crop_geometry.mjs
-          node --experimental-default-type=module tests/test_crop_dimensions.mjs
-          node --experimental-default-type=module tests/test_legacy_feedback.mjs
-          node --experimental-default-type=module tests/test_draft_guard.mjs
+          python - <<'PY'
+          import pathlib, subprocess
+          for test in sorted(pathlib.Path('tests').glob('test_*.mjs')):
+              print(f'Running {test}', flush=True)
+              subprocess.run(['node', '--experimental-default-type=module', str(test)], check=True)
+          PY

CHANGELOG.md

@@ -1,5 +1,59 @@
 # Changelog
 
+## 2.1.1 · 2026-11-12
+
+- Remove the duplicate lower Fit button in the standalone workspace; the top Fit control and the workflow comparison node's button remain available.
+- Move the whole-image and masked-area choices directly below Generate in the workspace.
+- Place color-paint controls in the existing lower toolbar for both editing modes.
+
+## 2.1.0 · 2026-11-12
+
+- Add an independent color-paint layer to Mask and Crop & Blend modes. Alt-click samples the visible image color, Ctrl + wheel changes brush size, and the painted image is used for inpainting.
+- Show upload progress while merging an adopted crop before releasing the selection; keep the selection when the upload fails so it can be retried.
+- Keep the editor, comparison and parameter controls in the workspace when ComfyUI remounts DOM widgets during layout changes.
+- Show download and upload progress while adopting results; retry transient image-read failures after uploads and preserve the previous source on failure.
+- Add wheel zoom, middle-button pan and Fit to the standalone workspace's sliding and before/after comparison views.
+- Move Generate, width, height and denoise controls higher in the workspace settings, and allow positive and negative prompts to be collapsed.
+- Adopt GPL-3.0-only for the current project and preserve the original MIT copyright and permission notice for earlier releases and applicable legacy material. Previous releases retain the permissions under which they were distributed.
+- Update bilingual documentation with real workspace screenshots, a tested-model compatibility matrix, workflow limits and a concise release history.
+
+## 2.0.1 · stability fixes (2026-11-10)
+
+- Release late preview object URLs after sibling failures, discard corrupt cached PNGs, bound decoding and cancel stale preview reads. Downloads and both ordinary/crop adoption use bounded transfers too.
+- Add upload inactivity detection and cancellation without limiting the overall duration of advancing XHR transfers; keep authentication fallback and real byte progress.
+- Dispose workspaces safely during initialization/validation, coalesce background checks, and hand submitted task IDs to a reopened workspace before result recovery. Recovery selects sliding comparison even when the result was already cached.
+- Share one exact-task history poller between node and workspace; cancel disposed recovery requests and release discarded pending states.
+- Keep the last good source usable after an invalid replacement. Protect source rollback from intervening completed strokes/crop changes and release partially decoded masks and retired blend canvases.
+- Bound preview-cache batch metadata to 512 batches as well as the existing byte limit. Empty/invalid batches leave cached images unchanged.
+- Find dense mask bounds from row/column occupancy instead of allocating coordinates per painted pixel; sanitize into a private tensor with one less full-image allocation.
+- Reject malformed workflow input mappings before core replacement hooks can crash. Existing node IDs, workflows, masks, crop layers, presets and sampling behavior are retained.
+
+## 2.0.0 · 2026-11-09
+
+- Ship the standalone Adachi Workbench with English default labels and Simplified Chinese translations following ComfyUI's language setting.
+- Add one official text-to-image / inpainting workflow with group bypass presets and automatic exclusive routing, using neutral prompts and a user-selected checkpoint.
+- Use a transparent title treatment with semi-transparent black lettering instead of a white title background.
+
+- Rename the page brand to Adachi Workbench and add a remembered, keyboard-accessible canvas/settings divider.
+- Remove personal-template node IDs and preset/model-name matching. Discover components from the native execution graph, including Use Everywhere and subgraphs.
+- Preserve intermediate model, conditioning, image and output processing. Add explicit pipeline/controller selection for ambiguous workflows.
+- Distinguish inherited LoRA chains from custom overrides; preserve split CLIP paths and allow execution-only custom LoRAs without a loader in the editable graph.
+
+- Keep the canvas and editing controls available during generation; submit an independent snapshot and defer automatic view switching while a pointer stroke is active.
+- Show actual execution stages and sampler steps above workflow settings, including queued, cached, reconnect and completion states.
+- Return to mask editing after adopting a crop, preserving its region, result layer and repaint mask.
+- List missing model components and their model folders, and expose separate text encoder / VAE choices for Anima-style profiles.
+
+- Detect missing backend routes before submitting and support API-prefixed proxy paths.
+- Add remembered light/dark themes, compact edit and before/after icons, hover help and default sliding comparison after generation.
+- Follow sampler conditioning through Get/Set and exclusive routes; derive preset buttons from the enabled controller and warn when unavailable.
+- Keep crop and result controls above the measured source-history dock on narrow screens.
+- Recover lost result notifications by queued task ID in both node and workspace; add streamed image progress, inactivity timeouts, cancellation, automatic retries and reconnect recovery.
+
+## 1.0.1
+
+- Retry comparison image loading after network errors or timeouts and add a manual reload button. Expired preview references still require a new generation.
+
 ## 1.0.0
 
 - First stable release of the inline inpainting workspace, comparison, crop blending and workflow switching tools.

LICENSE

@@ -1,21 +1,674 @@
-MIT License
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LICENSES/MIT-previous-releases.txt

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Adachi Workbench contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSES/README.md

@@ -0,0 +1,5 @@
+# License history
+
+The current project is licensed under GPL-3.0-only; see the root [LICENSE](../LICENSE).
+
+Releases up to and including v2.0.1 were distributed under the MIT License. Their original copyright and permission notice is reproduced in [MIT-previous-releases.txt](MIT-previous-releases.txt), including for previously MIT-licensed material carried forward where applicable. Recipients of older versions retain the permissions granted with those versions. The retained notice does not grant an additional MIT license to new GPL-only changes.

README.md

@@ -8,7 +8,7 @@ An inline inpainting workspace for ComfyUI, with WebUI-style controls and tools
 
 **English** · [简体中文](README.zh-CN.md)
 
-[![License: MIT](https://img.shields.io/badge/License-MIT-38966b)](LICENSE)
+[![License: GPL-3.0-only](https://img.shields.io/badge/License-GPL--3.0--only-38966b)](LICENSE)
 [![ComfyUI custom nodes](https://img.shields.io/badge/ComfyUI-Custom_Nodes-4776b4)](https://github.com/Comfy-Org/ComfyUI)
 [![Python 3.10+](https://img.shields.io/badge/Python-3.10%2B-4776b4)](pyproject.toml)
 [![Validate plugin](https://github.com/adachi0130/Adachi-Inpaint-Workbench/actions/workflows/ci.yml/badge.svg)](https://github.com/adachi0130/Adachi-Inpaint-Workbench/actions/workflows/ci.yml)
@@ -28,7 +28,7 @@ Inpainting usually means moving between the workflow, a mask editor and the gene
 | Tool | What it adds |
 | --- | --- |
 | **Inline Mask** | Paint masks or crop, inpaint and blend two layers in the same node. |
-| **WebUI Inpaint** | Whole-image or masked-area sampling, familiar inpainting controls and compositing back at the source resolution. |
+| **Adachi Inpaint Workbench** | Whole-image or masked-area sampling, familiar inpainting controls and compositing back at the source resolution. |
 | **Image Compare** | Hover comparison, result history and one-click adoption for another editing round. |
 | **Group Bypass Presets** | Save combinations of enabled/bypassed groups and apply them with one click. |
 | **Auto Exclusive Switch** | Route the only enabled branch to a shared output, without a manual switch widget. |
@@ -37,16 +37,51 @@ English and Simplified Chinese interfaces follow the ComfyUI language setting. T
 
 ## Features
 
+<details open>
+<summary>Workbench screenshots</summary>
+
+![Light workbench with an inline mask and workflow settings](preview/workbench-light.png)
+
+![Dark workbench with the comparison divider](preview/workbench-compare-dark.png)
+
+*Screenshots captured from the running plugin using a synthetic illustration. The comparison result is a CPU color inversion to demonstrate the divider, not an AI-generated inpaint.*
+
+</details>
+
+### Adachi Workbench · light and dark themes
+
+Click **Open Adachi Workbench** on an Adachi Inpaint Workbench node. Workflows need the plugin’s Inline Mask, inpaint and Image Compare nodes; their IDs, titles, preset names and model filenames can be different. The workspace follows the selected node’s actual connections to its editor and result. If several candidates are ambiguous, choose them under **Workflow connections**. An enabled Group Bypass Presets node supplies its own preset buttons; missing or ambiguous controllers show a reminder.
+
+Models, VAE, text encoders and prompts are discovered from the native execution graph, including Get/Set, Use Everywhere broadcasts and subgraph execution IDs. Intermediate model patches, ControlNet, multiple conditioning encoders, image processing and result postprocessing remain connected. Recognizable components get editing controls; other custom processing remains under the workflow’s control. No personal template IDs or model-family name matching are used.
+
+New profiles inherit the workflow’s LoRA chains, including different positive/negative CLIP paths. Clear **Inherit workflow LoRAs** to use a custom list; an empty custom list disables recognized LoRAs. Custom LoRAs can also be applied when the editable graph has no LoRA loader. Refiner use is available in the model menu. Existing explicit workspace selections remain stored per preset.
+
+Drag the divider between the image and settings to resize them. The width is remembered; double-click resets it, and arrow keys make small adjustments. Narrow screens keep the stacked layout. The theme icon remembers the light/dark preference. Hover controls for help.
+
+The Generate button, width, height and denoise controls are near the top of the settings panel. Collapse the positive and negative prompt sections when you need more room.
+
+Generation shows actual workflow stages and sampler steps above settings. You can keep painting, zooming and changing parameters; the queued task uses its submitted snapshot. Generated results open sliding comparison without replacing the source. Use the single before/after icon to toggle images, the pencil to edit, and **Adopt** to adopt. Crop adoption returns to editing with its region and mask intact. Source history can restore previous images, masks and crop state for the loaded browser session.
+
+In the standalone workspace's sliding and before/after comparison views, scroll over the image to zoom, drag with the middle mouse button to pan, and use **Fit** to restore the fitted view. The workflow's Image Compare node continues to use the wheel for navigating the workflow canvas.
+
+The comparison node and workspace recover lost execution notifications by queued task ID. Image loading reports actual received bytes, a percentage when size is known, then decoding; transient failures retry and can resume after reconnecting. Expired server-side previews require another run. Recovery does not create preview files. Updating backend code requires a full ComfyUI restart; frontend-only updates need a hard refresh.
+
+The [official workflow](examples/Adachi-Workbench.json) is a starting point, not a required template. Validation also covers independently built multi-pipeline workflows, changed node IDs and renamed presets. Labels default to English; choose Simplified Chinese in ComfyUI settings for the Chinese interface. Other locales use the English fallback.
+
 ### Paint directly on the graph
 
 Upload, drop or paste a source image and paint on **Inline Mask** itself. In Mask mode, uploading an image automatically fills the connected inpaint dimensions; a replacement of the same size keeps the mask, while a different-sized image starts with a fresh mask. Mask strokes stay in the browser and are saved with the workflow; painting does not require a disk save/load round-trip for every stroke.
 
+Use the **✎ color paint** button at the lower left to paint directly on the image in either mode. Choose a color or **Alt + click** the visible image to sample one; **Ctrl + wheel** changes brush size. Color painting uses a separate layer with its own undo and redo, and the painted image becomes the source for subsequent inpainting. Click the button again to return to mask editing.
+
+If browser draft storage is too small, the color layer may be saved as a PNG in ComfyUI's input directory instead of embedded in the workflow. Include that referenced file when moving the workflow to another machine.
+
 While a source image uploads, a progress bar reports the bytes actually sent and then shows when the image is loading. On platforms requiring a special authentication fallback, the indicator stays indeterminate rather than showing an estimated percentage.
 
 - Brush, soft edges, hardness, opacity, pen pressure, temporary erasing and shape tools.
-- A compact **↑ upload / ⛶ fit / pin** toolbar, with a mode selector at the upper right. Enable the pin (**Keep**) to keep the image fitted and centered; plain wheel then navigates the workflow, while `Ctrl` + wheel still changes brush size and `Shift` + wheel changes hardness.
+- A compact **↑ upload / ⛶ fit / pin** toolbar, with a mode selector at the upper right. The pin (**Keep**) preserves the current view; use **Fit** first if desired. Plain wheel then navigates the workflow, while `Ctrl` + wheel still changes brush size and `Shift` + wheel changes hardness.
 - Resize the editor horizontally or vertically. The pin state and node dimensions survive workflow reload.
-- The connected **WebUI Inpaint** node hosts the painting controls and sampling parameters, leaving more space for the picture. Its painting tools, mask mode and fill content fold behind an arrow; **Undo / Redo / Invert / Fill / Clear / Import / Export** remain visible. Fold state is saved with the workflow.
+- The connected **Adachi Inpaint Workbench** node hosts the painting controls and sampling parameters, leaving more space for the picture. Its painting tools, mask mode and fill content fold behind an arrow; **Undo / Redo / Invert / Fill / Clear / Import / Export** remain visible. Fold state is saved with the workflow.
 - Bounded display buffers and cached image/mask compositing reduce redraw cost at large graph zoom; the saved mask retains its source resolution.
 
 <details>
@@ -68,14 +103,16 @@ In Crop & Blend mode, choose one of six 64-aligned presets spanning 512–2048 p
 
 | Connection | Purpose |
 | --- | --- |
-| `Inline Mask.image` + `mask` → `WebUI Inpaint.image` + `mask` | Send the selected crop and its repaint mask. |
-| `Inline Mask.image` → `Image Compare.original`; `WebUI Inpaint.image` → `Image Compare.result` | Compare the crop before adopting it. |
+| `Inline Mask.image` + `mask` → `Adachi Inpaint Workbench.image` + `mask` | Send the selected crop and its repaint mask. |
+| `Inline Mask.image` → `Image Compare.original`; `Adachi Inpaint Workbench.image` → `Image Compare.result` | Compare the crop before adopting it. |
 | `Inline Mask.full_image` → `Save Image.images` | Save the current full image with the **adopted** layer stitched in. |
 
-Generate, inspect the result in **Image Compare**, then click **Adopt this result** to return it. There is no feedback wire and generation does not automatically replace the editor image. Use the inpaint node's **image** output for comparison; its `crop` output is the sampling canvas and can have a different size. [Open the ready-wired example](examples/05-inline-crop-blend.json).
+Generate, inspect the result in **Image Compare**, then click **Adopt this result** to return it. There is no feedback wire and generation does not automatically replace the editor image. Use the inpaint node's **image** output for comparison; its `crop` output is the sampling canvas and can have a different size. In the [official workflow](examples/Adachi-Workbench.json), select **Inpaint**, then switch Inline Mask to **Crop & Blend**.
 
 After adoption, the result appears in the selected area and the editor returns to the repaint mask, ready for another pass. Select **◐ blend layers** to paint the layer mask: brush keeps new pixels, **Alt** restores original pixels, and soft edges blend seams. The blend mask is independent of the repaint mask. While editing the blend mask, **hold the right mouse button** to preview the original and release it to return to the workspace. To select a new region, switch to **◌ repaint mask** and right-click (or press Escape); the visible result is merged before the selection is released. Left-click places the next region. The **↶ Undo** button undoes strokes in the active mask. Hover the bottom controls for instructions. For a generated batch, select the desired result in Image Compare before adopting it. A result tagged with an older crop is rejected after selecting another region.
 
+Merging an adopted crop can take time on a slow connection: upload progress is shown while the selection is being released. If the upload fails, the selection remains in place and the operation can be retried.
+
 ### Inpaint the whole image or just the masked region
 
 | Sampling area | Behaviour |
@@ -91,6 +128,8 @@ The panel includes mask inside/outside, original/fill/noise/zero-latent content,
 
 Move the pointer over **Image Compare**: **result on the left, original on the right**. Leave the picture to see the full result. The divider stays thin, the image stays fitted, and scrolling navigates the workflow background.
 
+Loading errors and timeouts are retried automatically; **↻** reloads the comparison manually. If the temporary memory preview has expired after server restart or cache eviction, run the workflow again.
+
 Results accumulate within an editing round, with the newest selected automatically. Each result retains its matching original; replayed preview notifications are not counted twice.
 
 Use the **↓** button to download the latest generated result at its original resolution, even when an older result is selected in the list. For a batch, it downloads the last image in that batch.
@@ -103,13 +142,13 @@ Save group states for your own setups: text-to-image, inpainting, model variants
 
 ![Group Bypass Presets with a preset list on the left and per-group states on the right](preview/group-bypass-presets.png)
 
-Choose a preset on the left, configure **Enabled / Bypassed / Keep current** on the right, or apply it from the node's right-click menu. Presets are stored in the workflow and need no wires or third-party group controller. Missing groups are reported; overlapping groups give the smaller group's setting priority.
+Choose a preset on the left, configure **Enabled / Bypassed / Keep current** on the right, or apply it from the node's right-click menu. Use the arrow to collapse or reopen the group details; this preference is saved in the workflow. Presets are stored in the workflow and need no wires or third-party group controller. Missing groups are reported; overlapping groups give the smaller group's setting priority.
 
 ### Automatically use the remaining branch
 
 Connect two alternatives to **Auto Exclusive Switch** and bypass one. The remaining enabled branch flows to the shared output, with no `switch` toggle to maintain.
 
-![Two Auto Exclusive Switch nodes routing positive and negative conditioning into WebUI Inpaint](preview/auto-exclusive-switch.png)
+![Two Auto Exclusive Switch nodes routing positive and negative conditioning into Adachi Inpaint Workbench](preview/auto-exclusive-switch.png)
 
 Use it for conditioning, strings, images, masks, models or latents; the two alternatives must use the same data type. Both enabled, or neither available, is an error rather than a silent preference for A.
 
@@ -125,7 +164,7 @@ Run from your `ComfyUI/custom_nodes` directory:
 git clone https://github.com/adachi0130/Adachi-Inpaint-Workbench.git
 ```
 
-**Restart ComfyUI completely, then hard-refresh the browser with `Ctrl+F5`** (`Cmd+Shift+R` on macOS). Search for `Inline Mask`, `WebUI Inpaint` or `Adachi` in the node menu.
+**Restart ComfyUI completely, then hard-refresh the browser with `Ctrl+F5`** (`Cmd+Shift+R` on macOS). Search for `Inline Mask`, `Adachi Inpaint Workbench` or `Adachi` in the node menu.
 
 ### Other installation options
 
@@ -143,14 +182,15 @@ For a Git installation, update with `git pull` inside the plugin folder, then re
 
 ## Quick start
 
-1. Drag [01-inline-inpaint.json](examples/01-inline-inpaint.json) into ComfyUI and select a compatible checkpoint, or connect your existing model, VAE and conditioning nodes.
-2. In **Inline Mask**, upload a picture and paint the region to change. **White repaints; black preserves.** Orange is only the on-screen overlay.
-3. Edit the upstream positive/negative prompts. Set the sampling area, width, height and denoise in **WebUI Inpaint**, then queue the workflow.
-4. Compare the output. Adopt a result when you want it to become the next source, and continue editing with the mask intact.
+1. Drag [Adachi-Workbench.json](examples/Adachi-Workbench.json) into ComfyUI. Replace **YOUR_CHECKPOINT.safetensors** with your own compatible checkpoint; the template does not download models or require a LoRA.
+2. Click **Text to image** in Group Bypass Presets, edit the neutral example prompts, and queue to create an image.
+3. Click **Inpaint**. In **Inline Mask**, upload or drop a source image and paint the region to change. **White repaints; black preserves.** Orange is only the on-screen overlay.
+4. Set the sampling area, dimensions and denoise in **Adachi Inpaint Workbench**. Queue on the graph, or click **Open Adachi Workbench** to edit in the separate workspace.
+5. Compare the output. Adopt a result when you want it to become the next source, and continue editing with the mask intact.
 
 ```mermaid
 flowchart LR
-    Source[Inline Mask] -->|image + mask| Inpaint[WebUI Inpaint]
+    Source[Inline Mask] -->|image + mask| Inpaint[Adachi Inpaint Workbench]
     Inputs[Model · VAE · Conditioning] --> Inpaint
     Source -->|original| Compare[Image Compare]
     Inpaint -->|result| Compare
@@ -162,10 +202,10 @@ flowchart LR
 
 | From | To |
 | --- | --- |
-| `Inline Mask.image` / `mask` | `WebUI Inpaint.image` / `mask` |
-| Your model / VAE / positive / negative conditioning | The matching inputs of `WebUI Inpaint` |
+| `Inline Mask.image` / `mask` | `Adachi Inpaint Workbench.image` / `mask` |
+| Your model / VAE / positive / negative conditioning | The matching inputs of `Adachi Inpaint Workbench` |
 | `Inline Mask.image` | `Image Compare.original` |
-| `WebUI Inpaint.image` | `Image Compare.result` and/or `Save Image.images` |
+| `Adachi Inpaint Workbench.image` | `Image Compare.result` and/or `Save Image.images` |
 
 The Refiner inputs are optional. Leave them disconnected unless you are using a compatible second-stage model.
 
@@ -176,14 +216,14 @@ All nodes live under **Adachi-Inpaint-Workbench**. The group preset controller i
 | Node | Purpose | Outputs |
 | --- | --- | --- |
 | **Inline Mask** | Mask painting or crop/inpaint/layer blending | `image`, `mask`, `full_image` |
-| **WebUI Inpaint** | Prepare, sample and composite in one node | `image` = full composite; `crop` = sampling canvas; `mask` = sampling mask |
+| **Adachi Inpaint Workbench** | Prepare, sample and composite in one node | `image` = full composite; `crop` = sampling canvas; `mask` = sampling mask |
 | **Image Compare** | Preview, compare and adopt results | `image` = unchanged result batch |
 | **Group Bypass Presets** | Apply saved group states | No connections needed |
 | **Auto Exclusive Switch** | Forward exactly one enabled alternative | `output` of the selected type |
 | **Inpaint Prepare** | Crop/resize pixels and mask for a custom sampler workflow | `pixels`, `mask`, `context` |
 | **Inpaint Composite** | Return a decoded local result to source coordinates | `image` |
 
-For modular sampling: `Prepare.pixels → VAE Encode → Set Latent Noise Mask → sampler → VAE Decode → Composite`. Connect `Prepare.mask` to the latent mask node and **always connect `Prepare.context` to `Composite.context`**. See the [modular example](examples/02-modular-inpaint.json).
+For modular sampling: `Prepare.pixels → VAE Encode → Set Latent Noise Mask → sampler → VAE Decode → Composite`. Connect `Prepare.mask` to the latent mask node and **always connect `Prepare.context` to `Composite.context`**.
 
 ## Canvas shortcuts
 
@@ -197,22 +237,33 @@ For modular sampling: `Prepare.pixels → VAE Encode → Set Latent Noise Mask
 | Release crop selection | In **◌ repaint mask**, right-click or press Escape; left-click to select a new region |
 | Undo / redo | `Ctrl+Z` / `Ctrl+Shift+Z`, or `Ctrl+Y` |
 | Image zoom / pan, when unpinned | Wheel / Space + drag, middle-button drag, or the pan tool (`H`) |
-| Keep the image fitted | Pin beside **Fit**; click again to unlock |
+| Keep the current view | Fit first if desired, then use the pin; click again to unlock |
 | Adjust editor height | Drag the bottom `↕` handle |
 
 The painting panel also provides invert, fill, clear, PNG mask import/export, image/mask/overlay views and **Embed source in workflow**. Overlay opacity affects display only. Scrolling over buttons and parameter controls navigates the outer workflow; a gesture starting on the workflow keeps navigating it when the pointer crosses the picture.
 
 ## Example workflows
 
-Drag a JSON file into ComfyUI:
+Use the single [official template: Adachi-Workbench.json](examples/Adachi-Workbench.json). It includes text-to-image and inpainting branches, a shared checkpoint, Group Bypass Presets, automatic exclusive conditioning/image selection, comparison and saving. The preset controller stays outside the groups it controls. Select one preset at a time; enabling both branches intentionally fails exclusive selection.
 
-| Example | What to try |
-| --- | --- |
-| [01 · Inline inpainting](examples/01-inline-inpaint.json) | The complete painting and inpainting loop; select your own compatible checkpoint. |
-| [02 · Modular inpainting](examples/02-modular-inpaint.json) | Use standard encode/sample/decode nodes with Prepare and Composite. |
-| [03 · Group presets](examples/03-group-presets.json) | Model-free preset switching with image branches. |
-| [04 · Exclusive switch](examples/04-exclusive-switch.json) | Model-free A/B selection controlled by group presets. |
-| [05 · Inline crop and blend](examples/05-inline-crop-blend.json) | One editor, crop presets, comparison adoption and accepted full-image output; select your checkpoint and upload a source. |
+All example labels are English. Prompts are newly written neutral examples; the checkpoint is a placeholder for your own model. Inpaint requires uploading a source first. Crop & Blend uses the same connected editor, so no second workflow is needed. For model families with separate model, text encoder and VAE loaders, replace the checkpoint block with compatible loaders and connect the matching outputs.
+
+## Model and workflow compatibility
+
+The inpaint node uses ComfyUI `MODEL`, `CONDITIONING`, `VAE`, image and mask inputs with `common_ksampler`. Matching interfaces alone do not establish compatibility with a model's required conditioning, sampler, latent format or reference-image pipeline. Use a matched model, encoder and VAE; the **inpaint_model** switch is for compatible dedicated inpainting architectures.
+
+| Family / case | Evidence | What remains unverified |
+| --- | --- | --- |
+| WAI (SDXL-based) | End-to-end 512×512 generation without LoRA, including two- and six-step runs; template text-to-image and inpaint branches both ran. | This does not establish support for every SDXL checkpoint, LoRA or extension. |
+| SD 1.5 | Workflow validation plus real checkpoint VAE encode/decode and masked compositing on CPU; `[1,4,8,8]` latent. | The sampler was mocked in the VAE test; a full diffusion generation has not been verified. |
+| Anima / Wan-derived image VAE | Single-frame 5D latents and a real, randomly initialized Wan VAE were exercised. The user reported a remote workflow running after moving the CLIP encoder out of a subgraph. | No independently reproducible end-to-end run with real Anima weights was available in this audit. |
+| FLUX, SD3, Qwen and other families | Not verified. | Their model-specific conditioning, guidance, sampling, reference-image and VAE requirements may need separate workflow nodes; compatibility cannot be assumed. |
+
+Only still-image 4D latents and single-frame 5D `[B,C,1,H,W]` latents are supported; multi-frame video is rejected. To try a different model, first run its normal ComfyUI workflow, connect its matching model/conditioning/VAE to the inpaint node, start with **inpaint_model** off unless the architecture requires it, and check the protected pixels and output resolution. Start with a small image and few steps.
+
+The standalone page requires this plugin's **Inline Mask**, **Adachi Inpaint Workbench** and **Image Compare** nodes. It follows supported connections, Get/Set, Use Everywhere and subgraph execution IDs, and preserves intermediate processing in the tested pipelines. Unknown custom loaders, LoRA classes, prompt fields or virtual routes may remain controlled by the workflow rather than being editable in the page; custom LoRA override cannot be guaranteed for unrecognized loaders. Select explicit nodes under **Workflow connections** when discovery is ambiguous and inspect the result for complex graphs. The page validates and runs the chosen comparison output and its dependencies: unrelated `Save Image` or other output branches do not automatically run there; queue the original workflow when those outputs are needed.
+
+Group presets capture group-level enabled/bypassed states, not every node's individual mixed or muted state. Masks are embedded in saved workflows, while source images and unmerged crop layers normally reference files under `input/`; move those files too, or embed/merge before sharing. Source undo history is limited to the current browser session. Comparison previews are process-local and may expire on eviction or server restart; deployments with multiple backend instances need requests to reach the same instance. Local network-failure simulations passed, but a long-running real cloud soak test has not been performed. For crop/blend and source-history operations, use HTTPS or localhost: the browser's `crypto.randomUUID()` is unavailable in insecure contexts such as many plain-HTTP LAN addresses.
 
 ## Compatibility and important behaviour
 
@@ -222,7 +273,7 @@ Drag a JSON file into ComfyUI:
 - **Crop layers:** the fusion mask and crop coordinates are saved in the workflow; the latest layer is a relative image reference under `input/adachi-inpaint-layers/`. Include that file when moving an unmerged edit between machines, or merge layers and embed the source first.
 - **Sharing:** masks are embedded in saved workflows. Source images use a relative `input/` path by default; enable **Embed source in workflow** to include the picture too. Embedded images increase JSON size. If an embedded source would exceed browser draft storage when loading a workflow, uploading an image, changing modes or enabling embedding, the plugin first uploads an exact source copy and switches to an input-file reference, preserving masks and layers. To intentionally keep a very large source embedded, disable ComfyUI browser workflow persistence before embedding; exported files are not subject to the browser draft quota. If the page already reports draft failures on every edit, save with **Ctrl+S**, then reload with **Ctrl+F5** to reset ComfyUI's disabled draft-storage state.
 - **Adoption:** source and result dimensions must match to preserve mask coordinates. Undo/redo commands survive adoption in the current session; saving/reloading retains the mask, not the command history.
-- **Comparison previews:** new originals and results are held in server memory instead of temporary image files. The default cache is 512 MiB; set `ADACHI_COMPARE_MEMORY_MIB` to 64–4096 before starting ComfyUI to change it. Cache eviction or server restart expires old comparisons and their download references; rerun the workflow to refresh them. A single batch larger than the limit reports an error. Previous disk-based preview references remain supported while available, and expired old plugin preview files are still cleaned up. Images adopted into the editor are saved separately under `input/adachi-inpaint/` or `input/adachi-inpaint-layers/`.
+- **Comparison previews:** new originals and results are held in server memory instead of temporary image files. The default cache is 512 MiB and at most 512 comparison batches; set `ADACHI_COMPARE_MEMORY_MIB` to 64–4096 before starting ComfyUI to change it. Cache eviction or server restart expires old comparisons and their download references; rerun the workflow to refresh them. A single batch larger than the limit reports an error. Previous disk-based preview references remain supported while available, and expired old plugin preview files are still cleaned up. Images adopted into the editor are saved separately under `input/adachi-inpaint/` or `input/adachi-inpaint-layers/`.
 - **Scope:** this is an original WebUI-style implementation. It does not promise identical WebUI pixels, scripts or extension behaviour. Extra soft-edge feathering is not WebUI's full Soft Inpainting algorithm.
 
 <details>
@@ -231,7 +282,7 @@ Drag a JSON file into ComfyUI:
 - Sampling dimensions use multiples of 8. Padding, blur and mask growth are measured in source pixels; effective mask edges can change after blur/growth, while pixels with zero effective mask remain unchanged.
 - `mask_mode=outside` inverts the painted region before mask processing.
 - `resize_mode` controls whole-image resizing. Masked-area mode uses an aspect-preserving transform that retains the full mask, including at source edges.
-- Fill modes: **original**, surrounding-colour **fill**, **latent noise**, and **zero latent**. The latent modes belong to WebUI Inpaint; the modular Prepare node handles pixels and masks.
+- Fill modes: **original**, surrounding-colour **fill**, **latent noise**, and **zero latent**. The latent modes belong to Adachi Inpaint Workbench; the modular Prepare node handles pixels and masks.
 - An empty mask or `denoise=0` skips VAE/sampling. `batch_size` is variants per input image, not ComfyUI queue count.
 - For modular multi-source batches, group variants per source (`A,A,B,B`), rather than interleaving them (`A,B,A,B`).
 - Optional Refiner uses `refiner_model` and `refiner_switch`; `0.8` runs the last 20% with the Refiner. Compatible Refiner conditioning is recommended. A switch of `1` uses only the base model; `0` uses only the Refiner.
@@ -257,9 +308,26 @@ node --experimental-default-type=module tests/test_compare_history.mjs
 
 See [verification notes](VERIFICATION.md) for tested configurations and limits, [changelog](CHANGELOG.md) for updates, and [rollback instructions](ROLLBACK.md) for returning to an earlier version. Model-family and image-quality coverage is not exhaustive.
 
+## Release history
+
+| Versions | Highlights and fixes |
+| --- | --- |
+| 2.1.1 | Streamlined comparison Fit controls, moved repaint-area choices below Generate, and combined color-paint controls with the lower toolbar. |
+| 2.1.0 | Color-paint layer, crop merge progress, workspace comparison zoom, reordered controls, collapsible prompts and GPL-3.0-only licensing. |
+| 2.0.1 | Weak-network retry and cancellation, preview resource cleanup, rollback races, dense-mask memory reduction and safer malformed-workflow handling. |
+| 2.0.0 | Standalone light/dark workbench, workflow discovery, editable generation, task progress, result recovery and unified template. |
+| 1.0.1 / 1.0.0 / 0.9 | Stable release; preview reload/retry, in-memory comparisons and real upload progress. |
+| 0.8 | Crop adoption and dimension sync, latest-result download, different-sized upload refresh. |
+| 0.7 | Preserve masks on replacement, source download and pin-current-view behavior. |
+| 0.6 | Inline crop/blend, locked selection and dimension sync, right-click preview/reselection and draft recovery; magic wand and quick selection were later removed. |
+| 0.5 | Group presets and automatic exclusive switch, mask retention, 5D image VAE support and canvas performance fixes. |
+| 0.4 / 0.3 / 0.2 | Inline controls and vertical resizing, comparison/adoption, temporary eraser and bilingual node UI. |
+
+The [complete changelog](CHANGELOG.md) lists individual releases and fixes.
+
 ## Credits and license
 
-Created by **Adachi / 安达**. Licensed under [MIT](LICENSE).
+Created by **Adachi / 安达**. The current project is licensed under [GNU GPL-3.0-only](LICENSE). You may use it commercially; when distributing the covered program or modifications, follow GPL-3.0 source and license requirements. Releases through v2.0.1 were distributed under MIT; recipients retain those earlier permissions. The original copyright and license notice is preserved in [LICENSES](LICENSES/MIT-previous-releases.txt). The current branch's GPL terms do not retroactively revoke the earlier MIT grant.
 
 Built for [ComfyUI](https://github.com/Comfy-Org/ComfyUI), with familiar inpainting controls inspired by WebUI and hover-comparison interaction inspired by [rgthree-comfy](https://github.com/rgthree/rgthree-comfy). This repository contains its own implementation; those projects are not bundled dependencies.
 

README.zh-CN.md

@@ -8,7 +8,7 @@
 
 [English](README.md) · **简体中文**
 
-[![MIT 许可证](https://img.shields.io/badge/License-MIT-38966b)](LICENSE)
+[![GPL-3.0 许可证](https://img.shields.io/badge/License-GPL--3.0--only-38966b)](LICENSE)
 [![ComfyUI 自定义节点](https://img.shields.io/badge/ComfyUI-Custom_Nodes-4776b4)](https://github.com/Comfy-Org/ComfyUI)
 [![Python 3.10+](https://img.shields.io/badge/Python-3.10%2B-4776b4)](pyproject.toml)
 [![插件检查](https://github.com/adachi0130/Adachi-Inpaint-Workbench/actions/workflows/ci.yml/badge.svg)](https://github.com/adachi0130/Adachi-Inpaint-Workbench/actions/workflows/ci.yml)
@@ -28,7 +28,7 @@
 | 工具 | 用途 |
 | --- | --- |
 | **内联蒙版 · Inline Mask** | 同一节点内涂蒙版，或裁切、重绘、双图层融合。 |
-| **WebUI 局部重绘 · WebUI Inpaint** | 整图或蒙版区域采样，使用熟悉的重绘参数，按原图尺寸回贴结果。 |
+| **安达重绘工作台 · Adachi Inpaint Workbench** | 整图或蒙版区域采样，使用熟悉的重绘参数，按原图尺寸回贴结果。 |
 | **图像对比 · Image Compare** | 鼠标划线对比、查看结果历史，一键采用后继续重绘。 |
 | **组忽略预设 · Group Bypass Presets** | 保存各组的打开/忽略组合，一键切换工作流配置。 |
 | **自动二选一 · Auto Exclusive Switch** | 自动输出唯一启用的分支，不用手动设置 switch。 |
@@ -37,16 +37,51 @@
 
 ## 功能介绍
 
+<details open>
+<summary>工作台实机截图</summary>
+
+![浅色工作台中的内联蒙版和工作流设置](preview/workbench-light.png)
+
+![深色工作台中的图片对比分割线](preview/workbench-compare-dark.png)
+
+*截图来自实际运行的插件，图片是自制示例；对比结果使用 CPU 反相演示分割线，并非 AI 重绘结果。*
+
+</details>
+
+### Adachi Workbench · 黑白主题
+
+在任意安达重绘工作台节点中点击「打开安达工作台」。工作流需包含本插件的内联蒙版、重绘和图像对比节点，但节点编号、标题、预设名称及模型文件名均不需与示例一致。页面沿所选重绘节点的实际连线寻找图像和结果；多个候选无法唯一判断时，在「工作流连接」中选择。已启用的组忽略预设节点提供预设按钮，缺失或存在多个控制器时会提醒。
+
+模型、VAE、文本编码器和提示词从原生执行图读取，支持 Get/Set、Use Everywhere 广播及子图执行编号。模型采样设置、ControlNet、多编码器条件合并、图像处理和结果后处理会保留；可识别的组件显示编辑控件，其余自定义处理按原工作流执行，不按私人节点编号或模型家族名称重新接线。
+
+新方案默认「沿用工作流 LoRA」，保留原有 LoRA 和正负 CLIP 分叉。取消勾选后使用自定义列表，空列表会禁用已识别的 LoRA；原工作流没有 LoRA 节点也可添加自定义 LoRA。Refiner 可在模型菜单选择，旧版已明确设置的方案仍会保留。
+
+画布与配置之间的分隔条可以左右拖动，宽度会记住；双击恢复默认，方向键可微调。窄屏保持上下排列，右上角可切换并记住黑白主题。操作说明放在悬停提示中。
+
+生成按钮、宽度、高度和重绘幅度位于设置面板靠上位置。正面和负面提示词可以折叠，腾出更多操作空间。
+
+生成时可以继续涂蒙版、缩放、移动和调整参数，已提交任务使用当时的快照。工作流设置上方显示真实阶段和采样步数；结果默认滑动对比，前后图共用一个切换图标，点击「采用」才替换原图。裁切融合采用后返回编辑，保留选区与蒙版。下方可回退或选择之前的原图，历史限当前已加载的浏览器会话。
+
+独立工作台的滑动对比和前后图视图支持在图片上滚动鼠标滚轮缩放、按住鼠标中键拖动画面，点击「适应」恢复适合画布的视图。工作流内的图像对比节点仍使用滚轮操作工作流画布。
+
+图像对比节点和网页按本次任务编号找回丢失的结果通知。图片加载显示真实接收字节、已知总大小时的百分比及解码状态；弱网失败自动重试，重连后可恢复，不产生预览文件。服务器重启或缓存淘汰造成的预览过期仍需重新运行。后端升级需重启 ComfyUI，仅前端改动强刷网页即可。
+
+[官方模板](examples/Adachi-Workbench.json) 仅作为起点，不是必需的固定工作流。已验证不同编号和预设名的副本，以及完全新建的多链路工作流。界面默认英文，在 ComfyUI 设置中选择简体中文后显示中文，其他语言暂时回退英文。模型权重须与原工作流匹配；缺失文件会列出文件名和目标目录。
+
 ### 直接在工作流里画蒙版
 
 在**内联蒙版**上传、拖入或粘贴原图，然后直接在节点画布上涂抹。普通蒙版模式上传图片时会自动填写已连接的局部重绘宽高；替换同尺寸图片时保留蒙版，尺寸不同则载入新图并重置蒙版。蒙版在浏览器内更新，随工作流保存，不需要每画一笔都保存、加载磁盘文件。
 
+两种模式都可以点击左下角的 **✎ 彩色画笔**直接在图像上绘制。可手动选色，或按住 **Alt 并点击图像**吸取当前可见颜色；使用 **Ctrl + 鼠标滚轮**调整笔径。彩色画笔使用独立图层，提供自己的撤销和重做，画完的图像会作为后续重绘的原图。再次点击画笔按钮可回到蒙版编辑。
+
+如果浏览器草稿存储空间不足，画笔图层可能会保存为 ComfyUI 输入目录中的 PNG，而不是嵌入工作流；将工作流转移到其他机器时，也需要带上引用的文件。
+
 上传原图时，进度条显示浏览器实际发送的数据比例，上传完成后提示正在加载图片。需要特殊认证回退的平台会显示不定进度，不会虚构百分比。
 
 - 支持画笔软边、硬度、不透明度、数位笔压感、临时擦除和形状工具。
-- 顶部使用**↑ 上传、⛶ 适应、图钉**，右上角切换模式。图钉的悬停提示为「保持」：开启后图片持续适应并居中，普通滚轮控制工作流背景，`Ctrl` + 滚轮调整笔径，`Shift` + 滚轮调整硬度。
+- 顶部使用**↑ 上传、⛶ 适应、图钉**，右上角切换模式。图钉的悬停提示为「保持」：开启后保持当前视图；需要适应画面时请先点击「适应」再钉住，普通滚轮控制工作流背景，`Ctrl` + 滚轮调整笔径，`Shift` + 滚轮调整硬度。
 - 支持横向、纵向调整编辑区大小；图钉状态和节点尺寸都能随工作流保存。
-- 连到 **WebUI 局部重绘**后，画笔工具和采样参数显示在重绘节点内，让图片编辑区保持简洁。画笔工具、蒙版内外和填充内容收进箭头折叠区，**撤销、重做、反转、全选、清空、导入蒙版、导出**整行始终显示；折叠状态随工作流保存。
+- 连到 **安达重绘工作台**后，画笔工具和采样参数显示在重绘节点内，让图片编辑区保持简洁。画笔工具、蒙版内外和填充内容收进箭头折叠区，**撤销、重做、反转、全选、清空、导入蒙版、导出**整行始终显示；折叠状态随工作流保存。
 - 放大工作流时限制显示画布的分配尺寸，并缓存原图/蒙版合成，减少反复重绘；实际保存的蒙版仍保持原图分辨率。
 
 <details>
@@ -68,14 +103,16 @@
 
 | 连线 | 用途 |
 | --- | --- |
-| `内联蒙版.image`、`mask` → `WebUI 局部重绘.image`、`mask` | 把裁片和重绘蒙版送去生成。 |
-| `内联蒙版.image` → `图像对比.original`；`WebUI 局部重绘.image` → `图像对比.result` | 先对比裁片，再选择采用。 |
+| `内联蒙版.image`、`mask` → `安达重绘工作台.image`、`mask` | 把裁片和重绘蒙版送去生成。 |
+| `内联蒙版.image` → `图像对比.original`；`安达重绘工作台.image` → `图像对比.result` | 先对比裁片，再选择采用。 |
 | `内联蒙版.full_image` → `保存图像.images` | 保存包含**已采用图层**的完整图像。 |
 
-先生成，在**图像对比**中查看，满意后点击**采用此结果**，才会嵌回当前裁切位置；没有回接输入线，也不会生成后自动替换。比较结果使用重绘节点的 **image** 输出；`crop` 是采样画布，尺寸可能不同。[已连好的示例](examples/05-inline-crop-blend.json)。
+先生成，在**图像对比**中查看，满意后点击**采用此结果**，才会嵌回当前裁切位置；没有回接输入线，也不会生成后自动替换。比较结果使用重绘节点的 **image** 输出；`crop` 是采样画布，尺寸可能不同。在[官方模板](examples/Adachi-Workbench.json)中选择 **Inpaint**，再将内联蒙版切换到**裁切融合**即可。
 
 采用后结果显示在选区中，编辑器回到重绘蒙版，可直接继续生成。点击 **◐ 图层融合**可编辑融合蒙版：画笔保留新图，按住 **Alt** 擦回原图，软笔刷可融合接缝；融合蒙版与重绘蒙版相互独立。编辑融合蒙版时，**按住右键看原图，松开恢复工作区**。要选择新区域，请切回 **◌ 重绘蒙版**后右键，或按 Escape；当前可见结果会先合并，再取消选定，接着左键选择新区域。**↶ 撤销**可撤销当前蒙版的涂抹，鼠标悬停底部控件可查看说明。批量生成时，在图像对比中选中想要的结果再采用；换到其他选区后，带有旧选区标记的结果会拒绝回贴。
 
+网络较慢时，取消选区前合并已采用的裁片可能需要一些时间，界面会显示上传进度；上传失败会保留选区，可再次尝试。
+
 ### 整图重绘与蒙版区域重绘
 
 | 采样区域 | 工作方式 |
@@ -91,6 +128,8 @@
 
 鼠标移入**图像对比**：**左边是重绘结果，右边是原图**；移开后显示完整结果。分隔线保持细线，图片持续适应编辑区，滚轮作用于工作流背景。
 
+网络错误或加载超时时会自动重试，也可点击 **↻** 手动重新加载；如果临时预览已因服务器重启或缓存淘汰而失效，请重新运行工作流。
+
 同一轮编辑中的结果会累计保存并默认选中最新一张，每张结果对应当时的原图；重复的预览通知不会重复计数。
 
 点击 **↓** 可以按原始分辨率下载最新生成的结果，即使列表中正在查看旧图也会下载最新一张；批量生成时下载该批最后一张。
@@ -103,13 +142,13 @@
 
 ![组忽略预设：左侧选择预设，右侧设置每个组的状态](preview/group-bypass-presets.png)
 
-左侧点选预设，右侧配置各组**打开 / 忽略 / 保持当前**，也能通过节点右键菜单应用。预设随工作流保存，不需要连线，也不依赖第三方组控制节点。已删除的组会显示提示；分组重叠时，较小组的设置优先。
+左侧点选预设，右侧配置各组**打开 / 忽略 / 保持当前**，也能通过节点右键菜单应用。点击箭头可折叠或展开右侧分组详情，状态随工作流保存。预设随工作流保存，不需要连线，也不依赖第三方组控制节点。已删除的组会显示提示；分组重叠时，较小组的设置优先。
 
 ### 自动使用剩下的一路输入
 
 将两路备选输入连接到**自动二选一**，忽略其中一路后，另一条有效分支自动流向共同输出，无需手动切换 `switch`。
 
-![两个自动二选一节点分别把正面、负面条件连接到 WebUI 局部重绘](preview/auto-exclusive-switch.png)
+![两个自动二选一节点分别把正面、负面条件连接到 安达重绘工作台](preview/auto-exclusive-switch.png)
 
 可用于提示词条件、字符串、图像、蒙版、模型、潜空间等数据；两路输入应为同一类型。两路都启用或都不可用时会报错，不会擅自优先选择 A。
 
@@ -125,7 +164,7 @@
 git clone https://github.com/adachi0130/Adachi-Inpaint-Workbench.git
 ```
 
-**完整重启 ComfyUI，再按 `Ctrl+F5` 强制刷新网页**，macOS 可用 `Cmd+Shift+R`。在节点菜单搜索 `Inline Mask`、`WebUI Inpaint` 或 `Adachi`。
+**完整重启 ComfyUI，再按 `Ctrl+F5` 强制刷新网页**，macOS 可用 `Cmd+Shift+R`。在节点菜单搜索 `Inline Mask`、`Adachi Inpaint Workbench` 或 `Adachi`。
 
 ### 其他安装方式
 
@@ -143,14 +182,15 @@ Git 安装用户可在插件目录运行 `git pull` 更新，然后重启 ComfyU
 
 ## 快速开始
 
-1. 将 [01-inline-inpaint.json](examples/01-inline-inpaint.json) 拖入 ComfyUI，选择兼容的 checkpoint；也可以连接现有工作流的模型、VAE 和文本条件。
-2. 在**内联蒙版**上传图片，涂出需要修改的部分。**白色重绘、黑色保留**，橙色只是界面叠加显示。
-3. 编辑上游节点的正面/负面提示词，在 **WebUI 局部重绘**里设置采样区域、宽高和重绘幅度，运行工作流。
-4. 查看对比结果，满意时点击采用，将它作为新原图，保留蒙版继续修改。
+1. 将 [Adachi-Workbench.json](examples/Adachi-Workbench.json) 拖入 ComfyUI，把 **YOUR_CHECKPOINT.safetensors** 换成自己兼容的 checkpoint；模板不下载模型，也不要求 LoRA。
+2. 在组忽略预设中点击 **Text to image**，修改中性的示例提示词，运行生图。
+3. 点击 **Inpaint**，在**内联蒙版**上传或拖入原图，涂抹需要修改的区域。**白色重绘，黑色保留**，橙色仅为显示叠加。
+4. 在**安达重绘工作台**设置重绘范围、宽高和重绘幅度，直接运行，或点击**打开安达工作台**进入独立界面编辑。
+5. 对比结果，满意后采用为新原图，保留蒙版继续修改。
 
 ```mermaid
 flowchart LR
-    Source[内联蒙版] -->|image + mask| Inpaint[WebUI 局部重绘]
+    Source[内联蒙版] -->|image + mask| Inpaint[安达重绘工作台]
     Inputs[模型 · VAE · 文本条件] --> Inpaint
     Source -->|original| Compare[图像对比]
     Inpaint -->|result| Compare
@@ -162,10 +202,10 @@ flowchart LR
 
 | 从哪里 | 连到哪里 |
 | --- | --- |
-| `内联蒙版.image` / `mask` | `WebUI 局部重绘.image` / `mask` |
-| 模型 / VAE / 正面条件 / 负面条件 | `WebUI 局部重绘`对应输入 |
+| `内联蒙版.image` / `mask` | `安达重绘工作台.image` / `mask` |
+| 模型 / VAE / 正面条件 / 负面条件 | `安达重绘工作台`对应输入 |
 | `内联蒙版.image` | `图像对比.original` |
-| `WebUI 局部重绘.image` | `图像对比.result`，以及需要时的 `保存图像.images` |
+| `安达重绘工作台.image` | `图像对比.result`，以及需要时的 `保存图像.images` |
 
 Refiner 输入是可选项。只有需要兼容的第二阶段模型时才连接，否则留空即可。
 
@@ -176,14 +216,14 @@ Refiner 输入是可选项。只有需要兼容的第二阶段模型时才连接
 | 节点 | 用途 | 输出 |
 | --- | --- | --- |
 | **内联蒙版 · Inline Mask** | 普通蒙版或裁切重绘、双图层融合 | `image`、`mask`、`full_image` |
-| **WebUI 局部重绘 · WebUI Inpaint** | 一体化准备、采样、合成 | `image`：完整合成图；`crop`：采样画布；`mask`：采样蒙版 |
+| **安达重绘工作台 · Adachi Inpaint Workbench** | 一体化准备、采样、合成 | `image`：完整合成图；`crop`：采样画布；`mask`：采样蒙版 |
 | **图像对比 · Image Compare** | 预览、对比、采用结果 | `image`：原样传递结果批次 |
 | **组忽略预设 · Group Bypass Presets** | 应用已保存的组状态 | 无需连线 |
 | **自动二选一 · Auto Exclusive Switch** | 传递唯一启用的输入 | `output`：被选中分支的数据类型 |
 | **重绘准备 · Inpaint Prepare** | 为自定义采样流程裁剪、调整图像和蒙版 | `pixels`、`mask`、`context` |
 | **重绘合成 · Inpaint Composite** | 将局部解码结果回贴到原图 | `image` |
 
-模块化流程可使用 `Prepare.pixels → VAE 编码 → 设置潜空间噪声蒙版 → 采样器 → VAE 解码 → Composite`。`Prepare.mask` 连接噪声蒙版节点，**务必把 `Prepare.context` 连到 `Composite.context`**，详见[模块化示例](examples/02-modular-inpaint.json)。
+模块化流程可使用 `Prepare.pixels → VAE 编码 → 设置潜空间噪声蒙版 → 采样器 → VAE 解码 → Composite`。`Prepare.mask` 连接噪声蒙版节点，**务必把 `Prepare.context` 连到 `Composite.context`**。
 
 ## 画布快捷操作
 
@@ -197,22 +237,33 @@ Refiner 输入是可选项。只有需要兼容的第二阶段模型时才连接
 | 取消裁切选定 | 在 **◌ 重绘蒙版**中右键或按 Escape，再左键选择新区域 |
 | 撤销 / 重做 | `Ctrl+Z` / `Ctrl+Shift+Z`，或 `Ctrl+Y` |
 | 未固定时的图片缩放 / 移动 | 滚轮 / 空格拖动、中键拖动，或移动工具 `H` |
-| 保持图片适应 | 点击「适应」旁的图钉，再点一次解除 |
+| 保持当前视图 | 需要时先点击「适应」，再点击图钉；再点一次解除 |
 | 调整编辑区高度 | 拖动底部 `↕` 手柄 |
 
 画笔面板还提供反转、全选、清空、PNG 蒙版导入/导出、原图/蒙版/叠加视图和**原图嵌入工作流**。叠加不透明度只影响显示。鼠标在按钮、参数区滚动时控制外部工作流；从工作流背景开始的连续滚轮手势，移入图片后仍控制工作流。
 
 ## 示例工作流
 
-将对应 JSON 拖入 ComfyUI：
+只提供一个[官方模板：Adachi-Workbench.json](examples/Adachi-Workbench.json)，包含生图与修图两条分支、共用模型、组忽略预设、条件／图像自动二选一、图像对比和保存。预设控制器位于受控组外；每次选择一个预设，同时打开两路会触发二选一的检查。
 
-| 示例 | 内容 |
-| --- | --- |
-| [01 · 内联局部重绘](examples/01-inline-inpaint.json) | 完整绘制与重绘流程，需要自行选择兼容模型。 |
-| [02 · 模块化重绘](examples/02-modular-inpaint.json) | Prepare / Composite 配合常规编解码与采样节点。 |
-| [03 · 分组预设](examples/03-group-presets.json) | 使用图像分支演示预设切换，不需要模型。 |
-| [04 · 自动二选一](examples/04-exclusive-switch.json) | 分组预设控制两路输入，不需要模型。 |
-| [05 · 内联裁切融合](examples/05-inline-crop-blend.json) | 同一编辑器裁切、接收结果和输出完整回贴图，需要选择模型并上传原图。 |
+模板标题使用英文，提示词为重新编写的中性示例，模型为占位名称，需自行选择。修图前请先上传原图；裁切融合直接切换同一个内联蒙版即可。使用分离模型、文本编码器和 VAE 的模型家族时，请用匹配的加载节点替换 checkpoint 区块并连接对应输出。
+
+## 模型和工作流兼容性
+
+重绘节点使用 ComfyUI 的 `MODEL`、`CONDITIONING`、`VAE`、图像和蒙版输入，并调用 `common_ksampler`。接口能接上，并不代表模型所需的条件、采样器、潜空间格式或参考图流程一定兼容；请使用相互匹配的模型、文本编码器和 VAE。**inpaint_model** 只用于兼容的专用修复架构。
+
+| 模型／情况 | 已有证据 | 尚未验证 |
+| --- | --- | --- |
+| WAI（基于 SDXL） | 无 LoRA 的 512×512 完整生成已通过，包括 2 步、6 步测试；官方模板的生图和修图分支都已运行。 | 不代表所有 SDXL 模型、LoRA 或扩展都已验证。 |
+| SD 1.5 | 工作流校验通过；本次用真实 checkpoint 的 VAE 在 CPU 上完成编码、解码和蒙版回贴，潜空间为 `[1,4,8,8]`。 | VAE 测试中的采样器使用模拟实现，尚未完成完整扩散生成验证。 |
+| Anima／Wan 系图像 VAE | 已测试单帧 5D 潜空间和真实但随机初始化的 Wan VAE；主人反馈曾将 CLIP 编码器移出子图后跑通远程工作流。 | 本次没有可独立复核的真实 Anima 权重端到端生成记录。 |
+| FLUX、SD3、Qwen 等其他模型 | 尚未验证。 | 专用条件、引导、采样、参考图及 VAE 流程可能需要额外节点，不能直接保证兼容。 |
+
+目前只支持静态图 4D 潜空间或单帧 5D `[B,C,1,H,W]` 潜空间，真正的多帧视频会被拒绝。尝试新模型时，先确保它自己的 ComfyUI 流程能运行，再把匹配的模型、条件和 VAE 接到重绘节点；除非架构明确需要，否则先关闭 **inpaint_model**，用小图和少量步数检查尺寸与蒙版外像素。
+
+独立页面需要本插件的**内联蒙版、安达重绘工作台和图像对比**节点。已测试的流程可跟随连线、Get/Set、Use Everywhere 和子图执行编号，并保留中间处理链；未知自定义加载器、LoRA、提示词字段或虚拟路由可能仍由原工作流控制，不能保证在页面里识别和编辑，也不能保证自定义 LoRA 覆盖适用于未知加载器。候选不唯一时请在**工作流连接**中选择，复杂流程应检查实际输出。页面只校验并运行所选图像对比及其依赖，不会自动运行无依赖关系的「保存图像」等其他输出；需要它们时请运行原工作流。
+
+组预设保存的是组级打开／忽略状态，不会完整记录组内逐节点的混合或静音状态。蒙版随工作流保存，原图和未合并的裁切图层默认引用 `input/` 文件；换机时请带上文件，或先嵌入原图／合并图层。原图回退历史仅限当前浏览器会话。对比预览保存在单个服务进程内，重启或被淘汰后可能失效；多实例部署需保证请求落到同一个后端。本地已模拟断网重连，但未做仙宫云长期实机压测。裁切融合和历史记录使用浏览器的 `crypto.randomUUID()`：请优先使用 HTTPS 或 localhost，部分普通 HTTP 局域网地址下可能不可用。
 
 ## 兼容性与重要行为
 
@@ -222,7 +273,7 @@ Refiner 输入是可选项。只有需要兼容的第二阶段模型时才连接
 - **裁切图层：**选区和融合蒙版会保存到工作流，最新重绘图层引用 `input/adachi-inpaint-layers/` 中的图片。跨机器移动尚未合并的编辑时需带上这张图，或先合并图层再嵌入原图。
 - **分享工作流：**蒙版会写入 JSON。原图默认只存 `input/` 下的相对路径，开启**原图嵌入工作流**才会把图片也写进去，文件会变大。加载工作流、上传图片、切换模式或勾选嵌入时，如果浏览器草稿空间不足，插件先保存一份完全相同的原图到 input 图片目录，再改用文件引用，保留蒙版、图层和笔画记录。若确实要把大图嵌入 JSON，可先关闭 ComfyUI 的浏览器工作流持久化，再勾选嵌入；导出文件不受浏览器草稿限额影响。若当前页面已经每次操作都提示草稿失败，请先按 **Ctrl+S** 保存，再按 **Ctrl+F5** 刷新一次，重置 ComfyUI 本页已停用的草稿状态。
 - **采用结果：**结果尺寸必须与原图一致，才能保留蒙版坐标。撤销/重做记录在本次会话中保留；保存重开保留蒙版，不保存逐笔命令历史。
-- **对比预览：**新的原图和重绘结果保存在服务器内存中，不再生成对比临时图片。默认缓存上限为 512 MiB，可在启动 ComfyUI 前设置 `ADACHI_COMPARE_MEMORY_MIB` 为 64～4096 调整。内存淘汰或服务器重启后，旧对比和下载引用会失效，重新运行工作流即可恢复；单批超过上限会提示错误。旧版磁盘预览文件存在时仍可读取，其过期清理也继续保留。采用到编辑器的图片另存于 `input/adachi-inpaint/` 或 `input/adachi-inpaint-layers/`。
+- **对比预览：**新的原图和重绘结果保存在服务器内存中，不再生成对比临时图片。默认缓存上限为 512 MiB，同时最多保留 512 批对比，可在启动 ComfyUI 前设置 `ADACHI_COMPARE_MEMORY_MIB` 为 64～4096 调整字节上限。内存淘汰或服务器重启后，旧对比和下载引用会失效，重新运行工作流即可恢复；单批超过上限会提示错误。旧版磁盘预览文件存在时仍可读取，其过期清理也继续保留。采用到编辑器的图片另存于 `input/adachi-inpaint/` 或 `input/adachi-inpaint-layers/`。
 - **功能范围：**这是独立实现的 WebUI 风格工具，不保证与 WebUI 像素、脚本和扩展行为完全一致；额外软边羽化并非 WebUI 的完整 Soft Inpainting 算法。
 
 <details>
@@ -257,9 +308,26 @@ node --experimental-default-type=module tests/test_compare_history.mjs
 
 已测试配置和范围见[验证记录](VERIFICATION.md)，版本变化见[更新日志](CHANGELOG.md)，恢复旧版本见[回滚说明](ROLLBACK.md)。模型家族和实际画质测试并非全覆盖。
 
+## 版本更新摘要
+
+| 版本 | 主要功能和修复 |
+| --- | --- |
+| 2.1.1 | 精简对比适应按钮、将重绘画布选项移至生成按钮下方，并把彩色画笔并入左下角工具栏。 |
+| 2.1.0 | 彩色画笔图层、裁切合并进度、工作台对比缩放、常用参数上移、提示词折叠及 GPL-3.0-only 许可证。 |
+| 2.0.1 | 弱网重试与取消、预览资源清理、回退竞态、大蒙版内存优化和异常工作流校验。 |
+| 2.0.0 | 独立黑白工作台、工作流发现、生成中编辑、进度、结果恢复和统一模板。 |
+| 1.0.1／1.0.0／0.9 | 稳定版、预览重试与手动刷新、内存对比、真实上传进度。 |
+| 0.8 | 裁切采用和尺寸同步、下载最新结果、不同尺寸上传刷新。 |
+| 0.7 | 替换图片保留蒙版、下载原图、图钉保持当前视图。 |
+| 0.6 | 裁切融合、选区和尺寸同步、右键预览／重选与草稿恢复；魔棒和快速选择后来已移除。 |
+| 0.5 | 组忽略预设、自动二选一、保留蒙版、单帧 5D 图像 VAE 和画布性能修复。 |
+| 0.4／0.3／0.2 | 内联控件与纵向调整、图片对比／采用、临时橡皮擦及中英文节点界面。 |
+
+逐版本的详细修复见[完整更新日志](CHANGELOG.md)。
+
 ## 致谢与许可证
 
-由 **Adachi / 安达** 制作，采用 [MIT 许可证](LICENSE)。
+由 **Adachi / 安达** 制作，当前项目采用 [GNU GPL-3.0-only 许可证](LICENSE)。GPL 允许商业使用；分发受许可程序或其修改版时，应遵守 GPL-3.0 的源码与许可要求。v2.0.1 及更早版本按 MIT 发布，已有接收者仍保留此前获得的权限；原版权和许可通知保留在 [LICENSES](LICENSES/MIT-previous-releases.txt)，当前分支改用 GPL 不会撤销先前的 MIT 授权。
 
 基于 [ComfyUI](https://github.com/Comfy-Org/ComfyUI) 构建，重绘交互参考 WebUI，鼠标划线对比体验参考 [rgthree-comfy](https://github.com/rgthree/rgthree-comfy)。代码由本仓库独立实现，这些项目不作为捆绑依赖。
 

ROLLBACK.md

@@ -1,11 +1,16 @@
 # Git versions and rollback
 
-The current version is **v1.0.0**. Git history lives in the source repository. The installed custom-node folder may be a ZIP/file copy without its own `.git`; do not run rollback commands in ComfyUI's parent repository.
+The stability fixes in 2.0.1 start from `local-before-stability-20261110` (the published `v2.0.0` commit). A complete copied-installation ZIP is stored in `ComfyUI/user/adachi-workbench-backups/` with prefix `Adachi-Inpaint-Workbench-before-stability-20261110-`. Restore that backup or switch a clean source checkout to the baseline tag, then reinstall, restart ComfyUI and hard-refresh. The published 2.0.0 archive remains unchanged.
+
+The current version is **v2.0.1**. Git history lives in the source repository. The installed custom-node folder may be a ZIP/file copy without its own `.git`; do not run rollback commands in ComfyUI's parent repository.
 
 Before installing, the installer saves the previous plugin directory under `ComfyUI/user/adachi-workbench-backups/`. Restore that ZIP to roll back a copied installation. For a Git clone, use the tags below.
 
 | Tag | Contents |
 |---|---|
+| `v2.0.1` | Stability, cancellation, recovery and dense-mask memory fixes |
+| `v2.0.0` | Standalone workbench, workflow discovery, cloud recovery, localization and unified template |
+| `v1.0.1` | Previous published version with comparison retry |
 | `v1.0.0` | First stable release with current bilingual crop instructions |
 | `local-before-v1.0.0` / `v0.9.0` | Source before stable-release documentation and metadata |
 | `v0.9.0` | In-memory comparison previews and real upload progress |
@@ -47,14 +52,23 @@ To undo only this update, run in the plugin folder:
 
 ```powershell
 git status --short
-git switch --detach local-before-v1.0.0
+git switch --detach v2.0.0
 ```
 
 Return to this version with:
 
 ```powershell
-git switch --detach v1.0.0
+git switch --detach v2.0.1
 ```
 
 Restart ComfyUI and hard-refresh the browser (`Ctrl+F5`) after switching versions.
 Commit or back up any local modifications before switching. A release ZIP does not contain `.git`; use the installer backup for a copied installation.
+
+
+Local workbench UI / network preview (2026-11-09) baseline: `local-before-workspace-ui-network-20261109` (`392149f`). To undo this local work on a clean checkout, use `git switch --detach local-before-workspace-ui-network-20261109`, reinstall those files, restart ComfyUI and hard-refresh. The installed directory also has a full ZIP backup in `user/adachi-workbench-backups/` whose name starts with `Adachi-Inpaint-Workbench-before-workspace-ui-network-20261109-`.
+
+
+The editable-generation / execution-stage update starts at `local-before-workspace-run-progress-20261109` (`8ec5281`). A copied-installation ZIP backup named `Adachi-Inpaint-Workbench-before-run-progress-20261109-*.zip` is in the same backup directory. This update changes frontend files only; hard-refresh after restoring them.
+
+
+Generic routing / resizable workspace baseline: `local-before-generic-workbench-20261109` (`02719c3`). The copied-installation backup starts with `Adachi-Inpaint-Workbench-before-generic-layout-20261109-` in `user/adachi-workbench-backups/`. This update changes frontend files; hard-refresh after restoring them.

VERIFICATION.md

@@ -1,5 +1,29 @@
 # Verification record
 
+## 2026-11-12 · model compatibility and documentation
+
+- A real SD 1.5 checkpoint VAE was loaded on CPU and tested through the plugin: 64×64 encode, mock sampling, decode and masked compositing succeeded with a [1,4,8,8] latent, finite output and exact protected pixels. This is not a complete diffusion-generation test.
+- The installed 2.0.1 frontend was captured in an isolated ComfyUI instance. Screenshots use a synthetic image and a CPU ImageInvert result to demonstrate the interface, not an AI-generated inpaint.
+
+## 2.0.1 · stability audit (2026-11-10)
+
+- 68 Python regression tests and all 20 JavaScript test files cover new cancellation, stalled decoding/upload, corrupt-cache retry, dense/sparse/edge masks, bounded cache metadata, partial rollback failures, concurrent completed edits and malformed input mappings.
+- Real ComfyUI browser checks pass on frontends 1.42.11 and 1.52.7 in classic and Nodes 2.0 rendering. Each configuration performs 20 mount/close cycles with zero remaining workspace API listeners, delayed initialization disposal, a delayed submit response across close/reopen, and recovery with execution notifications suppressed.
+- Actual CPU image queues cover normal adoption/undo and crop-origin validation, crop/mask retention, layer adoption, automatic return to editing, protected exterior pixels and blend clear/undo. Invalid source replacement retains the previous usable image. Model sampling algorithms are unchanged; no new model-quality claim is based on these CPU queues.
+- Browser resource checks recover a corrupt PNG, reload 25 times and overlap 30 cancellation attempts. At settled checkpoints exactly two preview object URLs remain, destruction releases all tracked URLs, and no unhandled promise rejection is observed. Network fault tests exhaust immediate retries, then recover on reconnect with byte progress and no duplicate history entries.
+- Isolated CPU benchmark: a full 2048×4096 mask, four threads, four iterations per process averages 203.4 ms before and 14.6 ms after. Additional measured process peak working set is 521.0 MiB before versus 9.2 MiB after. This measures mask-bound computation only, not overall generation time or workflow frame rate.
+- Scope: local fault injection is not a long-duration cloud soak test, and cannot establish compatibility with every third-party plugin/model combination. The public 2.0.0 Registry version remains flagged pending external review; this local audit does not establish Registry approval.
+
+## 2.0.0 · 2026-11-09
+
+- All 63 Python regression tests and 19 JavaScript test files pass. Frontend modules pass syntax checks; locale JSON, release metadata and local links in both READMEs validate.
+- The single official template imports into a real ComfyUI frontend. Both presets compile through the native graph serializer and pass backend validation with no missing links. Text-to-image excludes the uploaded-image branch; inpainting excludes the latent-generation branch. The three exclusive selectors consistently select the only enabled input.
+- Both template presets complete actual 512×512, two-step WAI generation without LoRA, using newly authored neutral prompts and a synthetic input. Inpainting changes the nonempty masked region while pixels outside the protected region remain exact. The distributed template keeps its checkpoint placeholder and contains no model names, local paths, source images or personal prompts.
+- Real frontend settings expose the locale at `comfyAPI.app.app.ui.settings`. The translation reader supports that path, older frontend shapes and the English fallback; tests cover interpolation, context keys and current execution messages.
+- GitHub publication, Registry upload and Registry approval are checked separately. See the Registry review notes for public scan findings; local testing does not constitute Registry security approval.
+
+- Local white workspace preview: real `gpt test` WAI v160 generation with no LoRA, 512×512, two sampler steps and a nonempty mask succeeds. Protected pixels remain exact. The UI run is also verified: immediate opening, background backend validation, invalid-model rejection without queueing, result preview without adopting, before/after, explicit adoption, mask-preserving rollback and source selection. Classic and Nodes 2.0 browser tests cover actual mouse painting, comparison, clean close and reopen; 768/390 layouts have no horizontal overflow. Source history tests include crop/layer/fusion-mask restoration. No remote cloud or Anima model inference is claimed by these checks.
+
 - 1.0.0: all 54 CPU backend tests and all seven JavaScript regression suites pass; every frontend module passes syntax checking and all bundled examples parse as JSON. The release updates documentation and metadata on top of 0.9.0; no full model generation was run for this release.
 
 - 0.9.0: 54 backend CPU tests cover in-memory PNG pixels, atomic batch storage, LRU eviction, cached execution invalidation and oversized batch rejection. Actual CPU image queues in frontend 1.52.7 and both node renderers verify comparison history, download bytes, ordinary and crop adoption, mask retention, layer blending, workflow reload and legacy disk-backed references; no new comparison temp files are created. Real Chrome network throttling confirms intermediate upload percentages, loading indication, user header, failure and concurrent upload behavior in both renderers. Proxy paths and auth fallback were separately tested; the user's actual cloud environment and full model inference were not tested.
@@ -97,3 +121,33 @@ References used during implementation:
 - [rgthree image comparison interaction reference](https://github.com/rgthree/rgthree-comfy/blob/main/py/image_comparer.py)
 
 The plugin code is an independent implementation; see LICENSE for the release licence. No source from the projects above is bundled.
+
+
+## 2026-11-09 · local workspace UI and cloud recovery
+
+- 58 Python tests and all JavaScript test files pass, including new protocol, conditioning-route, preview stream and result-recovery cases.
+- Real `gpt test` WAI profile without LoRA validates against ComfyUI: positive #521, negative #520, model #518. The original graph modes and links are restored after compilation. Missing models are blocked before queueing.
+- Real CPU image processing verifies manual adoption, unchanged mask pixels, undo/original restoration and result-count reset. Generation defaults to sliding comparison without adopting.
+- Chrome interaction checks verify remembered light/dark themes, icon tooltips, one before/after toggle, enabled/missing controllers and dynamically added presets.
+- Classic and Nodes 2.0 crop controls pass at 1440, 768 and 390px in both themes, including wrapped history labels, custom dimensions, painting and dimension synchronization.
+- Cloud failure simulation drops `executed` alone, then all execution notifications. Exact-task history recovery succeeds in both the node and workspace. Three image-load attempts are exhausted before restoring connectivity; byte progress is visible and preview recovery succeeds. Replayed output does not increase the result count.
+- Existing source workflows and images are not modified. Runtime files are compared with the preceding Git checkpoint before installation; the installed package is backed up before copying changes.
+
+
+## 2026-11-09 · editable generation and execution stages
+
+- An actual WAI 512px / six-step generation reports node stages and sampler fractions. A real mouse stroke was added during sampling; the queued mask remained byte-identical to its submitted snapshot, and both the source and new mask edits survived result delivery.
+- Crop adoption was checked independently with a real processed image and crop-origin metadata. It returns to the editor with the locked region, result layer and repaint mask intact.
+- Progress rendering fits above workflow settings at 1440, 768 and 390px in both themes. Unit checks cover prompt isolation, early events before the HTTP response, cached nodes, reconnects and late progress packets after completion.
+- Both local Anima profiles compile their subgraph correctly and fail validation only for the three absent model components. The installed backend and model inventory confirm the missing checkpoint, text encoder and VAE. Model UI now lists filenames and target folders; missing-component checks never infer absent files from a network failure.
+
+- Legacy frontend scalar/null `executing` messages and a submit HTTP response deliberately delayed until after task completion are covered, so early completion cannot cause a false error or leave the workbench busy.
+
+
+## 2026-11-09 · generic workflow routing and resizable workspace
+
+- Real divider drag, keyboard resize, persisted width and reset pass; 768px/390px layouts keep stacked panels and the English brand without overflow.
+- All three existing example presets compile through Use Everywhere’s public native serialization API. MODEL and positive/negative CLIP branches retain their original LoRA routes in inherited mode. Bypassed routing is enabled only for the selected bypassed workbench group, and all editable modes are restored. Unique exclusive switches are resolved in the separate execution graph before backend metadata normalization.
+- A copy with every root node ID changed and all preset titles replaced with unrelated names still discovers and validates the correct components.
+- A newly built two-pipeline workflow validates with SD1.5, selects the connected editor/result instead of an unrelated first loader, and preserves ModelSamplingDiscrete, CLIPSetLastLayer, two-encoder conditioning, negative conditioning processing, image resizing and result postprocessing. A real WAI generation in that workflow confirms the final ImageInvert is executed by checking outside-mask pixels.
+- A custom execution-only LoRA validates without any editable LoRA nodes. Pure tests cover independent IDs/filenames, ControlNet positive/negative slots, SDXL text fields, inherited/custom split CLIP paths, untouched unrelated branches, Vue proxy JSON copying, explicit ambiguity, group activation safety and subgraph result recovery.

__init__.py

@@ -3,6 +3,7 @@
 from .backend import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS, normalize_exclusive_prompt
 from .preview_cleanup import start_preview_cleanup
 from .preview_store import PREVIEWS
+from .workspace_execution import register_workspace_routes
 from aiohttp import web
 from server import PromptServer
 import re
@@ -25,6 +26,7 @@ if not getattr(PromptServer.instance, "_adachi_preview_route", False):
     PromptServer.instance._adachi_preview_route = True
 
 start_preview_cleanup()
+register_workspace_routes(PromptServer.instance)
 
 WEB_DIRECTORY = "./web"
 

backend.py

@@ -1,4 +1,6 @@
-"""Portable inline inpainting nodes for ComfyUI (MIT licensed).
+"""Portable inline inpainting nodes for ComfyUI (GPL-3.0-only).
+
+SPDX-License-Identifier: GPL-3.0-only
 
 All image and crop operations below are original implementations. No code from
 AUTOMATIC1111, Forge or their AGPL components is included.
@@ -100,7 +102,7 @@ def _image_tensor(image):
     value = torch.as_tensor(image)
     if value.ndim != 4 or value.shape[-1] not in (3, 4) or min(value.shape[:3]) < 1:
         raise ValueError("IMAGE must have shape [batch, height, width, 3 or 4].")
-    return torch.nan_to_num(value[..., :3].float(), nan=0.0, posinf=1.0, neginf=0.0).clamp(0.0, 1.0)
+    return torch.nan_to_num(value[..., :3].float(), nan=0.0, posinf=1.0, neginf=0.0).clamp_(0.0, 1.0)
 
 
 def _mask_tensor(mask, images):
@@ -117,7 +119,7 @@ def _mask_tensor(mask, images):
         value = value.expand(images.shape[0], -1, -1)
     if value.shape[0] != images.shape[0]:
         raise ValueError("Mask batch must contain one mask or match the image batch.")
-    value = torch.nan_to_num(value, nan=0.0, posinf=1.0, neginf=0.0).clamp(0, 1)
+    value = torch.nan_to_num(value, nan=0.0, posinf=1.0, neginf=0.0).clamp_(0, 1)
     if value.shape[-2:] != images.shape[1:3]:
         value = F.interpolate(value[:, None], size=images.shape[1:3], mode="bilinear", align_corners=False)[:, 0]
     return value
@@ -143,11 +145,15 @@ def _feather(mask, grow, blur):
 
 def _bbox(mask, padding, target_ratio):
     height, width = mask.shape
-    nonzero = torch.nonzero(mask > 0, as_tuple=False)
-    if not len(nonzero):
+    occupied = mask > 0
+    rows = torch.where(occupied.any(dim=1))[0]
+    if not len(rows):
         return (0, 0, width, height)
-    y0, x0 = nonzero.amin(0).tolist()
-    y1, x1 = (nonzero.amax(0) + 1).tolist()
+    # Dense masks previously allocated two int64 coordinates per painted pixel
+    # (512 MB for a 32 MP mask). Only row/column occupancy is needed for bounds.
+    columns = torch.where(occupied.any(dim=0))[0]
+    y0, y1 = int(rows[0]), int(rows[-1]) + 1
+    x0, x1 = int(columns[0]), int(columns[-1]) + 1
     x0, y0 = max(0, x0 - padding), max(0, y0 - padding)
     x1, y1 = min(width, x1 + padding), min(height, y1 + padding)
     crop_width, crop_height = x1 - x0, y1 - y0
@@ -322,6 +328,7 @@ class AdachiInlineMask:
             "crop_state": ("STRING", {"default": "{}"}),
             "blend_data": ("STRING", {"default": ""}),
             "layer_image": ("STRING", {"default": ""}),
+            "paint_data": ("STRING", {"default": "", "multiline": False, "tooltip": "Transparent color paint layer PNG."}),
         }}
 
     RETURN_TYPES = ("IMAGE", "MASK", "IMAGE")
@@ -337,6 +344,13 @@ class AdachiInlineMask:
         for value in (image, mask_data, source_data, json.dumps(kwargs, sort_keys=True, default=str)):
             digest.update(str(value).encode("utf-8"))
             digest.update(b"\x00")
+        paint_data = kwargs.get("paint_data", "")
+        if paint_data and not paint_data.startswith("data:"):
+            try:
+                stat = _input_path(paint_data).stat()
+                digest.update(f"{stat.st_size}:{stat.st_mtime_ns}".encode("utf-8"))
+            except (ValueError, OSError):
+                return float("nan")
         if not source_data:
             # The source is a stable input file; hashing its size and mtime is
             # enough to detect a replacement and avoids reading a full high-res
@@ -349,7 +363,7 @@ class AdachiInlineMask:
                 return float("nan")
         return digest.hexdigest()
 
-    def load(self, image="", mask_data="", source_data="", edit_mode="mask", crop_state="{}", blend_data="", layer_image="", result=None):
+    def load(self, image="", mask_data="", source_data="", edit_mode="mask", crop_state="{}", blend_data="", layer_image="", paint_data="", result=None):
         raster = _data_image(source_data) if source_data else _read_raster(_input_path(image))
         rgba = raster.convert("RGBA")
         pixels = torch.from_numpy(np.asarray(rgba.convert("RGB"), dtype=np.float32).copy() / 255.0)[None]
@@ -365,11 +379,24 @@ class AdachiInlineMask:
             state = _crop_state(crop_state)
             if state.get("locked"):
                 x, y, width, height = _crop_box(state, pixels.shape[2], pixels.shape[1])
-                composite = _blend_layer(pixels, _load_layer(layer_image), blend_data, state)
+                composite = _paint_layer(_blend_layer(pixels, _load_layer(layer_image), blend_data, state), paint_data)
                 return composite[:, y:y+height, x:x+width].clone(), mask[:, y:y+height, x:x+width].clone(), composite
+        pixels = _paint_layer(pixels, paint_data)
         return pixels, mask, pixels
 
 
+def _paint_layer(pixels, paint_data):
+    """Composite a full-image RGBA paint layer without changing the repaint mask."""
+    if not paint_data:
+        return pixels
+    layer = (_data_image(paint_data) if paint_data.startswith("data:") else _read_raster(_input_path(paint_data))).convert("RGBA")
+    if layer.size != (pixels.shape[2], pixels.shape[1]):
+        raise ValueError("The paint layer dimensions must match the source image.")
+    rgba = torch.from_numpy(np.asarray(layer, dtype=np.float32).copy() / 255.0)
+    alpha = rgba[..., 3:4].unsqueeze(0)
+    return pixels * (1.0 - alpha) + rgba[..., :3].unsqueeze(0) * alpha
+
+
 class AdachiInpaintPrepare:
     @classmethod
     def INPUT_TYPES(cls):
@@ -527,7 +554,7 @@ class AdachiWebUIInpaint:
     FUNCTION = "sample"
     CATEGORY = CATEGORY
     DESCRIPTION = "WebUI-style inpainting, crop, latent fill, sampling and original-size compositing."
-    SEARCH_ALIASES = ["webui", "img2img", "inpaint", "局部重绘", "安达", "adachi"]
+    SEARCH_ALIASES = ["webui", "img2img", "inpaint", "局部重绘", "安达重绘工作台", "安达", "adachi"]
 
     def sample(self, model, positive, negative, vae, image, mask, seed=0, steps=20, cfg=7.0,
                sampler_name="euler", scheduler="normal", denoise=0.75, batch_size=1, inpaint_model=False,
@@ -967,6 +994,7 @@ class AdachiLayerCommit:
             "result": ("IMAGE",), "image": ("STRING", {"default": ""}),
             "source_data": ("STRING", {"default": ""}), "crop_state": ("STRING", {"default": "{}"}),
             "blend_data": ("STRING", {"default": ""}), "target": ("STRING", {"default": ""}),
+            "paint_data": ("STRING", {"default": ""}),
         }}
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "compose"
@@ -974,12 +1002,12 @@ class AdachiLayerCommit:
     CATEGORY = "_Adachi/internal"
     DESCRIPTION = "Internal layer sink. Use Inline Mask in Crop & Blend mode."
 
-    def compose(self, result, image="", source_data="", crop_state="{}", blend_data="", target=""):
+    def compose(self, result, image="", source_data="", crop_state="{}", blend_data="", target="", paint_data=""):
         raster = (_data_image(source_data) if source_data else _read_raster(_input_path(image))).convert("RGB")
         original = torch.from_numpy(np.asarray(raster, dtype=np.float32).copy()/255)[None]
         state = _crop_state(crop_state)
         generated = _image_tensor(result).cpu()
-        composite = _blend_layer(original, generated, blend_data, state)
+        composite = _paint_layer(_blend_layer(original, generated, blend_data, state), paint_data)
         layer = _store_layer(generated[-1])
         return {"ui": {"adachi_layer": [{"target": target, "job": state.get("job", ""), "image": layer}]}, "result": (composite,)}
 
@@ -1041,7 +1069,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "AdachiInlineMask": "Inline Mask",
     "AdachiInpaintPrepare": "Inpaint Prepare",
     "AdachiInpaintComposite": "Inpaint Composite",
-    "AdachiWebUIInpaint": "WebUI Inpaint",
+    "AdachiWebUIInpaint": "Adachi Inpaint Workbench",
     "AdachiImageCompare": "Image Compare",
     "AdachiExclusiveSwitch": "Auto Exclusive Switch",
     "AdachiLayerCommit": "Internal Layer Commit",

examples/01-inline-inpaint.json

@@ -1,694 +0,0 @@
-{
-  "id": "00000000-0000-0000-0000-000000000000",
-  "revision": 0,
-  "last_node_id": 8,
-  "last_link_id": 11,
-  "nodes": [
-    {
-      "id": 1,
-      "type": "AdachiInlineMask",
-      "pos": [
-        40,
-        80
-      ],
-      "size": [
-        660,
-        700
-      ],
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "STRING",
-          "widget": {
-            "name": "image"
-          },
-          "link": null
-        },
-        {
-          "name": "mask_data",
-          "type": "STRING",
-          "widget": {
-            "name": "mask_data"
-          },
-          "link": null
-        },
-        {
-          "name": "source_data",
-          "type": "STRING",
-          "widget": {
-            "name": "source_data"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "links": [
-            7,
-            9
-          ]
-        },
-        {
-          "name": "mask",
-          "type": "MASK",
-          "links": [
-            8
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "AdachiInlineMask"
-      },
-      "widgets_values": [
-        "",
-        "",
-        ""
-      ]
-    },
-    {
-      "id": 2,
-      "type": "CheckpointLoaderSimple",
-      "pos": [
-        780,
-        80
-      ],
-      "size": [
-        340,
-        130.65625
-      ],
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "ckpt_name",
-          "type": "COMBO",
-          "widget": {
-            "name": "ckpt_name"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "MODEL",
-          "type": "MODEL",
-          "links": [
-            3
-          ]
-        },
-        {
-          "name": "CLIP",
-          "type": "CLIP",
-          "links": [
-            1,
-            2
-          ]
-        },
-        {
-          "name": "VAE",
-          "type": "VAE",
-          "links": [
-            4
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "CheckpointLoaderSimple"
-      },
-      "widgets_values": [
-        "CHOOSE_YOUR_CHECKPOINT.safetensors"
-      ]
-    },
-    {
-      "id": 3,
-      "type": "CLIPTextEncode",
-      "pos": [
-        780,
-        250
-      ],
-      "size": [
-        350,
-        150
-      ],
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "clip",
-          "type": "CLIP",
-          "link": 1
-        },
-        {
-          "name": "text",
-          "type": "STRING",
-          "widget": {
-            "name": "text"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "CONDITIONING",
-          "type": "CONDITIONING",
-          "links": [
-            5
-          ]
-        }
-      ],
-      "title": "Positive",
-      "properties": {
-        "Node name for S&R": "CLIPTextEncode"
-      },
-      "widgets_values": [
-        "A detailed natural photograph, coherent lighting, high quality"
-      ]
-    },
-    {
-      "id": 4,
-      "type": "CLIPTextEncode",
-      "pos": [
-        780,
-        450
-      ],
-      "size": [
-        350,
-        150
-      ],
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "clip",
-          "type": "CLIP",
-          "link": 2
-        },
-        {
-          "name": "text",
-          "type": "STRING",
-          "widget": {
-            "name": "text"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "CONDITIONING",
-          "type": "CONDITIONING",
-          "links": [
-            6
-          ]
-        }
-      ],
-      "title": "Negative",
-      "properties": {
-        "Node name for S&R": "CLIPTextEncode"
-      },
-      "widgets_values": [
-        "blurry, distorted, artifacts"
-      ]
-    },
-    {
-      "id": 5,
-      "type": "AdachiWebUIInpaint",
-      "pos": [
-        1220,
-        80
-      ],
-      "size": [
-        430,
-        1020
-      ],
-      "flags": {},
-      "order": 5,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "model",
-          "type": "MODEL",
-          "link": 3
-        },
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "link": 5
-        },
-        {
-          "name": "negative",
-          "type": "CONDITIONING",
-          "link": 6
-        },
-        {
-          "name": "vae",
-          "type": "VAE",
-          "link": 4
-        },
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 7
-        },
-        {
-          "name": "mask",
-          "type": "MASK",
-          "link": 8
-        },
-        {
-          "name": "refiner_model",
-          "shape": 7,
-          "type": "MODEL",
-          "link": null
-        },
-        {
-          "name": "refiner_positive",
-          "shape": 7,
-          "type": "CONDITIONING",
-          "link": null
-        },
-        {
-          "name": "refiner_negative",
-          "shape": 7,
-          "type": "CONDITIONING",
-          "link": null
-        },
-        {
-          "name": "area",
-          "type": "COMBO",
-          "widget": {
-            "name": "area"
-          },
-          "link": null
-        },
-        {
-          "name": "width",
-          "type": "INT",
-          "widget": {
-            "name": "width"
-          },
-          "link": null
-        },
-        {
-          "name": "height",
-          "type": "INT",
-          "widget": {
-            "name": "height"
-          },
-          "link": null
-        },
-        {
-          "name": "padding",
-          "type": "INT",
-          "widget": {
-            "name": "padding"
-          },
-          "link": null
-        },
-        {
-          "name": "mask_blur",
-          "type": "FLOAT",
-          "widget": {
-            "name": "mask_blur"
-          },
-          "link": null
-        },
-        {
-          "name": "mask_grow",
-          "type": "INT",
-          "widget": {
-            "name": "mask_grow"
-          },
-          "link": null
-        },
-        {
-          "name": "mask_mode",
-          "type": "COMBO",
-          "widget": {
-            "name": "mask_mode"
-          },
-          "link": null
-        },
-        {
-          "name": "fill",
-          "type": "COMBO",
-          "widget": {
-            "name": "fill"
-          },
-          "link": null
-        },
-        {
-          "name": "resize_mode",
-          "type": "COMBO",
-          "widget": {
-            "name": "resize_mode"
-          },
-          "link": null
-        },
-        {
-          "name": "seed",
-          "type": "INT",
-          "widget": {
-            "name": "seed"
-          },
-          "link": null
-        },
-        {
-          "name": "steps",
-          "type": "INT",
-          "widget": {
-            "name": "steps"
-          },
-          "link": null
-        },
-        {
-          "name": "cfg",
-          "type": "FLOAT",
-          "widget": {
-            "name": "cfg"
-          },
-          "link": null
-        },
-        {
-          "name": "sampler_name",
-          "type": "COMBO",
-          "widget": {
-            "name": "sampler_name"
-          },
-          "link": null
-        },
-        {
-          "name": "scheduler",
-          "type": "COMBO",
-          "widget": {
-            "name": "scheduler"
-          },
-          "link": null
-        },
-        {
-          "name": "denoise",
-          "type": "FLOAT",
-          "widget": {
-            "name": "denoise"
-          },
-          "link": null
-        },
-        {
-          "name": "batch_size",
-          "type": "INT",
-          "widget": {
-            "name": "batch_size"
-          },
-          "link": null
-        },
-        {
-          "name": "refiner_switch",
-          "type": "FLOAT",
-          "widget": {
-            "name": "refiner_switch"
-          },
-          "link": null
-        },
-        {
-          "name": "inpaint_model",
-          "shape": 7,
-          "type": "BOOLEAN",
-          "widget": {
-            "name": "inpaint_model"
-          },
-          "link": null
-        },
-        {
-          "name": "soft_edge",
-          "shape": 7,
-          "type": "BOOLEAN",
-          "widget": {
-            "name": "soft_edge"
-          },
-          "link": null
-        },
-        {
-          "name": "soft_strength",
-          "shape": 7,
-          "type": "FLOAT",
-          "widget": {
-            "name": "soft_strength"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "links": [
-            10
-          ]
-        },
-        {
-          "name": "crop",
-          "type": "IMAGE",
-          "links": null
-        },
-        {
-          "name": "mask",
-          "type": "MASK",
-          "links": null
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "AdachiWebUIInpaint"
-      },
-      "widgets_values": [
-        "only_masked",
-        1024,
-        1024,
-        32,
-        4,
-        0,
-        "inside",
-        "original",
-        "stretch",
-        42,
-        "fixed",
-        20,
-        7,
-        "dpmpp_2m",
-        "karras",
-        0.75,
-        1,
-        0.8,
-        false,
-        false,
-        0.5
-      ]
-    },
-    {
-      "id": 6,
-      "type": "AdachiImageCompare",
-      "pos": [
-        1770,
-        80
-      ],
-      "size": [
-        590,
-        620
-      ],
-      "flags": {},
-      "order": 6,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "original",
-          "type": "IMAGE",
-          "link": 9
-        },
-        {
-          "name": "result",
-          "type": "IMAGE",
-          "link": 10
-        }
-      ],
-      "outputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "links": [
-            11
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "AdachiImageCompare"
-      },
-      "widgets_values": []
-    },
-    {
-      "id": 7,
-      "type": "SaveImage",
-      "pos": [
-        2470,
-        80
-      ],
-      "size": [
-        430,
-        450
-      ],
-      "flags": {},
-      "order": 7,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 11
-        },
-        {
-          "name": "filename_prefix",
-          "type": "STRING",
-          "widget": {
-            "name": "filename_prefix"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Adachi/Inpaint"
-      ]
-    },
-    {
-      "id": 8,
-      "type": "Note",
-      "pos": [
-        780,
-        670
-      ],
-      "size": [
-        350,
-        220
-      ],
-      "flags": {},
-      "order": 2,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Adachi-Inpaint-Workbench\n1. Pick your own checkpoint\n2. Load an image in the left node and paint directly on it\n3. Select the brush and adjust inpainting parameters in the WebUI Inpaint node\n4. width/height is the sampling resolution; the final image is composited back at the source size\nTick \"Embed source in workflow\" in the inpaint node before sharing"
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    }
-  ],
-  "links": [
-    [
-      1,
-      2,
-      1,
-      3,
-      0,
-      "CLIP"
-    ],
-    [
-      2,
-      2,
-      1,
-      4,
-      0,
-      "CLIP"
-    ],
-    [
-      3,
-      2,
-      0,
-      5,
-      0,
-      "MODEL"
-    ],
-    [
-      4,
-      2,
-      2,
-      5,
-      3,
-      "VAE"
-    ],
-    [
-      5,
-      3,
-      0,
-      5,
-      1,
-      "CONDITIONING"
-    ],
-    [
-      6,
-      4,
-      0,
-      5,
-      2,
-      "CONDITIONING"
-    ],
-    [
-      7,
-      1,
-      0,
-      5,
-      4,
-      "IMAGE"
-    ],
-    [
-      8,
-      1,
-      1,
-      5,
-      5,
-      "MASK"
-    ],
-    [
-      9,
-      1,
-      0,
-      6,
-      0,
-      "IMAGE"
-    ],
-    [
-      10,
-      5,
-      0,
-      6,
-      1,
-      "IMAGE"
-    ],
-    [
-      11,
-      6,
-      0,
-      7,
-      0,
-      "IMAGE"
-    ]
-  ],
-  "groups": [],
-  "config": {},
-  "extra": {
-    "ds": {
-      "scale": 1,
-      "offset": [
-        0,
-        0
-      ]
-    }
-  },
-  "version": 0.4
-}

examples/03-group-presets.json

@@ -1,335 +0,0 @@
-{
-  "id": "00000000-0000-0000-0000-000000000000",
-  "revision": 0,
-  "last_node_id": 6,
-  "last_link_id": 3,
-  "nodes": [
-    {
-      "id": 1,
-      "type": "EmptyImage",
-      "pos": [
-        -350,
-        140
-      ],
-      "size": [
-        270,
-        160
-      ],
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "width",
-          "type": "INT",
-          "widget": {
-            "name": "width"
-          },
-          "link": null
-        },
-        {
-          "name": "height",
-          "type": "INT",
-          "widget": {
-            "name": "height"
-          },
-          "link": null
-        },
-        {
-          "name": "batch_size",
-          "type": "INT",
-          "widget": {
-            "name": "batch_size"
-          },
-          "link": null
-        },
-        {
-          "name": "color",
-          "type": "INT",
-          "widget": {
-            "name": "color"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            1
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "EmptyImage"
-      },
-      "widgets_values": [
-        512,
-        512,
-        1,
-        8096934
-      ]
-    },
-    {
-      "id": 2,
-      "type": "ImageInvert",
-      "pos": [
-        120,
-        160
-      ],
-      "size": [
-        225,
-        48
-      ],
-      "flags": {},
-      "order": 3,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 1
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            2
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "ImageInvert"
-      },
-      "widgets_values": []
-    },
-    {
-      "id": 3,
-      "type": "ImageInvert",
-      "pos": [
-        510,
-        160
-      ],
-      "size": [
-        225,
-        48
-      ],
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 2
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            3
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "ImageInvert"
-      },
-      "widgets_values": []
-    },
-    {
-      "id": 4,
-      "type": "SaveImage",
-      "pos": [
-        920,
-        140
-      ],
-      "size": [
-        270,
-        76
-      ],
-      "flags": {},
-      "order": 5,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "images",
-          "type": "IMAGE",
-          "link": 3
-        },
-        {
-          "name": "filename_prefix",
-          "type": "STRING",
-          "widget": {
-            "name": "filename_prefix"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Adachi/GroupPresetExample"
-      ]
-    },
-    {
-      "id": 5,
-      "type": "AdachiGroupPresets",
-      "pos": [
-        80,
-        440
-      ],
-      "size": [
-        620,
-        410
-      ],
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {
-        "adachi_group_presets": {
-          "version": 1,
-          "activeId": "01dbf1d1-c15a-4db1-97d5-9d522781c482",
-          "presets": [
-            {
-              "id": "01dbf1d1-c15a-4db1-97d5-9d522781c482",
-              "name": "All enabled",
-              "groups": {
-                "group:1": {
-                  "title": "Base",
-                  "mode": 0
-                },
-                "group:2": {
-                  "title": "Detail",
-                  "mode": 0
-                }
-              }
-            },
-            {
-              "id": "fe43bc1f-1a1e-4f49-a37b-c6e6ca7cbc8a",
-              "name": "Skip detail",
-              "groups": {
-                "group:1": {
-                  "title": "Base",
-                  "mode": 0
-                },
-                "group:2": {
-                  "title": "Detail",
-                  "mode": 4
-                }
-              }
-            },
-            {
-              "id": "b881a666-4643-4af6-8feb-f1d02c47f113",
-              "name": "Bypass both",
-              "groups": {
-                "group:1": {
-                  "title": "Base",
-                  "mode": 4
-                },
-                "group:2": {
-                  "title": "Detail",
-                  "mode": 4
-                }
-              }
-            }
-          ]
-        }
-      }
-    },
-    {
-      "id": 6,
-      "type": "Note",
-      "pos": [
-        820,
-        550
-      ],
-      "size": [
-        350,
-        180
-      ],
-      "flags": {},
-      "order": 2,
-      "mode": 0,
-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Adachi-Inpaint-Workbench - Group Bypass Presets\nSelect a preset on the left to switch a whole group between enabled and bypassed; no connections required\nAdjust each group's state on the right, or click \"Save current group states\" to store the current workflow\nRight-click the node -> Apply preset to switch quickly\nThis example only inverts an image, so no model is needed"
-      ],
-      "color": "#432",
-      "bgcolor": "#653"
-    }
-  ],
-  "links": [
-    [
-      1,
-      1,
-      0,
-      2,
-      0,
-      "IMAGE"
-    ],
-    [
-      2,
-      2,
-      0,
-      3,
-      0,
-      "IMAGE"
-    ],
-    [
-      3,
-      3,
-      0,
-      4,
-      0,
-      "IMAGE"
-    ]
-  ],
-  "groups": [
-    {
-      "id": 1,
-      "title": "Base",
-      "bounding": [
-        80,
-        100,
-        300,
-        230
-      ],
-      "color": "#3f789e",
-      "font_size": 24,
-      "flags": {}
-    },
-    {
-      "id": 2,
-      "title": "Detail",
-      "bounding": [
-        470,
-        100,
-        300,
-        230
-      ],
-      "color": "#3f789e",
-      "font_size": 24,
-      "flags": {}
-    }
-  ],
-  "config": {},
-  "extra": {
-    "ds": {
-      "scale": 1,
-      "offset": [
-        0,
-        0
-      ]
-    }
-  },
-  "version": 0.4
-}

examples/04-exclusive-switch.json

@@ -1,423 +0,0 @@
-{
-  "id": "00000000-0000-0000-0000-000000000000",
-  "revision": 0,
-  "last_node_id": 7,
-  "last_link_id": 5,
-  "nodes": [
-    {
-      "id": 1,
-      "type": "EmptyImage",
-      "pos": [
-        0,
-        120
-      ],
-      "size": [
-        270,
-        130
-      ],
-      "flags": {},
-      "order": 0,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "width",
-          "type": "INT",
-          "widget": {
-            "name": "width"
-          },
-          "link": null
-        },
-        {
-          "name": "height",
-          "type": "INT",
-          "widget": {
-            "name": "height"
-          },
-          "link": null
-        },
-        {
-          "name": "batch_size",
-          "type": "INT",
-          "widget": {
-            "name": "batch_size"
-          },
-          "link": null
-        },
-        {
-          "name": "color",
-          "type": "INT",
-          "widget": {
-            "name": "color"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            1
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "EmptyImage"
-      },
-      "widgets_values": [
-        64,
-        64,
-        1,
-        16711680
-      ]
-    },
-    {
-      "id": 2,
-      "type": "EmptyImage",
-      "pos": [
-        0,
-        450
-      ],
-      "size": [
-        270,
-        130
-      ],
-      "flags": {},
-      "order": 1,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "width",
-          "type": "INT",
-          "widget": {
-            "name": "width"
-          },
-          "link": null
-        },
-        {
-          "name": "height",
-          "type": "INT",
-          "widget": {
-            "name": "height"
-          },
-          "link": null
-        },
-        {
-          "name": "batch_size",
-          "type": "INT",
-          "widget": {
-            "name": "batch_size"
-          },
-          "link": null
-        },
-        {
-          "name": "color",
-          "type": "INT",
-          "widget": {
-            "name": "color"
-          },
-          "link": null
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            2
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "EmptyImage"
-      },
-      "widgets_values": [
-        64,
-        64,
-        1,
-        255
-      ]
-    },
-    {
-      "id": 3,
-      "type": "ImageInvert",
-      "pos": [
-        300,
-        120
-      ],
-      "size": [
-        140,
-        26
-      ],
-      "flags": {},
-      "order": 3,
-      "mode": 4,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 1
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            3
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "ImageInvert"
-      }
-    },
-    {
-      "id": 4,
-      "type": "ImageInvert",
-      "pos": [
-        300,
-        450
-      ],
-      "size": [
-        140,
-        26
-      ],
-      "flags": {},
-      "order": 4,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 2
-        }
-      ],
-      "outputs": [
-        {
-          "name": "IMAGE",
-          "type": "IMAGE",
-          "links": [
-            4
-          ]
-        }
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examples/05-inline-crop-blend.json

@@ -1,787 +0,0 @@
-{
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-  "revision": 0,
-  "last_node_id": 8,
-  "last_link_id": 15,
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-          "link": null
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-          "type": "STRING",
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-          "name": "MODEL",
-          "type": "MODEL",
-          "links": [
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-          "link": null
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-        "mask_mode": "inside",
-        "fill": "original",
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-        "control_after_generate": "fixed",
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-        "cfg": 7,
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-          "type": "IMAGE",
-          "links": []
-        }
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-      "properties": {},
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-      "flags": {},
-      "order": 2,
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-      "inputs": [],
-      "outputs": [],
-      "properties": {},
-      "widgets_values": [
-        "Inline Mask: Crop & Blend\n1. Select your checkpoint and upload the full source.\n2. Choose Crop & Blend and a size preset, then left-click to lock the black dashed frame. Inpaint width/height follow the crop automatically.\n3. Paint inside the empty crop mask and run the workflow.\n4. Inspect Image Compare and click Adopt this result. The patch returns to this crop; Inline Mask has no result input.\n5. Click the blend button to edit the blend mask: paint keeps new pixels and Alt restores original pixels. The repaint mask is retained.\n6. full_image is the current adopted full composite. In blend mode, hold right-click to preview the original. Switch to the repaint mask and right-click or press Escape to merge the visible result and release the selection, then left-click a new area. Hover the bottom controls for instructions."
-      ],
-      "widgets_values_named": {
-        "text": "Inline Mask: Crop & Blend\n1. Select your checkpoint and upload the full source.\n2. Choose Crop & Blend and a size preset, then left-click to lock the black dashed frame. Inpaint width/height follow the crop automatically.\n3. Paint inside the empty crop mask and run the workflow.\n4. Inspect Image Compare and click Adopt this result. The patch returns to this crop; Inline Mask has no result input.\n5. Click the blend button to edit the blend mask: paint keeps new pixels and Alt restores original pixels. The repaint mask is retained.\n6. full_image is the current adopted full composite. Reselect merges it before choosing a new area."
-      },
-      "color": "#432",
-      "bgcolor": "#653"
-    }
-  ],
-  "links": [
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-  "groups": [],
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-  "extra": {
-    "ds": {
-      "scale": 0.5,
-      "offset": [
-        0,
-        400
-      ]
-    }
-  },
-  "version": 0.4
-}

locales/en/nodeDefs.json

@@ -14,6 +14,18 @@
       "source_data": {
         "name": "source_data",
         "tooltip": "Embedded source image for portable workflows."
+      },
+      "edit_mode": {
+        "name": "edit_mode"
+      },
+      "crop_state": {
+        "name": "crop_state"
+      },
+      "blend_data": {
+        "name": "blend_data"
+      },
+      "layer_image": {
+        "name": "layer_image"
       }
     },
     "outputs": {
@@ -22,6 +34,9 @@
       },
       "1": {
         "name": "mask"
+      },
+      "2": {
+        "name": "full_image"
       }
     }
   },
@@ -114,7 +129,7 @@
     }
   },
   "AdachiWebUIInpaint": {
-    "display_name": "WebUI Inpaint",
+    "display_name": "Adachi Inpaint Workbench",
     "description": "WebUI-style inpainting, crop, latent fill, sampling and original-size compositing.",
     "inputs": {
       "image": {
@@ -185,6 +200,10 @@
         "name": "soft_edge",
         "tooltip": "Extra feathering, not A1111 Soft Inpainting."
       },
+      "soft_strength": {
+        "name": "soft_strength",
+        "tooltip": "Adds 0–16 pixels of Gaussian feathering."
+      },
       "refiner_model": {
         "name": "refiner_model",
         "tooltip": "Optional compatible refiner model, e.g. SDXL refiner."

locales/zh/nodeDefs.json

@@ -129,7 +129,7 @@
     }
   },
   "AdachiWebUIInpaint": {
-    "display_name": "WebUI 局部重绘 / WebUI Inpaint",
+    "display_name": "安达重绘工作台",
     "description": "WebUI 式局部重绘：整图/蒙版区域、填充、采样与原尺寸回贴。",
     "inputs": {
       "image": {

preview_store.py

@@ -16,8 +16,9 @@ def _limit():
 
 
 class PreviewStore:
-    def __init__(self, limit=None):
+    def __init__(self, limit=None, max_batches=512):
         self.limit = _limit() if limit is None else limit
+        self.max_batches = max(1, int(max_batches))
         self.nonce = secrets.token_hex(12)
         self.epoch = 0
         self.size = 0
@@ -32,6 +33,8 @@ class PreviewStore:
 
     def put_batch(self, images, owner):
         """Atomically retain a whole comparison batch, or explicitly reject it."""
+        if not images or any(not image for image in images):
+            raise ValueError("The comparison batch must contain nonempty images.")
         total = sum(len(image) for image in images)
         if total > self.limit:
             raise ValueError("The comparison batch exceeds the in-memory preview limit. Reduce batch size or increase ADACHI_COMPARE_MEMORY_MIB (64–4096 MiB).")
@@ -52,7 +55,7 @@ class PreviewStore:
                     self.groups.move_to_end(last[0])
                     self.latest[owner] = (last[0], before)
                     return list(group["descriptors"])
-            while self.groups and self.size + total > self.limit:
+            while self.groups and (self.size + total > self.limit or len(self.groups) >= self.max_batches):
                 group_id, group = self.groups.popitem(last=False)
                 self.size -= group["size"]
                 for key in group["keys"]:

pyproject.toml

@@ -1,13 +1,14 @@
 [project]
 name = "adachi-inpaint-workbench"
-version = "1.0.0"
-description = "Inline mask painting and WebUI-style inpainting nodes for ComfyUI"
+version = "2.1.1"
+description = "Inline mask painting, crop blending and a standalone inpainting workbench for ComfyUI"
 requires-python = ">=3.10"
 license = { file = "LICENSE" }
 readme = "README.md"
 authors = [{ name = "Adachi" }]
 dependencies = ["numpy", "Pillow", "torch"]
 classifiers = [
+    "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
 ]

registry/README.md

@@ -19,3 +19,7 @@ Per the [official publishing guide](https://docs.comfy.org/registry/publishing),
 
 The publishing workflow is manual-only. Check its result and the Registry version status after publishing.
 A Registry version cannot be overwritten once published, so later releases have to bump the version in `pyproject.toml`.
+
+## 2.0.1 verification
+
+After publishing 2.0.1, check both the Actions result and the new version's status in the [public Registry API](https://api.comfy.org/nodes/adachi-inpaint-workbench/versions?include_status_reason=true). A successful publishing job confirms upload, not Registry approval or Manager availability. Previous versions received automated scan flags; [scan review notes](SECURITY-REVIEW.md) explain the public findings and the checks required for this release. Do not report the version as approved while its status is `Pending` or `Flagged`.

registry/SECURITY-REVIEW.md

@@ -0,0 +1,23 @@
+# Registry scan review notes
+
+Publication and Registry approval are separate steps. Check the [public version API, including scan reasons](https://api.comfy.org/nodes/adachi-inpaint-workbench/versions?include_status_reason=true) after publishing **2.0.0**; a successful upload does not establish an `Active` version or Manager availability. The publisher cannot change the Registry review status through this release workflow.
+
+## Previous scan findings
+
+On 2026-11-10, **2.0.0** is also `NodeVersionStatusFlagged`, with extraction `pending`. Its six `info` records match the configuration read, `Function.bind()` in `web/compare_node.js`, `web/inline_crop.js`, `web/result_recovery.js` and `web/workspace_ui.js`, and the upload send in `web/upload_transport.js`. The same code-purpose explanations below apply; no official approval is claimed.
+
+On 2026-11-09, versions **1.0.0** and **1.0.1** were `NodeVersionStatusFlagged`, with `comfy_node_extract_status: pending`. Their public scan reasons contained the following three `info` findings. Line numbers refer to those releases.
+
+| File / line | Reported rule | Purpose and assessment |
+| --- | --- | --- |
+| `preview_store.py:12` | `python_environment_manipulation` | Reads `ADACHI_COMPARE_MEMORY_MIB` to bound the in-memory image cache. It reads one documented setting and does not modify environment variables. We infer that the rule is flagging a benign configuration read. |
+| `web/inline_crop.js:47` (also 55, 92 and 93) | `python_network_operations` | JavaScript `Function.bind()` retains the editor object as `this` when wrapping upload, flush and pointer handlers. This does not open a network socket; we infer a cross-language pattern false positive. |
+| `web/upload_transport.js:15` | `python_network_operations` | `XMLHttpRequest.send()` uploads a user-selected image to ComfyUI's own `/upload/image` route through its API URL, allowing real upload progress. Network activity here is intentional; we infer that the finding reflects required functionality rather than data exfiltration. |
+
+These assessments describe the matched code, not an official security clearance or a comprehensive audit. Required functionality remains readable; no code is obfuscated to avoid scanning. Development tests and review documents are excluded from the Registry archive by `.comfyignore`.
+
+## Release checks
+
+- Inspect the new version's actual `status` and any `status_reason`; do not assume the previous findings describe a new release.
+- If flagged, retain the version and artifact identifiers and provide the relevant code explanation for manual review. Registry approval remains an external decision.
+- Follow the [official Registry quality and security standards](https://docs.comfy.org/registry/standards), including the prohibitions on code obfuscation, `eval` / `exec` and runtime package installation.

tests/test_adopt_progress.mjs

@@ -0,0 +1,7 @@
+import assert from 'node:assert/strict';
+import {ImageCompareView} from '../web/compare.js';
+const view=Object.create(ImageCompareView.prototype),events=[];
+Object.assign(view,{ready:true,pendingOutputs:0,targetSelect:{value:'7'},results:[{}],index:0,progressBox:{hidden:true},refreshTargets(){},updateButton(){},status(s,e){events.push(['status',s,e]);},loading(s,v){this.progressBox.hidden=false;events.push(['progress',s,v]);},options:{async onAdopt(id,image,{onProgress}){onProgress({phase:'download',loaded:20,total:100});onProgress({phase:'upload',loaded:30,total:100});onProgress({phase:'processing'});}}});
+await view.adopt();assert.equal(view.busy,false);assert.equal(view.progressBox.hidden,true);const progress=events.filter(e=>e[0]==='progress');assert.equal(progress.length,4);assert.equal(progress[1][2][0].loaded,20);assert.equal(progress[2][2][0].loaded,30);
+view.options.onAdopt=async()=>{throw Error('network failure')};await view.adopt();assert.equal(view.progressBox.hidden,true);assert.equal(view.busy,false);assert(events.some(e=>e[0]==='status'&&e[1]==='network failure'&&e[2]));
+console.log('Adoption progress: actual download/upload bytes, loading phase and failed retry cleanup passed');

tests/test_color_paint.mjs

@@ -0,0 +1,21 @@
+import assert from 'node:assert/strict';
+class Element {
+  constructor(tag){this.tag=tag;this.style={};this.dataset={};this.classList={toggle(){}};this.children=[];this.width=0;this.height=0;this.value='';}
+  append(...children){this.children.push(...children)} prepend(...children){this.children.unshift(...children)} setAttribute(){} hasPointerCapture(){return false} setPointerCapture(){}
+  getContext(){return {save(){},restore(){},beginPath(){},rect(){},clip(){},arc(){},fill(){},moveTo(){},lineTo(){},stroke(){},translate(){},clearRect(){},drawImage(){},getImageData(){return {data:[12,34,56,255]}}};}
+  toDataURL(){return 'data:image/png;base64,paint';}
+}
+globalThis.document={createElement:tag=>new Element(tag)};globalThis.ResizeObserver=class {observe(){} disconnect(){}};
+globalThis.Image=class {constructor(){this.width=16;this.height=12;} async decode(){if(this.src==='bad')throw Error('bad image');}};
+const {ColorPaint}=await import('../web/color_paint.js');
+const editor={image:{width:16,height:12},ready:true,view:'overlay',brushSize:8,brushOpacity:100,stage:new Element('div'),root:new Element('div'),canvas:new Element('canvas'),options:{drawSource:()=>false},point:e=>({x:e.x,y:e.y}),pointerDown(){},pointerMove(){},pointerUp(){},schedule(){},status(){}};
+const crop={mode:'mask',bar:new Element('div'),region:{locked:false}},widget={value:''};let changes=0;
+const paint=new ColorPaint(editor,crop,widget,()=>changes++);assert.equal(crop.bar.children[0],paint.controls);paint.button.onclick({preventDefault(){},stopPropagation(){}});
+const event={button:0,pointerId:1,x:2,y:3,preventDefault(){},stopPropagation(){}};
+editor.pointerDown(event);assert.equal(editor.pointerId,1);editor.pointerUp(event);assert.equal(editor.pointerId,null);assert.match(widget.value,/data:image\/png/);assert.equal(changes,1);
+const saved=widget.value;editor.pointerDown({...event,altKey:true});assert.equal(paint.color,'#0c2238');assert.equal(widget.value,saved);
+await assert.rejects(()=>paint.prepareRestore('bad',16,12));await assert.rejects(()=>paint.prepareRestore('anything',17,12));
+const loaded=await paint.prepareRestore('anything',16,12);paint.commitRestore(loaded,16,12);assert.equal(paint.undo.length,0);
+paint.clearRegion({x:0,y:0,width:4,height:4});assert.equal(changes,2);paint.clear();assert.equal(widget.value,'');
+widget.value='old';let finish;paint.prepareRestore=()=>new Promise(resolve=>{finish=resolve});const restoring=paint.restore('old');paint.clear();finish(new Image());assert.equal(await restoring,false);assert.equal(paint.layer.width,0);assert.equal(paint.restoring,false);
+console.log('Color painting: stroke commits, Alt sampling, immutable restore validation and region clearing pass');

tests/test_compare_viewport.mjs

@@ -0,0 +1,36 @@
+import assert from 'node:assert/strict';
+import {CompareViewport} from '../web/compare_viewport.js';
+import {ImageCompareView} from '../web/compare.js';
+const v=new CompareViewport();
+const size=[1000,600,800,400],at=[235,417];
+const original=v.transform(...size);
+assert.equal(original.scale,1.25);assert.equal(original.y,50);
+const pixel=t=>[(at[0]-t.x)/t.scale,(at[1]-t.y)/t.scale];
+const initial=pixel(original);
+v.zoomAt(...size,...at,-120);
+assert.ok(v.zoom>1);const enlarged=v.transform(...size);
+assert.ok(Math.abs(pixel(enlarged)[0]-initial[0])<1e-9);
+assert.ok(Math.abs(pixel(enlarged)[1]-initial[1])<1e-9,'wheel zoom keeps the image point under the pointer');
+v.pan(20,-10);const moved=v.transform(...size);assert.equal(moved.x,enlarged.x+20);assert.equal(moved.y,enlarged.y-10);
+for(let i=0;i<500;i++)v.zoomAt(...size,...at,-120);assert.equal(v.zoom,16);
+for(let i=0;i<1000;i++)v.zoomAt(...size,...at,120);assert.equal(v.zoom,.1);
+v.fit();assert.deepEqual(v.transform(...size),original);
+v.zoomAt(0,0,800,400,0,0,120);assert.equal(v.zoom,1);
+console.log('Compare viewport: pointer-anchored zoom, panning, limits, fit and zero-size protection pass');
+
+{
+ const draws=[];const context={setTransform(){},clearRect(){},save(){},restore(){},beginPath(){},rect(){},clip(){},drawImage(image){draws.push(image);}};
+ const view=Object.create(ImageCompareView.prototype),before={width:800,height:400},after={width:800,height:400};
+ Object.assign(view,{viewport:new CompareViewport(),workspaceZoom:false,displayMode:'compare',ready:true,before,after,hovered:true,split:.5,version:1,divider:{style:{}},canvas:{width:0,height:0,clientWidth:1000,getBoundingClientRect:()=>({width:1000,height:600,left:0,top:0}),getContext:()=>context},options:{onGraphWheel:()=>graphWheels++},schedule:()=>schedules++});
+ let graphWheels=0,schedules=0;globalThis.devicePixelRatio=1;
+ const event={deltaY:-120,deltaMode:0,clientX:235,clientY:417,preventDefault(){},stopPropagation(){}};
+ view.wheel(event);assert.equal(graphWheels,1,'normal graph node wheel must still navigate the workflow');
+ view.enableWorkspaceZoom(true);view.wheel(event);assert.equal(graphWheels,1);assert.ok(view.viewport.zoom>1);
+ const shared=view.transform();
+ view.setDisplayMode('before');view.render();assert.deepEqual(draws.splice(0),[before]);assert.deepEqual(view.transform(),shared);
+ view.setDisplayMode('after');view.render();assert.deepEqual(draws.splice(0),[after]);assert.deepEqual(view.transform(),shared);
+ view.setDisplayMode('compare');view.render();assert.deepEqual(draws.splice(0),[after,before]);
+ view.fitView();assert.equal(view.viewport.zoom,1);assert.ok(schedules>0);
+ view.viewport.pan(50,30);view.enableWorkspaceZoom(false);assert.equal(view.displayMode,'compare');assert.equal(view.viewport.panX,0);assert.equal(view.viewport.panY,0);
+}
+console.log('Compare integration: graph wheel routing, workspace zoom, shared before/after transform, display pixels and teardown reset pass');

tests/test_crop_workbench.py

@@ -30,6 +30,25 @@ class InlineCropTests(unittest.TestCase):
         image,mask,full=backend.AdachiInlineMask().load(source_data=self.source,mask_data=url(Image.fromarray(pixels)),edit_mode='crop',crop_state=self.state)
         self.assertTrue(torch.equal(image,self.original[:,16:80,32:96]));self.assertTrue(torch.equal(full,self.original))
         self.assertEqual(mask.sum().item(),20);self.assertEqual(mask[0,4,3].item(),1)
+    def test_color_paint_composites_after_crop_layer_before_crop_without_touching_mask(self):
+        paint=np.zeros((96,128,4),dtype=np.uint8)
+        paint[20,35]=[255,0,0,255]
+        paint[21,36]=[0,255,0,128]
+        paint[4,5]=[0,0,255,255]
+        paint_data=url(Image.fromarray(paint))
+        mask=np.zeros((96,128),dtype=np.uint8);mask[20,35]=255
+        with patch.object(backend,'_load_layer',return_value=torch.ones(1,64,64,3)):
+            image,m,full=backend.AdachiInlineMask().load(source_data=self.source,mask_data=url(Image.fromarray(mask)),edit_mode='crop',crop_state=self.state,layer_image='layer.png',paint_data=paint_data)
+        self.assertTrue(torch.equal(image,full[:,16:80,32:96]))
+        self.assertTrue(torch.equal(full[0,20,35],torch.tensor([1.,0.,0.])))
+        self.assertTrue(torch.allclose(full[0,21,36],torch.tensor([127/255,1.,127/255])))
+        self.assertTrue(torch.equal(full[0,4,5],torch.tensor([0.,0.,1.])))
+        self.assertEqual(m.sum().item(),1)
+        flat,_,_=backend.AdachiInlineMask().load(source_data=self.source,paint_data=paint_data)
+        self.assertTrue(torch.equal(flat[0,20,35],torch.tensor([1.,0.,0.])))
+        self.assertNotEqual(backend.AdachiInlineMask.IS_CHANGED(source_data=self.source),backend.AdachiInlineMask.IS_CHANGED(source_data=self.source,paint_data=paint_data))
+        with self.assertRaisesRegex(ValueError,'dimensions must match'):
+            backend.AdachiInlineMask().load(source_data=self.source,paint_data=url(Image.new('RGBA',(1,1))))
     def test_layer_blend_preserves_outside_and_supports_batch_and_soft_edges(self):
         alpha=np.zeros((64,64),dtype=np.uint8);alpha[:,:32]=255;alpha[:,32:48]=128
         result=torch.stack([torch.zeros(64,64,3),torch.ones(64,64,3)])
@@ -51,6 +70,22 @@ class InlineCropTests(unittest.TestCase):
             descriptor=a['ui']['adachi_layer'][0]['image'];name=descriptor['subfolder']+'/'+descriptor['filename']
             image,_,full=backend.AdachiInlineMask().load(source_data=self.source,edit_mode='crop',crop_state=self.state,layer_image=name)
             self.assertTrue(torch.equal(image,torch.ones(1,64,64,3)));self.assertTrue(torch.equal(full,a['result'][0][:1]))
+    def test_legacy_layer_sink_applies_paint_above_generated_layer(self):
+        paint=np.zeros((96,128,4),dtype=np.uint8);paint[20,35]=[255,0,0,255]
+        with tempfile.TemporaryDirectory() as folder,patch.dict('sys.modules',{'folder_paths':types.SimpleNamespace(get_input_directory=lambda:folder)}):
+            output=backend.AdachiLayerCommit().compose(torch.ones(1,64,64,3),source_data=self.source,crop_state=self.state,paint_data=url(Image.fromarray(paint)))['result'][0]
+            self.assertTrue(torch.equal(output[0,20,35],torch.tensor([1.,0.,0.])))
+            self.assertTrue(torch.equal(output[0,20,36],torch.ones(3)))
+    def test_paint_input_file_preserves_transparency_and_changes_fingerprint(self):
+        pixels=np.zeros((96,128,4),dtype=np.uint8);pixels[20,35]=[255,0,0,255]
+        with tempfile.TemporaryDirectory() as folder,patch.dict('sys.modules',{'folder_paths':types.SimpleNamespace(get_input_directory=lambda:folder)}):
+            path=Path(folder)/'paint.png';Image.fromarray(pixels).save(path)
+            a=backend.AdachiInlineMask.IS_CHANGED(source_data=self.source,paint_data='paint.png')
+            result,_,_=backend.AdachiInlineMask().load(source_data=self.source,paint_data='paint.png')
+            self.assertTrue(torch.equal(result[0,20,35],torch.tensor([1.,0.,0.])))
+            path.unlink()
+            self.assertTrue(np.isnan(backend.AdachiInlineMask.IS_CHANGED(source_data=self.source,paint_data='paint.png')))
+            self.assertIsInstance(a,str)
     def test_invalid_regions_or_result_sizes_fail_before_writing(self):
         for change in ({'x':-1},{'y':80},{'width':65},{'height':0},{'x':True}):
             with self.subTest(change=change),self.assertRaises(ValueError):

tests/test_draft_guard.mjs

@@ -105,6 +105,14 @@ const namedOnly = {nodes:[{type:"AdachiInlineMask", widgets_values_named:{source
 await prepareInlineDraft(namedOnly,{fits:()=>false,upload:async()=>"named.png"});
 assert.equal(namedOnly.nodes[0].widgets_values_named.source_data,"");
 assert.equal(namedOnly.nodes[0].widgets_values_named.mask_data,"keep");
+const painted={nodes:[{type:'AdachiInlineMask',widgets_values:['file.png','mask','','crop','region','blend','layer.png',large],widgets_values_named:{paint_data:'stale'}}]};
+await prepareInlineDraft(painted,{fits:g=>g.nodes[0].widgets_values[7].length<100,upload:async data=>{assert.equal(data,large);return 'adachi-inpaint/paint.png';}});
+assert.equal(painted.nodes[0].widgets_values[7],'adachi-inpaint/paint.png');
+assert.equal(painted.nodes[0].widgets_values_named.paint_data,'adachi-inpaint/paint.png');
+assert.equal(painted.nodes[0].widgets_values[0],'file.png');
+const failPaint={nodes:[{type:'AdachiInlineMask',widgets_values:['file.png','mask','','crop','region','blend','layer.png',large]}]};
+await assert.rejects(prepareInlineDraft(failPaint,{fits:()=>false,upload:async()=>{throw Error('offline')}}),/offline/);
+assert.equal(failPaint.nodes[0].widgets_values[7],large);
 const widgets=inlineWidgetNames.map((name,index)=>({name,value:`live-${index}`}));
 widgets.splice(1,0,{name:"unrelated",value:"untouched"});
 const snapshot={widgets_values:Array(8).fill("old"),widgets_values_named:{source_data:large,unrelated:"keep"}};

tests/test_i18n.mjs

@@ -0,0 +1,55 @@
+import assert from 'node:assert/strict';
+import {T, localeDict} from '../web/i18n.js';
+import {WorkspaceProgress} from '../web/workspace_progress.js';
+
+const saved = Object.fromEntries(['comfyAPI','app','navigator'].map(key => [key,Object.getOwnPropertyDescriptor(globalThis,key)]));
+const settings = getLocale => ({ui:{settings:{getSettingValue(key) {
+    assert.equal(key,'Comfy.Locale');
+    return getLocale();
+}}}});
+try {
+    delete globalThis.comfyAPI; delete globalThis.app;
+    Object.defineProperty(globalThis,'navigator',{configurable:true,value:{language:'zh-CN',languages:['zh-CN']}});
+    assert.equal(T('Adopt'),'Adopt','English remains the default even for a Chinese-language browser');
+    assert.equal(localeDict(),null);
+    assert.equal(T('Missing {count} model files',{count:0}),'Missing 0 model files');
+
+    let locale='en-US';
+    globalThis.comfyAPI={app:{app:settings(()=>locale)}};
+    globalThis.app=settings(()=>'zh');
+    assert.equal(T('Open Adachi Workbench'),'Open Adachi Workbench','the current ComfyUI API takes priority over legacy globals');
+    locale='zh-CN';
+    assert.equal(T('Open Adachi Workbench'),'打开安达工作台');
+    assert.equal(T('Missing {count} model files',{count:3}),'缺少 3 份模型文件');
+    assert.equal(T('Settings panel {width} pixels wide',{width:360}),'右侧配置 360 像素');
+    assert.equal(T('Fill','enum'),'填充','existing enum contexts remain compatible');
+    assert.equal(T('New message {count}',{count:false}),'New message false','untranslated strings still interpolate');
+    assert.equal(T('Unknown {value} / {missing}',{value:'<img src=x>'}),'Unknown <img src=x> / {missing}','values remain literal text and missing placeholders remain visible');
+    assert.equal(T('toString'),'toString','dictionary prototype properties are not translations');
+
+    locale='zh_TW';
+    assert.equal(T('Workflow connections'),'工作流连接','regional locale separators both resolve to the Chinese dictionary');
+    const progress=new WorkspaceProgress();
+    progress.begin({'7':{class_type:'AdachiWebUIInpaint'}},'task');
+    progress.handle('progress',{prompt_id:'task',node:'7',value:2,max:10});
+    assert.equal(progress.label,'重绘采样（K 采样器） · 2 / 10');
+    locale='en';
+    progress.handle('progress',{prompt_id:'task',node:'7',value:3,max:10});
+    assert.equal(progress.label,'Inpaint sampling (KSampler) · 3 / 10','execution messages use the current setting rather than an import-time locale');
+    assert.equal(T('Adopt'),'Adopt','locale changes do not require module reload');
+    locale='fr';
+    assert.equal(T('Adopt'),'Adopt','unsupported locales fall back to English');
+
+    globalThis.comfyAPI={app:settings(()=>'zh')}; delete globalThis.app;
+    assert.equal(T('Adopt'),'采用','older ComfyUI API shape is supported');
+    globalThis.comfyAPI={app:{app:settings(()=>{throw Error('not initialized');})}};
+    globalThis.app=settings(()=>'zh');
+    assert.equal(T('Adopt'),'采用','a not-yet-ready modern setting can fall back to the legacy app');
+    delete globalThis.comfyAPI; delete globalThis.app;
+    assert.equal(T('Adopt'),'Adopt','an unavailable app does not break custom UI initialization');
+} finally {
+    for(const [key,descriptor] of Object.entries(saved)) {
+        if(descriptor)Object.defineProperty(globalThis,key,descriptor);else delete globalThis[key];
+    }
+}
+console.log('Localization: ComfyUI settings precedence, English fallback, live locale changes, placeholders, regional locales and enum compatibility pass');

tests/test_image_load.mjs

@@ -0,0 +1,8 @@
+import assert from 'node:assert/strict';
+globalThis.location=new URL('https://example.test/app');let calls=[];
+globalThis.Image=class {set src(value){this.url=value;if(!value)return;calls.push(value);queueMicrotask(()=>calls.length<3?this.onerror?.():this.onload?.());}};
+const {loadImage}=await import('../web/image_load.js');
+const image=await loadImage('/view?filename=test.png',{retry:true,delays:[0,0]});assert.equal(calls.length,3);assert.match(image.url,/_adachi_retry=2/);
+calls=[];await assert.rejects(loadImage('data:image/png;base64,invalid',{retry:true,delays:[0,0]}));assert.equal(calls.length,1);
+calls=[];const c=new AbortController();c.abort();await assert.rejects(loadImage('/view?filename=test.png',{retry:true,signal:c.signal}),{name:'AbortError'});assert.equal(calls.length,0);
+console.log('Fresh uploaded image loading: bounded retry, cache bypass, non-network image and cancellation passed');

tests/test_mask_boundaries.py

@@ -0,0 +1,34 @@
+"""Image-edge and dense-mask equivalence for the bounded-memory preparation path."""
+import unittest
+import torch
+from test_backend import backend
+
+
+class MaskBoundaryTests(unittest.TestCase):
+    def test_dense_sparse_empty_and_skinny_mask_bounds(self):
+        for height, width in [(1, 1), (1, 79), (81, 1), (192, 256)]:
+            for kind in ('empty', 'full', 'corners', 'middle'):
+                mask = torch.zeros(height, width)
+                if kind == 'full': mask.fill_(1)
+                elif kind == 'corners': mask[0, 0] = mask[-1, -1] = .01
+                elif kind == 'middle': mask[height//2, width//2] = .7
+                for padding in (0, 7, 2048):
+                    box = backend._bbox(mask, padding, width/height)
+                    x0, y0, x1, y1 = box
+                    self.assertTrue(0 <= x0 < x1 <= width)
+                    self.assertTrue(0 <= y0 < y1 <= height)
+                    self.assertEqual(float(mask.sum()), float(mask[y0:y1, x0:x1].sum()))
+                    if kind in ('full', 'corners', 'empty'):
+                        self.assertEqual(box, (0, 0, width, height))
+
+    def test_sanitizing_never_mutates_upstream_tensors(self):
+        image = torch.tensor([float('nan'), float('inf'), -1.0, 2.0]*3).reshape(1, 2, 2, 3)
+        original = image.clone()
+        output = backend._image_tensor(image)
+        self.assertTrue(torch.equal(torch.isnan(original), torch.isnan(image)))
+        self.assertTrue(torch.equal(original[~torch.isnan(original)], image[~torch.isnan(image)]))
+        self.assertTrue(torch.isfinite(output).all())
+        self.assertTrue(((output >= 0) & (output <= 1)).all())
+        mask = torch.full((1, 2, 2), 2.0)
+        self.assertEqual(float(backend._mask_tensor(mask, output).max()), 1)
+        self.assertEqual(float(mask.min()), 2)

tests/test_official_workflow.py

@@ -0,0 +1,131 @@
+"""The public template stays portable and routes each preset independently."""
+import json
+from pathlib import Path
+import re
+import unittest
+
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+class OfficialWorkflowTests(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.path = ROOT / "examples" / "Adachi-Workbench.json"
+        cls.raw = cls.path.read_text(encoding="utf-8")
+        cls.workflow = json.loads(cls.raw)
+        cls.nodes = {node["id"]: node for node in cls.workflow["nodes"]}
+        cls.links = {link[0]: link for link in cls.workflow["links"]}
+        cls.groups = {group["id"]: group for group in cls.workflow["groups"]}
+
+    def typed(self, name):
+        return [node for node in self.nodes.values() if node["type"] == name]
+
+    def group_members(self, group):
+        x, y, width, height = group["bounding"]
+        return [node for node in self.nodes.values()
+                if x <= node["pos"][0] and y <= node["pos"][1]
+                and node["pos"][0] + node["size"][0] <= x + width
+                and node["pos"][1] + node["size"][1] <= y + height]
+
+    def test_one_complete_official_template(self):
+        self.assertEqual([self.path.name], sorted(p.name for p in (ROOT / "examples").glob("*.json")))
+        for name in ("CheckpointLoaderSimple", "EmptyLatentImage", "KSampler", "VAEDecode",
+                     "SaveImage", "AdachiInlineMask", "AdachiWebUIInpaint", "AdachiImageCompare",
+                     "AdachiGroupPresets"):
+            self.assertEqual(len(self.typed(name)), 1, name)
+        self.assertEqual(len(self.typed("AdachiExclusiveSwitch")), 3)
+        self.assertEqual(len(self.typed("CLIPTextEncode")), 4)
+        allowed = {"CheckpointLoaderSimple", "EmptyLatentImage", "KSampler", "VAEDecode", "SaveImage",
+                   "CLIPTextEncode", "Note", "AdachiInlineMask", "AdachiWebUIInpaint",
+                   "AdachiImageCompare", "AdachiGroupPresets", "AdachiExclusiveSwitch"}
+        self.assertTrue({node["type"] for node in self.nodes.values()} <= allowed)
+
+    def test_ids_and_reciprocal_link_types(self):
+        self.assertEqual(len(self.nodes), len(self.workflow["nodes"]))
+        self.assertEqual(len(self.links), len(self.workflow["links"]))
+        self.assertEqual(self.workflow["last_node_id"], max(self.nodes))
+        self.assertEqual(self.workflow["last_link_id"], max(self.links))
+        for key, source, out, target, inp, kind in self.links.values():
+            origin = self.nodes[source]["outputs"][out]
+            destination = self.nodes[target]["inputs"][inp]
+            self.assertIn(key, origin["links"])
+            self.assertEqual(destination["link"], key)
+            for socket in (origin, destination):
+                self.assertTrue(kind == socket["type"] or "*" in (kind, socket["type"]),
+                                (key, kind, socket))
+        for node in self.nodes.values():
+            for index, socket in enumerate(node.get("inputs", [])):
+                if socket.get("link") is not None:
+                    self.assertEqual(self.links[socket["link"]][3:5], [node["id"], index])
+            for index, socket in enumerate(node.get("outputs", [])):
+                for key in socket.get("links") or []:
+                    self.assertEqual(self.links[key][1:3], [node["id"], index])
+
+    def test_presets_enable_one_branch_and_keep_common_nodes_enabled(self):
+        controller = self.typed("AdachiGroupPresets")[0]
+        state = controller["properties"]["adachi_group_presets"]
+        self.assertEqual(state["activeId"], "text-to-image")
+        self.assertEqual({preset["id"] for preset in state["presets"]}, {"text-to-image", "inpaint"})
+        membership = {}
+        for key, group in self.groups.items():
+            for node in self.group_members(group):
+                self.assertNotIn(node["id"], membership, "Mode groups must not overlap")
+                membership[node["id"]] = key
+        for node in self.nodes.values():
+            if node["type"] in ("AdachiExclusiveSwitch", "CheckpointLoaderSimple", "SaveImage", "AdachiGroupPresets"):
+                self.assertNotIn(node["id"], membership, node["type"])
+        for preset in state["presets"]:
+            self.assertEqual({value["mode"] for value in preset["groups"].values()}, {0, 4})
+            modes = {node["id"]: preset["groups"][f"group:{membership[node['id']]}"]["mode"]
+                     if node["id"] in membership else node["mode"] for node in self.nodes.values()}
+            expected = 1 if preset["id"] == "text-to-image" else 2
+            for switch in self.typed("AdachiExclusiveSwitch"):
+                active = sum((1 << index) for index, socket in enumerate(switch["inputs"])
+                             if modes[self.links[socket["link"]][1]] == 0)
+                self.assertEqual(active, expected, (preset["id"], switch["title"]))
+            if preset["id"] == state["activeId"]:
+                for node in self.nodes.values():
+                    self.assertEqual(node["mode"], modes[node["id"]], node["title"])
+
+    def test_no_private_source_or_locale_is_bundled(self):
+        self.assertEqual(self.typed("CheckpointLoaderSimple")[0]["widgets_values"], ["YOUR_CHECKPOINT.safetensors"])
+        self.assertIsNone(re.search(r"[\u3400-\u9fff]", self.raw), "Template text must be English")
+        self.assertIsNone(re.search(r"[A-Za-z]:[\\/]|data:image|https?://|/Users/|/root/", self.raw))
+        inline = self.typed("AdachiInlineMask")[0]
+        self.assertEqual(inline["widgets_values"][:7], ["", "", "", "mask", "{}", "", ""])
+        self.assertEqual(set(self.workflow["extra"]), {"ds"})
+
+    def test_saving_text_to_image_does_not_depend_on_an_uploaded_image(self):
+        controller = self.typed("AdachiGroupPresets")[0]
+        presets = controller["properties"]["adachi_group_presets"]["presets"]
+        members = {node["id"]: group["id"] for group in self.groups.values()
+                   for node in self.group_members(group)}
+        for preset in presets:
+            enabled = {key for key, node in self.nodes.items()
+                       if (preset["groups"][f"group:{members[key]}"]["mode"]
+                           if key in members else node["mode"]) == 0}
+            seen, todo = set(), [self.typed("SaveImage")[0]["id"]]
+            while todo:
+                key = todo.pop()
+                if key in seen:
+                    continue
+                self.assertIn(key, enabled, "Active output must not use a disabled branch")
+                seen.add(key)
+                node = self.nodes[key]
+                sockets = node.get("inputs", [])
+                if node["type"] == "AdachiExclusiveSwitch":
+                    sockets = [socket for socket in sockets if self.links[socket["link"]][1] in enabled]
+                    self.assertEqual(len(sockets), 1)
+                todo.extend(self.links[socket["link"]][1] for socket in sockets if socket.get("link") is not None)
+            types = {self.nodes[key]["type"] for key in seen}
+            if preset["id"] == "text-to-image":
+                self.assertTrue({"KSampler", "VAEDecode", "EmptyLatentImage"} <= types)
+                self.assertTrue({"AdachiInlineMask", "AdachiWebUIInpaint", "AdachiImageCompare"}.isdisjoint(types))
+            else:
+                self.assertTrue({"AdachiInlineMask", "AdachiWebUIInpaint", "AdachiImageCompare"} <= types)
+                self.assertTrue({"KSampler", "VAEDecode", "EmptyLatentImage"}.isdisjoint(types))
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_paint_draft.mjs

@@ -0,0 +1,13 @@
+import assert from 'node:assert/strict';
+import {createPaintDraftProtection} from '../web/paint_draft.js';
+const tick=()=>new Promise(r=>setTimeout(r,20));
+let w={value:'data:old'},p={revision:1,drawing:false},checks=0,marks=0,errors=[],requests=[];
+const protect=createPaintDraftProtection({paint:()=>p,widget:()=>w,graph:()=>({}),disposed:()=>false,persist:()=>true,fits:()=>{checks++;return false;},upload:data=>new Promise((resolve,reject)=>requests.push({data,resolve,reject})),changed:()=>marks++,onError:e=>errors.push(e.message)});
+protect.schedule();await tick();assert.equal(requests.length,1);
+protect.schedule();await tick();assert.equal(checks,1,'slow upload must not spin');
+w.value='data:new';p.revision++;protect.schedule();await tick();assert.equal(requests.length,1);
+requests[0].resolve('old.png');await tick();assert.equal(w.value,'data:new');assert.equal(requests.length,2,'new edit is uploaded after old request settles');
+requests[1].resolve('new.png');await tick();assert.equal(w.value,'new.png');assert(marks>0);
+p.drawing=true;w.value='data:stroke';p.revision++;const before=checks;protect.schedule();await tick();assert.equal(checks,before,'drawing must not spin');
+p.drawing=false;protect.schedule();await tick();assert.equal(requests.length,3);requests[2].reject(Error('offline'));await tick();assert.equal(w.value,'data:stroke');assert.deepEqual(errors,['offline']);
+protect.dispose();console.log('Paint draft: pending upload and stroke do not spin; stale upload, retry and offline retention passed');

tests/test_preview_images.mjs

@@ -0,0 +1,36 @@
+import assert from 'node:assert/strict';
+import {decodePreview,loadPreviewPair} from '../web/preview_images.js';
+const deferred=()=>{let resolve,reject;const promise=new Promise((a,b)=>{resolve=a;reject=b;});return{promise,resolve,reject};};
+const blob=new Blob(['PNG']);
+let allocated=0;const revoked=[];
+const urls={createObjectURL(){return 'blob:'+ ++allocated;},revokeObjectURL:url=>revoked.push(url)};
+class ImageStub{width=512;height=512;decode(){return Promise.resolve();}}
+const canceled=new AbortController();canceled.abort();
+await assert.rejects(decodePreview(blob,canceled.signal,{urls,ImageClass:ImageStub}),{name:'AbortError'});
+assert.equal(allocated,0,'already-canceled decoding never allocates a URL');
+class Stalled extends ImageStub{decode(){return new Promise(()=>{});}}
+await assert.rejects(decodePreview(blob,new AbortController().signal,{urls,ImageClass:Stalled,timeoutMs:5}),/timed out/);
+assert.deepEqual(revoked,['blob:1'],'a stalled decode settles and releases the URL');
+class Huge extends ImageStub{width=20000;}
+await assert.rejects(decodePreview(blob,new AbortController().signal,{urls,ImageClass:Huge}),/dimensions/);
+class Borderline extends ImageStub{width=5500;height=6000;}
+await assert.rejects(decodePreview(blob,new AbortController().signal,{urls,ImageClass:Borderline}),/dimensions/);
+const abort=new AbortController(),decode=decodePreview(blob,abort.signal,{urls,ImageClass:Stalled});abort.abort();
+await assert.rejects(decode,{name:'AbortError'});
+assert.equal(revoked.length,4);
+
+// A sibling may finish after the first failure, even if an integration ignores
+// cancellation. Wait for it and release its late URL before returning.
+const later=deferred(),lost=[];let decodes=0;
+const pending=loadPreviewPair(['a','b'],{cached:[null,null],signal:new AbortController().signal,
+ loadPreview:async()=>blob,decode:async()=>{if(++decodes===1)throw Error('corrupt PNG');return later.promise;},revoke:url=>lost.push(url)});
+await new Promise(r=>setTimeout(r,0));later.resolve({url:'late-url'});
+await assert.rejects(pending,/corrupt PNG/);assert.deepEqual(lost,['late-url']);
+
+const bad=new Blob(['bad']),good=new Blob(['good']),cache=[bad,good];let reads=0;
+const options={cached:cache,signal:new AbortController().signal,loadPreview:async()=>{reads++;return good;},
+ decode:async b=>{if(b===bad)throw Error('invalid pixels');return{url:'good-url'};},revoke:()=>{}};
+await assert.rejects(loadPreviewPair(['a','b'],options),/invalid pixels/);
+assert.equal(cache[0],null,'invalid downloaded bytes cannot poison every future retry');
+await loadPreviewPair(['a','b'],options);assert.equal(reads,1,'retry fetches the corrupt half again and keeps the valid half');
+console.log('Preview decoding: pre-cancel, decode timeout, dimension limits, late sibling URL cleanup and corrupt-cache recovery pass');

tests/test_preview_store.py

@@ -7,6 +7,23 @@ def key(descriptor):
 
 
 class PreviewStoreTests(unittest.TestCase):
+    def test_tiny_batches_have_a_metadata_budget_and_empty_batches_are_atomic(self):
+        store = PreviewStore(1024 * 1024, max_batches=2)
+        first = store.put_batch([b"a"], "first")
+        second = store.put_batch([b"b"], "second")
+        store.get(key(first[0]))
+        generation = store.fingerprint()
+        with self.assertRaises(ValueError):
+            store.put_batch([], "empty")
+        with self.assertRaises(ValueError):
+            store.put_batch([b""], "empty")
+        self.assertEqual(store.fingerprint(), generation)
+        store.put_batch([b"c"], "third")
+        self.assertEqual(store.get(key(first[0])), b"a")
+        self.assertIsNone(store.get(key(second[0])))
+        self.assertEqual(len(store.groups), 2)
+        self.assertEqual(store.size, 2)
+
     def test_whole_batch_lru_and_cache_generation(self):
         store = PreviewStore(10)
         first = store.put_batch([b"aaa", b"bbb"], "1")

tests/test_preview_transport.mjs

@@ -0,0 +1,23 @@
+import assert from 'node:assert/strict';
+import {readPreview} from '../web/preview_transport.js';
+const bytes=new TextEncoder().encode('image-bytes');
+const events=[];
+const blob=await readPreview(async()=>new Response(new ReadableStream({start(c){c.enqueue(bytes.slice(0,3));c.enqueue(bytes.slice(3));c.close();}}),{headers:{'content-length':String(bytes.length),'content-type':'image/png'}}),'/preview',{onProgress:e=>events.push(e)});
+assert.equal(await blob.text(),'image-bytes');assert.equal(events[1].loaded,3);assert.equal(events[1].total,bytes.length);assert.equal(events.at(-1).complete,true);
+const unknown=[];await readPreview(async()=>new Response(bytes),'/preview',{onProgress:e=>unknown.push(e)});assert.equal(unknown[0].total,0);assert.equal(unknown.at(-1).loaded,bytes.length);
+await assert.rejects(readPreview(async()=>new Response(bytes,{headers:{'content-length':'99'}}),'/truncated'),/interrupted/);
+await assert.rejects(readPreview(async()=>new Response(bytes,{status:404}),'/expired'),e=>e.status===404);
+await assert.rejects(readPreview(async()=>new Response(bytes),'/too-large',{maxBytes:3}),/size limit/);
+const cancel=new AbortController();
+const stalled=(_,options)=>Promise.resolve(new Response(new ReadableStream({start(c){options.signal.addEventListener('abort',()=>c.error(new DOMException('Aborted','AbortError')));}})));
+await assert.rejects(readPreview(stalled,'/stalled',{idleMs:10}),/timed out/);
+const pending=readPreview(stalled,'/cancel',{signal:cancel.signal});cancel.abort();await assert.rejects(pending,e=>e.name==='AbortError');
+// A long transfer is allowed while actual data continues to arrive.
+let ticks=0;await readPreview(async(_,options)=>new Response(new ReadableStream({start(c){const t=setInterval(()=>{if(++ticks===5){clearInterval(t);c.close();}else c.enqueue(bytes);},5);options.signal.addEventListener('abort',()=>{clearInterval(t);c.error(Error('timed out'));});}})),'/slow',{idleMs:20});assert.equal(ticks,5);
+console.log('Preview transport: streamed byte progress, unknown length, truncation, expiry, size limit, inactivity timeout, cancellation and slow advancing transfer pass');
+let requests=0;
+await assert.rejects(readPreview(async()=>{requests++;return new Response(bytes);},'/never-start',{signal:AbortSignal.abort()}),{name:'AbortError'});
+assert.equal(requests,0);
+let stopped=false;
+await assert.rejects(readPreview(async()=>new Response(new ReadableStream({cancel(){stopped=true;}})),'/uncooperative-wrapper',{idleMs:5}),/timed out/);
+assert.equal(stopped,true,'cancel the response reader even when a custom fetch wrapper ignores its signal');

tests/test_result_recovery.mjs

@@ -0,0 +1,32 @@
+import assert from 'node:assert/strict';
+import {ResultRecovery} from '../web/result_recovery.js';
+const node={id:3,type:'AdachiImageCompare'},graph={getNodeById:id=>String(id)==='3'?node:null};
+let active=graph,calls=0,fail=true,output=[],terminal=[];
+const entry={status:{completed:true,status_str:'success'},outputs:{'3':{adachi_originals:[{filename:'a'}],adachi_results:[{filename:'b'}]}}};
+const r=new ResultRecovery({getGraph:()=>active,interval:60000,fetchApi:async path=>{calls++;assert.equal(path,'/history/task');if(fail)throw Error('offline');return {ok:true,json:async()=>({task:entry})};},onOutput:(n,o,id)=>output.push({n,o,id}),onTerminal:(...x)=>terminal.push(x)});
+try {
+ r.track(graph,'task','3');await r.recover();assert.equal(output.length,0);assert.equal(r.pending.size,1,'network failure retains the task even without any WebSocket events');
+ fail=false;await r.recover();assert.equal(output.length,1);assert.equal(output[0].n,node);assert.equal(r.pending.size,0);
+ r.track(graph,'task','3');await r.recover();assert.equal(output.length,1,'success cannot replay after adoption');
+ r.delivered.clear();r.track(graph,'task','3');active={getNodeById:()=>node};await r.recover();assert.equal(output.length,1,'another graph must not receive a result with the same node ID');
+ active=graph;r.track(graph,'task','3');graph.getNodeById=()=>({...node});await r.recover();assert.equal(output.length,1,'reconfigured nodes are not the queued node');graph.getNodeById=id=>String(id)==='3'?node:null;
+ r.track(graph,'task','3');entry.outputs={};entry.status.status_str='error';await r.recover();assert.equal(terminal.length,1);assert.equal(r.pending.size,0);
+ assert.ok(calls>=3);
+} finally {r.destroy();}
+console.log('Result recovery: lost notifications, offline retries, duplicate delivery, workflow/node replacement and terminal errors pass');
+
+const nested={id:8,type:'AdachiImageCompare'},child={getNodeById:id=>String(id)==='8'?nested:null},container={id:5,subgraph:child},root={getNodeById:id=>String(id)==='5'?container:null};
+let nestedResult;
+const sub=new ResultRecovery({getGraph:()=>root,fetchApi:async()=>({ok:true,json:async()=>({nestedTask:{status:{completed:true,status_str:'success'},outputs:{'5:8':{adachi_originals:[{}],adachi_results:[{}]}}}})}),onOutput:n=>{nestedResult=n;}});
+try{sub.track(root,'nestedTask','5:8');await sub.recover();assert.equal(nestedResult,nested);}finally{sub.destroy();}
+console.log('Result recovery: native subgraph execution IDs resolve to the queued live comparison');
+{
+ let resolve,signal,discarded=0,delivered=0;
+ const pending=new ResultRecovery({getGraph:()=>graph,onOutput:()=>delivered++,onDiscard:()=>discarded++,
+  fetchApi:async(_path,options)=>{signal=options.signal;return new Promise(r=>resolve=r);}});
+ pending.track(graph,'late','3');const task=pending.recover();pending.destroy();
+ assert.equal(signal.aborted,true);assert.equal(discarded,1);
+ resolve({ok:true,json:async()=>({late:{status:{completed:true},outputs:{'3':{adachi_originals:[{}],adachi_results:[{}]}}}})});
+ await task;assert.equal(delivered,0,'destroyed recovery cannot deliver a late response');
+ pending.track(graph,'new','3');assert.equal(pending.pending.size,0);assert.equal(pending.controllers.size,0);
+}

tests/test_upload_transport.mjs

@@ -42,3 +42,27 @@ assert.equal(phases.at(-1).phase, "processing");
 status = 500;
 await assert.rejects(uploadImageWithProgress(api, body), /500/);
 console.log("Upload transport: real byte progress, proxy URL, multi-user header, auth fallback and server error passed");
+let aborted=0;
+globalThis.XMLHttpRequest=class {
+ constructor(){this.upload={};}open(){}setRequestHeader(){}send(){}abort(){aborted++;this.onabort?.();}
+};
+await assert.rejects(uploadImageWithProgress(api,body,null,{idleMs:5}),/timed out/);
+assert.equal(aborted,1);
+const cancel=new AbortController(),pending=uploadImageWithProgress(api,body,null,{signal:cancel.signal});cancel.abort();
+await assert.rejects(pending,{name:'AbortError'});assert.equal(aborted,2);
+// Overall duration may exceed the inactivity limit as long as real bytes move.
+globalThis.XMLHttpRequest=class {
+ constructor(){this.upload={};}open(){}setRequestHeader(){}
+ send(){let n=0;this.timer=setInterval(()=>{this.upload.onprogress?.({loaded:++n,total:6,lengthComputable:true});if(n===6){clearInterval(this.timer);this.status=200;this.responseText='{"name":"slow.png"}';this.onload();}},3);}
+ abort(){clearInterval(this.timer);this.onabort?.();}
+};
+assert.equal((await uploadImageWithProgress(api,body,null,{idleMs:12})).name,'slow.png');
+console.log('Upload transport: inactivity timeout, cancellation and slow advancing uploads pass');
+globalThis.XMLHttpRequest=class {
+ constructor(){this.upload={};}open(){}setRequestHeader(){}
+ send(){this.status=403;this.onload();}abort(){this.onabort?.();}
+};
+let fallbackSignal;
+const stalledAuth={...api,fetchApi:async(_path,options)=>{fallbackSignal=options.signal;return new Promise((_,reject)=>options.signal.addEventListener('abort',()=>reject(new DOMException('Aborted','AbortError')),{once:true}));}};
+await assert.rejects(uploadImageWithProgress(stalledAuth,body,null,{idleMs:5}),/timed out/);
+assert.equal(fallbackSignal.aborted,true,'the authenticated fallback also has a cancellation deadline');

tests/test_workbench_analysis.mjs

@@ -0,0 +1,17 @@
+import assert from 'node:assert/strict';
+import {inspectWorkbench,selectWorkbenchPipeline} from '../web/workbench_analysis.js';
+const graph={_nodes:[{type:'AdachiInlineMask'},{type:'AdachiWebUIInpaint'},
+ {type:'AdachiImageCompare'},{type:'AdachiGroupPresets'},
+ {type:'CheckpointLoaderSimple'},{type:'Power Lora Loader (rgthree)'}]};
+const result=inspectWorkbench(graph);
+assert.deepEqual(result.missing,[]);
+assert.equal(result.checkpoints.length,1);
+assert.equal(result.loras.length,1);
+assert.deepEqual(inspectWorkbench(null).missing,['inline_mask','inpaint','compare']);
+console.log('Workbench discovery checks passed');
+
+const first={id:10,type:'AdachiInlineMask',mode:0,inputs:[]},second={id:20,type:'AdachiInlineMask',mode:0,inputs:[]},a={id:30,type:'AdachiWebUIInpaint',mode:0,inputs:[{name:'image',link:1}]},b={id:40,type:'AdachiWebUIInpaint',mode:0,inputs:[{name:'image',link:2}]},outA={id:50,type:'AdachiImageCompare',mode:0,inputs:[{name:'result',link:3}]},outB={id:60,type:'AdachiImageCompare',mode:0,inputs:[{name:'result',link:4}]};
+const multi={_nodes:[first,second,a,b,outA,outB],links:{1:{origin_id:10},2:{origin_id:20},3:{origin_id:30},4:{origin_id:40}},getNodeById(id){return this._nodes.find(n=>n.id==id);}};multi._nodes.forEach(n=>n.graph=multi);
+const chosen=selectWorkbenchPipeline(multi,b);assert.equal(chosen.editor,second);assert.equal(chosen.compare,outB);assert.equal(chosen.ambiguous,false);
+b.inputs=[];outB.inputs=[];assert.equal(selectWorkbenchPipeline(multi,b).ambiguous,true,'unconnected ambiguous canvases need an explicit choice');
+console.log('Workbench selection: multiple independent pipelines follow actual connections; ambiguity is explicit');

tests/test_workspace_activation.mjs

@@ -0,0 +1,13 @@
+import assert from 'node:assert/strict';
+import {workspaceRoutingNodes} from '../web/workspace_activation.js';
+const model={id:11,type:'CLIPTextEncode',mode:4,inputs:[]},setter={id:12,type:'SetNode',mode:4,inputs:[{link:1}]},getter={id:13,type:'GetNode',mode:4,inputs:[],findSetter:()=>setter},gate={id:14,type:'AdachiExclusiveSwitch',mode:4,inputs:[{link:2}]},root={id:15,type:'AdachiWebUIInpaint',mode:4,inputs:[{link:3}]};
+const nodes=[model,setter,getter,gate,root],graph={_nodes:nodes,links:{1:{origin_id:11},2:{origin_id:13},3:{origin_id:14}},getNodeById:id=>nodes.find(n=>n.id==id)};nodes.forEach(n=>n.graph=graph);
+graph._groups=[{size:[500,500],_nodes:[getter,gate,root]}];
+assert.deepEqual([...workspaceRoutingNodes([root])].map(n=>n.id).sort(),[13,14]);
+assert.equal(setter.mode,4);assert.equal(model.mode,4,'model processing is never activated by routing discovery');
+root.mode=0;assert.equal(workspaceRoutingNodes([root]).size,0,'manually ignored routes of an enabled workbench stay ignored');
+root.mode=4;gate.mode=0;assert.equal(workspaceRoutingNodes([root]).size,0,'a mixed group is not guessed to be entirely bypassed');
+const controller={active:{id:'preset'},planStates:()=>({plan:new Map([[root,4],[getter,4],[gate,4]])})};
+assert.deepEqual([...workspaceRoutingNodes([root],controller)].map(n=>n.id),[13],'an explicit bypass preset allows only its necessary routing');
+controller.planStates=()=>({plan:new Map([[root,0]])});assert.equal(workspaceRoutingNodes([root],controller).size,0,'an individually ignored sampler cannot revive other intentionally disabled nodes');
+console.log('Workspace activation: bypassed group routing only, preserved external setters and processors, explicit preset state and mixed-group safety pass');

tests/test_workspace_bindings.mjs

@@ -0,0 +1,37 @@
+import assert from 'node:assert/strict';
+import {WorkspaceBindings} from '../web/workspace_bindings.js';
+const nodes=[];
+const add=(id,type,values={},inputs=[],outputs=[])=>{const n={id,type,mode:0,properties:{},widgets:Object.entries(values).map(([name,value])=>({name,value})),inputs,outputs:outputs.map(type=>({type,name:type}))};nodes.push(n);return n;};
+const unrelated=add('old-unrelated','CheckpointLoaderSimple',{ckpt_name:'do-not-pick.safetensors'});
+const a=add('base-a','CheckpointLoaderSimple',{ckpt_name:'custom-A.safetensors'});
+const b=add('base-b','UNETLoader',{unet_name:'anything-B.safetensors'});
+const clip=add('separate-encoder','CLIPLoader',{clip_name:'language.safetensors'});
+const vae=add('separate-vae','VAELoader',{vae_name:'image.safetensors'});
+const posA=add('encode-a','CLIPTextEncode',{text:'original A'},[{name:'clip',type:'CLIP'}],['CONDITIONING']);
+const negA=add('negative-a','CLIPTextEncode',{text:'negative A'},[{name:'clip',type:'CLIP'}],['CONDITIONING']);
+const posB=add('encode-b','CLIPTextEncode',{text:'original B'},[{name:'clip',type:'CLIP'}],['CONDITIONING']);
+const negB=add('negative-b','CLIPTextEncode',{text:'negative B'},[{name:'clip',type:'CLIP'}],['CONDITIONING']);
+add('model-patch','ModelSamplingSD3',{},[{name:'model',type:'MODEL'}],['MODEL']);
+const sampler=add('workbench','AdachiWebUIInpaint',{refiner_switch:.8},[{name:'model',type:'MODEL'},{name:'positive',type:'CONDITIONING'},{name:'negative',type:'CONDITIONING'},{name:'vae',type:'VAE'}]);
+const controller=add('preset-owner','AdachiGroupPresets');const applied=[];
+controller.adachiGroupPresets={model:{node:controller,data:{activeId:'one',presets:[{id:'one',name:'Portrait'},{id:'two',name:'Studio'}]},apply(id){this.data.activeId=id;applied.push(id);}}};
+const graph={_nodes:nodes,getNodeById:id=>nodes.find(n=>String(n.id)===String(id)),links:{}};
+const p=(kind)=>{
+ const root=kind==='one'?'base-a':'base-b',positive=kind==='one'?'encode-a':'encode-b',negative=kind==='one'?'negative-a':'negative-b';
+ return {[root]:{class_type:graph.getNodeById(root).type,inputs:{}},'separate-encoder':{class_type:'CLIPLoader',inputs:{}},'separate-vae':{class_type:'VAELoader',inputs:{}},
+  'model-patch':{class_type:'ModelSamplingSD3',inputs:{model:[root,0]}},
+  [positive]:{class_type:'CLIPTextEncode',inputs:{clip:kind==='one'?[root,1]:['separate-encoder',0],text:'base text'}},
+  [negative]:{class_type:'CLIPTextEncode',inputs:{clip:kind==='one'?[root,1]:['separate-encoder',0],text:'negative text'}},
+  workbench:{class_type:'AdachiWebUIInpaint',inputs:{model:['model-patch',0],positive:[positive,0],negative:[negative,0],vae:kind==='one'?[root,2]:['separate-vae',0]}}};
+};
+const x=new WorkspaceBindings({graph,sampler});assert.equal(x.profileId,'one');assert.equal(x.model,null,'discovery cannot guess from filenames or active loader order');
+x.updateExecutionGraph(p('one'),'workbench');assert.equal(x.model,a);assert.notEqual(x.model,unrelated);assert.equal(x.positive,posA);assert.equal(x.getExecutionBinding().loraMode,'inherit');
+assert.deepEqual(x.getExecutionBinding().samplerInputs,{},'final model-processing references are preserved');
+x.settings.positive='custom A';assert.deepEqual(x.getExecutionBinding().inputOverrides['encode-a'],{text:'custom A'});
+x.settings.loraMode='override';x.settings.loras=[{name:'style.safetensors',strength:.7}];assert.equal(x.getExecutionBinding().loras[0].name,'style.safetensors');
+x.selectProfile('two');x.updateExecutionGraph(p('two'),'workbench');assert.equal(x.model,b);assert.equal(x.clip,clip);assert.equal(x.vae,vae);assert.equal(x.positive,posB);assert.equal(x.getExecutionBinding().loraMode,'inherit');assert.equal(x.getExecutionBinding().inputOverrides['encode-b'],undefined);
+x.selectProfile('one');x.updateExecutionGraph(p('one'),'workbench');assert.equal(x.settings.positive,'custom A');assert.deepEqual(applied,['two','one']);
+controller.mode=4;const ignored=new WorkspaceBindings({graph,sampler});assert.equal(ignored.controller,undefined);assert.deepEqual(ignored.profiles.map(p=>p.id),['current']);
+controller.mode=0;controller.adachiGroupPresets.model.data.presets.push({id:'new',name:'Any other title'});ignored.refreshProfiles();assert.equal(ignored.profiles.length,3);
+controller.adachiGroupPresets.model.data.activeId='two';ignored.refreshProfiles();assert.equal(ignored.profileId,'two');
+console.log('Workspace bindings: arbitrary IDs and titles, actual loader/CLIP/VAE routes, preserved model patches, inherited/custom LoRAs, per-profile edits and dynamic controllers pass');

tests/test_workspace_execution.py

@@ -0,0 +1,84 @@
+"""Workspace validation must not execute, save or modify the submitted graph."""
+import importlib.util
+from pathlib import Path
+import types
+import unittest
+
+SPEC = importlib.util.spec_from_file_location("adachi_workspace_execution", Path(__file__).resolve().parents[1] / "workspace_execution.py")
+workspace = importlib.util.module_from_spec(SPEC)
+SPEC.loader.exec_module(workspace)
+
+
+class WorkspaceTests(unittest.IsolatedAsyncioTestCase):
+    def prompt(self):
+        return {
+            "1": {"class_type": "ImageSource", "inputs": {}},
+            "2": {"class_type": "ImageInvert", "inputs": {"image": ["1", 0]}},
+            "3": {"class_type": "AdachiImageCompare", "inputs": {"original": ["1", 0], "result": ["2", 0]}},
+            "4": {"class_type": "SaveImage", "inputs": {"images": ["2", 0]}},
+            "5": {"class_type": "NotInstalled", "inputs": {}},
+        }
+
+    async def test_only_comparison_branch_is_validated(self):
+        original = self.prompt()
+        calls = []
+
+        async def validate(prompt_id, prompt, targets):
+            calls.append((prompt_id, prompt, targets))
+            return True, None, ["3"], {}
+
+        server = types.SimpleNamespace(trigger_on_prompt=lambda data: data)
+        data, _, valid = await workspace.prepare_workspace(server, types.SimpleNamespace(validate_prompt=validate), {"prompt": original, "compare_id": "3"})
+        self.assertTrue(valid[0])
+        self.assertEqual(set(data["prompt"]), {"1", "2", "3"})
+        self.assertEqual(calls[0][2], ["3"])
+        self.assertEqual(set(original), {"1", "2", "3", "4", "5"})
+
+    async def test_hooks_restore_links_before_pruning(self):
+        original = self.prompt()
+        original["2"]["inputs"].clear()
+
+        def hook(data):
+            data["prompt"]["2"]["inputs"]["image"] = ["1", 0]
+            return data
+
+        def validate(prompt):
+            self.assertIn("1", prompt)
+            return True, None, ["3"], {}
+
+        server = types.SimpleNamespace(trigger_on_prompt=hook)
+        await workspace.prepare_workspace(server, types.SimpleNamespace(validate_prompt=validate), {"prompt": original, "compare_id": "3"})
+        self.assertEqual(original["2"]["inputs"], {})
+
+    def test_missing_dependency_and_non_comparison_output_rejected(self):
+        with self.assertRaises(ValueError):
+            workspace.dependency_prompt(self.prompt(), "4")
+        prompt = self.prompt()
+        del prompt["2"]
+        with self.assertRaisesRegex(ValueError, "missing node"):
+            workspace.dependency_prompt(prompt, "3")
+
+    def test_malformed_node_inputs_are_a_validation_error(self):
+        for value in ([], None, "invalid", 42):
+            prompt = self.prompt()
+            prompt["2"]["inputs"] = value
+            with self.assertRaisesRegex(ValueError, "Invalid input mapping"):
+                workspace.dependency_prompt(prompt, "3")
+
+    async def test_bad_inputs_never_reach_core_replacement_hooks(self):
+        def unexpected(_prompt):
+            self.fail("Malformed inputs reached a core hook")
+        server = types.SimpleNamespace(trigger_on_prompt=lambda data: data,
+            node_replace_manager=types.SimpleNamespace(apply_replacements=unexpected))
+        prompt = self.prompt()
+        prompt["2"]["inputs"] = None
+        with self.assertRaisesRegex(ValueError, "Invalid input mapping"):
+            await workspace.prepare_workspace(server, types.SimpleNamespace(), {"prompt":prompt, "compare_id":"3"})
+
+    async def test_validation_error_is_returned_without_queueing(self):
+        def validate(prompt):
+            return False, {"message": "missing checkpoint"}, [], {"1": {"errors": []}}
+        server = types.SimpleNamespace(trigger_on_prompt=lambda data: data)
+        _, _, valid = await workspace.prepare_workspace(server, types.SimpleNamespace(validate_prompt=validate), {"prompt": self.prompt(), "compare_id": "3"})
+        self.assertFalse(valid[0])
+        self.assertEqual(valid[1]["message"], "missing checkpoint")

tests/test_workspace_flow.mjs

@@ -0,0 +1,206 @@
+import assert from 'node:assert/strict';
+import {inspectExecutionFlow, applyExecutionBinding} from '../web/workspace_flow.js';
+
+// Execution IDs, filenames and titles deliberately have no relationship to the
+// author's personal workflow. Colon IDs represent nodes inside a subgraph.
+function fixture(prefix='graph-a') {
+    const ids=Object.fromEntries(['checkpoint','clip','vae','modelLora','negativeLora','modelPatch','clipPatch','positive','positive2','negative','combine','control','controlLoader','image','unusedCheckpoint','unusedEncoder','unusedLora','gate','sampler','compare'].map((k,i)=>[k,`${prefix}-${113+i*17}`]));
+    ids.positive2=`${prefix}-instance:937`;
+    const prompt={},live=new Map();
+    function add(key,type,inputs,outputs=[],fields=[]) {
+        const id=ids[key];prompt[id]={class_type:type,inputs};
+        live.set(id,{id:id.includes(':')?id.split(':').at(-1):id,type,mode:0,
+            outputs:outputs.map((o,i)=>typeof o==='string'?{name:o,type:o}:{...o,slot_index:i}),
+            inputs:Object.entries(inputs).map(([name,value])=>({name,type:Array.isArray(value)?'CONDITIONING':'STRING'})),
+            widgets:fields.map(name=>({name,value:inputs[name]}))});
+    }
+    add('checkpoint','CheckpointLoaderSimple',{ckpt_name:'arbitrary-custom-model.safetensors'},['MODEL','CLIP','VAE']);
+    add('clip','CLIPLoader',{clip_name:'independent-language-encoder.safetensors'},['CLIP']);
+    add('vae','VAELoader',{vae_name:'independent-image-vae.safetensors'},['VAE']);
+    add('modelLora','Power Lora Loader (rgthree)',{model:[ids.checkpoint,0],clip:[ids.checkpoint,1],
+        lora_1:{on:true,lora:'original-model-style.safetensors',strength:.8,strengthTwo:.4},
+        lora_9:{on:false,lora:'original-disabled.safetensors',strength:1}},['MODEL','CLIP']);
+    add('negativeLora','LoraLoader',{model:[ids.checkpoint,0],clip:[ids.clip,0],lora_name:'original-negative-style.safetensors',strength_model:.6,strength_clip:.3},['MODEL','CLIP']);
+    add('modelPatch','ModelSamplingSD3',{model:[ids.modelLora,0],shift:2.7},['MODEL']);
+    add('clipPatch','CLIPSetLastLayer',{clip:[ids.modelLora,1],stop_at_clip_layer:-2},['CLIP']);
+    add('positive','CLIPTextEncode',{clip:[ids.clipPatch,0],text:'a quiet city'},['CONDITIONING'],['text']);
+    add('positive2','CLIPTextEncodeSDXL',{clip:[ids.clipPatch,0],text_g:'city details',text_l:'architecture',width:1024,height:1024},['CONDITIONING'],['text_g','text_l']);
+    add('negative','CLIPTextEncode',{clip:[ids.negativeLora,1],text:'blurry'},['CONDITIONING'],['text']);
+    add('combine','ConditioningCombine',{conditioning_1:[ids.positive,0],conditioning_2:[ids.positive2,0]},['CONDITIONING']);
+    add('controlLoader','ControlNetLoader',{control_net_name:'edge-control.safetensors'},['CONTROL_NET']);
+    add('image','LoadImage',{image:'fixture.png'},['IMAGE','MASK']);
+    add('control','ControlNetApplyAdvanced',{positive:[ids.combine,0],negative:[ids.negative,0],control_net:[ids.controlLoader,0],image:[ids.image,0],strength:.7},
+        [{name:'positive',type:'CONDITIONING'},{name:'negative',type:'CONDITIONING'}]);
+    add('unusedCheckpoint','CheckpointLoaderSimple',{ckpt_name:'a-different-family.safetensors'},['MODEL','CLIP','VAE']);
+    add('unusedEncoder','CLIPTextEncode',{clip:[ids.unusedCheckpoint,1],text:'unused prompt'},['CONDITIONING'],['text']);
+    add('unusedLora','LoraLoader',{model:[ids.unusedCheckpoint,0],clip:[ids.unusedCheckpoint,1],lora_name:'unrelated.safetensors',strength_model:1,strength_clip:1},['MODEL','CLIP']);
+    add('gate','AdachiExclusiveSwitch',{active_inputs:1,input_a:[ids.control,0],input_b:[ids.unusedEncoder,0]},['CONDITIONING']);
+    add('sampler','AdachiWebUIInpaint',{model:[ids.modelPatch,0],positive:[ids.gate,0],negative:[ids.control,1],vae:[ids.vae,0],image:[ids.image,0],mask:[ids.image,1],steps:23,cfg:5.5},['IMAGE','IMAGE','MASK']);
+    add('compare','AdachiImageCompare',{original:[ids.image,0],result:[ids.sampler,0]},['IMAGE']);
+    for(const [id,node] of live)node.inputs=Object.entries(prompt[id].inputs).map(([name,value])=>({name,
+        type:Array.isArray(value)?live.get(value[0])?.outputs?.[value[1]]?.type||'*':typeof value==='number'?'FLOAT':'STRING'}));
+    return {ids,prompt,lookup:id=>live.get(String(id))||null,live};
+}
+const sorted=values=>[...values].sort();
+const entryIds=entries=>sorted(entries.map(e=>String(e.id)));
+const effective=(prompt,ref)=>{
+    const seen=new Set();
+    while(ref && prompt[ref[0]]?.class_type==='AdachiExclusiveSwitch' && !seen.has(ref[0])) {
+        seen.add(ref[0]);const n=prompt[ref[0]],flag=n.inputs.active_inputs;
+        if(flag!==1 && flag!==2)break;
+        ref=n.inputs[flag===1?'input_a':'input_b'];
+    }
+    return ref;
+};
+function loraChain(prompt,initial,field) {
+    const rows=[],seen=new Set();let ref=initial;
+    while(ref && prompt[ref[0]]?.class_type==='LoraLoader') {
+        assert.ok(!seen.has(ref[0]),'temporary LoRA chain cannot contain a cycle');seen.add(ref[0]);
+        assert.equal(ref[1],field==='model'?0:1,'model and CLIP must use the correct LoRA output slot');
+        const n=prompt[ref[0]];rows.unshift(n.inputs);ref=n.inputs[field];
+    }
+    return {rows,base:ref};
+}
+const inherit={loraMode:'inherit',loras:[]};
+
+// Inspection preserves the actual producer and discovers editable components
+// behind model/CLIP processing; it does not guess from a preset/model name.
+for(const prefix of ['renumbered-12001','completely-different-workflow']) {
+    const {ids,prompt,lookup}=fixture(prefix),before=structuredClone(prompt);
+    const flow=inspectExecutionFlow(prompt,ids.sampler,lookup);
+    assert.deepEqual(flow.refs.model,[ids.modelPatch,0]);
+    assert.deepEqual(effective(prompt,flow.refs.positive),[ids.control,0]);
+    assert.deepEqual(flow.refs.negative,[ids.control,1]);
+    assert.deepEqual(flow.refs.vae,[ids.vae,0]);
+    assert.deepEqual(entryIds(flow.modelNodes),[ids.checkpoint]);
+    assert.deepEqual(entryIds(flow.clipNodes),sorted([ids.checkpoint,ids.clip]));
+    assert.deepEqual(entryIds(flow.vaeNodes),[ids.vae]);
+    assert.deepEqual(entryIds(flow.loras),sorted([ids.modelLora,ids.negativeLora]));
+    assert.deepEqual(entryIds(flow.encoders.positive),sorted([ids.positive,ids.positive2]));
+    assert.deepEqual(entryIds(flow.encoders.negative),[ids.negative]);
+    const second=flow.encoders.positive.find(e=>e.id===ids.positive2);
+    assert.equal(second.node,lookup(ids.positive2),'execution IDs map back to the actual live subgraph node');
+    assert.deepEqual(sorted(second.fields),['text_g','text_l']);
+    assert.equal(flow.modelNodes[0].api,prompt[ids.checkpoint]);
+    assert.deepEqual(prompt,before,'inspection is read-only');
+}
+
+// A checkpoint's unused CLIP/VAE outputs must not displace separately wired
+// components merely because that checkpoint supplies the MODEL input.
+{
+    const {ids,prompt,lookup}=fixture();
+    prompt[ids.modelLora].inputs.clip=[ids.clip,0];
+    const flow=inspectExecutionFlow(prompt,ids.sampler,lookup);
+    assert.deepEqual(entryIds(flow.clipNodes),[ids.clip]);
+    assert.deepEqual(entryIds(flow.vaeNodes),[ids.vae]);
+}
+
+// Inherited LoRA rows and processing nodes survive switch simplification.
+{
+    const {ids,prompt}=fixture(),before=structuredClone(prompt);
+    const result=applyExecutionBinding(prompt,ids.sampler,inherit);
+    assert.notEqual(result,prompt);assert.notEqual(result[ids.sampler].inputs,prompt[ids.sampler].inputs);
+    assert.deepEqual(result[ids.sampler].inputs.positive,[ids.control,0]);
+    assert.deepEqual(result[ids.sampler].inputs.model,[ids.modelPatch,0]);
+    for(const key of ['modelLora','negativeLora','modelPatch','clipPatch','control','combine','unusedCheckpoint','unusedEncoder','unusedLora'])assert.deepEqual(result[ids[key]],before[ids[key]],key+' must keep its original fields');
+    assert.deepEqual(prompt,before);
+}
+
+// Explicitly disabling LoRAs bypasses both output types inside this sampler's
+// dependency chain while retaining model-sampling and conditioning processors.
+{
+    const {ids,prompt}=fixture(),before=structuredClone(prompt);
+    const result=applyExecutionBinding(prompt,ids.sampler,{loraMode:'override',loras:[]});
+    assert.deepEqual(result[ids.sampler].inputs.model,[ids.modelPatch,0]);
+    assert.deepEqual(result[ids.modelPatch].inputs.model,[ids.checkpoint,0]);
+    assert.deepEqual(result[ids.clipPatch].inputs.clip,[ids.checkpoint,1]);
+    assert.deepEqual(result[ids.negative].inputs.clip,[ids.clip,0]);
+    assert.deepEqual(result[ids.positive].inputs.clip,[ids.clipPatch,0]);
+    assert.deepEqual(result[ids.sampler].inputs.positive,[ids.control,0]);
+    assert.deepEqual(result[ids.sampler].inputs.negative,[ids.control,1]);
+    assert.deepEqual(result[ids.control],before[ids.control]);
+    assert.deepEqual(result[ids.unusedLora],before[ids.unusedLora]);
+    assert.deepEqual(prompt,before,'LoRA overrides only affect the returned execution copy');
+}
+
+// Added LoRAs affect MODEL and each explicitly selected CLIP boundary. Distinct
+// positive/negative CLIP sources stay distinct and downstream conditions stay put.
+{
+    const {ids,prompt}=fixture(),before=structuredClone(prompt);
+    const chosen=[{name:'custom-one.safetensors',strength:.7,clipStrength:0,on:true},
+        {name:'custom-two.safetensors',strength:1.1,clipStrength:.25,on:true},
+        {name:'disabled-row.safetensors',strength:9,on:false}];
+    const result=applyExecutionBinding(prompt,ids.sampler,{loraMode:'override',loras:chosen,
+        clipConsumers:[{id:ids.clipPatch,input:'clip'},{id:ids.negative,input:'clip'}]});
+    const model=loraChain(result,result[ids.sampler].inputs.model,'model');
+    assert.deepEqual(model.base,[ids.modelPatch,0]);
+    assert.deepEqual(model.rows.map(r=>r.lora_name),chosen.slice(0,2).map(r=>r.name));
+    assert.deepEqual(model.rows.map(r=>r.strength_model),[.7,1.1]);
+    const positive=loraChain(result,result[ids.clipPatch].inputs.clip,'clip');
+    const negative=loraChain(result,result[ids.negative].inputs.clip,'clip');
+    for(const chain of [positive,negative]) {
+        assert.deepEqual(chain.rows.map(r=>r.lora_name),chosen.slice(0,2).map(r=>r.name));
+        assert.deepEqual(chain.rows.map(r=>r.strength_clip),[0,.25],'zero CLIP strength must not fall back to model strength');
+    }
+    assert.deepEqual(positive.base,[ids.checkpoint,1]);assert.deepEqual(negative.base,[ids.clip,0]);
+    assert.deepEqual(result[ids.positive].inputs.clip,[ids.clipPatch,0]);
+    assert.deepEqual(result[ids.sampler].inputs.positive,[ids.control,0]);assert.deepEqual(result[ids.sampler].inputs.negative,[ids.control,1]);
+    assert.deepEqual(result[ids.control],before[ids.control]);assert.deepEqual(result[ids.unusedLora],before[ids.unusedLora]);
+    assert.ok(Object.keys(result).some(id=>!Object.hasOwn(prompt,id)),'custom LoRAs are execution-only nodes');
+    assert.deepEqual(prompt,before);
+}
+
+// Primitive edits can target an encoder inside a subgraph without replacing
+// its CLIP or the downstream ControlNet/conditioning route.
+{
+    const {ids,prompt}=fixture(),before=structuredClone(prompt);
+    prompt[ids.sampler].inputs.positive=[ids.control,0];
+    prompt[ids.sampler].inputs.refiner_model=[ids.checkpoint,0];
+    const result=applyExecutionBinding(prompt,ids.sampler,{...inherit,
+        inputOverrides:{[ids.positive2]:{text_g:'edited global prompt'}},
+        removeInputs:{[ids.sampler]:['refiner_model']}});
+    assert.equal(result[ids.positive2].inputs.text_g,'edited global prompt');
+    assert.equal(result[ids.positive2].inputs.text_l,before[ids.positive2].inputs.text_l);
+    assert.deepEqual(result[ids.positive2].inputs.clip,before[ids.positive2].inputs.clip);
+    assert.deepEqual(result[ids.control],before[ids.control]);
+    assert.deepEqual(result[ids.gate],before[ids.gate],'unreachable routers must remain untouched');
+    assert.equal(Object.hasOwn(result[ids.sampler].inputs,'refiner_model'),false);
+    assert.equal(prompt[ids.positive2].inputs.text_g,before[ids.positive2].inputs.text_g);
+    assert.ok(Object.hasOwn(prompt[ids.sampler].inputs,'refiner_model'));
+}
+
+// Selecting B is deterministic; unresolved/invalid selectors may be rejected
+// explicitly or left intact for validation, but must never silently select A.
+{
+    const {ids,prompt,lookup}=fixture();prompt[ids.gate].inputs.active_inputs=2;
+    const flow=inspectExecutionFlow(prompt,ids.sampler,lookup);
+    assert.deepEqual(entryIds(flow.encoders.positive),[ids.unusedEncoder]);
+    assert.deepEqual(applyExecutionBinding(prompt,ids.sampler,inherit)[ids.sampler].inputs.positive,[ids.unusedEncoder,0]);
+    for(const flags of [0,3,-1]) {
+        prompt[ids.gate].inputs.active_inputs=flags;
+        try {
+            const result=applyExecutionBinding(prompt,ids.sampler,inherit);
+            assert.deepEqual(result[ids.sampler].inputs.positive,[ids.gate,0]);
+            assert.deepEqual(result[ids.gate].inputs,prompt[ids.gate].inputs);
+        } catch(error) {
+            assert.notEqual(error.name,'TypeError');
+            assert.match(error.message,/唯一|歧义|互斥|启用|exclusive|ambiguous|enabled|branch|input/i);
+        }
+    }
+}
+
+console.log('Workspace execution flow: dynamic IDs, processing chains, split CLIP sources, multi-encoder conditioning, inherited/overridden LoRAs, switch safety and immutable unrelated branches pass');
+
+// Real Vue-backed widget rows are proxies; ComfyUI transmits their JSON data.
+{
+ const {ids,prompt}=fixture();prompt[ids.modelLora].inputs.lora_1=new Proxy({on:true,lora:'vue-row.safetensors',strength:.4},{});
+ const copy=applyExecutionBinding(prompt,ids.sampler,inherit);assert.equal(copy[ids.modelLora].inputs.lora_1.lora,'vue-row.safetensors');
+}
+
+{
+ const {ids,prompt,lookup}=fixture();prompt[ids.gate]={class_type:'ComfySwitchNode',inputs:{switch:false,on_true:[ids.control,0],on_false:[ids.unusedEncoder,0]}};
+ assert.deepEqual(entryIds(inspectExecutionFlow(prompt,ids.sampler,lookup).encoders.positive),[ids.unusedEncoder]);
+ assert.deepEqual(applyExecutionBinding(prompt,ids.sampler,inherit)[ids.sampler].inputs.positive,[ids.gate,0],'native switch execution is preserved');
+ prompt[ids.gate]={class_type:'ComfySoftSwitchNode',inputs:{switch:true,on_false:[ids.unusedEncoder,0]}};
+ assert.deepEqual(entryIds(inspectExecutionFlow(prompt,ids.sampler,lookup).encoders.positive),[ids.unusedEncoder]);
+}

tests/test_workspace_history.mjs

@@ -0,0 +1,82 @@
+import assert from "node:assert/strict";
+import {WorkspaceHistory,captureSourceState,restoreSourceState} from "../web/workspace_history.js";
+
+class Raster {
+    constructor(pixels) { this.pixels = pixels; this.width = 4; this.height = 3; }
+    toDataURL() { return JSON.stringify({pixels:this.pixels}); }
+}
+const decode = async data => new Raster(JSON.parse(data).pixels);
+const source = name => ({src:name, width:4,height:3});
+const context = prefix => ({mask:new Raster(prefix+"-mask"), baseMask:new Raster(prefix+"-base"),history:[{type:"brush",points:[{x:1,y:2}]}],future:[{type:"erase",points:[{x:2,y:1}]}],lastMask:prefix+"-serialized",dirty:false});
+const widgetNames=["image","mask_data","source_data","edit_mode","crop_state","blend_data","layer_image","paint_data"];
+function node() {
+    const n={properties:{},widgets:widgetNames.map(name=>({name,value:name})),graph:{setDirtyCanvas(){}}};
+    const e=n.adachiEditor={...context("repaint"),image:source("original"),ready:true,loadVersion:1,maskRevision:0,pan:{x:1,y:2},zoom:2,keepFit:true,view:"overlay",filename:{textContent:"original.png"},sizeLabel:{},embed:{checked:false},flush(){},schedule(){},updateButtons(){}};
+    n.adachiCrop={contexts:{blend:context("blend")},target:"mask",layer:source("layer"),cropWidth:512,cropHeight:768,revision:0,acceptVersion:0,sync(){},syncPreset(){},stopOriginalPreview(){}};
+    return n;
+}
+
+{
+ const n=node(),e=n.adachiEditor,c=n.adachiCrop;
+ n.adachiColorPaint={async prepareRestore(data){return data;},commitRestore(data){this.restored=data;}};
+ n.widgets.find(w=>w.name==="edit_mode").value="crop";
+ n.widgets.find(w=>w.name==="crop_state").value=JSON.stringify({locked:true,x:1,y:2,width:512,height:768,job:"job-a"});
+ const before=captureSourceState(n);
+ e.mask.pixels="edited";e.history[0].points[0].x=99;e.image=source("adopted");c.layer=source("new-layer");c.target="blend";
+ n.widgets.find(w=>w.name==="crop_state").value="{}";
+ await restoreSourceState(n,before,{decode});
+ assert.equal(e.image.src,"original");assert.equal(c.layer.src,"layer");
+ assert.equal(e.mask.pixels,"repaint-mask");assert.equal(e.baseMask.pixels,"repaint-base");
+ assert.equal(c.contexts.blend.mask.pixels,"blend-mask");assert.equal(c.target,"mask");
+ assert.equal(e.history[0].points[0].x,1);assert.equal(e.future[0].type,"erase");
+ assert.equal(JSON.parse(n.widgets.find(w=>w.name==="crop_state").value).job,"job-a");
+ assert.equal(n.adachiColorPaint.restored,'paint_data');
+ assert.deepEqual(e.pan,{x:1,y:2});assert.equal(e.zoom,2);assert.equal(e.keepFit,true);
+ assert.notEqual(e.mask,before.contexts.mask.mask);
+ e.mask.pixels="changed-again";await restoreSourceState(n,before,{decode});assert.equal(e.mask.pixels,"repaint-mask");
+}
+{
+ const n=node(),c=n.adachiCrop,e=n.adachiEditor;
+ c.contexts.mask=context("saved-repaint");Object.assign(e,context("active-blend"));c.target="blend";
+ const before=captureSourceState(n);e.mask.pixels="lost";await restoreSourceState(n,before,{decode});
+ assert.equal(e.mask.pixels,"active-blend-mask");assert.equal(c.contexts.mask.mask.pixels,"saved-repaint-mask");assert.equal(c.target,"blend");
+}
+{
+ const n=node(),before=captureSourceState(n),old=n.adachiEditor.image;
+ await assert.rejects(restoreSourceState(n,before,{decode:async()=>{throw Error("broken PNG")}}),/broken PNG/);
+ assert.equal(n.adachiEditor.image,old);
+ n.adachiColorPaint={async prepareRestore(){throw Error('bad paint');},commitRestore(){throw Error('must not commit');}};
+ await assert.rejects(restoreSourceState(n,before,{decode}),/bad paint/);
+ assert.equal(n.adachiEditor.image,old,'paint decode failure preserves the current image');
+ delete n.adachiColorPaint;
+ await assert.rejects(restoreSourceState(n,before,{decode:async data=>{n.adachiEditor.loadVersion++;return decode(data)}}),/image changed/);
+ assert.equal(n.adachiEditor.image,old);
+}
+{
+ const n=node(),before=captureSourceState(n),old=n.adachiEditor.image;
+ n.adachiColorPaint={revision:1,async prepareRestore(){this.revision++;return null;},commitRestore(){throw Error('must not commit');}};
+ await assert.rejects(restoreSourceState(n,before,{decode}),/image changed/);
+ assert.equal(n.adachiEditor.image,old,'paint changes during history decode must not be overwritten');
+}
+{
+ const n=node(),h=new WorkspaceHistory(n,{maxEntries:3});h.checkpoint("original");
+ await h.transact("adopted",async()=>{n.adachiEditor.image=source("adopted");n.widgets[0].value="adopted.png"});
+ assert.equal(h.entries.length,2);assert.equal(h.current.label,"adopted");assert.equal(h.entries[0].state.image.src,"original");
+ const count=h.entries.length;await assert.rejects(h.transact("failed",async()=>{throw Error("upload failed")}),/upload failed/);assert.equal(h.entries.length,count);assert.equal(h.busy,false);
+ for(let i=0;i<6;i++){n.adachiEditor.image=source("next"+i);n.widgets[0].value="next"+i;h.checkpoint("next"+i);}
+ assert.equal(h.entries.length,3);assert.equal(h.entries[0].label,"original");assert.equal(h.current.label,"next5");
+ n.adachiEditor.stroke={};assert.throws(()=>h.checkpoint("stroke"),/Finish the current edit/);
+}
+console.log("Workspace source history: repaint/blend pixels, crop state, layer, commands, failure atomicity and retention passed");
+{
+ const n=node(),before=captureSourceState(n),created=[];
+ let count=0;
+ await assert.rejects(restoreSourceState(n,before,{decode:async data=>{if(++count===2)throw Error('bad base');const c=await decode(data);created.push(c);return c;}}),/bad base/);
+ assert.equal(created[0].width,0,'a partial decode failure frees already allocated masks');
+ assert.equal(n.adachiEditor.image,before.image);
+ for(const change of [()=>n.adachiEditor.maskRevision++,()=>n.adachiCrop.revision++]){
+  await assert.rejects(restoreSourceState(n,before,{decode:async data=>{change();return decode(data);}}),/image changed/);
+  assert.equal(n.adachiEditor.image,before.image,'a completed stroke or crop change during decoding is preserved');
+ }
+ await assert.rejects(restoreSourceState(n,before,{decode:async data=>{n.graph=null;return decode(data);}}),/image changed/);
+}

tests/test_workspace_models.mjs

@@ -0,0 +1,23 @@
+import assert from 'node:assert/strict';
+import {WorkspaceBindings} from '../web/workspace_bindings.js';
+const n=(id,type,values={})=>({id,type,mode:0,properties:{},widgets:Object.entries(values).map(([name,value])=>({name,value})),inputs:[]});
+const sampler=n(501,'AdachiWebUIInpaint');
+const nodes=[sampler,n(359,'CheckpointLoaderSimple',{ckpt_name:'anima_baseV10.safetensors'}),n(357,'CLIPLoader',{clip_name:'qwen_3_06b_base.safetensors'}),n(358,'VAELoader',{vae_name:'qwen_image_vae.safetensors'}),n(547,'CLIPTextEncode',{text:''}),n(16,'CLIPTextEncode',{text:''}),n(518,'CheckpointLoaderSimple',{ckpt_name:'wai.safetensors'}),n(521,'CLIPTextEncode',{text:''}),n(520,'CLIPTextEncode',{text:''})];
+const controller=n(524,'AdachiGroupPresets');nodes.push(controller);
+controller.adachiGroupPresets={model:{node:controller,data:{activeId:'anima',presets:[{id:'anima',name:'anima修图'},{id:'wai',name:'wai生图'}]},apply(id){this.data.activeId=id;}}};
+const graph={_nodes:nodes,links:{},getNodeById:id=>nodes.find(n=>String(n.id)===String(id))};
+const compiled=(profile)=>profile==='anima'?{
+ '359':{class_type:'CheckpointLoaderSimple',inputs:{}},'357':{class_type:'CLIPLoader',inputs:{}},'358':{class_type:'VAELoader',inputs:{}},
+ '547':{class_type:'CLIPTextEncode',inputs:{clip:['357',0],text:''}},'16':{class_type:'CLIPTextEncode',inputs:{clip:['357',0],text:''}},
+ '501':{class_type:'AdachiWebUIInpaint',inputs:{model:['359',0],positive:['547',0],negative:['16',0],vae:['358',0]}}
+}:{'518':{class_type:'CheckpointLoaderSimple',inputs:{}},'521':{class_type:'CLIPTextEncode',inputs:{clip:['518',1],text:''}},'520':{class_type:'CLIPTextEncode',inputs:{clip:['518',1],text:''}},'501':{class_type:'AdachiWebUIInpaint',inputs:{model:['518',0],positive:['521',0],negative:['520',0],vae:['518',2]}}};
+const b=new WorkspaceBindings({graph,sampler});b.updateExecutionGraph(compiled('anima'),'501');assert.equal(b.missingDependencies().length,0,'not-yet-loaded lists cannot prove missing weights');
+const info=(type,name,values)=>({[type]:{input:{required:{[name]:[values]}}}});
+const sources={'/object_info/CheckpointLoaderSimple':info('CheckpointLoaderSimple','ckpt_name',['wai.safetensors']),'/object_info/UNETLoader':info('UNETLoader','unet_name',[]),'/object_info/CLIPLoader':info('CLIPLoader','clip_name',[]),'/object_info/VAELoader':info('VAELoader','vae_name',['pixel_space']),'/models/loras':[]};
+await b.loadCatalog(async path=>({ok:true,json:async()=>sources[path]}));
+assert.deepEqual(b.missingDependencies().map(d=>d.widget.value),['anima_baseV10.safetensors','qwen_3_06b_base.safetensors','qwen_image_vae.safetensors']);
+assert.deepEqual(b.missingDependencies().map(d=>d.folder),['checkpoints','text_encoders','vae']);
+b.selectProfile('wai');b.updateExecutionGraph(compiled('wai'),'501');assert.equal(b.missingDependencies().length,0,'an available checkpoint supplies its own CLIP and VAE');assert.equal(b.modelDependencies().length,1);
+b.selectProfile('anima');b.updateExecutionGraph(compiled('anima'),'501');b.catalog.checkpoints.push('anima_baseV10.safetensors');b.catalog.clips.push('qwen_3_06b_base.safetensors');b.catalog.vaes.push('qwen_image_vae.safetensors');assert.equal(b.missingDependencies().length,0);
+const failed=new WorkspaceBindings({graph,sampler});failed.updateExecutionGraph(compiled('anima'),'501');await failed.loadCatalog(async()=>{throw Error('network offline');});assert.equal(failed.missingDependencies().length,0,'a network failure must not be reported as missing models');assert.ok(failed.catalogError);
+console.log('Workspace model dependencies: separate model/CLIP/VAE, absent weights, built-in checkpoint components and unavailable catalogs pass');

tests/test_workspace_progress.mjs

@@ -0,0 +1,22 @@
+import assert from 'node:assert/strict';
+import {WorkspaceProgress} from '../web/workspace_progress.js';
+const nodes={'1':{class_type:'CheckpointLoaderSimple'},'2':{class_type:'AdachiWebUIInpaint'},'3':{class_type:'AdachiImageCompare'}};
+const p=new WorkspaceProgress();p.begin(nodes);
+p.handle('executing',null);
+p.handle('execution_start',{prompt_id:'mine'});p.handle('progress',{prompt_id:'other',node:'2',value:9,max:10});
+p.attach('mine');assert.equal(p.state,'running');assert.equal(p.value,null,'a different prompt must not set the percentage');
+p.handle('executing',1);assert.equal(p.label,'Loading main model','legacy scalar node IDs remain supported');
+p.handle('executing',{prompt_id:'mine',node:'1'});assert.equal(p.label,'Loading main model');assert.equal(p.max,null);
+p.handle('progress',{prompt_id:'mine',node:'2',value:3,max:20});assert.equal(p.value,3);assert.equal(p.max,20);assert.match(p.label,/KSampler/);
+p.handle('executing',{prompt_id:'mine',node:null});assert.equal(p.value,3,'terminal executing packets cannot reset the sampler progress');
+assert.equal(p.handle('progress',{prompt_id:'other',node:'2',value:19,max:20}),false);assert.equal(p.value,3);
+p.handle('progress_state',{prompt_id:'mine',nodes:{'1':{state:'finished',value:1,max:1},'2':{state:'running',value:4,max:20}}});assert.equal(p.value,4);
+p.handle('executing',{prompt_id:'mine',node:'3'});assert.equal(p.value,null,'a new node cannot inherit the sampler percentage');assert.equal(p.label,'Preparing comparison images');
+p.connection(false);assert.equal(p.max,null);assert.match(p.label,/Connection lost/);
+p.handle('execution_success',{prompt_id:'mine'});assert.equal(p.value/p.max,1);assert.equal(p.state,'complete');
+p.handle('progress',{prompt_id:'mine',node:'2',value:1,max:20});assert.equal(p.state,'complete','late packets must not regress completion');
+p.begin(nodes,'error');p.handle('execution_error',{prompt_id:'error',exception_message:'missing model'});assert.equal(p.state,'error');assert.equal(p.label,'missing model');assert.equal(p.value,null);
+p.begin(nodes,'cache');p.handle('execution_cached',{prompt_id:'cache',nodes:['1','2']});assert.match(p.label,/2 nodes/);assert.equal(p.value,null);
+p.handle('progress_state',{prompt_id:'cache',nodes:{'2':{state:'running',value:0,max:1}}});assert.equal(p.max,null,'node-start placeholder 0/1 must remain indeterminate');
+p.begin(nodes);p.handle('execution_success',{prompt_id:'fast'});p.handle('executing',null);p.attach('fast');assert.equal(p.state,'complete','legacy completion before HTTP acknowledgment must not throw');
+console.log('Workspace progress: actual stage/steps, task filtering, early events, both progress protocols, cache, reconnect and late-packet safety pass');

tests/test_workspace_prompt_fold.mjs

@@ -0,0 +1,58 @@
+import assert from 'node:assert/strict';
+import {WorkspaceBindings} from '../web/workspace_bindings.js';
+
+class Element {
+    constructor(tag,doc){this.tagName=tag.toUpperCase();this.ownerDocument=doc;this.children=[];this.dataset={};this.isConnected=true;this.attributes={};}
+    append(...nodes){for(const node of nodes)node.parentElement=this;this.children.push(...nodes);}
+    replaceChildren(...nodes){this.children.forEach(child=>{child.isConnected=false;});this.children=[...nodes];}
+    setAttribute(name,value){this.attributes[name]=value;}
+    remove(){this.isConnected=false;}
+    contains(node){return this===node||this.children.some(child=>child.contains?.(node));}
+    querySelectorAll(tag){return this.children.flatMap(child=>[...(child.tagName===tag.toUpperCase()?[child]:[]),...child.querySelectorAll(tag)]);}
+    closest(){let node=this;while(node){if(node.tagName==='DETAILS'&&!node.open)return node;node=node.parentElement;}return null;}
+    focus(){this.ownerDocument.activeElement=this;}
+    setSelectionRange(start,end,direction){this.selectionStart=start;this.selectionEnd=end;this.selectionDirection=direction;}
+}
+const doc={createElement:tag=>new Element(tag,doc)};globalThis.document=doc;
+const sampler={id:1,type:'AdachiWebUIInpaint',mode:0,properties:{},inputs:[],widgets:[]};
+const controller={id:2,type:'AdachiGroupPresets',mode:0,properties:{}};
+controller.adachiGroupPresets={model:{node:controller,data:{activeId:'one',presets:[{id:'one',name:'One'},{id:'two',name:'Two'}]},apply(id){this.data.activeId=id;}}};
+const graph={_nodes:[sampler,controller],getNodeById:id=>graph._nodes.find(n=>String(n.id)===String(id)),links:{}};
+let changed=0,checks=0;
+const binding=new WorkspaceBindings({graph,sampler,markChanged:()=>changed++,onChange:()=>checks++});
+const entry=(id,text)=>({id,node:{type:'CLIPTextEncode',widgets:[{name:'text',value:text}]},api:{class_type:'CLIPTextEncode',inputs:{text}},fields:['text']});
+const positive=entry('p','positive original'),negative=entry('n','negative original');
+const flow=(positives=[positive])=>({encoders:{positive:positives,negative:[negative]},modelNodes:[],clipNodes:[],vaeNodes:[],loras:[],refs:{},clipConsumers:[]});
+binding.flow=flow();binding.samplerId='1';binding.createPanel();
+const section=kind=>binding.root.children.find(x=>x.dataset.promptKind===kind);
+const textarea=group=>group.children.flatMap(x=>x.children||[]).find(x=>x.tagName==='TEXTAREA');
+assert.equal(section('positive').open,true);assert.equal(section('negative').open,true);
+let positivePanel=section('positive');positivePanel.ontoggle();
+assert.equal(changed,0,'initial native toggle does not dirty the workflow');
+positivePanel.open=false;positivePanel.ontoggle();
+assert.equal(changed,1);assert.equal(checks,0,'folding is cosmetic and does not trigger workflow validation');
+assert.equal(sampler.properties.adachi_workspace_ui.promptOpen.positive,false);
+assert.equal(section('negative').open,true,'fold states are independent');
+const n=textarea(section('negative'));n.value='edited negative';n.oninput();n.setSelectionRange(3,7,'forward');n.scrollTop=12;n.focus();
+assert.deepEqual(binding.getExecutionBinding().inputOverrides.n,{text:'edited negative'});
+binding.render();assert.equal(section('positive').open,false);assert.equal(section('negative').open,true);
+assert.equal(doc.activeElement,textarea(section('negative')),'asynchronous panel rendering retains the focused prompt');
+assert.equal(doc.activeElement.selectionStart,3);assert.equal(doc.activeElement.selectionEnd,7);assert.equal(doc.activeElement.scrollTop,12);
+positivePanel.open=true;positivePanel.ontoggle();
+assert.equal(sampler.properties.adachi_workspace_ui.promptOpen.positive,false,'events from detached panels cannot override current state');
+binding.selectProfile('two');assert.equal(section('positive').open,false);
+section('negative').open=false;section('negative').ontoggle();
+binding.selectProfile('one');binding.flow=flow();binding.samplerId='1';binding.render();
+assert.equal(section('positive').open,false);assert.equal(section('negative').open,false);
+assert.deepEqual(binding.getExecutionBinding().inputOverrides.n,{text:'edited negative'},'profile changes preserve prompt overrides');
+const restoredSampler={...sampler,properties:JSON.parse(JSON.stringify(sampler.properties))};
+const restoredGraph={_nodes:[restoredSampler],getNodeById:()=>restoredSampler,links:{}};
+const restored=new WorkspaceBindings({graph:restoredGraph,sampler:restoredSampler});restored.flow=flow();restored.createPanel();
+assert.equal(restored.root.children.find(x=>x.dataset.promptKind==='positive').open,false);
+assert.equal(restored.root.children.find(x=>x.dataset.promptKind==='negative').open,false,'saved workflow retains both folds');
+delete restoredSampler.properties.adachi_workspace_ui;
+restored.flow=flow([positive,entry('p2','other')]);restored.render();
+const multi=restored.root.children.find(x=>x.dataset.promptKind==='positive');
+assert.equal(multi.open,false,'existing multi-encoder panels default to collapsed');
+assert.equal(multi.children.filter(x=>x.tagName==='LABEL').length,2,'all encoder fields remain available');
+console.log('Workspace prompt folding: independent states, cosmetic toggles, profile/workflow persistence, stale events and multi-encoder prompts pass');

tests/test_workspace_routes.mjs

@@ -0,0 +1,10 @@
+import assert from 'node:assert/strict';import {conditioningSource} from '../web/workspace_routes.js';
+const nodes=[];const add=(id,type,inputs=[],value)=>{const n={id,type,mode:0,inputs,widgets:[{value}]};nodes.push(n);return n};
+const a=add(1,'CLIPTextEncode'),b=add(2,'CLIPTextEncode');const sa=add(3,'SetNode',[{name:'x',link:1}],'p');const ga=add(4,'GetNode',[],'p');const sb=add(5,'SetNode',[{name:'x',link:2}],'p2');const gb=add(6,'GetNode',[],'p2');const sw=add(7,'AdachiExclusiveSwitch',[{name:'input_a',link:3},{name:'input_b',link:4}]);const sampler=add(8,'AdachiWebUIInpaint',[{name:'positive',link:5},{name:'negative',link:6}]);
+const links={1:{origin_id:1,origin_slot:0},2:{origin_id:2,origin_slot:0},3:{origin_id:4,origin_slot:0},4:{origin_id:6,origin_slot:0},5:{origin_id:7,origin_slot:0},6:{origin_id:2,origin_slot:0}};
+const g={_nodes:nodes,links,getNodeById:id=>nodes.find(n=>n.id==id)};nodes.forEach(n=>n.graph=g);
+assert.equal(conditioningSource(g,sampler,'positive'),null,'ambiguous branches must not be guessed');
+assert.equal(conditioningSource(g,sampler,'positive',new Map([[sb,4]])),a);
+assert.equal(conditioningSource(g,sampler,'negative'),b);
+sa.inputs[0].link=3;assert.equal(conditioningSource(g,sampler,'positive',new Map([[sb,4]])),null,'cycle must stop');
+console.log('Conditioning discovery: actual sampler route, Get/Set, preset state, ambiguity and cycles pass');

tests/test_workspace_transport.mjs

@@ -0,0 +1,15 @@
+import assert from 'node:assert/strict';
+import {workspaceRequest} from '../web/workspace_transport.js';
+let posts=0;const reply=(status,data)=>({status,ok:status<300,json:async()=>data});
+await assert.rejects(workspaceRequest({fetchApi:async(p,o)=>{if(o.method)posts++;return reply(405,{});}},'submit',{}),/backend is not loaded/);assert.equal(posts,0);
+const seen=[];
+const api={fetchApi:async(p,o)=>{seen.push(p);if(p==='/adachi-inpaint/workspace/capabilities')return reply(404,{});if(p.endsWith('/capabilities'))return reply(200,{api_version:1,can_validate:true});return reply(200,{valid:true});}};
+assert.equal((await workspaceRequest(api,'validate',{})).valid,true);assert.equal(seen.at(-1),'/api/adachi-inpaint/workspace/validate');
+await assert.rejects(workspaceRequest({fetchApi:async(p)=>p.endsWith('/capabilities')?reply(200,{api_version:1,can_validate:true}):reply(400,{valid:false,error:{message:'bad model'}})},'submit',{}),/bad model/);
+console.log('Workspace transport: missing backend blocks submission, /api proxy fallback and validation errors pass');
+const missing={fetchApi:async p=>p.endsWith('/capabilities')?reply(200,{api_version:1,can_validate:true}):reply(200,{valid:false,node_errors:{'357':{errors:[{type:'value_not_in_list',message:'Value not in list',details:'long technical inventory',extra_info:{input_name:'clip_name',received_value:'qwen_3_06b_base.safetensors'}}]}}})};
+await assert.rejects(workspaceRequest(missing,'validate',{}),e=>e.message==='Text encoder not found: qwen_3_06b_base.safetensors' && !!e.nodeErrors['357']);
+globalThis.comfyAPI={app:{app:{ui:{settings:{getSettingValue:()=> 'zh'}}}}};
+try {
+    await assert.rejects(workspaceRequest(missing,'validate',{}),e=>e.message==='未找到文本编码器：qwen_3_06b_base.safetensors' && !!e.nodeErrors['357']);
+} finally {delete globalThis.comfyAPI;}

web/color_paint.js

@@ -0,0 +1,40 @@
+import {T} from './i18n.js';
+
+// A separate transparent image-space layer. It never mutates source Image
+// objects held by the workspace's history and is persisted in paint_data.
+export class ColorPaint {
+    constructor(editor,crop,widget,changed,imageUrl=x=>x){
+        Object.assign(this,{editor,crop,widget,changed,imageUrl});this.active=false;this.color='#ff8a32';this.undo=[];this.redo=[];this.revision=0;
+        this.layer=document.createElement('canvas');
+        const controls=document.createElement('div');controls.className='dd-color-paint';
+        this.button=document.createElement('button');this.button.type='button';this.button.textContent='✎';this.button.title=T('Paint image pixels; Alt-click picks a color; Ctrl+wheel changes brush size');this.button.setAttribute('aria-label',this.button.title);
+        this.button.onclick=e=>{e.preventDefault();e.stopPropagation();if(!this.widget){editor.status(T('The paint layer is unavailable; update and restart ComfyUI'),true);return;}this.active=!this.active;if(this.active && editor.view==='mask')editor.view='overlay';this.sync();editor.schedule();};
+        this.picker=document.createElement('input');this.picker.type='color';this.picker.value=this.color;this.picker.title=T('Brush color');this.picker.setAttribute('aria-label',this.picker.title);this.picker.oninput=()=>{this.color=this.picker.value;};
+        this.undoButton=document.createElement('button');this.undoButton.type='button';this.undoButton.textContent='↶';this.undoButton.title=T('Undo color painting');this.undoButton.onclick=()=>this.step(this.undo,this.redo);
+        this.redoButton=document.createElement('button');this.redoButton.type='button';this.redoButton.textContent='↷';this.redoButton.title=T('Redo color painting');this.redoButton.onclick=()=>this.step(this.redo,this.undo);
+        controls.append(this.button,this.picker,this.undoButton,this.redoButton);crop.bar.prepend(controls);this.controls=controls;
+        const draw=editor.options.drawSource,revision=editor.options.sceneRevision;
+        editor.options.drawSource=ctx=>{const done=draw?.(ctx);if(!done)ctx.drawImage(editor.image,0,0);if(this.layer.width&&!crop.previewOriginal)ctx.drawImage(this.layer,0,0);return true;};
+        editor.options.sceneRevision=()=>`${revision?.()||''}:paint:${this.revision}`;
+        const down=editor.pointerDown.bind(editor),move=editor.pointerMove.bind(editor),up=editor.pointerUp.bind(editor);
+        editor.pointerDown=e=>{if(this.active && this.restoring){e.preventDefault();e.stopPropagation();return;}if(!this.active||e.button!==0||editor.space||!editor.ready||crop.busy||crop.previewOriginal||(crop.mode==='crop'&&!crop.region?.locked))return down(e);
+            e.preventDefault();e.stopPropagation();const p=editor.point(e);if(e.altKey){this.pick(p);return;}
+            this.ensure();this.remember();this.redo=[];this.drawing={id:e.pointerId,last:p};editor.pointerId=e.pointerId;editor.canvas.setPointerCapture(e.pointerId);this.segment(p,p);this.sync();};
+        editor.pointerMove=e=>{if(!this.drawing||this.drawing.id!==e.pointerId)return move(e);e.preventDefault();e.stopPropagation();const events=e.getCoalescedEvents?.()||[];for(const event of events.length?events:[e]){const p=editor.point(event);this.segment(this.drawing.last,p);this.drawing.last=p;}editor.cursor=editor.point(e);editor.schedule();};
+        editor.pointerUp=e=>{if(!this.drawing||this.drawing.id!==e.pointerId)return up(e);e.preventDefault();e.stopPropagation();this.drawing=null;editor.pointerId=null;if(editor.canvas.hasPointerCapture(e.pointerId))editor.canvas.releasePointerCapture(e.pointerId);this.flush();this.sync();};
+        this.sync();
+    }
+    ensure(){const {image}=this.editor;if(!image)return;if(this.layer.width!==image.width||this.layer.height!==image.height){this.layer.width=image.width;this.layer.height=image.height;}}
+    segment(a,b){const ctx=this.layer.getContext('2d');ctx.save();const bounds=this.editor.options.paintBounds?.();if(bounds){ctx.beginPath();ctx.rect(bounds.x,bounds.y,bounds.width,bounds.height);ctx.clip();}ctx.strokeStyle=this.color;ctx.fillStyle=this.color;ctx.lineWidth=this.editor.brushSize;ctx.lineCap='round';ctx.lineJoin='round';ctx.globalAlpha=this.editor.brushOpacity/100;if(a.x===b.x&&a.y===b.y){ctx.beginPath();ctx.arc(a.x,a.y,ctx.lineWidth/2,0,Math.PI*2);ctx.fill();}else{ctx.beginPath();ctx.moveTo(a.x,a.y);ctx.lineTo(b.x,b.y);ctx.stroke();}ctx.restore();this.revision++;this.editor.schedule();}
+    pick(p){const c=document.createElement('canvas');c.width=c.height=1;const x=c.getContext('2d',{willReadFrequently:true});x.translate(-Math.floor(p.x),-Math.floor(p.y));this.editor.options.drawSource(x);const [r,g,b,a]=x.getImageData(0,0,1,1).data;if(a){this.color='#'+[r,g,b].map(n=>n.toString(16).padStart(2,'0')).join('');this.picker.value=this.color;}}
+    flush(){if(!this.widget||!this.layer.width)return;try{this.widget.value=this.layer.toDataURL('image/png');this.changed();}catch(error){this.editor.status(error.message,true);throw error;}}
+    async prepareRestore(data,width,height){if(!data)return null;const image=new Image();image.src=data.startsWith('data:')?data:this.imageUrl(data);await image.decode();if(image.width!==width||image.height!==height)throw Error(T('Paint layer dimensions do not match the source image'));return image;}
+    commitRestore(image,width,height){this.undo=[];this.redo=[];this.layer.width=width;this.layer.height=height;if(image)this.layer.getContext('2d').drawImage(image,0,0);this.revision++;this.editor.schedule();this.sync();}
+    async restore(data){const width=this.editor.image.width,height=this.editor.image.height,loadVersion=this.editor.loadVersion,revision=this.revision,version=this.restoreVersion=(this.restoreVersion||0)+1;this.restoring=true;try{const image=await this.prepareRestore(data,width,height);if(this.editor.destroyed||this.restoreVersion!==version||this.editor.loadVersion!==loadVersion||this.revision!==revision||this.widget?.value!==data)return false;this.commitRestore(image,width,height);return true;}finally{if(this.restoreVersion===version)this.restoring=false;}}
+    remember(){this.undo.push(this.layer.toDataURL('image/png'));let bytes=this.undo.reduce((n,s)=>n+s.length*2,0);while(this.undo.length>1&&(this.undo.length>20||bytes>64*1024*1024))bytes-=this.undo.shift().length*2;}
+    async step(from,to){if(this.drawing||this.restoring||!from.length)return;this.restoring=true;const current=this.layer.toDataURL('image/png'),data=from.pop(),image=new Image();image.src=data;try{await image.decode();to.push(current);const ctx=this.layer.getContext('2d');ctx.clearRect(0,0,this.layer.width,this.layer.height);ctx.drawImage(image,0,0);this.revision++;this.flush();this.editor.schedule();this.sync();}catch(e){from.push(data);this.editor.status(e.message,true);}finally{this.restoring=false;}}
+    clear(){this.undo=[];this.redo=[];this.layer.width=this.layer.height=0;if(this.widget)this.widget.value='';this.revision++;this.sync();}
+    destroy(){this.layer.width=this.layer.height=0;this.controls.remove();}
+    clearRegion(r){if(!this.layer.width)return;this.remember();this.redo=[];this.layer.getContext('2d').clearRect(r.x,r.y,r.width,r.height);this.revision++;this.flush();this.editor.schedule();this.sync();}
+    sync(){this.editor.stage.classList.toggle('dd-color-active',this.active);this.button.classList.toggle('dd-active',this.active);this.button.setAttribute('aria-pressed',String(this.active));this.picker.hidden=this.undoButton.hidden=this.redoButton.hidden=!this.active;this.undoButton.disabled=!this.undo.length;this.redoButton.disabled=!this.redo.length;this.editor.updateButtons?.();}
+}

web/compare.js

@@ -1,17 +1,14 @@
-/* Original hover-comparison UI, MIT licensed. */
+/* SPDX-License-Identifier: GPL-3.0-only
+ * Original hover-comparison UI. */
 import { T } from "./i18n.js";
+import {loadPreviewPair} from './preview_images.js';
+import {CompareViewport} from './compare_viewport.js';
 const element = (tag, className, text) => {
     const node = document.createElement(tag);
     if (className) node.className = className;
     if (text) node.textContent = text;
     return node;
 };
-const imageFrom = url => new Promise((resolve, reject) => {
-    const image = new Image();
-    image.onload = () => resolve(image);
-    image.onerror = () => reject(new Error(T("Preview unavailable; run the workflow again")));
-    image.src = url;
-});
 
 export class ImageCompareView {
     constructor(options) {
@@ -20,6 +17,7 @@ export class ImageCompareView {
         this.originals = []; this.results = []; this.index = 0;
         this.split = .5;
         this.version = 0; this.ready = false;
+        this.viewport = new CompareViewport();this.workspaceZoom=false;this.displayMode='compare';
         this.dimensionsLabel = element("span", "dd-dimensions");
         const toolbar = element("div", "dd-row dd-compare-toolbar");
         toolbar.append(element("span", "dd-compare-label", T("Result")));
@@ -27,13 +25,17 @@ export class ImageCompareView {
         this.resultSelect.onchange = () => { this.index = Number(this.resultSelect.value); this.options.onSelect?.(this.index); this.loadSelected(); };
         toolbar.append(this.resultSelect, this.dimensionsLabel);
         const spacer = element("span", "dd-spacer"); toolbar.append(spacer);
+        this.reloadButton = element("button", "", "↻"); this.reloadButton.type = "button";
+        this.reloadButton.title = T("Reload comparison images"); this.reloadButton.setAttribute("aria-label", this.reloadButton.title);
+        this.reloadButton.onclick = async event => { event.preventDefault(); event.stopPropagation(); await this.options.recover?.(); this.loadSelected(); };
+        toolbar.append(this.reloadButton);
         this.downloadButton = element("button", "", "↓"); this.downloadButton.type = "button";
         this.downloadButton.title = T("Download the latest generated image");
         this.downloadButton.setAttribute("aria-label", this.downloadButton.title);
         this.downloadButton.onclick = event => { event.preventDefault(); event.stopPropagation(); this.downloadLatest(); };
         toolbar.append(this.downloadButton);
-        const fit = element("button", "", T("Fit")); fit.type = "button";
-        fit.onclick = event => { event.preventDefault(); event.stopPropagation(); this.schedule(); }; toolbar.append(fit);
+        const fit = element("button", "dd-compare-fit", T("Fit")); fit.type = "button";
+        fit.onclick = event => { event.preventDefault(); event.stopPropagation(); this.fitView(); }; toolbar.append(fit);
         this.stage = element("div", "dd-stage dd-compare-stage");
         this.canvas = document.createElement("canvas"); this.canvas.tabIndex = 0;
         this.canvas.setAttribute("aria-label", T("Result left, original right; hover to compare"));
@@ -44,6 +46,13 @@ export class ImageCompareView {
         Object.assign(this.divider.style, { position: "absolute", background: "#ffffffb3", pointerEvents: "none" });
         this.divider.hidden = true;
         this.stage.append(this.canvas, this.divider);
+        this.progressBox=element("div","dd-preview-progress");this.progressBox.hidden=true;
+        this.progressBox.setAttribute("role","status");
+        this.progressText=element("span");this.progressBar=document.createElement("progress");this.progressBar.max=1;
+        this.progressBar.setAttribute("aria-label",T("Comparison image loading progress"));
+        this.progressBox.append(this.progressText,this.progressBar);this.stage.append(this.progressBox);
+        this.retryOnOnline=()=>{if(!this.ready && !this.loadingActive && this.results.length)this.loadSelected();};
+        window.addEventListener("online",this.retryOnOnline);
         this.empty = element("div", "dd-empty", T("Connect an original image and a result, then run the workflow")); this.stage.append(this.empty);
         const adoption = element("div", "dd-row dd-adoption");
         adoption.append(element("span", "dd-compare-label", T("Adopt into")));
@@ -58,10 +67,12 @@ export class ImageCompareView {
         this.root.append(this.stage, toolbar, adoption, this.message);
         this.canvas.addEventListener("pointermove", event => this.move(event));
         this.canvas.addEventListener("pointerdown", event => {
+            if(this.workspaceZoom && this.ready && event.button===1){event.preventDefault();event.stopPropagation();this.panDrag={id:event.pointerId,x:event.clientX,y:event.clientY};this.canvas.setPointerCapture(event.pointerId);return;}
             if (!this.ready || event.button !== 0) return;
             event.preventDefault(); event.stopPropagation(); this.canvas.focus({ preventScroll: true });
             this.move(event);
         });
+        for(const type of ['pointerup','pointercancel','lostpointercapture'])this.canvas.addEventListener(type,event=>{if(this.panDrag?.id===event.pointerId)this.panDrag=null;});
         this.canvas.addEventListener("wheel", event => this.wheel(event), { passive: false });
         this.canvas.addEventListener("keydown", event => {
             if (["ArrowLeft", "ArrowRight"].includes(event.key)) {
@@ -89,7 +100,7 @@ export class ImageCompareView {
     }
 
     updateButton() {
-        this.adoptButton.disabled = !this.ready || !this.targetSelect.value || !!this.busy;
+        this.adoptButton.disabled = !this.ready || !this.targetSelect.value || !!this.busy || this.pendingOutputs>0;
         this.adoptButton.textContent = this.busy ? T("Adopting…") : T("Adopt this result");
         this.downloadButton.disabled = !this.latestResult || !!this.downloading;
     }
@@ -100,8 +111,9 @@ export class ImageCompareView {
         if (!this.latestResult || this.downloading) return;
         const result = this.latestResult;
         this.downloading = true; this.updateButton();
+        const controller=this.downloadController=new AbortController();
         try {
-            const blob = await this.options.fetchResult(result);
+            const blob = await this.options.fetchResult(result,{signal:controller.signal});
             if (this.destroyed) return;
             const url = URL.createObjectURL(blob), link = document.createElement("a");
             link.href = url; link.download = "adachi-inpaint-result.png";
@@ -109,7 +121,7 @@ export class ImageCompareView {
             setTimeout(() => URL.revokeObjectURL(url), 60000);
             this.status("");
         } catch (error) { if (!this.destroyed) this.status(error.message, true); }
-        finally { this.downloading = false; if (!this.destroyed) this.updateButton(); }
+        finally {if(this.downloadController===controller)this.downloadController=null;this.downloading = false; if (!this.destroyed) this.updateButton();}
     }
 
     async setData(data, index = this.index) {
@@ -126,39 +138,86 @@ export class ImageCompareView {
         await this.loadSelected();
     }
 
-    async loadSelected() {
-        const version = ++this.version;
-        this.ready = false; this.updateButton();
-        if (!this.originals.length || !this.results.length) return;
-        const repetitions = this.results.length / this.originals.length;
-        const original = this.originals[Math.min(this.originals.length - 1, Math.floor(this.index / repetitions))];
+    loading(text, states) {
+        this.progressBox.hidden=false;this.progressText.textContent=text;
+        if(states) {
+            const loaded=states.reduce((n,s)=>n+s.loaded,0),total=states.every(s=>s.total>0)?states.reduce((n,s)=>n+s.total,0):0;
+            const size=n=>n>=1048576?`${(n/1048576).toFixed(1)} MiB`:`${Math.round(n/1024)} KiB`;
+            this.progressText.textContent+=total?` · ${Math.min(100,Math.round(loaded/total*100))}% · ${size(loaded)} / ${size(total)}`:` · ${size(loaded)}`;
+            if(total)this.progressBar.value=Math.min(1,loaded/total);else this.progressBar.removeAttribute("value");
+        } else this.progressBar.removeAttribute("value");
+    }
+
+    async loadSelected({background=false}={}) {
+        if(this.destroyed)return;
+        clearTimeout(this.retryTimer);this.loadController?.abort();
+        const version=++this.version,controller=this.loadController=new AbortController();
+        this.reloadButton.disabled=false;this.loadingActive=true;
+        this.ready=false;this.updateButton();this.schedule();
+        if(!this.originals.length || !this.results.length){this.loadingActive=false;this.progressBox.hidden=true;return;}
+        const repetitions=this.results.length/this.originals.length;
+        const original=this.originals[Math.min(this.originals.length-1,Math.floor(this.index/repetitions))];
+        const current=()=>version===this.version && !this.destroyed && !controller.signal.aborted;
+        const blobKey=JSON.stringify([original,this.results[this.index]]);
+        if(this.blobKey!==blobKey){this.blobKey=blobKey;this.pendingBlobs=[null,null];}
+        const blobs=this.pendingBlobs||[null,null];
         try {
-            const images = await Promise.all([imageFrom(this.options.resolveUrl(original)), imageFrom(this.options.resolveUrl(this.results[this.index]))]);
-            if (version !== this.version || this.destroyed) return;
-            this.before = images[0]; this.after = images[1];
-            this.ready = true; this.empty.hidden = true;
-            this.dimensionsLabel.textContent = `${this.before.width} × ${this.before.height}`;
-            this.status("");
-            this.updateButton(); this.schedule();
-        } catch (error) { if (version === this.version && !this.destroyed) this.status(error.message, true); }
+            let images;
+            for(let attempt=0;attempt<3;attempt++) {
+                const states=blobs.map(blob=>({loaded:blob?.size||0,total:blob?.size||0,complete:!!blob}));
+                this.loading(attempt?T("Retrying comparison images")+` (${attempt+1}/3)`:T("Loading comparison images"),states);
+                try {
+                    images=await loadPreviewPair([original,this.results[this.index]],{loadPreview:(...args)=>this.options.loadPreview(...args),cached:blobs,signal:controller.signal,
+                        onProgress:(i,state)=>{states[i]=state;if(current())this.loading(T("Loading comparison images"),states);},
+                        onDecoding:()=>{if(current() && states.every(s=>s.complete))this.loading(T("Decoding comparison images…"));}});
+                    break;
+                } catch(error) {
+                    if(!current())return;
+                    if(attempt===2 || [404,410].includes(error.status))throw error;
+                    await new Promise(resolve=>{const done=()=>{clearTimeout(timer);controller.signal.removeEventListener('abort',done);resolve();};const timer=setTimeout(done,1000*(attempt+1));controller.signal.addEventListener('abort',done,{once:true});});
+                }
+            }
+            if(!current()){for(const item of images||[])URL.revokeObjectURL(item.url);return;}
+            if(this.before && (this.before.width!==images[0].image.width || this.before.height!==images[0].image.height))this.viewport.fit();
+            for(const url of this.previewUrls||[])URL.revokeObjectURL(url);
+            this.previewUrls=images.map(item=>item.url);this.before=images[0].image;this.after=images[1].image;
+            this.ready=true;this.pendingBlobs=null;this.retryCount=0;this.empty.hidden=true;this.progressBox.hidden=true;
+            this.dimensionsLabel.textContent=`${this.before.width} × ${this.before.height}`;
+            this.status("");this.updateButton();this.schedule();
+        } catch(error) {
+            if(!current())return;
+            this.progressBox.title=error.message;
+            if([404,410].includes(error.status)){this.progressBox.hidden=true;this.pendingBlobs=null;this.status(T("Result preview expired; run the workflow again"),true);return;}
+            this.status(T("Image loading failed; retrying automatically. You can also click reload."),true);
+            const seconds=Math.min(60,5*2**Math.min(this.retryCount||0,4));this.retryCount=(this.retryCount||0)+1;
+            this.loading(T("Waiting to retry comparison images")+` · ${seconds}s`);
+            this.retryTimer=setTimeout(()=>this.loadSelected({background:true}),seconds*1000);
+        } finally {if(version===this.version)this.loadingActive=false;}
     }
 
     async adopt() {
         this.refreshTargets();
         if (this.busy) return;
-        if (!this.ready) { this.status(T("The result preview is still loading"), true); return; }
+        if (!this.ready || this.pendingOutputs>0) { this.status(T("The result preview is still loading"), true); return; }
         if (!this.targetSelect.value) { this.status(T("Select an inline mask to adopt into"), true); return; }
         const target = this.targetSelect.value, result = this.results[this.index];
         this.busy = true; this.updateButton(); this.status(T("Setting the result as the new source image…"));
+        const progress = ({phase, loaded=0, total=0}={}) => {
+            const text = phase === 'download' ? T('Downloading result…') : phase === 'upload' ? T('Uploading result…') : phase === 'authenticated' ? T('Uploading with authentication…') : phase === 'processing' ? T('Upload complete, loading image…') : T('Preparing result…');
+            this.loading(text, phase === 'download' || phase === 'upload' ? [{loaded,total}] : undefined);
+        };
+        progress({phase:'prepare'});
+        const controller=this.adoptController=new AbortController();
         try {
-            await this.options.onAdopt(target, result);
+            await this.options.onAdopt(target, result,{signal:controller.signal,onProgress:progress});
             if (!this.destroyed) this.status(T("Adopted: back in the inline mask, keep painting to inpaint again"));
         } catch (error) { if (!this.destroyed) this.status(error.message, true); }
-        finally { this.busy = false; if (!this.destroyed) this.updateButton(); }
+        finally {if(this.adoptController===controller)this.adoptController=null;this.busy = false; if (!this.destroyed) {this.progressBox.hidden=true;this.updateButton();}}
     }
 
     transform() {
         const rect = this.canvas.getBoundingClientRect();
+        if(this.workspaceZoom && this.before)return this.viewport.transform(rect.width,rect.height,this.before.width,this.before.height);
         const scale = this.before ? Math.min(rect.width / this.before.width, rect.height / this.before.height) : 1;
         return { width: rect.width, height: rect.height, scale, x: (rect.width - (this.before?.width || 0) * scale) / 2, y: (rect.height - (this.before?.height || 0) * scale) / 2 };
     }
@@ -167,11 +226,19 @@ export class ImageCompareView {
 
     wheel(event) {
         event.preventDefault(); event.stopPropagation();
+        if(this.workspaceZoom){
+            if(!this.ready)return;
+            const rect=this.canvas.getBoundingClientRect(),delta=event.deltaY*(event.deltaMode===1?16:event.deltaMode===2?rect.height:1);
+            this.viewport.zoomAt(rect.width,rect.height,this.before.width,this.before.height,event.clientX-rect.left,event.clientY-rect.top,delta);
+            if(this.displayMode==='compare')this.move(event);this.schedule();return;
+        }
         this.options.onGraphWheel?.(event);
     }
 
     move(event) {
         if (!this.ready) return;
+        if(this.panDrag && this.panDrag.id===event.pointerId){this.viewport.pan(event.clientX-this.panDrag.x,event.clientY-this.panDrag.y);this.panDrag.x=event.clientX;this.panDrag.y=event.clientY;this.schedule();return;}
+        if(this.displayMode!=='compare')return;
         this.hovered = true;
         this.split = Math.max(0, Math.min(1, this.position(event).x / this.before.width));
         this.schedule();
@@ -179,50 +246,57 @@ export class ImageCompareView {
 
     schedule() { if (!this.frame && !this.destroyed) this.frame = requestAnimationFrame(() => { this.frame = 0; this.render(); }); }
 
+    enableWorkspaceZoom(enabled) {this.workspaceZoom=!!enabled;this.panDrag=null;this.displayMode='compare';this.viewport.fit();this.lastPaint=null;this.schedule();}
+    setDisplayMode(mode) {this.displayMode=['compare','before','after'].includes(mode)?mode:'compare';this.lastPaint=null;this.schedule();}
+    fitView() {this.viewport.fit();this.lastPaint=null;this.schedule();}
+
     render() {
         const t = this.transform(), ratio = Math.min(devicePixelRatio || 1, 2);
         if (!t.width || !t.height) return;
         // Graph zoom changes the screen rect, not the amount of source detail.
         // Never allocate a huge upscaled bitmap just to magnify existing pixels.
-        const rasterRatio = Math.min(ratio, this.ready ? 1 / t.scale : ratio,
+        const rasterRatio = Math.min(ratio, this.ready && !this.workspaceZoom ? 1 / t.scale : ratio,
             8192 / t.width, 8192 / t.height, Math.sqrt(16 * 1024 * 1024 / (t.width * t.height)));
         const width = Math.max(1, Math.round(t.width * rasterRatio)), height = Math.max(1, Math.round(t.height * rasterRatio));
         if (this.canvas.width !== width || this.canvas.height !== height) { this.canvas.width = width; this.canvas.height = height; }
         const ctx = this.canvas.getContext("2d");
         ctx.setTransform(1, 0, 0, 1, 0, 0);
-        this.divider.hidden = !this.ready || !this.hovered;
+        this.divider.hidden = !this.ready || !this.hovered || this.displayMode!=='compare';
         if (!this.ready) { ctx.clearRect(0, 0, width, height); this.lastPaint = null; return; }
         const split = this.split * this.before.width;
         const lineX = Math.round((t.x + split * t.scale) * rasterRatio) + .5;
-        if (this.hovered) {
+        if (this.hovered && this.displayMode==='compare') {
             const screenScale = t.width / this.canvas.clientWidth || 1;
             Object.assign(this.divider.style, {
                 left: `${(t.x + split * t.scale) / screenScale}px`, top: `${t.y / screenScale}px`,
                 height: `${this.before.height * t.scale / screenScale}px`, width: `${1 / screenScale}px`,
             });
         }
-        const key = [this.version, width, height, t.scale * rasterRatio, t.x * rasterRatio, t.y * rasterRatio].join(":");
+        const key = [this.version, this.displayMode, width, height, t.scale * rasterRatio, t.x * rasterRatio, t.y * rasterRatio].join(":");
         const previous = this.lastPaint;
         ctx.save();
         // While hovering, pixels outside the old/new divider positions are
         // unchanged. Clip the redraw to that strip rather than repainting all.
-        if (previous?.key === key && previous.hovered && this.hovered) {
+        if (this.displayMode==='compare' && previous?.key === key && previous.hovered && this.hovered) {
             const left = Math.max(0, Math.floor(Math.min(previous.lineX, lineX)) - 2);
             const right = Math.min(width, Math.ceil(Math.max(previous.lineX, lineX)) + 2);
             ctx.beginPath(); ctx.rect(left, 0, right - left, height); ctx.clip();
         }
         ctx.clearRect(0, 0, width, height);
         ctx.setTransform(t.scale * rasterRatio, 0, 0, t.scale * rasterRatio, t.x * rasterRatio, t.y * rasterRatio);
-        ctx.drawImage(this.after, 0, 0, this.before.width, this.before.height);
+        ctx.drawImage(this.displayMode==='before'?this.before:this.after, 0, 0, this.before.width, this.before.height);
         this.lastPaint = { key, hovered: this.hovered, lineX };
-        if (!this.hovered) { ctx.restore(); return; }
+        if (!this.hovered || this.displayMode!=='compare') { ctx.restore(); return; }
         ctx.save(); ctx.beginPath(); ctx.rect(split, 0, this.before.width - split, this.before.height); ctx.clip();
         ctx.drawImage(this.before, 0, 0); ctx.restore();
         ctx.restore();
     }
 
     destroy() {
-        this.destroyed = true; ++this.version; cancelAnimationFrame(this.frame); this.observer.disconnect();
-        this.before = this.after = null; this.canvas.width = this.canvas.height = 0; this.root.remove();
+        this.destroyed = true; ++this.version; clearTimeout(this.retryTimer);this.loadController?.abort();
+        this.downloadController?.abort();this.adoptController?.abort();
+        window.removeEventListener("online",this.retryOnOnline);for(const url of this.previewUrls||[])URL.revokeObjectURL(url);
+        cancelAnimationFrame(this.frame); this.observer.disconnect();
+        this.pendingBlobs=null;this.before = this.after = null; this.canvas.width = this.canvas.height = 0; this.root.remove();
     }
 }

web/compare_node.js

@@ -1,10 +1,14 @@
 import { app } from "../../scripts/app.js";
 import { api } from "../../scripts/api.js";
-import { ImageCompareView } from "./compare.js?v=0.8.1";
+import { ImageCompareView } from "./compare.js?v=toolbar-layout-20261112";
+import { readPreview } from "./preview_transport.js";
+import { installComparisonRecovery } from "./result_recovery.js";
+import {executionId,executionNode,graphNodeEntries} from "./workspace_flow.js";
+import {upstreamNodes} from "./workbench_analysis.js";
 import { appendComparison } from "./compare_history.js?v=0.5.8";
 import { routeWheelOutsideImage } from "./wheel_routing.js";
 import { T } from "./i18n.js";
-import { bindWidgetToNodeWidth } from "./widget_layout.js?v=0.5.5";
+import { bindWidgetToNodeWidth, createWidgetHost } from "./widget_layout.js?v=stable-host-20261112";
 
 function viewPath(image) {
     if (image?.type === "adachi_memory") return `/adachi-inpaint/compare/${encodeURIComponent(image.filename || "")}`;
@@ -14,48 +18,44 @@ function viewPath(image) {
 const viewUrl = image => api.apiURL(viewPath(image));
 
 function targets(node) {
-    const graph = node.graph;
-    const editors = (graph?._nodes || []).filter(candidate => candidate.type === "AdachiInlineMask" && candidate.adachiUseResult)
-        .map(candidate => ({ id: candidate.id, label: `${candidate.title || T("Inline Mask")} #${candidate.id}` }));
-    const sourceLink = graph?.links?.[node.inputs?.find(input => input.name === "original")?.link];
-    const queue = sourceLink ? [sourceLink.origin_id] : [], seen = new Set(), upstream = new Set();
-    while (queue.length && seen.size < 256) {
-        const id = queue.shift(); if (seen.has(id)) continue; seen.add(id);
-        const current = graph.getNodeById(id); if (!current) continue;
-        if (current.type === "AdachiInlineMask") { upstream.add(String(id)); continue; }
-        for (const input of current.inputs || []) {
-            if (!["IMAGE", "*"].includes(input.type)) continue;
-            const link = graph.links?.[input.link]; if (link) queue.push(link.origin_id);
-        }
-    }
+    const graph=app.rootGraph||app.graph;
+    const editors=graphNodeEntries(graph).filter(({node})=>node.type==='AdachiInlineMask' && node.adachiUseResult)
+        .map(({node:editor,id})=>({id,label:`${editor.title||T('Inline Mask')} #${id}`}));
+    const upstream=new Set([...upstreamNodes(node,'original')].filter(n=>n.type==='AdachiInlineMask').map(n=>executionId(graph,n)));
     return { editors, preferred: upstream.size === 1 ? [...upstream][0] : "" };
 }
 
 app.registerExtension({
     name: "Adachi.ImageCompare",
+    setup() { installComparisonRecovery(api,()=>app.rootGraph||app.graph); },
     async beforeRegisterNodeDef(nodeType, nodeData) {
         if (nodeData.name !== "AdachiImageCompare") return;
         const created = nodeType.prototype.onNodeCreated;
         nodeType.prototype.onNodeCreated = function () {
             const value = created?.apply(this, arguments), node = this;
+            const recovery=installComparisonRecovery(api,()=>app.rootGraph||app.graph);
+            node.adachiTrackPrompt=(id,graph=app.rootGraph||app.graph)=>recovery.track(graph,id,executionId(graph,node));
             const compare = new ImageCompareView({
                 resolveUrl: viewUrl,
+                loadPreview: (image,options)=>readPreview(api.fetchApi.bind(api),viewPath(image),options),
+                recover: ()=>recovery.recover(),
+                waitingText: T("Waiting for the generated image…"),
+                failedText: T("Generation failed; check the ComfyUI task history"),
                 onGraphWheel: event => app.canvas?.processMouseWheel(event),
                 getTargets: () => targets(node),
                 onSelect: index => { node.properties.adachi_result_index = index; },
-                async fetchResult(image) {
-                    const response = await api.fetchApi(viewPath(image));
-                    if (!response.ok) throw new Error(T("Result preview expired; run the workflow again"));
-                    return response.blob();
+                async fetchResult(image, options) {
+                    return readPreview(api.fetchApi.bind(api),viewPath(image),options);
                 },
-                async onAdopt(id, image) {
-                    const target = node.graph?.getNodeById(id);
+                async onAdopt(id, image, options={}) {
+                    const graph=app.rootGraph||app.graph,target = executionNode(graph,id);
                     if (!target?.adachiUseResult) throw new Error(T("No inline mask node is available to receive the result"));
-                    const response = await api.fetchApi(viewPath(image));
-                    if (!response.ok) throw new Error(T("Result preview expired; run the workflow again"));
-                    const blob = await response.blob();
+                    options.onProgress?.({phase:'download'});
+                    const blob = await readPreview(api.fetchApi.bind(api),viewPath(image),{...options,onProgress:p=>options.onProgress?.({phase:'download',...p}),maxBytes:64*1024*1024});
+                    options.signal?.throwIfAborted();
+                    if(graph!==(app.rootGraph||app.graph)||target!==executionNode(graph,id))throw Error(T("The workflow changed; check connections again"));
                     if (blob.size > 64 * 1024 * 1024) throw new Error(T("Result image exceeds 64 MiB; downscale it first"));
-                    await target.adachiUseResult(new File([blob], `adachi-result-${Date.now()}.png`, { type: "image/png" }), image.adachi_origin);
+                    await target.adachiUseResult(new File([blob], `adachi-result-${Date.now()}.png`, { type: "image/png" }), image.adachi_origin, options);
                     // Adoption starts a new round. Keep the accepted image visible
                     // as 1/1, then replace it with the next round's first outputs.
                     const data = { originals: [image], results: [image] };
@@ -68,11 +68,12 @@ app.registerExtension({
             });
             node.adachiCompare = compare;
             const stopWheelRouting = routeWheelOutsideImage(compare.root, null, () => false);
-            const widget = node.addDOMWidget("adachi_compare", "adachi_compare_view", compare.root, {
+            const widgetHost = createWidgetHost(compare.root);
+            const widget = node.addDOMWidget("adachi_compare", "adachi_compare_view", widgetHost, {
                 serialize: false, hideOnZoom: false, getMinHeight: () => 420, getMaxHeight: () => 4096,
             });
             widget.serialize = false;
-            bindWidgetToNodeWidth(node, widget, compare.root);
+            bindWidgetToNodeWidth(node, widget, widgetHost);
             const executed = node.onExecuted;
             node.onExecuted = function (output) {
                 const result = executed?.apply(this, arguments);

web/compare_viewport.js

@@ -0,0 +1,22 @@
+/* SPDX-License-Identifier: GPL-3.0-only */
+// Shared viewport for sliding comparison and single-image modes. Coordinates
+// are CSS pixels relative to the visible stage, not physical canvas pixels.
+export class CompareViewport {
+    constructor() { this.fit(); }
+    fit() { this.zoom=1; this.panX=0; this.panY=0; }
+    transform(width,height,imageWidth,imageHeight) {
+        const base=Math.min(width/imageWidth,height/imageHeight),scale=base*this.zoom;
+        return {width,height,scale,x:(width-imageWidth*scale)/2+this.panX,y:(height-imageHeight*scale)/2+this.panY};
+    }
+    zoomAt(width,height,imageWidth,imageHeight,x,y,deltaY) {
+        if(!(width>0&&height>0&&imageWidth>0&&imageHeight>0))return;
+        const current=this.transform(width,height,imageWidth,imageHeight);
+        const next=Math.max(0.1,Math.min(16,this.zoom*Math.exp(-Math.max(-240,Math.min(240,deltaY))*.0015)));
+        const ratio=next/this.zoom;
+        const nextX=x-(x-current.x)*ratio,nextY=y-(y-current.y)*ratio;
+        this.zoom=next;
+        const centered=this.transform(width,height,imageWidth,imageHeight);
+        this.panX+=nextX-centered.x;this.panY+=nextY-centered.y;
+    }
+    pan(dx,dy) {this.panX+=dx;this.panY+=dy;}
+}

web/draft_guard.js

@@ -1,6 +1,6 @@
 // Probe only our own temporary key. Existing ComfyUI drafts are never edited or deleted.
 export const inlineWidgetNames = [
-  "image", "mask_data", "source_data", "edit_mode", "crop_state", "blend_data", "layer_image",
+  "image", "mask_data", "source_data", "edit_mode", "crop_state", "blend_data", "layer_image", "paint_data",
 ];
 
 // Some extensions also serialize a named snapshot. Keep it in step with the
@@ -35,24 +35,22 @@ export async function prepareInlineDraft(graph, { fits, upload }) {
         node.widgets_values_named[name] = node.widgets_values[index];
     }
   }
-  const candidates = nodes.filter((node) => {
-    const embedded = node.widgets_values?.[2] ?? node.widgets_values_named?.source_data;
-    return typeof embedded === "string" && embedded.startsWith("data:") && embedded.length >= 256 * 1024;
-  }).sort((a, b) => (b.widgets_values?.[2] ?? b.widgets_values_named.source_data).length - (a.widgets_values?.[2] ?? a.widgets_values_named.source_data).length);
+  const candidates = nodes.flatMap(node => [[2,"source_data"],[7,"paint_data"]].map(([index,name]) => ({node,index,name,embedded:node.widgets_values?.[index] ?? node.widgets_values_named?.[name]})))
+    .filter(({embedded})=>typeof embedded === "string" && embedded.startsWith("data:") && embedded.length >= 256 * 1024)
+    .sort((a,b)=>b.embedded.length-a.embedded.length);
   let converted = 0;
-  for (const node of candidates) {
+  for (const {node,index,name,embedded} of candidates) {
     if (fits(graph) !== false) break;
-    const embedded = node.widgets_values?.[2] ?? node.widgets_values_named.source_data;
     const filename = await upload(embedded);
     if (typeof filename !== "string" || !filename) throw new Error("Source upload returned no filename");
     // Commit only after a successful exact upload. All masks and layers stay intact.
     if (Array.isArray(node.widgets_values)) {
-      node.widgets_values[0] = filename;
-      node.widgets_values[2] = "";
+      if(name === "source_data") node.widgets_values[0] = filename;
+      node.widgets_values[index] = name === "source_data" ? "" : filename;
     }
     if (node.widgets_values_named) {
-      node.widgets_values_named.image = filename;
-      node.widgets_values_named.source_data = "";
+      if(name === "source_data") node.widgets_values_named.image = filename;
+      node.widgets_values_named[name] = name === "source_data" ? "" : filename;
     }
     converted++;
   }

web/editor.css

@@ -26,8 +26,14 @@
 .dd-inpaint input[type="range"] { display: block; width: 100%; min-width: 0; height: 18px; margin: 3px 0 0; accent-color: #f3b06a; cursor: pointer; }
 .dd-inpaint .dd-stage { position: relative; flex: 1 1 290px; min-height: 170px; overflow: hidden; border-top: 1px solid var(--dd-line); border-bottom: 1px solid var(--dd-line); background-color: #161a20; background-image: linear-gradient(45deg, #222831 25%, transparent 25%), linear-gradient(-45deg, #222831 25%, transparent 25%), linear-gradient(45deg, transparent 75%, #222831 75%), linear-gradient(-45deg, transparent 75%, #222831 75%); background-size: 20px 20px; background-position: 0 0, 0 10px, 10px -10px, -10px 0; }
 .dd-inpaint .dd-stage canvas { position: absolute; inset: 0; width: 100%; height: 100%; display: block; touch-action: none; cursor: crosshair; }
+.dd-inpaint .dd-color-paint {display:flex;flex:none;gap:3px;align-items:center;}
+.dd-inpaint .dd-color-paint button {min-width:26px;padding:3px 6px;}
+.dd-inpaint .dd-color-paint input[type=color] {width:26px;height:25px;padding:1px;border:0;background:transparent;cursor:pointer;}
+.dd-inpaint .dd-color-paint [hidden] {display:none;}
+.dd-inpaint .dd-stage.dd-color-active canvas {cursor:crosshair;}
 .dd-inpaint .dd-stage.dd-pan canvas { cursor: grab; }
 .dd-inpaint .dd-stage.dd-erasing canvas { cursor: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='32' height='32' viewBox='0 0 32 32'%3E%3Cpath d='M6 19 18 7a3 3 0 0 1 4 0l5 5a3 3 0 0 1 0 4L16 27h-5l-5-5a2 2 0 0 1 0-3Z' fill='%23ffb3c0' stroke='%23151a22' stroke-width='3' stroke-linejoin='round'/%3E%3Cpath d='m7 19 7-7 10 10-5 5h-8l-4-4a3 3 0 0 1 0-4Z' fill='%23fff4f6'/%3E%3Cpath d='m13 13 10 10M11 28h17' fill='none' stroke='%23151a22' stroke-width='2'/%3E%3C/svg%3E") 16 16, crosshair; }
+.dd-inpaint .dd-stage.dd-color-active.dd-erasing canvas {cursor:crosshair;}
 .dd-inpaint .dd-stage.dd-drop { outline: 3px solid var(--dd-accent); outline-offset: -3px; }
 .dd-inpaint .dd-empty { position: absolute; inset: 0; display: flex; flex-direction: column; align-items: center; justify-content: center; pointer-events: none; gap: 6px; color: var(--dd-muted); padding: 15px; text-align: center; }
 .dd-inpaint .dd-empty[hidden] { display: none; }
@@ -96,6 +102,7 @@
 .dd-comparer .dd-compare-stage { border: 0; }
 .dd-comparer .dd-compare-toolbar { padding-top: 5px; padding-bottom: 2px; }
 .dd-comparer .dd-compare-toolbar .dd-dimensions { margin-left: 5px; }
+.adachi-workspace .dd-comparer .dd-compare-fit { display: none; }
 .dd-comparer .dd-adoption { padding-top: 3px; padding-bottom: 5px; }
 .dd-comparer .dd-compare-captions { position: absolute; top: 8px; left: 8px; right: 8px; display: flex; justify-content: space-between; pointer-events: none; }
 .dd-comparer .dd-compare-captions span { background: #171d27cc; color: #f1e3cf; padding: 3px 7px; border-radius: 3px; font-size: 11px; }
@@ -103,10 +110,12 @@
 .dd-group-presets { border: 0; border-radius: 4px; container-type: inline-size; contain: size layout; }
 .dd-gp-toolbar, .dd-gp-form { display: flex; align-items: center; gap: 7px; padding: 9px 10px; flex: 0 0 auto; }
 .dd-gp-toolbar { justify-content: space-between; border-bottom: 1px solid var(--dd-line); }
+.dd-gp-toolbar-actions { display: flex; align-items: center; gap: 5px; }
 .dd-gp-toolbar strong { font-size: 12px; font-weight: 500; }
 .dd-group-presets button { min-height: 26px; padding: 4px 7px; font-size: 11px; }
 .dd-gp-form input { flex: 1; min-width: 0; color: var(--dd-text); background: var(--dd-panel); border: 1px solid var(--dd-line); padding: 5px 6px; font: inherit; border-radius: 3px; }
 .dd-gp-body { display: grid; grid-template-columns: minmax(130px, 40%) minmax(0, 1fr); flex: 1; min-height: 0; }
+.dd-gp-body.dd-gp-collapsed { grid-template-columns: minmax(0, 1fr); }
 .dd-gp-presets { border-right: 1px solid var(--dd-line); padding: 7px; display: flex; flex-direction: column; gap: 5px; }
 .dd-gp-presets button { text-align: left; flex: 0 0 auto; white-space: normal; overflow-wrap: anywhere; }
 .dd-gp-detail { display: flex; flex-direction: column; min-height: 0; min-width: 0; }
@@ -145,3 +154,7 @@
 .dd-workbench .dd-workbench-actions:empty {display:none;}
 .dd-workbench .dd-workbench-actions .dd-actions {padding:6px 10px;gap:4px;}
 .dd-workbench .dd-workbench-actions .dd-actions button {min-height:24px;padding:3px 7px;}
+
+/* Network progress belongs to the image surface, never to the graph canvas. */
+.dd-comparer .dd-preview-progress {position:absolute;left:10px;right:10px;bottom:12px;z-index:4;max-width:380px;padding:9px 12px;border:1px solid var(--dd-line);border-radius:5px;background:var(--dd-bg);color:var(--dd-text);pointer-events:none;font-size:12px;}
+.dd-comparer .dd-preview-progress progress {display:block;width:100%;height:7px;margin-top:6px;accent-color:var(--dd-accent);}

web/editor.js

@@ -1,6 +1,8 @@
-/* Original implementation, MIT licensed. No WebUI source is bundled. */
+/* SPDX-License-Identifier: GPL-3.0-only
+ * Original implementation. No WebUI source is bundled. */
 import { registerImageWheel } from "./wheel_gestures.js";
 import { T } from "./i18n.js";
+import { loadImage } from "./image_load.js";
 const el = (tag, cls, text) => {
     const node = document.createElement(tag);
     if (cls) node.className = cls;
@@ -8,12 +10,6 @@ const el = (tag, cls, text) => {
     return node;
 };
 const makeCanvas = () => document.createElement("canvas");
-const loadImage = (url) => new Promise((resolve, reject) => {
-    const image = new Image();
-    image.onload = () => resolve(image);
-        image.onerror = () => reject(new Error(T("Cannot load image")));
-    image.src = url;
-});
 
 export class InlineMaskEditor {
     constructor(options = {}) {
@@ -46,7 +42,7 @@ export class InlineMaskEditor {
         // this canvas at window capture so image gestures stay inside it.
         this.stopWheelCapture = registerImageWheel(this.canvas, () => this.ready, event => this.wheel(event), options.onGraphWheel);
         this.modifierDown = event => {
-            if (event.key !== "Alt" || !this.ready || !this.canvas.matches(":hover")) return;
+            if (event.key !== "Alt" || this.colorPaint?.active || !this.ready || !this.canvas.matches(":hover")) return;
             event.preventDefault(); this.altErase = true; this.updateButtons(); this.schedule();
         };
         this.modifierUp = event => {
@@ -249,6 +245,8 @@ export class InlineMaskEditor {
 
     async upload(file) {
         if (file.size > 64 * 1024 * 1024) { this.status(T("File is too large (max 64 MB)"), true); return; }
+        this.uploadController?.abort();
+        const controller=this.uploadController=new AbortController();
         const version = this.uploadUiVersion = (this.uploadUiVersion || 0) + 1;
         const progress = ({phase, loaded = 0, total = 0}) => {
             if (version !== this.uploadUiVersion || this.destroyed) return;
@@ -267,22 +265,24 @@ export class InlineMaskEditor {
             this.status(T("Loading image…"));
             // Keep the painted mask when a new source replaces the current one,
             // the same way adopting a result does. A first upload starts empty.
-            await this.options.onUpload?.(file, { preserveMask: !!this.image, onProgress: progress });
+            await this.options.onUpload?.(file, { preserveMask: !!this.image, onProgress: progress, signal:controller.signal });
         } catch (error) {
             if (version === this.uploadUiVersion && !this.destroyed) this.status(error.message, true);
         } finally {
+            if(this.uploadController===controller)this.uploadController=null;
             if (version === this.uploadUiVersion && !this.destroyed) this.uploadIndicator.hidden = true;
         }
     }
 
-    async setImage(url, maskData = "", name = "") {
+    async setImage(url, maskData = "", name = "", options = {}) {
         this.stroke = null; this.pointerId = null;
         const version = ++this.loadVersion;
+        const wasReady=this.ready;
         this.ready = false;
         try {
-            const [image, loadedMask] = await Promise.all([loadImage(url), maskData ? loadImage(maskData) : Promise.resolve(null)]);
+            const [image, loadedMask] = await Promise.all([loadImage(url,options), maskData ? loadImage(maskData) : Promise.resolve(null)]);
             if (version !== this.loadVersion || this.destroyed) return;
-            if (image.width * image.height > 32 * 1024 * 1024 || Math.max(image.width, image.height) > 16384) {
+            if (image.width * image.height > 32_000_000 || Math.max(image.width, image.height) > 16384) {
                 throw new Error(T("Image is too large; keep it under 32 MP and 16384 px per side"));
             }
             this.image = image;
@@ -316,14 +316,14 @@ export class InlineMaskEditor {
             this.options.onImage?.(image);
             this.status(T("Orange is the painted mask · Alt = temporary erase · Ctrl+wheel = brush size"));
         } catch (error) {
-            if (version === this.loadVersion && !this.destroyed) this.status(error.message, true);
+            if (version === this.loadVersion && !this.destroyed) {this.ready=!!this.image && wasReady;this.updateButtons();this.schedule();this.status(error.message, true);}
             throw error;
         }
     }
 
-    async replaceSource(url, name = "") {
+    async replaceSource(url, name = "", options = {}) {
         const version = ++this.loadVersion;
-        const image = await loadImage(url);
+        const image = await loadImage(url,options);
         if (version !== this.loadVersion || this.destroyed) return false;
         // A different size cannot keep the painted mask; report it so the caller
         // can fall back to a fresh load instead of failing the upload.
@@ -357,6 +357,7 @@ export class InlineMaskEditor {
     }
 
     setTool(tool) {
+        if (this.colorPaint?.active) { this.colorPaint.active = false; this.colorPaint.sync(); }
         this.tool = tool;
         if (this.stage) this.stage.classList.toggle("dd-pan", tool === "pan");
         this.updateButtons();
@@ -368,7 +369,7 @@ export class InlineMaskEditor {
         if (this.downloadButton) this.downloadButton.disabled = !this.image;
         this.stage?.classList.toggle("dd-erasing", !!(this.altErase || this.tool === "erase" || this.stroke?.type === "erase"));
         for (const [name, button] of Object.entries(this.toolButtons || {})) {
-            const active = name === (this.altErase ? "erase" : this.tool);
+            const active = !this.colorPaint?.active && name === (this.altErase ? "erase" : this.tool);
             button.classList.toggle("dd-active", active);
             button.setAttribute("aria-pressed", String(active));
         }
@@ -418,7 +419,8 @@ export class InlineMaskEditor {
 
     pointerMove(event) {
         if (!this.ready) return;
-        if (this.altErase !== !!event.altKey) { this.altErase = !!event.altKey; this.updateButtons(); }
+        const eraseModifier=!!event.altKey && !this.colorPaint?.active;
+        if (this.altErase !== eraseModifier) { this.altErase = eraseModifier; this.updateButtons(); }
         this.cursor = this.point(event);
         if (event.pointerId === this.pointerId) {
             event.preventDefault(); event.stopPropagation();
@@ -718,6 +720,7 @@ export class InlineMaskEditor {
     }
 
     destroy() {
+        this.uploadController?.abort();++this.uploadUiVersion;
         this.destroyed = true; ++this.loadVersion;
         cancelAnimationFrame(this.frame); this.observer.disconnect();
         this.stopWheelCapture();

web/group_presets.js

@@ -19,7 +19,15 @@ class GroupPresetsPanel {
             this.refresh(true);
         });
         const toolbar = el("div", "dd-gp-toolbar"); toolbar.append(el("strong", "", T("Group presets")));
-        this.add = this.button(toolbar, T("+ New preset"), () => this.showForm("add"));
+        const tools = el("div", "dd-gp-toolbar-actions"); toolbar.append(tools);
+        this.toggleDetail = this.button(tools, "", () => {
+            app.canvas?.emitBeforeChange?.();
+            this.node.properties.adachi_group_detail_hidden = !this.node.properties.adachi_group_detail_hidden;
+            this.updateDetail();
+            app.canvas?.emitAfterChange?.();
+            this.node.graph?.setDirtyCanvas(true, true);
+        });
+        this.add = this.button(tools, T("+ New preset"), () => this.showForm("add"));
         this.form = el("form", "dd-gp-form"); this.form.hidden = true;
         this.nameInput = el("input"); this.nameInput.type = "text"; this.nameInput.maxLength = 120;
         this.nameInput.setAttribute("aria-label", T("Preset name"));
@@ -28,9 +36,9 @@ class GroupPresetsPanel {
         this.button(this.form, T("Cancel"), () => { this.form.hidden = true; });
         this.form.onsubmit = event => { event.preventDefault(); this.submitName(); };
         this.nameInput.onkeydown = event => { event.stopPropagation(); if (event.key === "Escape") { event.preventDefault(); this.form.hidden = true; } };
-        const body = el("div", "dd-gp-body");
+        const body = this.body = el("div", "dd-gp-body");
         this.presets = el("nav", "dd-gp-presets dd-gp-scroll"); this.presets.setAttribute("aria-label", T("Presets"));
-        const detail = el("section", "dd-gp-detail");
+        const detail = this.detail = el("section", "dd-gp-detail");
         const head = el("div", "dd-gp-detail-head"); this.title = el("strong"); head.append(this.title);
         this.rename = this.button(head, T("Rename"), () => this.showForm("rename"));
         this.groups = el("div", "dd-gp-groups dd-gp-scroll"); this.groups.setAttribute("aria-label", T("Group states"));
@@ -50,7 +58,16 @@ class GroupPresetsPanel {
         };
         window.addEventListener("wheel", this.onWheel, { capture: true, passive: false });
         this.timer = setInterval(() => { if (this.root.isConnected && !document.hidden) this.refresh(); }, 500);
-        this.refresh(true);
+        this.updateDetail(); this.refresh(true);
+    }
+    updateDetail() {
+        const hidden = !!this.node.properties.adachi_group_detail_hidden;
+        this.detail.hidden = hidden;
+        this.body.classList.toggle("dd-gp-collapsed", hidden);
+        this.toggleDetail.textContent = hidden ? "▶" : "◀";
+        this.toggleDetail.title = T(hidden ? "Show group details" : "Hide group details");
+        this.toggleDetail.setAttribute("aria-label", this.toggleDetail.title);
+        this.toggleDetail.setAttribute("aria-expanded", String(!hidden));
     }
     button(parent, label, callback) { const button = el("button", "", label); button.type = "button"; button.onclick = event => { event.stopPropagation(); callback(); }; parent.append(button); return button; }
     showForm(mode) {
@@ -122,7 +139,7 @@ app.registerExtension({
                 widget.serialize = false; this.setSize([620, 410]);
             }
             onAdded() { this.adachiGroupPresets.refresh(true); }
-            onConfigure() { this.adachiGroupPresets.model.restore(); this.adachiGroupPresets.refresh(true); }
+            onConfigure() { this.adachiGroupPresets.model.restore(); this.adachiGroupPresets.updateDetail(); this.adachiGroupPresets.refresh(true); }
             onRemoved() { this.adachiGroupPresets.destroy(); }
             getExtraMenuOptions(_, options) {
                 const panel = this.adachiGroupPresets;

web/i18n.js

@@ -6,8 +6,155 @@
 // buttons are drawn by this plugin, so they translate here by reading Comfy.Locale.
 
 const ZH = {
+  "Image upload timed out; check the connection and try again": "图片上传超时，请检查连接后重试",
+  "Load a source image first": "请先载入原图",
+  "Finish the current edit first": "请先结束当前编辑",
+  "The source image node was removed": "原图节点已移除",
+  "The image changed during restoration; try again": "图片在恢复过程中发生变化，请重试",
+  "The saved mask state is invalid": "历史蒙版状态无效",
+  "Source image": "原图",
+  "Edited source": "编辑中的原图",
+  "Processing the source image; please wait": "正在处理原图，请稍候",
+  "The source image history entry no longer exists": "原图历史不存在",
+  // Workbench panels, execution status and accessibility labels.
+  "Reading the current workflow…": "正在读取当前工作流…",
+  "Switch theme": "切换主题",
+  "Check connections": "检查连接",
+  "Return to workflow": "返回工作流",
+  "Edit mask": "编辑蒙版",
+  "Slide to compare": "滑动对比",
+  "Show before": "查看前图",
+  "Show after": "查看后图",
+  "Adopt": "采用",
+  "Use this result as the next source image and keep the mask; restore earlier images below": "采用当前结果作为下一轮原图，保留蒙版；下方可回退或选择之前的原图",
+  "Selected source image or generated result": "当前选择的前图或重绘结果",
+  "↶ Undo": "↶ 回退",
+  "Initial source": "初始原图",
+  "Choose an adopted source image": "选择已采用原图",
+  "Restore the previous source image, mask and crop": "回退到之前的原图，同时恢复蒙版和裁切状态",
+  "Restore the initial source image of this session": "恢复本次工作流会话中的初始原图",
+  "Choose an earlier adopted or uploaded source image": "选择之前采用或上传的原图",
+  "Current stage progress": "当前执行阶段进度",
+  "Actual progress from the current node; stages without step counts show an indeterminate bar": "显示当前节点的真实进度；没有步数的阶段显示等待动画",
+  "Workflow settings": "工作流设置",
+  "Generate": "生成",
+  "Generating": "生成中",
+  "Generation complete": "生成完成",
+  "Controls are not ready; reopen the workbench shortly": "控件尚未初始化，请稍后重新打开",
+  "This workflow needs Inline Mask, Adachi Inpaint Workbench and Image Compare nodes": "当前工作流需要内联蒙版、安达重绘工作台和图像对比节点",
+  "Source when opened": "打开时原图",
+  "Adopted result": "采用重绘结果",
+  "Uploaded source": "上传原图",
+  "Generation stopped": "生成已停止",
+  "Generating…": "生成中…",
+  "Workflow connections": "工作流连接",
+  "Multiple candidates found; select the nodes to use": "存在多个候选，请选择本次使用的节点",
+  "Inpaint node": "重绘节点",
+  "Image editor": "图像编辑",
+  "Image comparison": "图像对比",
+  "No preset controller": "不使用预设",
+  "Use these connections": "使用此连接",
+  "Select nodes from this workflow; this inpaint node remembers your choices": "选择当前工作流中的节点；同一重绘节点会记住本次选择",
+  "The workflow changed": "工作流已切换",
+  "Select the nodes to use in Workflow connections first": "请先在工作流连接中选择本次使用的节点",
+  "Upload a source image first": "请先上传原图",
+  "Checking in the background…": "后台检查中…",
+  "Workflow validation failed": "工作流检查未通过",
+  "Ready to generate": "检查通过 · 可以生成",
+  "Checking…": "检查中…",
+  "Queued for generation": "已进入生成队列",
+  "Generation failed; check the ComfyUI error log": "生成失败，请查看 ComfyUI 错误信息",
+  "Switch to light theme": "切换为白色主题",
+  "Switch to dark theme": "切换为黑色主题",
+  "Current workflow": "当前工作流",
+  "Reading workflow connections": "正在读取工作流连接",
+  "Actual sampler connections": "实际采样器连线",
+  "Main model": "主模型",
+  "Text encoder": "文本编码器",
+  "The group preset no longer exists": "分组预设不存在",
+  "Reading workflow connections; please wait": "正在读取工作流连接，请稍候",
+  "Some model lists are unavailable; existing workflow selections remain usable": "部分模型列表不可用，可保留工作流中的现有选择",
+  "Multiple group preset controllers found; choose one in Workflow connections.": "存在多个分组预设控制器，请在工作流连接中选择。",
+  "No enabled Group Bypass Presets node; using the current workflow settings.": "未启用组忽略预设节点，当前使用原工作流设置。",
+  "Main model and LoRA": "主模型与 LoRA",
+  "This profile uses the model from the workflow": "当前方案的模型由原工作流控制",
+  "Inherit workflow LoRAs": "沿用工作流 LoRA",
+  "Keep existing LoRA nodes and both CLIP branches; uncheck to use the custom list below. An empty custom list disables recognized LoRAs.": "保留原有 LoRA 节点及正负 CLIP 分支；取消后使用下方自定义列表，空列表即禁用已识别的 LoRA",
+  "No active LoRAs in the original workflow": "原工作流没有启用的 LoRA",
+  "No LoRA": "不使用 LoRA",
+  "None": "不使用",
+  "Remove this LoRA": "移除此 LoRA",
+  "＋ Add LoRA": "＋ 添加 LoRA",
+  "Use the workflow Refiner (must be compatible with the main model)": "使用工作流中的 Refiner（需与主模型兼容）",
+  "Positive prompt": "正面提示词",
+  "Negative prompt": "负面提示词",
+  "Fit comparison image": "适应对比图片",
+  "Controlled by the original workflow": "由原工作流控制",
+  "Reading connections…": "正在读取连接…",
+  "Encoders are identified from the execution graph; unrecognized conditioning stays controlled by the original workflow": "通过实际执行图查找编码器；无法明确识别的条件保留原工作流",
+  "Inherit upstream dynamic text; type to override": "沿用上游动态文本；输入后覆盖",
+  "Text comes from upstream; typing creates an override.": "文本来自上游；主动输入才覆盖。",
+  "Changes affect only this encoder; downstream conditioning is preserved.": "修改仅影响所选编码器，保留下游条件处理。",
+  "Loading main model": "加载主模型",
+  "Loading text encoder": "加载文本编码器",
+  "Loading VAE": "加载 VAE",
+  "Encoding prompts": "编码提示词",
+  "Loading LoRA": "加载 LoRA",
+  "Reading source image and mask": "读取原图与蒙版",
+  "Preparing inpaint sampling": "重绘采样准备",
+  "KSampler": "K 采样器",
+  "VAE decode": "VAE 解码",
+  "VAE encode": "VAE 编码",
+  "Preparing comparison images": "准备对比图片",
+  "Queued…": "排队中…",
+  "Executing workflow": "正在执行工作流",
+  "Reconnected; waiting for execution progress…": "已重连，等待执行进度…",
+  "Connection lost; recovering execution progress…": "连接中断，正在恢复进度…",
+  "Starting execution…": "开始执行…",
+  "Inpaint sampling (KSampler)": "重绘采样（K 采样器）",
+  "Resize canvas and settings": "调整画布与配置宽度",
+  "Drag to resize the canvas and settings; double-click to reset, or use arrow keys for fine adjustments": "拖动调整画布与配置宽度；双击恢复，方向键微调",
+  "The workbench backend is not loaded. Stop and restart ComfyUI, then check connections again; refreshing the browser is not enough.": "工作台后端尚未加载：请在 ComfyUI 启动器中停止后重新启动服务，再点击检查连接（仅刷新网页不够）",
+  "Submission timed out. Check the task queue before retrying to avoid duplicate generations.": "提交超时，请先检查任务队列，避免重复生成",
+  "Connection check timed out; check your network and retry": "连接检查超时，请检查网络后重试",
+  "The workflow changed; reopen the workbench": "工作流已切换，请重新打开工作台",
+  "Workflow connections could not be resolved; check bypass states, Get/Set and broadcast connections": "工作流连线无法解析，请检查忽略状态、Get/Set 或广播连线",
+  "The workflow changed; check connections again": "工作流已切换，请重新检查",
+  "The selected image, inpaint or comparison node is missing from the execution graph": "选中的图像、重绘或对比节点未出现在执行图中",
+  "The selected inpaint node is missing from the execution graph": "所选重绘节点未出现在执行图中",
+  "Connect a main model before adding LoRAs": "请连接主模型后再添加 LoRA",
+  "Open Adachi Workbench": "打开安达工作台",
+  "Text encoder {index}": "文本编码器 {index}",
+  "Model list request failed ({status})": "模型列表加载失败（{status}）",
+  "Missing {count} model files": "缺少 {count} 份模型文件",
+  "{label}: {value}": "{label}：{value}",
+  "LoRA {index} strength": "LoRA {index} 强度",
+  "LoRA {index}": "LoRA {index}",
+  "{label} · {count} encoders": "{label} · {count} 个编码器",
+  "Actual sampler connections · {node} #{id} · {field}. {description}": "实际采样器连线 · {node} #{id} · {field}。{description}",
+  "Restore {label} from the workflow": "恢复工作流中的{label}",
+  "Reading cache · {count} nodes": "读取缓存 · {count} 个节点",
+  "Settings panel {width} pixels wide": "右侧配置 {width} 像素",
+  "Invalid workbench response ({status}); check your proxy settings or restart ComfyUI": "工作台服务响应无效（{status}），请检查代理配置或重启 ComfyUI",
+  "{label} not found: {value}": "未找到{label}：{value}",
+  "The selected parameter node is missing from the execution graph #{id}": "所选参数节点未出现在执行图中 #{id}",
+
+  "Comparison image loading progress": "对比图片加载进度",
+  "Waiting for the generated image…": "等待生成结果，完成后自动找回…",
+  "Generation failed; check the ComfyUI task history": "生成失败，请查看 ComfyUI 任务历史",
+  "Loading comparison images": "正在加载对比图片",
+  "Retrying comparison images": "正在重试对比图片",
+  "Decoding comparison images…": "下载完成，正在解码图片…",
+  "Waiting to retry comparison images": "等待自动重试图片",
+  "Image loading failed; retrying automatically. You can also click reload.": "图片加载失败，正在自动重试；也可点击刷新。",
+  "Show group details": "展开分组详情",
+  "Hide group details": "收起分组详情",
+  "Reload comparison images": "重新加载对比图片",
   "Image upload progress": "图片上传进度",
   "Uploading image": "正在上传图片",
+  "Downloading result…": "正在下载结果…",
+  "Uploading result…": "正在上传结果…",
+  "Preparing result…": "正在准备结果…",
   "Uploading image…": "正在上传图片…",
   "Upload complete, loading image…": "上传完成，正在加载图片…",
   "Uploading with authentication…": "正在通过身份验证上传…",
@@ -100,6 +247,13 @@ const ZH = {
   "Pan": "移动",
   "Pan (H), or hold Space": "移动 (H)，或按住空格",
   "Brush size": "笔径",
+  "Paint image pixels; Alt-click picks a color; Ctrl+wheel changes brush size": "画笔：Alt 加左键吸取颜色，Ctrl 加滚轮调整笔径",
+  "Brush color": "画笔颜色",
+  "Undo color painting": "撤销画笔",
+  "Redo color painting": "重做画笔",
+  "Paint layer dimensions do not match the source image": "画笔图层尺寸与原图不一致",
+  "Paint layer could not be saved as an input file; embedded data was retained": "无法将画笔图层保存到输入目录，已保留嵌入数据",
+  "The paint layer is unavailable; update and restart ComfyUI": "画笔图层不可用，请更新并重启 ComfyUI",
   "Hardness": "硬度",
   "Brush opacity": "笔触",
   "Overlay": "叠加",
@@ -147,9 +301,9 @@ const ZH = {
   "The painting tools live in the other inpaint node connected to this image": "画笔工具位于连接此原图的另一个重绘节点",
 
   // inpaint_panel.js
-  "WebUI Inpaint": "WebUI 局部重绘",
+  "Adachi Inpaint Workbench": "安达重绘工作台",
   "Controlled WebUI inpaint node": "控制的局部重绘节点",
-  "Connect a WebUI inpaint node to edit its parameters here": "连接 WebUI 局部重绘节点后，在这里调整参数",
+  "Connect a WebUI inpaint node to edit its parameters here": "连接安达重绘工作台后，在这里调整参数",
   "Mask mode": "重绘区域",
   "Fill content": "重绘参考内容",
   "Sampling area": "重绘画布",
@@ -203,28 +357,33 @@ const ZH = {
 const DICTS = { zh: ZH };
 
 function readLocale() {
-  try {
-    const api = globalThis.comfyAPI;
-    const value = api?.app?.ui?.settings?.getSettingValue?.("Comfy.Locale");
-    if (value) return String(value);
-  } catch (_) { /* settings unavailable before the app boots */ }
-  try {
-    const value = globalThis.app?.ui?.settings?.getSettingValue?.("Comfy.Locale");
-    if (value) return String(value);
-  } catch (_) { /* ignore */ }
+  // Modern frontends expose an ES-module namespace at comfyAPI.app, while
+  // earlier builds exposed the app directly. Never infer the UI language from
+  // the browser: ComfyUI's selected locale is the user's explicit preference.
+  const api = globalThis.comfyAPI;
+  for (const app of [api?.app?.app, api?.app, globalThis.app]) {
+    try {
+      const value = app?.ui?.settings?.getSettingValue?.("Comfy.Locale");
+      if (value) return String(value);
+    } catch (_) { /* settings may be unavailable before the app boots */ }
+  }
   return "en";
 }
 
 export function localeDict() {
-  const base = readLocale().split("-")[0].toLowerCase();
-  return DICTS[base] || null;
+  const base = readLocale().split(/[-_]/)[0].toLowerCase();
+  return Object.hasOwn(DICTS, base) ? DICTS[base] : null;
 }
 
-// Translate a user-facing string. `context` disambiguates identical English strings
-// that need different translations (for example the Fill button and the Fill enum).
-export function T(text, context) {
+// English is the fallback for every locale. The optional string context retains
+// enum disambiguation; an object supplies named values without concatenating
+// translated fragments. Values remain text and are never interpreted as HTML.
+export function T(text, contextOrParams, params = {}) {
+  const context = typeof contextOrParams === "string" ? contextOrParams : null;
+  const values = contextOrParams && typeof contextOrParams === "object" ? contextOrParams : params;
   const dict = localeDict();
-  if (!dict) return text;
   const key = context ? `${context}:${text}` : text;
-  return dict[key] ?? text;
+  const translated = dict && Object.hasOwn(dict, key) ? dict[key] : text;
+  return translated.replace(/\{([A-Za-z][A-Za-z0-9_]*)\}/g, (placeholder, name) =>
+    Object.hasOwn(values, name) ? String(values[name]) : placeholder);
 }

web/image_load.js

@@ -0,0 +1,24 @@
+import {T} from './i18n.js';
+
+// Retry only freshly uploaded same-origin view URLs. Local files, data URLs and
+// restored inputs keep their original behavior. Each retry bypasses cached 404s.
+export async function loadImage(url,{retry=false,signal,timeoutMs=15000,delays=[300,900]}={}) {
+    const parsed=new URL(url,location.href);
+    const canRetry=retry && parsed.origin===location.origin && /\/view$/.test(parsed.pathname);
+    const attempts=canRetry?delays.length+1:1;
+    for(let i=0;i<attempts;i++){
+        signal?.throwIfAborted();
+        if(i){await new Promise((resolve,reject)=>{const timer=setTimeout(done,delays[i-1]);function done(){signal?.removeEventListener('abort',abort);resolve();}function abort(){clearTimeout(timer);reject(new DOMException('Aborted','AbortError'));}signal?.addEventListener('abort',abort,{once:true});});}
+        const image=new Image();
+        try{
+            await new Promise((resolve,reject)=>{
+                const finish=fn=>value=>{clearTimeout(timer);signal?.removeEventListener('abort',abort);image.onload=image.onerror=null;fn(value);};
+                const success=finish(resolve),failure=finish(reject),abort=()=>{image.src='';failure(new DOMException('Aborted','AbortError'));};
+                const timer=setTimeout(()=>failure(new Error(T('Cannot load image'))),timeoutMs);
+                image.onload=success;image.onerror=()=>failure(new Error(T('Cannot load image')));signal?.addEventListener('abort',abort,{once:true});
+                const request=new URL(parsed);if(i)request.searchParams.set('_adachi_retry',String(i));image.src=request.href;
+            });
+            return image;
+        }catch(error){if(error.name==='AbortError'||i===attempts-1)throw error;}
+    }
+}

web/inline_crop.js

@@ -1,7 +1,7 @@
 import { CROP_PRESETS, cropAt } from "./crop_geometry.js?v=0.6.2";
 import { T } from "./i18n.js";
 import { syncCropDimensions, syncCurrentDimensions } from "./parameter_bridge.js?v=0.8.2";
-import { installResultAdoption } from "./result_adoption.js?v=0.7.2";
+import { installResultAdoption } from "./result_adoption.js?v=2.1.0";
 
 const fields = ["mask", "baseMask", "history", "future", "lastMask", "dirty"];
 const canvas = (w, h) =>
@@ -628,9 +628,26 @@ export class InlineCropController {
     this.editor.flush();
     this.busy = true;
     this.sync();
+    // Releasing an adopted crop must first preserve the visible composite on
+    // the server. Show its real upload progress, particularly on remote hosts;
+    // do not unlock or discard the layer if that upload fails.
+    const e = this.editor;
+    const version = e.uploadUiVersion = (e.uploadUiVersion || 0) + 1;
+    const progress = ({phase, loaded = 0, total = 0}) => {
+      if (version !== e.uploadUiVersion || e.destroyed) return;
+      e.uploadIndicator.hidden = false;
+      if (phase === "upload" && total > 0) {
+        const percent = Math.max(0, Math.min(100, Math.round(100 * loaded / total)));
+        e.uploadLabel.textContent = `${T("Uploading image")} ${percent}%`;
+        e.uploadBar.value = percent;
+      } else {
+        e.uploadLabel.textContent = T(phase === "processing" ? "Upload complete, loading image…" : phase === "authenticated" ? "Uploading with authentication…" : "Uploading image…");
+        e.uploadBar.removeAttribute("value");
+      }
+    };
+    progress({phase:"upload"});
     try {
-      const e = this.editor,
-        c = canvas(e.image.width, e.image.height);
+      const c = canvas(e.image.width, e.image.height);
       this.drawSource(c.getContext("2d"));
       const blob = await new Promise((resolve) =>
         c.toBlob(resolve, "image/png"),
@@ -641,14 +658,17 @@ export class InlineCropController {
         new File([blob], `merged-${crypto.randomUUID()}.png`, {
           type: "image/png",
         }),
-        { preserveMask: true, preserveCrop: true },
+        { preserveMask: true, preserveCrop: true, onProgress: progress },
       );
+      e.status("");
       this.layer = null;
       this.widgets.layer_image.value = "";
       this.widgets.blend_data.value = "";
+      for(const key of ['mask','baseMask']){const raster=this.contexts.blend?.[key];if(raster && raster!==e.mask && raster!==e.baseMask)raster.width=raster.height=0;}
       this.contexts.blend = null;
       this.state({ ...this.region, job: crypto.randomUUID() });
     } finally {
+      if (version === e.uploadUiVersion && !e.destroyed) e.uploadIndicator.hidden = true;
       this.busy = false;
       this.sync();
       this.editor.schedule();
@@ -670,6 +690,7 @@ export class InlineCropController {
     this.changed();
   }
   destroy() {
+    this.adoptController?.abort();
     this.stopOriginalPreview();
     window.removeEventListener("blur", this.previewBlur);
     for (const name of ["pointerup", "pointercancel"]) {

web/inline_inpaint.js

@@ -1,19 +1,21 @@
 import { app } from "../../scripts/app.js";
 import { api } from "../../scripts/api.js";
-import { InlineMaskEditor } from "./editor.js?v=0.9.0";
-import { installInpaintWorkbench } from "./inpaint_node.js?v=0.8.2";
-import { bindWidgetToNodeWidth } from "./widget_layout.js?v=0.5.5";
+import { InlineMaskEditor } from "./editor.js?v=2.1.0";
+import { installInpaintWorkbench } from "./inpaint_node.js?v=toolbar-layout-20261112";
+import { bindWidgetToNodeWidth, createWidgetHost } from "./widget_layout.js?v=stable-host-20261112";
 import { routeWheelOutsideImage } from "./wheel_routing.js";
-import { InlineCropController } from "./inline_crop.js?v=0.8.2";
-import { canStoreDraft, prepareInlineDraft, syncInlineWidgets } from "./draft_guard.js?v=0.6.3";
+import { InlineCropController } from "./inline_crop.js?v=2.1.0";
+import { canStoreDraft, prepareInlineDraft, syncInlineWidgets } from "./draft_guard.js?v=2.1.0";
 import { T } from "./i18n.js";
 import { removeLegacyFeedback } from "./legacy_feedback.js?v=0.6.4";
-import { uploadImageWithProgress } from "./upload_transport.js?v=0.9.0";
+import { uploadImageWithProgress } from "./upload_transport.js?v=stability1";
+import { ColorPaint } from "./color_paint.js?v=toolbar-layout-20261112";
+import { createPaintDraftProtection } from "./paint_draft.js";
 
 const styleId = "adachi-inpaint-style";
 const stylesheet = document.getElementById(styleId) || document.createElement("link");
 stylesheet.id = styleId; stylesheet.rel = "stylesheet";
-stylesheet.href = new URL("./editor.css?v=0.9.0", import.meta.url).href;
+stylesheet.href = new URL("./editor.css?v=toolbar-layout-20261112", import.meta.url).href;
 if (!stylesheet.isConnected) document.head.append(stylesheet);
 
 function hide(widget) {
@@ -71,7 +73,7 @@ app.registerExtension({
             const count = await prepareInlineDraft(graphData, {
                 fits: graph => canStoreDraft(graph, options), upload: uploadEmbeddedSource,
             });
-            if (count) console.info(`[Adachi Inpaint] Saved ${count} oversized embedded source(s) as exact input files before workflow draft initialization. Masks and layers were preserved.`);
+            if (count) console.info(`[Adachi Inpaint] Saved ${count} oversized embedded source or paint layer(s) as input files before workflow draft initialization.`);
         } catch (error) {
             console.warn("[Adachi Inpaint] Draft preflight failed; embedded source data was retained.", error);
         }
@@ -93,8 +95,8 @@ app.registerExtension({
                 node.graph?.setDirtyCanvas(true, true);
             };
             const find = name => node.widgets?.find(widget => widget.name === name);
-            const imageWidget = find("image"), maskWidget = find("mask_data"), sourceWidget = find("source_data");
-            for (const widget of [imageWidget, maskWidget, sourceWidget]) hide(widget);
+            const imageWidget = find("image"), maskWidget = find("mask_data"), sourceWidget = find("source_data"), paintWidget=find("paint_data");
+            for (const widget of [imageWidget, maskWidget, sourceWidget, paintWidget]) hide(widget);
             let crop;
             let draftRecovery = null;
             let draftNoticeTimer = 0;
@@ -105,7 +107,7 @@ app.registerExtension({
             const fitNodeToImage = () => {
                 cancelAnimationFrame(fitFrame);
                 fitFrame = requestAnimationFrame(() => {
-                    if (!editor.ready || editor.destroyed || !node.graph) return;
+                    if (!editor.ready || editor.destroyed || !node.graph || editor.root.closest(".adachi-workspace")) return;
                     const width = editor.canvas.clientWidth, height = editor.canvas.clientHeight;
                     if (!width || !height) return;
                     const overhead = node.size[1] - height;
@@ -121,8 +123,8 @@ app.registerExtension({
                 if (!embedded && !filename) return;
                 restoring = true;
                 editor.embed.checked = !!embedded;
-                try { crop?.activate("mask"); await editor.setImage(embedded || imageUrl(filename), maskWidget?.value || "", embedded ? T("Embedded image") : filename); await crop?.restore(); }
-                catch (error) { console.warn("[Adachi Inpaint]", error); }
+                try { crop?.activate("mask"); await editor.setImage(embedded || imageUrl(filename), maskWidget?.value || "", embedded ? T("Embedded image") : filename); await crop?.restore(); await node.adachiColorPaint?.restore(paintWidget?.value || ""); }
+                catch (error) { console.warn("[Adachi Inpaint]", error); editor.status(error.message, true); }
                 finally { restoring = false; }
             };
             const editor = new InlineMaskEditor({
@@ -132,34 +134,30 @@ app.registerExtension({
                 onKeepFit(enabled) { node.properties.adachi_keep_fit = enabled; markChanged(); },
                 onImage() { if (!restoring || !node.properties.adachi_compact_ui) fitNodeToImage(); },
                 onGraphWheel: event => app.canvas?.processMouseWheel(event),
-                async onUpload(file, { preserveMask = false, preserveCrop = false, onProgress = null } = {}) {
+                async onUpload(file, { preserveMask = false, preserveCrop = false, onProgress = null, signal } = {}) {
                     if (preserveMask && editor.image && !editor.ready) throw new Error(T("Wait for the current image to finish loading"));
                     const version = ++uploadVersion;
                     const body = new FormData();
                     body.append("image", file, file.name);
                     body.append("type", "input");
                     body.append("subfolder", "adachi-inpaint");
-                    let uploaded;
-                    if (onProgress) uploaded = await uploadImageWithProgress(api, body, onProgress);
-                    else {
-                        const response = await api.fetchApi("/upload/image", { method: "POST", body });
-                        if (!response.ok) throw new Error(`${T("Upload failed")} (${response.status})`);
-                        uploaded = await response.json();
-                    }
+                    const uploaded = await uploadImageWithProgress(api, body, onProgress, {signal});
                     if (typeof uploaded?.name !== "string" || !uploaded.name) throw new Error(T("Upload failed"));
                     if (version !== uploadVersion || editor.destroyed) return;
+                    signal?.throwIfAborted();
                     const name = uploaded.subfolder ? `${uploaded.subfolder}/${uploaded.name}` : uploaded.name;
                     restoring = false;
                     crop?.activate("mask");
                     let kept = false;
                     if (preserveMask && editor.ready) {
-                        kept = await editor.replaceSource(imageUrl(name), file.name);
+                        kept = await editor.replaceSource(imageUrl(name), file.name, {retry:true,signal});
                         if (version !== uploadVersion || editor.destroyed) return;
                         // A different-sized replacement cannot reuse the old mask.
                         // Actually load it as a fresh image before clearing state.
-                        if (!kept) await editor.setImage(imageUrl(name), "", file.name);
-                    } else await editor.setImage(imageUrl(name), "", file.name);
+                        if (!kept) await editor.setImage(imageUrl(name), "", file.name, {retry:true,signal});
+                    } else await editor.setImage(imageUrl(name), "", file.name, {retry:true,signal});
                     if (version !== uploadVersion || editor.destroyed) return;
+                    if (!preserveCrop) node.adachiColorPaint?.clear();
                     imageWidget.value = name;
                     maskWidget.value = kept ? editor.flush() : "";
                     sourceWidget.value = editor.embed.checked ? editor.sourceData() : "";
@@ -203,22 +201,28 @@ app.registerExtension({
             crop = new InlineCropController(node, editor, {find, hide, changed:markChanged, imageUrl, beforeModeChange});
             node.adachiCrop = crop;
             node.adachiEditor = editor;
+            const paintDraft=createPaintDraftProtection({paint:()=>node.adachiColorPaint,widget:()=>paintWidget,graph:()=>app.rootGraph||node.graph,disposed:()=>editor.destroyed||!node.graph,persist:()=>app.ui.settings.getSettingValue('Comfy.Workflow.Persist')!==false,fits:graph=>canStoreDraft(graph.serialize(),draftOptions()),upload:uploadEmbeddedSource,changed:markChanged,onError:error=>editor.status(`${T("Paint layer could not be saved as an input file; embedded data was retained")}: ${error.message}`,true)});
+            node.adachiColorPaint = new ColorPaint(editor,crop,paintWidget,paintDraft.schedule,imageUrl);
+            editor.colorPaint=node.adachiColorPaint;
+            const acceptCrop=crop.accept.bind(crop);
+            crop.accept=async(...args)=>{const old=crop.widgets.layer_image.value,region={...crop.region};const result=await acceptCrop(...args);if(crop.widgets.layer_image.value && crop.widgets.layer_image.value!==old)node.adachiColorPaint.clearRegion(region);return result;};
             const stopWheelRouting = routeWheelOutsideImage(editor.root, editor.canvas, () => editor.ready);
-            node.adachiUseResult = async (file, origin) => {
+            node.adachiUseResult = async (file, origin, options={}) => {
                 if (editor.destroyed) throw new Error(T("The inline mask node was removed"));
-                if (crop.mode === "crop") return node.adachiAdoptCrop(file, origin);
-                await editor.options.onUpload(file, { preserveMask: true });
+                if (crop.mode === "crop") return node.adachiAdoptCrop(file, origin, options);
+                await editor.options.onUpload(file, { preserveMask: true, signal:options.signal, onProgress:options.onProgress });
                 editor.view = "overlay"; editor.updateButtons(); editor.schedule();
                 editor.status(T("Adopted the result as the new source image; the mask and undo history were preserved"));
             };
-            const domWidget = node.addDOMWidget("adachi_canvas", "adachi_inline_mask", editor.root, {
+            const widgetHost = createWidgetHost(editor.root);
+            const domWidget = node.addDOMWidget("adachi_canvas", "adachi_inline_mask", widgetHost, {
                 serialize: false,
                 hideOnZoom: false,
                 getMinHeight: () => 170,
                 getMaxHeight: () => 4096,
             });
             domWidget.serialize = false;
-            bindWidgetToNodeWidth(node, domWidget, editor.root);
+            bindWidgetToNodeWidth(node, domWidget, widgetHost);
             // Leave computeLayoutSize in charge: a fixed computeSize height
             // prevents the DOM canvas from growing with the node vertically.
             const resizeHandle = document.createElement("div");
@@ -265,17 +269,20 @@ app.registerExtension({
             const previousSerialize = maskWidget.serializeValue;
             maskWidget.serializeValue = function () {
                 editor.flush();
+                if(node.adachiColorPaint.drawing) node.adachiColorPaint.flush();
                 return previousSerialize ? previousSerialize.apply(this, arguments) : maskWidget.value;
             };
             const previousSerializeNode = node.onSerialize;
             node.onSerialize = function (data) {
                 const result = previousSerializeNode?.apply(this, arguments);
                 editor.flush();
+                if(node.adachiColorPaint.drawing) node.adachiColorPaint.flush();
                 if (data) syncInlineWidgets(data, node.widgets);
                 return result;
             };
             const previousQueued = maskWidget.beforeQueued;
-            maskWidget.beforeQueued = function () { editor.flush(); return previousQueued?.apply(this, arguments); };
+            maskWidget.beforeQueued = function () { editor.flush(); if(node.adachiColorPaint.drawing) node.adachiColorPaint.flush(); return previousQueued?.apply(this, arguments); };
+            if(paintWidget){const previousPaintSerialize=paintWidget.serializeValue;paintWidget.serializeValue=function(){if(node.adachiColorPaint.drawing)node.adachiColorPaint.flush();return previousPaintSerialize?previousPaintSerialize.apply(this,arguments):paintWidget.value;};}
             const previousConfigure = node.onConfigure;
             node.onConfigure = function () {
                 const configured = previousConfigure?.apply(this, arguments);
@@ -286,7 +293,7 @@ app.registerExtension({
             const previousImageCallback = imageWidget.callback;
             imageWidget.callback = function () { previousImageCallback?.apply(this, arguments); restore(); };
             const previousRemoved = node.onRemoved;
-            node.onRemoved = function () { clearTimeout(draftNoticeTimer); cancelAnimationFrame(restoreFrame); cancelAnimationFrame(fitFrame); stopWheelRouting(); crop.destroy(); editor.destroy(); return previousRemoved?.apply(this, arguments); };
+            node.onRemoved = function () { node.adachiWorkspaceHistory?.clear();node.adachiWorkspaceHistory=null;clearTimeout(draftNoticeTimer);paintDraft.dispose(); cancelAnimationFrame(restoreFrame); cancelAnimationFrame(fitFrame); stopWheelRouting(); node.adachiColorPaint.destroy();crop.destroy(); editor.destroy(); return previousRemoved?.apply(this, arguments); };
             node.setSize([Math.max(380, node.size[0]), Math.max(480, node.size[1])]);
             restoreFrame = requestAnimationFrame(restore);
             return result;

web/inpaint_node.js

@@ -1,15 +1,22 @@
 import { app } from "../../scripts/app.js";
-import { InpaintParameterPanel } from "./inpaint_panel.js?v=0.6.1";
+import { InpaintParameterPanel } from "./inpaint_panel.js?v=toolbar-layout-20261112";
 import { connectedEditor, connectedSamplers, relocateWidgets, syncCurrentDimensions } from "./parameter_bridge.js?v=0.8.2";
 import { routeWheelOutsideImage } from "./wheel_routing.js";
 import { T } from "./i18n.js";
-import { bindWidgetToNodeWidth } from "./widget_layout.js?v=0.5.5";
+import { bindWidgetToNodeWidth, createWidgetHost } from "./widget_layout.js?v=stable-host-20261112";
 
 export function installInpaintWorkbench(nodeType) {
     const created = nodeType.prototype.onNodeCreated;
     nodeType.prototype.onNodeCreated = function () {
         const result = created?.apply(this, arguments), node = this;
         const root = document.createElement("div"); root.className = "dd-inpaint dd-workbench";
+        if (node.comfyClass === "AdachiWebUIInpaint" || node.type === "AdachiWebUIInpaint") {
+            const launch = document.createElement("button");
+            launch.type = "button"; launch.textContent = T("Open Adachi Workbench");
+            launch.className = "adachi-workspace-launch";
+            launch.onclick = event => { event.preventDefault(); event.stopPropagation(); document.dispatchEvent(new CustomEvent("adachi-open-workspace", {detail:{sampler:node}})); };
+            root.append(launch);
+        }
         const fold = document.createElement("details"); fold.className = "dd-workbench-fold";
         const summary = document.createElement("summary"); summary.textContent = T("Painting tools and mask settings");
         summary.addEventListener("pointerdown", event => event.stopPropagation());
@@ -43,11 +50,11 @@ export function installInpaintWorkbench(nodeType) {
             placeholder.hidden = !!next;
             placeholder.textContent = editor ? T("The painting tools live in the other inpaint node connected to this image") : T("Connect an inline mask to show the painting tools");
         };
-        const contentHeight = () => fold.offsetHeight + actionHost.offsetHeight + (panel?.root.scrollHeight || 620);
+        const contentHeight = () => (root.querySelector('.adachi-workspace-launch')?.offsetHeight || 0) + fold.offsetHeight + actionHost.offsetHeight + (panel?.root.scrollHeight || 620);
         const scheduleSize = () => {
             cancelAnimationFrame(frame);
             frame = requestAnimationFrame(() => {
-                if (removed || !node.graph || !root.isConnected) return;
+                if (removed || !node.graph || !root.isConnected || root.closest(".adachi-workspace")) return;
                 const required = node.computeSize()[1];
                 if (Math.abs(node.size[1] - required) > 1) node.setSize([node.size[0], required]);
                 node.graph.setDirtyCanvas(true, true);
@@ -74,14 +81,24 @@ export function installInpaintWorkbench(nodeType) {
         root.append(panel.root);
         node.adachiParameters = panel; node.adachiWorkbench = { root, tools, fold, actionHost, get source() { return source; } };
         const stopWheelRouting = routeWheelOutsideImage(root, null, () => false);
-        const widget = node.addDOMWidget("adachi_workbench", "adachi_inpaint_controls", root, {
+        const widgetHost = createWidgetHost(root);
+        const widget = node.addDOMWidget("adachi_workbench", "adachi_inpaint_controls", widgetHost, {
             serialize: false, hideOnZoom: false, getMinHeight: contentHeight, getMaxHeight: () => Math.max(4096, contentHeight()),
         });
         widget.serialize = false;
-        bindWidgetToNodeWidth(node, widget, root);
+        bindWidgetToNodeWidth(node, widget, widgetHost);
         const observer = new ResizeObserver(scheduleSize); observer.observe(tools); observer.observe(fold); observer.observe(actionHost);
         const configured = node.onConfigure;
-        node.onConfigure = function () { const result = configured?.apply(this, arguments); fold.open = !!node.properties.adachi_tools_open; queueMicrotask(() => { if (!removed) { panel.refresh(); scheduleSize(); } }); return result; };
+        node.onConfigure = function () {
+            const result = configured?.apply(this, arguments);
+            const legacyTitles = ["WebUI Inpaint", "WebUI 局部重绘", "WebUI 局部重绘 / WebUI Inpaint", "安达局部重绘工作台"];
+            if (node.type === "AdachiWebUIInpaint" && legacyTitles.includes(node.title)) {
+                node.title = T("Adachi Inpaint Workbench");
+            }
+            fold.open = !!node.properties.adachi_tools_open;
+            queueMicrotask(() => { if (!removed) { panel.refresh(); scheduleSize(); } });
+            return result;
+        };
         const connections = node.onConnectionsChange;
         node.onConnectionsChange = function (type, slot, connected) {
             const result = connections?.apply(this, arguments);

web/inpaint_panel.js

@@ -13,7 +13,7 @@ const choices = {
 export class InpaintParameterPanel {
     constructor(options) {
         this.options = options; this.bindings = []; this.root = el("section", "dd-parameters");
-        const header = el("div", "dd-param-header"); header.append(el("strong", "", T("WebUI Inpaint")));
+        const header = el("div", "dd-param-header"); header.append(el("strong", "", T("Adachi Inpaint Workbench")));
         this.targetSelect = el("select"); this.targetSelect.setAttribute("aria-label", T("Controlled WebUI inpaint node"));
         this.targetSelect.onchange = () => { this.preferred = this.targetSelect.value; this.options.onPreferred?.(this.preferred); this.refresh(); };
         header.append(this.targetSelect); this.root.append(header);
@@ -31,7 +31,7 @@ export class InpaintParameterPanel {
         const signature = targets.map(n => `${n.id}:${n.title}`).join("|");
         if (signature !== this.signature) {
             this.signature = signature; this.targetSelect.replaceChildren();
-            for (const n of targets) { const option = el("option", "", `${n.title || T("WebUI Inpaint")} #${n.id}`); option.value = String(n.id); this.targetSelect.append(option); }
+            for (const n of targets) { const option = el("option", "", `${n.title || T("Adachi Inpaint Workbench")} #${n.id}`); option.value = String(n.id); this.targetSelect.append(option); }
         }
         this.targetSelect.hidden = targets.length < 2;
         if (next) this.targetSelect.value = String(next.id);
@@ -58,7 +58,7 @@ export class InpaintParameterPanel {
     enum(parent, name, label, pills = false) {
         const widget = this.widget(name); if (!widget) return;
         label = T(label);
-        const wrapper = el("div", "dd-param-field"); wrapper.append(el("span", "dd-param-label", label));
+        const wrapper = el("div", "dd-param-field"); wrapper.dataset.adachiParam = name; wrapper.append(el("span", "dd-param-label", label));
         let values = widget.options?.values; if (typeof values === "function") values = values();
         if (!Array.isArray(values)) values = Object.keys(choices[name] || {});
         if (!values.includes(widget.value)) values = [widget.value, ...values];
@@ -83,7 +83,7 @@ export class InpaintParameterPanel {
         const widget = this.widget(name); if (!widget) return;
         label = T(label);
         min ??= widget.options?.min ?? 0; max ??= widget.options?.max ?? 1000000;
-        const wrapper = el("label", "dd-param-field"); const row = el("span", "dd-param-number-label"); row.append(el("span", "", label));
+        const wrapper = el("label", "dd-param-field"); wrapper.dataset.adachiParam = name; const row = el("span", "dd-param-number-label"); row.append(el("span", "", label));
         const input = el("input"); input.type = "number"; input.min = min; input.max = max; input.step = step; input.setAttribute("aria-label", label); row.append(input); wrapper.append(row);
         let slider;
         const update = raw => {
@@ -120,7 +120,7 @@ export class InpaintParameterPanel {
         this.body.append(this.maskSettings);
         this.options.onMaskSettings?.(this.maskSettings);
         this.enum(this.body, "area", "Sampling area", true);
-        const resolution = el("div", "dd-param-resolution"); resolution.append(el("span", "dd-param-label", T("Sampling resolution")));
+        const resolution = el("div", "dd-param-resolution"); resolution.dataset.adachiParam = "resolution"; resolution.append(el("span", "dd-param-label", T("Sampling resolution")));
         this.sourceSize = el("button", "", T("Use source size")); this.sourceSize.type = "button";
         this.sourceSize.title = T("Fill width and height from the current source image; aligned to 8 px and clamped to 64-8192 px");
         this.sourceSize.onclick = () => {

web/paint_draft.js

@@ -0,0 +1,26 @@
+// A pending upload owns the retry: new edits are checked once it settles.
+// In particular, never poll a slow connection or an unfinished pointer stroke.
+export function createPaintDraftProtection({paint,widget,graph,disposed,persist,fits,upload,changed,onError}) {
+    let timer=0, pending=false, stopped=false;
+    const schedule=()=>{
+        if(stopped)return;
+        clearTimeout(timer);
+        timer=setTimeout(run,0);
+    };
+    const run=async()=>{
+        timer=0;
+        if(stopped || disposed() || paint()?.drawing || pending)return;
+        const data=widget()?.value||'',revision=paint()?.revision;
+        try {
+            if(!data.startsWith('data:') || !persist() || fits(graph())!==false){changed();return;}
+            pending=true;
+            const name=await upload(data);
+            if(!stopped && !disposed() && widget()?.value===data && paint()?.revision===revision){widget().value=name;changed();}
+        } catch(error) {if(!stopped && !disposed())onError(error);}
+        finally {
+            pending=false;
+            if(!stopped && !disposed() && (widget()?.value!==data || paint()?.revision!==revision))schedule();
+        }
+    };
+    return {schedule,dispose(){stopped=true;clearTimeout(timer);}};
+}

web/preview_images.js

@@ -0,0 +1,44 @@
+// A failed half of a comparison must not leave its sibling decoding in the
+// background, retain a corrupt blob forever, or leak a late object URL.
+export async function decodePreview(blob, signal, {ImageClass=globalThis.Image, urls=URL, timeoutMs=20000}={}) {
+    signal?.throwIfAborted();
+    const url=urls.createObjectURL(blob), image=new ImageClass();
+    let timer, abort;
+    const stopped=new Promise((_,reject)=>{
+        abort=()=>{image.src='';reject(new DOMException('Cancelled','AbortError'));};
+        signal?.addEventListener('abort',abort,{once:true});
+        timer=setTimeout(()=>{image.src='';reject(Error('Preview image decoding timed out'));},timeoutMs);
+    });
+    try {
+        image.src=url;
+        await Promise.race([image.decode(),stopped]);
+        signal?.throwIfAborted();
+        const width=image.naturalWidth||image.width,height=image.naturalHeight||image.height;
+        if(!width || !height || width*height>32_000_000 || Math.max(width,height)>16384)throw Error('Preview image exceeds supported dimensions');
+        return {image,url};
+    } catch(error) {urls.revokeObjectURL(url);throw error;}
+    finally {clearTimeout(timer);signal?.removeEventListener('abort',abort);}
+}
+
+export async function loadPreviewPair(refs,{loadPreview,cached,signal,onProgress,onDecoding,decode=decodePreview,revoke=url=>URL.revokeObjectURL(url)}) {
+    signal.throwIfAborted();
+    const pair=new AbortController(),abort=()=>pair.abort();
+    signal.addEventListener('abort',abort,{once:true});
+    let failure;
+    try {
+        const results=await Promise.allSettled(refs.map(async(ref,index)=>{
+            try {
+                const blob=cached[index]||await loadPreview(ref,{signal:pair.signal,onProgress:state=>{if(!pair.signal.aborted)onProgress?.(index,state);}});
+                pair.signal.throwIfAborted();cached[index]=blob;
+                onDecoding?.();
+                try {return await decode(blob,pair.signal);}
+                catch(error){if(error.name!=='AbortError')cached[index]=null;throw error;}
+            } catch(error) {failure??=error;pair.abort();throw error;}
+        }));
+        if(failure || signal.aborted) {
+            for(const result of results)if(result.status==='fulfilled')revoke(result.value.url);
+            signal.throwIfAborted();throw failure;
+        }
+        return results.map(result=>result.value);
+    } finally {signal.removeEventListener('abort',abort);}
+}

web/preview_transport.js

@@ -0,0 +1,51 @@
+// Read through ComfyUI's authenticated API and report received bytes. The
+// deadline measures inactivity, so a slow but advancing cloud download works.
+export async function readPreview(fetchApi, path, {signal, onProgress, idleMs=30000, maxBytes=128*1024*1024}={}) {
+    const controller=new AbortController();let timer,timedOut=false;
+    const abort=()=>controller.abort();
+    const reset=()=>{clearTimeout(timer);timer=setTimeout(()=>{timedOut=true;controller.abort();},idleMs);};
+    if(signal?.aborted)controller.abort();else signal?.addEventListener('abort',abort,{once:true});
+    try {
+        controller.signal.throwIfAborted();
+        reset();
+        const response=await fetchApi(path,{signal:controller.signal,cache:'no-store'});
+        if(!response.ok)throw Object.assign(new Error(`Preview request failed (${response.status})`),{status:response.status});
+        const encoded=response.headers?.get('content-encoding');
+        const length=Number(response.headers?.get('content-length'));
+        const total=encoded && encoded!=='identity'?0:Number.isFinite(length)&&length>0?length:0;
+        if(total>maxBytes)throw Error('Preview exceeds the image size limit');
+        onProgress?.({loaded:0,total});
+        let blob;
+        if(response.body?.getReader) {
+            const reader=response.body.getReader(),chunks=[];let loaded=0;
+            const cancelRead=()=>{reader.cancel().catch(()=>{});};
+            controller.signal.addEventListener('abort',cancelRead,{once:true});
+            try {
+                while(true) {
+                    controller.signal.throwIfAborted();
+                    const {done,value}=await reader.read();
+                    controller.signal.throwIfAborted();
+                    if(done)break;
+                    if(!value.byteLength)continue;
+                    reset();loaded+=value.byteLength;
+                    if(loaded>maxBytes)throw Error('Preview exceeds the image size limit');
+                    chunks.push(value);onProgress?.({loaded,total});
+                }
+                if(total && loaded<total)throw Error('Preview download was interrupted');
+                blob=new Blob(chunks,{type:response.headers?.get('content-type')||'image/png'});
+                onProgress?.({loaded,total:loaded,complete:true});
+            } catch(error) {await reader.cancel().catch(()=>{});throw error;}
+            finally {controller.signal.removeEventListener('abort',cancelRead);reader.releaseLock();}
+        } else {
+            blob=await response.blob();
+            controller.signal.throwIfAborted();
+            if(blob.size>maxBytes)throw Error('Preview exceeds the image size limit');
+            onProgress?.({loaded:blob.size,total:blob.size,complete:true});
+        }
+        if(!blob.size)throw Error('Empty preview image');
+        return blob;
+    } catch(error) {
+        if(timedOut)throw Error('Preview download timed out');
+        throw error;
+    } finally {clearTimeout(timer);signal?.removeEventListener('abort',abort);controller.abort();}
+}

web/result_adoption.js

@@ -1,5 +1,8 @@
 import { api } from "../../scripts/api.js";
+import { app } from "../../scripts/app.js";
+import { executionId } from "./workspace_flow.js";
 import { T } from "./i18n.js";
+import {uploadImageWithProgress} from './upload_transport.js?v=stability1';
 
 export function installResultAdoption(node, crop) {
     // Saved workflows may still contain the old feedback socket and wire.
@@ -14,27 +17,29 @@ export function installResultAdoption(node, crop) {
         removeLegacyInput();
         return result;
     };
-    node.adachiAdoptCrop = async (file, origin) => {
+    node.adachiAdoptCrop = async (file, origin, {signal,onProgress}={}) => {
         const editor = crop.editor, region = crop.region;
         if (!editor.ready || !region.locked) throw Error(T("Select a crop region before adopting a result"));
         if (crop.busy || editor.stroke) throw Error(T("Finish editing before adopting a result"));
-        if (origin && (origin.mode !== "crop" || String(origin.source) !== String(node.id) || origin.job !== region.job)) {
+        if (origin && (origin.mode !== "crop" || String(origin.source) !== executionId(app.rootGraph||app.graph,node) || origin.job !== region.job)) {
             throw Error(T("This result belongs to another crop; generate a result for the current region"));
         }
         if (file.size > 64 * 1024 * 1024) throw Error(T("File is too large (max 64 MB)"));
+        signal?.throwIfAborted();
+        const controller=crop.adoptController=new AbortController(),abort=()=>controller.abort();
+        signal?.addEventListener('abort',abort,{once:true});
         crop.busy = true; crop.sync();
         const objectUrl = URL.createObjectURL(file);
         try {
             const image = new Image(); image.src = objectUrl; await image.decode();
+            controller.signal.throwIfAborted();
             if (image.width !== region.width || image.height !== region.height) {
                 throw Error(T("Result dimensions must match the selected crop"));
             }
             const body = new FormData();
             body.append("image", file, `adopted-${crypto.randomUUID()}.png`);
             body.append("type", "input"); body.append("subfolder", "adachi-inpaint-layers");
-            const response = await api.fetchApi("/upload/image", {method:"POST", body});
-            if (!response.ok) throw Error(`${T("Upload failed")} (${response.status})`);
-            const uploaded = await response.json();
+            const uploaded = await uploadImageWithProgress(api,body,onProgress,{signal:controller.signal});
             if (typeof uploaded.name !== "string" || !uploaded.name) throw Error(T("Upload failed"));
             if (editor.destroyed || crop.mode !== "crop" || crop.region.job !== region.job) {
                 throw Error(T("The crop changed while adopting the result"));
@@ -48,6 +53,7 @@ export function installResultAdoption(node, crop) {
             }
             editor.status("");
         } finally {
+            signal?.removeEventListener('abort',abort);if(crop.adoptController===controller)crop.adoptController=null;
             URL.revokeObjectURL(objectUrl); crop.busy = false; crop.sync();
         }
     };

web/result_recovery.js

@@ -0,0 +1,93 @@
+import {T} from './i18n.js';
+// Execution notifications are an optimization, not the sole delivery channel.
+// Poll only IDs queued by this browser; never guess from another workflow's
+// latest history entry or from a coincidentally matching node ID.
+import {executionNode,graphNodeEntries} from './workspace_flow.js';
+export class ResultRecovery {
+    constructor({fetchApi,getGraph,onOutput,onPending=()=>{},onTerminal=()=>{},onDiscard=()=>{},interval=2500}) {
+        Object.assign(this,{fetchApi,getGraph,onOutput,onPending,onTerminal,onDiscard,interval});
+        this.pending=new Map();this.delivered=new Set();this.controllers=new Set();
+    }
+    track(graph,promptId,nodeId) {
+        const node=executionNode(graph,nodeId),key=`${promptId}:${nodeId}`;
+        if(this.destroyed || !promptId || node?.type!=='AdachiImageCompare' || this.delivered.has(key) || this.pending.has(key))return;
+        this.pending.set(key,{graph,node,promptId,nodeId:String(nodeId),key});
+        this.onPending(node);this.schedule(0);
+    }
+    schedule(ms=this.interval) {clearTimeout(this.timer);if(!this.destroyed && this.pending.size)this.timer=setTimeout(()=>this.recover(),ms);}
+    discard(record){if(this.pending.delete(record.key))this.onDiscard(record.node);}
+    async recover() {
+        if(this.destroyed || this.busy)return;this.busy=true;clearTimeout(this.timer);
+        const groups=new Map();
+        for(const record of this.pending.values()) {
+            if(record.graph!==this.getGraph() || executionNode(record.graph,record.nodeId)!==record.node){this.discard(record);continue;}
+            const records=groups.get(record.promptId)||[];records.push(record);groups.set(record.promptId,records);
+        }
+        try {
+            for(const [promptId,records] of groups) {
+                if(this.destroyed)break;
+                const controller=new AbortController(),timer=setTimeout(()=>controller.abort(),15000);
+                this.controllers.add(controller);
+                try {
+                    const response=await this.fetchApi(`/history/${encodeURIComponent(promptId)}`,{cache:'no-store',signal:controller.signal});
+                    if(!response.ok)continue;
+                    const entry=(await response.json())[promptId];if(!entry)continue;
+                    for(const r of records) {
+                        if(this.destroyed || !this.pending.has(r.key))continue;
+                        if(r.graph!==this.getGraph() || executionNode(r.graph,r.nodeId)!==r.node){this.discard(r);continue;}
+                        const output=entry.outputs?.[r.nodeId];
+                        if(output?.adachi_originals?.length && output?.adachi_results?.length) {
+                            await this.onOutput(r.node,output,promptId,entry);
+                            this.pending.delete(r.key);this.delivered.add(r.key);
+                        } else if(entry.status?.completed) {
+                            this.pending.delete(r.key);this.onTerminal(r.node,entry,promptId);
+                        }
+                    }
+                } catch {} finally {clearTimeout(timer);this.controllers.delete(controller);controller.abort();}
+            }
+        } finally {
+            while(this.delivered.size>256)this.delivered.delete(this.delivered.values().next().value);
+            this.busy=false;this.schedule();
+        }
+    }
+    destroy(){this.destroyed=true;clearTimeout(this.timer);for(const controller of this.controllers)controller.abort();for(const record of this.pending.values())this.discard(record);this.delivered.clear();}
+}
+
+const installed=new WeakMap();
+export function installComparisonRecovery(api,getGraph) {
+    if(installed.has(api))return installed.get(api);
+    const recovery=new ResultRecovery({fetchApi:api.fetchApi.bind(api),getGraph,
+        onDiscard:node=>{const view=node.adachiCompare;if(view){view.pendingOutputs=Math.max(0,(view.pendingOutputs||0)-1);view.updateButton();if(!view.pendingOutputs&&!view.loadingActive)view.progressBox.hidden=true;}},
+        onPending:node=>{const view=node.adachiCompare;if(view){view.pendingOutputs=(view.pendingOutputs||0)+1;view.updateButton();view.loading(view.options.waitingText||T("Waiting for the generated image…"));}},
+        onOutput(node,output,promptId,entry){
+            if(node.adachiCompare)node.adachiCompare.pendingOutputs=Math.max(0,(node.adachiCompare.pendingOutputs||0)-1);
+            const known=new Set((node.properties.adachi_compare?.results||[]).map(ref=>JSON.stringify([ref.type,ref.subfolder,ref.filename])));
+            if(output.adachi_results.some(ref=>!known.has(JSON.stringify([ref.type,ref.subfolder,ref.filename]))))node.onExecuted?.(output);
+            else if(node.adachiCompare?.ready)node.adachiCompare.progressBox.hidden=!(node.adachiCompare.pendingOutputs>0);
+            node.adachiCompare?.updateButton();
+            document.dispatchEvent(new CustomEvent('adachi-result-recovered',{detail:{node,promptId,entry}}));
+        },
+        onTerminal(node,entry,promptId){
+            const view=node.adachiCompare;if(view){view.pendingOutputs=Math.max(0,(view.pendingOutputs||0)-1);view.updateButton();view.progressBox.hidden=!(view.pendingOutputs>0);view.status(view.options.failedText||T("Generation failed; check the ComfyUI task history"),true);}
+            document.dispatchEvent(new CustomEvent('adachi-result-recovered',{detail:{node,promptId,entry}}));
+        },
+    });
+    const queued=api.queuePrompt;
+    api.queuePrompt=async function(...args) {
+        const graph=getGraph(),nodes=Object.entries(args[1]?.output||{}).filter(([,n])=>n.class_type==='AdachiImageCompare').map(([id])=>id);
+        const result=await queued.apply(this,args);
+        for(const id of nodes)recovery.track(graph,result.prompt_id,id);
+        return result;
+    };
+    const wake=()=>{
+        recovery.schedule(0);
+        for(const {node} of graphNodeEntries(getGraph())) {
+            const view=node.adachiCompare;
+            if(view && !view.ready && !view.loadingActive && view.results.length)view.loadSelected();
+        }
+    };
+    for(const event of ['reconnected','execution_success','execution_error','execution_interrupted'])api.addEventListener(event,()=>recovery.schedule(0));
+    api.addEventListener('reconnected',wake);window.addEventListener('online',wake);
+    document.addEventListener('visibilitychange',()=>{if(!document.hidden)wake();});
+    installed.set(api,recovery);return recovery;
+}

web/upload_transport.js

@@ -2,17 +2,27 @@ import { T } from "./i18n.js";
 
 // XMLHttpRequest reports bytes sent, unlike fetch. Keep ComfyUI's API URL and
 // per-user header; the browser automatically sends same-origin session cookies.
-export async function uploadImageWithProgress(api, body, onProgress) {
+export async function uploadImageWithProgress(api, body, onProgress, {signal,idleMs=60000}={}) {
+    const controller=new AbortController();let timer,timedOut=false;
+    const abort=()=>controller.abort();
+    const reset=(ms=idleMs)=>{clearTimeout(timer);timer=setTimeout(()=>{timedOut=true;controller.abort();},ms);};
+    if(signal?.aborted)controller.abort();else signal?.addEventListener('abort',abort,{once:true});
+    try {
+    controller.signal.throwIfAborted();reset();
     const response = await new Promise((resolve, reject) => {
         const xhr = new XMLHttpRequest();
+        let settled=false,lastLoaded=0;
+        const finish=(fn,value)=>{if(settled)return;settled=true;controller.signal.removeEventListener('abort',cancel);xhr.onload=xhr.onerror=xhr.onabort=null;xhr.upload.onprogress=xhr.upload.onload=null;fn(value);};
+        const cancel=()=>{xhr.abort();finish(reject,new DOMException(T('Upload was cancelled'),'AbortError'));};
+        controller.signal.addEventListener('abort',cancel,{once:true});
         xhr.open("POST", api.apiURL("/upload/image"));
         if (api.user) xhr.setRequestHeader("Comfy-User", api.user);
-        xhr.upload.onprogress = event => onProgress?.({phase: "upload", loaded: event.loaded, total: event.lengthComputable ? event.total : 0});
-        xhr.upload.onload = () => onProgress?.({phase: "processing"});
-        xhr.onload = () => resolve(xhr);
-        xhr.onerror = () => reject(new Error(T("Network error while uploading image")));
-        xhr.onabort = () => reject(new Error(T("Upload was cancelled")));
-        xhr.send(body);
+        xhr.upload.onprogress = event => {if(event.loaded>lastLoaded){lastLoaded=event.loaded;reset();}onProgress?.({phase: "upload", loaded: event.loaded, total: event.lengthComputable ? event.total : 0});};
+        xhr.upload.onload = () => {reset();onProgress?.({phase: "processing"});};
+        xhr.onload = () => finish(resolve,xhr);
+        xhr.onerror = () => finish(reject,new Error(T("Network error while uploading image")));
+        xhr.onabort = () => finish(reject,new DOMException(T("Upload was cancelled"),'AbortError'));
+        try{xhr.send(body);}catch(error){finish(reject,error);}
     });
 
     // Some cloud frontends wrap fetchApi with an authentication mechanism that
@@ -20,12 +30,19 @@ export async function uploadImageWithProgress(api, body, onProgress) {
     // frontend API, without inventing upload percentages for the fallback.
     if (response.status === 401 || response.status === 403) {
         onProgress?.({phase: "authenticated"});
-        const fallback = await api.fetchApi("/upload/image", {method: "POST", body});
+        // fetch cannot expose upload byte progress. Give authenticated uploads
+        // a larger bounded budget rather than applying XHR's inactivity limit.
+        reset(idleMs*5);
+        const fallback = await api.fetchApi("/upload/image", {method: "POST", body, signal:controller.signal});
         if (!fallback.ok) throw new Error(`${T("Upload failed")} (${fallback.status})`);
         onProgress?.({phase: "processing"});
-        return fallback.json();
+        return await fallback.json();
     }
     if (response.status < 200 || response.status >= 300) throw new Error(`${T("Upload failed")} (${response.status})`);
     try { return JSON.parse(response.responseText); }
     catch { throw new Error(T("Invalid upload response")); }
+    } catch(error) {
+        if(timedOut)throw Error(T('Image upload timed out; check the connection and try again'));
+        throw error;
+    } finally {clearTimeout(timer);signal?.removeEventListener('abort',abort);controller.abort();}
 }

web/wheel_routing.js

@@ -3,6 +3,7 @@ import { app } from "../../scripts/app.js";
 export function routeWheelOutsideImage(root, canvas, isReady) {
     const route = event => {
         if (!root.contains(event.target)) return;
+        if (root.closest(".adachi-workspace")) return;
         if (event.target === canvas && isReady()) return;
         event.preventDefault(); event.stopPropagation();
         // Preserve the user's ComfyUI navigation mode (zoom or pan).

web/widget_layout.js

@@ -1,3 +1,13 @@
+/** Keep the DOM widget host stable while its contents are mounted elsewhere.
+ * Vue may reattach widget.element when switching renderers or viewport sizes. */
+export function createWidgetHost(content) {
+    const host = document.createElement("div");
+    host.className = "adachi-widget-host";
+    Object.assign(host.style, {width:"100%", height:"100%", minWidth:"0", minHeight:"0"});
+    host.append(content);
+    return host;
+}
+
 /** Fill the node in graph coordinates, independently of cached DOM measurements. */
 export function bindWidgetToNodeWidth(node, widget, element) {
     // Classic ComfyUI uses widget.width before node.width for its DOM host.

web/workbench_analysis.js

@@ -0,0 +1,44 @@
+// Read-only discovery for the inpainting workbench. The live graph remains
+// authoritative: virtual Get/Set routes and group bypasses are resolved by
+// ComfyUI and its installed extensions when a prompt is actually queued.
+import {graphNodeEntries,executionNode} from './workspace_flow.js';
+export function inspectWorkbench(graph) {
+    const nodes = graphNodeEntries(graph).map(entry=>entry.node);
+    const find = type => nodes.filter(node => node.type === type);
+    const editors = find("AdachiInlineMask");
+    const samplers = find("AdachiWebUIInpaint");
+    const comparisons = find("AdachiImageCompare");
+    const presets = find("AdachiGroupPresets");
+    const checkpoints = find("CheckpointLoaderSimple");
+    const loras = nodes.filter(node => node.type === "LoraLoader" || node.type === "Power Lora Loader (rgthree)");
+    const missing = [];
+    if (!editors.length) missing.push("inline_mask");
+    if (!samplers.length) missing.push("inpaint");
+    if (!comparisons.length) missing.push("compare");
+    return { editors, samplers, comparisons, presets, checkpoints, loras, missing };
+}
+
+export function upstreamNodes(node,inputName) {
+    const found=new Set(),queue=[];
+    const addInput=(current,input)=>{const g=current.graph,l=g?.getLink?.(input?.link)??g?.links?.get?.(input?.link)??g?.links?.[input?.link];if(l)queue.push(g.getNodeById(l.origin_id));};
+    for(const input of node?.inputs||[])if(!inputName||input.name===inputName)addInput(node,input);
+    while(queue.length){const current=queue.shift();if(!current||found.has(current))continue;found.add(current);
+        if(current.type==='GetNode'){try{queue.push(current.findSetter?.(current.graph));}catch{}}
+        for(const input of current.inputs||[])addInput(current,input);
+    }
+    return found;
+}
+export function selectWorkbenchPipeline(graph,preferred,options={}) {
+    const nodes=inspectWorkbench(graph),choose=(list,explicit,candidates=[])=>{
+        if(explicit&&list.includes(explicit))return {node:explicit,ambiguous:false};
+        const pool=candidates.length?candidates:list,active=pool.filter(n=>n.mode===0);
+        if(pool.length===1)return {node:pool[0],ambiguous:false};
+        if(active.length===1)return {node:active[0],ambiguous:false};
+        return {node:active[0]||pool[0],ambiguous:pool.length>1};
+    };
+    const sampler=choose(nodes.samplers,preferred||options.samplerNode);
+    const saved=sampler.node?.properties?.adachi_workspace_connections;
+    const editor=choose(nodes.editors,options.editorNode||executionNode(graph,saved?.editorId),nodes.editors.filter(n=>upstreamNodes(sampler.node,'image').has(n)));
+    const compare=choose(nodes.comparisons,options.compareNode||executionNode(graph,saved?.compareId),nodes.comparisons.filter(n=>upstreamNodes(n,'result').has(sampler.node)));
+    return {...nodes,editor:editor.node,sampler:sampler.node,compare:compare.node,ambiguous:sampler.ambiguous||editor.ambiguous||compare.ambiguous};
+}

web/workspace.css

@@ -0,0 +1,158 @@
+.adachi-workspace {
+  --aw-bg:#eef1f4; --aw-panel:#fff; --aw-input:#f6f8fa; --aw-text:#273747;
+  --aw-muted:#61758a; --aw-line:#ced7e1; --aw-hover:#edf3f9;
+  --aw-accent:#276da7; --aw-selected:#eaf3fb; --aw-selected-text:#205b8b;
+  --aw-stage:#e9edf1; --aw-checker:#e0e5eb; --aw-error:#a93e34; --aw-ok:#237459;
+  position:fixed; inset:0; z-index:12000; display:flex; flex-direction:column;
+  background:var(--aw-bg); color:var(--aw-text); color-scheme:light;
+  font:14px/1.5 'Segoe UI','Microsoft YaHei',sans-serif;
+}
+.adachi-workspace[data-theme=dark] {
+  --aw-bg:#171a1e; --aw-panel:#24282e; --aw-input:#2d333b; --aw-text:#e3e8ef;
+  --aw-muted:#a2b1c2; --aw-line:#46515e; --aw-hover:#343e49;
+  --aw-accent:#357fb8; --aw-selected:#263f55; --aw-selected-text:#b4dcff;
+  --aw-stage:#191d22; --aw-checker:#232931; --aw-error:#ffa69a; --aw-ok:#83d5b5;
+  color-scheme:dark;
+}
+.adachi-workspace * {box-sizing:border-box}
+.adachi-workspace [hidden] {display:none!important}
+body.adachi-workspace-open > :not(.adachi-workspace):not(script):not(style):not(link) {opacity:0!important;pointer-events:none!important}
+.adachi-workspace button,.adachi-workspace select,.adachi-workspace input,.adachi-workspace textarea {
+  font:inherit; color:var(--aw-text); background:var(--aw-panel); border:1px solid var(--aw-line);
+  border-radius:5px; padding:7px 10px;
+}
+.adachi-workspace button {cursor:pointer;white-space:nowrap}
+.adachi-workspace button:hover {border-color:var(--aw-accent);background:var(--aw-hover)}
+.adachi-workspace button:disabled {opacity:.4;cursor:not-allowed}
+.adachi-workspace button:focus-visible,.adachi-workspace select:focus-visible {outline:2px solid var(--aw-accent);outline-offset:2px}
+.adachi-workspace button.active,.adachi-workspace button[aria-pressed=true],.adachi-workspace .dd-inpaint button.dd-active {
+  background:var(--aw-selected);color:var(--aw-selected-text);border-color:var(--aw-accent);
+}
+.adachi-workspace button.primary {background:var(--aw-accent);border-color:var(--aw-accent);color:#fff}
+.adachi-workspace button.primary:hover {filter:brightness(1.1)}
+.adachi-workspace .aw-icon {display:inline-flex;align-items:center;justify-content:center;width:32px;height:32px;padding:5px;flex-shrink:0}
+.adachi-workspace header {position:absolute;z-index:6;top:8px;left:20px;right:20px;height:36px;display:flex;align-items:center;gap:8px;pointer-events:none}
+.adachi-workspace header>* {pointer-events:auto}
+.adachi-workspace h1 {font-size:18px;font-weight:650;margin:0 auto 0 0;padding:3px 0;background:transparent;color:rgba(0,0,0,.62);white-space:nowrap}
+.adachi-workspace[data-theme=dark] h1 {text-shadow:0 0 1px rgba(255,255,255,.9),0 0 3px rgba(255,255,255,.65)}
+.adachi-workspace .aw-status {font-size:12px;min-width:0;max-width:42vw;flex:0 1 auto;padding:4px 8px;border-radius:4px;background:var(--aw-panel);color:var(--aw-muted);overflow:hidden;white-space:nowrap;text-overflow:ellipsis}
+.adachi-workspace .aw-status[data-state=ok] {color:var(--aw-ok)}
+.adachi-workspace .aw-status[data-state=error] {color:var(--aw-error)}
+.adachi-workspace main {display:grid;grid-template-columns:minmax(0,1fr) 10px var(--aw-sidebar-width,360px);gap:0;padding:6px;flex:1;min-height:0}
+.adachi-workspace .aw-canvas {position:relative;min-height:0;overflow:hidden;border:1px solid var(--aw-line);border-radius:8px;background:var(--aw-panel)}
+.adachi-workspace .aw-surface {position:absolute;inset:0;min-height:0;background:var(--aw-stage)}
+.adachi-workspace .aw-toolbar {position:absolute;top:48px;left:8px;right:8px;z-index:5;display:flex;gap:6px;align-items:center;pointer-events:none}
+.adachi-workspace .aw-toolbar button {pointer-events:auto;padding:5px 9px}
+.adachi-workspace .aw-toolbar .aw-icon {padding:5px}
+.adachi-workspace .aw-toolbar .spacer {flex:1}
+.adachi-workspace .aw-footer {position:absolute;bottom:8px;left:8px;z-index:5;display:flex;align-items:center;flex-wrap:wrap;gap:6px;padding:5px;border:1px solid var(--aw-line);border-radius:5px;background:var(--aw-panel);max-width:calc(100% - 16px);font-size:12px;color:var(--aw-muted)}
+.adachi-workspace .aw-footer button {padding:4px 8px}
+.adachi-workspace .aw-footer select {max-width:260px;min-width:0;padding:4px 7px}
+.adachi-workspace .aw-note {display:none}
+.adachi-workspace .aw-result-image {width:100%;height:100%;position:absolute;object-fit:contain;background:var(--aw-stage)}
+.adachi-workspace aside {overflow:auto;background:var(--aw-panel);border:1px solid var(--aw-line);border-radius:8px;padding:48px 16px 16px}
+.adachi-workspace aside h2 {font-size:12px;letter-spacing:1px;color:var(--aw-muted);margin:0 0 12px}
+.adachi-workspace aside label {margin-top:10px}
+.adachi-workspace aside select,.adachi-workspace aside textarea {max-width:100%}
+.adachi-workspace aside textarea {width:100%;min-height:85px;resize:vertical}
+.adachi-workspace details {margin:8px 0}
+.adachi-workspace summary {cursor:pointer}
+.adachi-workspace .aw-presets {display:flex;gap:6px;flex-wrap:wrap;margin-bottom:12px}
+.adachi-workspace .aw-presets button {flex:1;padding:7px 5px;font-size:12px}
+.adachi-workspace .aw-profile-warning {border:1px solid var(--aw-line);border-left:3px solid var(--aw-accent);padding:8px;margin:0 0 12px;font-size:12px;color:var(--aw-muted)}
+.adachi-workspace .aw-bindings label {display:block;font-size:12px;color:var(--aw-muted)}
+.adachi-workspace .aw-bindings label select {width:100%;display:block;margin:5px 0 10px}
+.adachi-workspace .aw-bindings textarea {display:block;margin-top:5px;line-height:1.5}
+.adachi-workspace .aw-bindings label>button {font-size:12px;padding:1px 6px;margin-top:3px}
+.adachi-workspace .aw-bindings details {border-bottom:1px solid var(--aw-line);padding:5px 0 10px}
+.adachi-workspace .aw-bindings summary {font-size:12px;color:var(--aw-muted)}
+.adachi-workspace .aw-lora-row {display:grid;grid-template-columns:minmax(0,1fr) 65px 30px;gap:4px;margin:6px 0}
+.adachi-workspace .aw-lora-row input {min-width:0;width:100%;padding:5px}
+.adachi-workspace .aw-lora-row button {padding:3px}
+.adachi-workspace .aw-embedded {position:absolute!important;inset:0!important;width:100%!important;height:100%!important;max-height:none!important;transform:none!important;visibility:visible!important}
+.adachi-workspace .dd-inpaint {--dd-bg:var(--aw-panel);--dd-panel:var(--aw-input);--dd-line:var(--aw-line);--dd-text:var(--aw-text);--dd-muted:var(--aw-muted);--dd-accent:var(--aw-accent);color:var(--aw-text);color-scheme:inherit;background:var(--aw-panel)}
+.adachi-workspace .dd-inpaint button {background:var(--aw-input);color:var(--aw-text)}
+.adachi-workspace .dd-inpaint .dd-stage {background-color:var(--aw-stage);background-image:linear-gradient(45deg,var(--aw-checker) 25%,transparent 25%),linear-gradient(-45deg,var(--aw-checker) 25%,transparent 25%),linear-gradient(45deg,transparent 75%,var(--aw-checker) 75%),linear-gradient(-45deg,transparent 75%,var(--aw-checker) 75%)}
+.adachi-workspace .dd-inpaint input,.adachi-workspace .dd-inpaint select {background:var(--aw-input);color:var(--aw-text)}
+.adachi-workspace .dd-inline-minimal {background:transparent}
+.adachi-workspace .dd-crop-bar {background:var(--aw-panel)}
+.adachi-workspace .dd-inpaint .dd-upload-progress {background:var(--aw-panel);color:var(--aw-text)}
+.adachi-workspace .aw-parameters {position:relative;min-height:100px}
+.adachi-workspace .aw-parameters>.dd-inpaint {position:relative!important;transform:none!important;inset:auto!important;height:auto!important;max-height:none!important;overflow:visible!important;width:100%!important}
+.adachi-workspace .dd-param-advanced-body {padding:8px 0}
+.adachi-workspace .dd-workbench {border:0}
+.adachi-workspace .dd-editor-controls {background:var(--aw-panel)}
+.adachi-workspace .dd-inpaint .dd-actions {padding:8px 0}
+.adachi-workspace .dd-inpaint .dd-settings {gap:6px;padding:6px 0}
+.adachi-workspace .dd-inpaint .dd-tools {padding:5px 0}
+.adachi-workspace .dd-inpaint .dd-tools button {padding:4px;font-size:11px}
+.adachi-workspace .dd-inpaint .dd-stage canvas {outline:none}
+.adachi-workspace .dd-inline-minimal>.dd-status:not([hidden]) {background:var(--aw-panel);color:var(--aw-error)}
+.adachi-workspace .dd-inpaint .dd-param-grid {gap:8px}
+.adachi-workspace .aw-canvas .dd-files,.adachi-workspace .aw-canvas .dd-mode-select {top:88px}
+.adachi-workspace .aw-canvas .dd-crop-bar {
+  bottom:calc(var(--aw-history-height,40px) + 16px);left:8px;right:8px;
+  background:var(--aw-panel);border:1px solid var(--aw-line);padding:5px;gap:5px;
+  box-shadow:0 2px 8px #0002;
+}
+.adachi-workspace .aw-canvas .dd-crop-bar button,.adachi-workspace .aw-canvas .dd-crop-bar select,.adachi-workspace .aw-canvas .dd-crop-bar input {
+  height:28px;min-height:28px;font-size:12px;color:var(--aw-text);
+}
+.adachi-workspace .aw-canvas .dd-files button {opacity:1}
+.adachi-workspace .aw-canvas .dd-adoption {display:none}
+.adachi-workspace .aw-canvas .dd-compare-stage {position:absolute;inset:0;min-height:0}
+.adachi-workspace .aw-canvas .dd-compare-toolbar {
+  position:absolute;left:8px;right:8px;bottom:calc(var(--aw-history-height,40px) + 16px);z-index:4;
+  padding:5px;border:1px solid var(--aw-line);border-radius:5px;background:var(--aw-panel);width:fit-content;max-width:calc(100% - 16px);
+}
+.adachi-workspace .aw-canvas .dd-status:not([hidden]) {
+  position:absolute;left:8px;right:8px;z-index:5;bottom:calc(var(--aw-history-height,40px) + var(--aw-crop-height,32px) + 24px);
+  padding:7px;border-radius:5px;background:var(--aw-panel);color:var(--aw-error);
+}
+.adachi-workspace .adachi-workspace-launch {display:none}
+@media(max-width:850px) {
+  .adachi-workspace main {grid-template-columns:1fr;overflow:auto}
+  .adachi-workspace .aw-canvas {min-height:78vh}
+  .adachi-workspace aside {overflow:visible;padding-top:14px}
+  .adachi-workspace header {left:12px;right:12px;height:36px;gap:5px}
+  .adachi-workspace header h1 {font-size:14px}
+  .adachi-workspace header button {padding:4px 6px;font-size:11px}
+  .adachi-workspace header .aw-status {max-width:25vw;font-size:10px}
+}
+
+.adachi-workspace .aw-canvas .dd-preview-progress {top:100px;bottom:auto;background:var(--aw-panel);color:var(--aw-text);border-color:var(--aw-line);}
+
+.adachi-workspace .aw-generation-progress {padding:9px 10px;margin:0 0 14px;border:1px solid var(--aw-line);border-radius:5px;background:var(--aw-input);color:var(--aw-text);font-size:12px;overflow-wrap:anywhere;}
+.adachi-workspace .aw-generation-progress progress {display:block;width:100%;height:7px;margin:6px 0 0;accent-color:var(--aw-accent);}
+.adachi-workspace .aw-generation-progress[data-state=error] {color:var(--aw-error);}
+.adachi-workspace .aw-generation-progress[data-state=complete] {color:var(--aw-ok);}
+
+.adachi-workspace .aw-generation-progress progress {appearance:none;border:0;border-radius:4px;overflow:hidden;background:var(--aw-line);}
+.adachi-workspace .aw-generation-progress progress::-webkit-progress-bar {background:var(--aw-line);border-radius:4px;}
+.adachi-workspace .aw-generation-progress progress::-webkit-progress-value {background:var(--aw-accent);border-radius:4px;}
+.adachi-workspace .aw-generation-progress progress::-moz-progress-bar {background:var(--aw-accent);border-radius:4px;}
+.adachi-workspace .aw-model-warning {padding:7px 9px;border:1px solid var(--aw-line);border-left:3px solid var(--aw-error);border-radius:4px;color:var(--aw-error);font-size:12px;}
+.adachi-workspace .aw-model-warning ul {margin:7px 0;padding-left:17px;overflow-wrap:anywhere;}
+.adachi-workspace .aw-model-warning li {margin:5px 0;}
+.adachi-workspace .aw-model-warning small {display:block;color:var(--aw-muted);}
+
+@keyframes aw-progress-wait {from{background-position:100% 0}to{background-position:-100% 0}}
+.adachi-workspace .aw-generation-progress progress:not([value]) {background:linear-gradient(90deg,var(--aw-line) 20%,var(--aw-accent) 50%,var(--aw-line) 80%);background-size:200% 100%;animation:aw-progress-wait 1.5s linear infinite;}
+.adachi-workspace .aw-generation-progress progress:not([value])::-webkit-progress-bar,.adachi-workspace .aw-generation-progress progress:not([value])::-webkit-progress-value {background:transparent;}
+@media(prefers-reduced-motion:reduce){.adachi-workspace .aw-generation-progress progress:not([value]){animation:none}}
+
+.adachi-workspace .aw-splitter {position:relative;cursor:col-resize;touch-action:none;outline:none;}
+.adachi-workspace .aw-splitter::before {content:"";position:absolute;top:12px;bottom:12px;left:4px;width:2px;background:var(--aw-line);border-radius:2px;}
+.adachi-workspace .aw-splitter:hover::before,.adachi-workspace .aw-splitter:focus-visible::before,.adachi-workspace[data-resizing] .aw-splitter::before {background:var(--aw-accent);}
+.adachi-workspace[data-resizing],.adachi-workspace[data-resizing] * {cursor:col-resize!important;user-select:none!important;}
+@media(max-width:850px){.adachi-workspace .aw-splitter{display:none}.adachi-workspace main{gap:8px}}
+
+.adachi-workspace .aw-connections {font-size:12px;border-bottom:1px solid var(--aw-line);padding:3px 0 8px;margin:0 0 10px;}
+.adachi-workspace .aw-connections summary {color:var(--aw-muted);}
+.adachi-workspace .aw-connections label {display:block;margin-top:8px;color:var(--aw-muted);}
+.adachi-workspace .aw-connections select {display:block;width:100%;margin-top:4px;}
+.adachi-workspace .aw-connections button {padding:4px 8px;margin-top:8px;}
+.adachi-workspace .aw-connections p {color:var(--aw-error);}
+.adachi-workspace .aw-bindings details small {display:block;overflow-wrap:anywhere;}
+
+.adachi-workspace .aw-quick-params {height:auto;flex:none;border:0;border-radius:0;overflow:visible;gap:8px;padding:12px 0;background:transparent;container-type:normal;}

web/workspace_activation.js

@@ -0,0 +1,27 @@
+const virtualTypes=new Set(['GetNode','SetNode','Reroute','AdachiExclusiveSwitch']);
+function members(group,seen=new Set()) {
+    if(seen.has(group))return [];seen.add(group);group.recomputeInsideNodes?.();
+    return [...new Set(Array.from(group._children||group._nodes||group.nodes||[]).flatMap(child=>
+        typeof child.recomputeInsideNodes==='function'?members(child,seen):[child]))];
+}
+export function workspaceRoutingNodes(roots,controller) {
+    const allowed=new Set();
+    const plan=controller?.active&&controller.planStates?controller.planStates(controller.active).plan:null;
+    for(const root of roots)if(root.mode===4){
+        const groups=Array.from(root.graph?.groups||root.graph?._groups||[]).map(group=>{
+            const nodes=members(group);return {nodes,area:Math.abs((group.size?.[0]||1)*(group.size?.[1]||1))};
+        }).filter(group=>group.nodes.includes(root)).sort((a,b)=>a.area-b.area);
+        const group=groups[0];if(!group)continue;
+        const inherited=plan?.has(root)?plan.get(root)===4:group.nodes.filter(n=>!['AdachiGroupPresets','Note','MarkdownNote'].includes(n.type)).every(n=>n.mode===4);
+        if(inherited)for(const node of group.nodes)allowed.add(node);
+    }
+    const found=new Set(),seen=new Set();
+    const visit=node=>{
+        if(!node||seen.has(node))return;seen.add(node);
+        if(!roots.includes(node)&&!virtualTypes.has(node.type))return;
+        if(virtualTypes.has(node.type)&&node.mode===4&&allowed.has(node))found.add(node);
+        if(node.type==='GetNode'){const setter=node.findSetter?.(node.graph);if(setter)visit(setter);}
+        for(const input of node.inputs||[]){const g=node.graph,l=g?.getLink?.(input.link)??g?.links?.get?.(input.link)??g?.links?.[input.link];if(l)visit(g.getNodeById(l.origin_id));}
+    };
+    roots.forEach(visit);return found;
+}

web/workspace_bindings.js

@@ -0,0 +1,226 @@
+import {T} from './i18n.js';
+import {inspectExecutionFlow,executionNode,executionId,graphNodeEntries} from './workspace_flow.js';
+// Bind the workbench to existing graph widgets; no model or LoRA is loaded here.
+const widget = (node, name) => node?.widgets?.find(w => w.name === name);
+const nodeList = graph => graphNodeEntries(graph).map(entry=>entry.node);
+const ref = (node, slot = 0) => [String(node.id), slot];
+const valueList = w => {
+    const values = typeof w?.options?.values === 'function' ? w.options.values() : w?.options?.values;
+    return Array.isArray(values) ? values.map(String) : [];
+};
+const stateKey = 'adachi_workspace_bindings';
+const presetController=(nodes,sampler,graph)=>{
+    const saved=sampler.properties?.adachi_workspace_connections;
+    if(saved && Object.hasOwn(saved,'controllerId'))return nodes.find(n=>n.type==='AdachiGroupPresets'&&n.mode===0&&executionId(graph,n)===saved.controllerId)?.adachiGroupPresets?.model;
+    const active=nodes.filter(n=>n.type==='AdachiGroupPresets'&&n.mode===0),local=active.filter(n=>n.graph===sampler.graph),pool=local.length?local:active;
+    return pool.length===1?pool[0].adachiGroupPresets?.model:undefined;
+};
+
+export class WorkspaceBindings {
+    constructor({graph, sampler, canvas, onChange = () => {}, markChanged = () => {}}) {
+        Object.assign(this, {graph, sampler, canvas, onChange, markChanged});
+        this.nodes = nodeList(graph);
+        this.controller = presetController(this.nodes,sampler,graph);
+        this.owner = this.controller?.node || sampler;
+        this.owner.properties ??= {};
+        this.owner.properties[stateKey] ??= {profiles:{}};
+        this.catalog = {checkpoints:[], unets:[], ggufs:[], clipggufs:[], clips:[], vaes:[], loras:[]};
+        this.catalogReady = new Set();
+        this.profiles = this.controller?.data?.presets?.map(p => ({id:p.id, name:p.name, preset:p})) || [];
+        if (!this.profiles.length) this.profiles = [{id:'current',name:T("Current workflow")}];
+        this.profileId = this.controller?.data?.activeId || this.profiles[0].id;
+        this.resolve();
+    }
+    resolve() {
+        const profile=this.profiles.find(p=>p.id===this.profileId)||this.profiles[0];this.profileId=profile.id;
+        const all=this.owner.properties[stateKey].profiles;
+        if(!all[this.profileId])all[this.profileId]={loraMode:'inherit',loras:[],useRefiner:!!this.sampler.inputs?.find(i=>i.name==='refiner_model'&&i.link!=null)};
+        this.settings=all[this.profileId];this.settings.loras??=[];
+        // Retain explicit selections made in older versions without retaining
+        // any of the old template IDs or model-family name matching.
+        this.settings.loraMode??='override';
+        this.settings.textOverrides??={};
+        if(this.compiledProfileId===this.profileId)this.updateExecutionGraph(this.compiled,this.samplerId,false);
+        else {this.flow=null;this.model=this.clip=this.vae=this.positive=this.negative=this.lora=null;this.promptSources={positive:T("Reading workflow connections"),negative:T("Reading workflow connections")};}
+        return profile;
+    }
+    updateExecutionGraph(output,samplerId=executionId(this.graph,this.sampler),render=true) {
+        this.compiled=output;this.compiledProfileId=this.profileId;this.samplerId=String(samplerId);
+        this.flow=inspectExecutionFlow(output,this.samplerId,id=>executionNode(this.graph,id));
+        this.model=this.flow.modelNodes[0]?.node||null;this.clip=this.flow.clipNodes[0]?.node||null;this.vae=this.flow.vaeNodes[0]?.node||null;
+        this.positive=this.flow.encoders.positive.length===1?this.flow.encoders.positive[0].node:null;
+        this.negative=this.flow.encoders.negative.length===1?this.flow.encoders.negative[0].node:null;
+        this.lora=this.flow.loras[0]?.node||null;
+        this.promptSources={positive:T("Actual sampler connections"),negative:T("Actual sampler connections")};
+        const signature=JSON.stringify([this.profileId,this.flow.refs,[...this.flow.modelNodes,...this.flow.clipNodes,...this.flow.vaeNodes].map(e=>e.id),Object.entries(this.flow.encoders).map(([kind,items])=>[kind,items.map(e=>[e.id,e.fields])])]);
+        // Do not replace a focused textarea for ordinary background validation.
+        if(render && signature!==this.routingSignature){this.routingSignature=signature;this.render();}
+    }
+    changed() { this.markChanged(); this.onChange(this); }
+    modelDependencies() {
+        const specs={CheckpointLoader:['ckpt_name','checkpoints',T("Main model"),'checkpoints'],CheckpointLoaderSimple:['ckpt_name','checkpoints',T("Main model"),'checkpoints'],
+            UNETLoader:['unet_name','unets',T("Main model"),'diffusion_models'],
+            UNETLoaderGGUF:['unet_name','ggufs',T("Main model"),'diffusion_models'],
+            CLIPLoader:['clip_name','clips',T("Text encoder"),'text_encoders'],
+            CLIPLoaderGGUF:['clip_name','clipggufs',T("Text encoder"),'text_encoders'],
+            VAELoader:['vae_name','vaes','VAE','vae']};
+        const entries=this.flow?[...this.flow.modelNodes,...this.flow.clipNodes,...this.flow.vaeNodes]:[];
+        const unique=entries.filter((e,i,all)=>all.findIndex(x=>x.id===e.id)===i);
+        return unique.flatMap(entry=>{
+            const node=entry.node;
+            if(['DualCLIPLoader','TripleCLIPLoader','DualCLIPLoaderGGUF'].includes(node?.type))return [1,2,3].flatMap(index=>{const w=widget(node,'clip_name'+index);return w?[{...entry,widget:w,key:node.type.endsWith('GGUF')?'clipggufs':'clips',label:T("Text encoder {index}",{index}),folder:'text_encoders'}]:[];});
+            const spec=specs[node?.type];if(!spec)return [];
+            const [name,key,label,folder]=spec,w=widget(node,name);
+            if(w)return [{...entry,widget:w,key,label,folder}];
+            return [];
+        });
+    }
+    missingDependencies() {
+        return this.modelDependencies().filter(d=>this.catalogReady.has(d.key) && d.widget.value && !this.catalog[d.key].includes(String(d.widget.value)));
+    }
+    refreshProfiles() {
+        this.nodes=nodeList(this.graph);
+        const controller = presetController(this.nodes,this.sampler,this.graph);
+        const signature = JSON.stringify([controller?.node?.id, controller?.data?.activeId, controller?.data?.presets?.map(p=>[p.id,p.name])]);
+        if(signature===this.presetSignature)return;
+        this.presetSignature=signature;
+        this.controller=controller;
+        this.owner=controller?.node || this.sampler;
+        this.owner.properties ??= {};
+        this.owner.properties[stateKey] ??= {profiles:{}};
+        this.profiles=controller?.data?.presets?.map(p=>({id:p.id,name:p.name,preset:p})) || [];
+        if(!this.profiles.length)this.profiles=[{id:'current',name:T("Current workflow")}];
+        this.profileId=controller?.data?.activeId || (this.profiles.some(p=>p.id===this.profileId)?this.profileId:this.profiles[0].id);
+        this.resolve();this.render();this.onChange(this);
+    }
+    selectProfile(id) {
+        if (!this.profiles.some(p=>p.id===id)) throw Error(T("The group preset no longer exists"));
+        this.profileId=id;
+        this.controller?.apply(id);
+        this.resolve(); this.render(); this.changed();
+    }
+    getExecutionBinding() {
+        const binding={samplerInputs:{},inputOverrides:{},removeInputs:{},
+            loraMode:this.settings.loraMode,loras:this.settings.loras,clipConsumers:this.flow?.clipConsumers||[]};
+        if(!this.flow)throw Error(T("Reading workflow connections; please wait"));
+        // Final MODEL and CONDITIONING refs remain untouched, including custom
+        // model patches, ControlNet and combinations of multiple encoders.
+        for(const [kind,entries] of Object.entries(this.flow.encoders))for(const entry of entries)for(const field of entry.fields){
+            const target=this.settings.textOverrides[entry.id]||{};
+            const legacy=entries.length===1 && field==='text' && Object.hasOwn(this.settings,kind);
+            if(Object.hasOwn(target,field)||legacy){binding.inputOverrides[entry.id]??={};binding.inputOverrides[entry.id][field]=Object.hasOwn(target,field)?target[field]:this.settings[kind];}
+        }
+        if(!this.settings.useRefiner || Number(widget(this.sampler,'refiner_switch')?.value??1)>=1)binding.removeInputs[this.samplerId]=['refiner_model','refiner_positive','refiner_negative'];
+        return binding;
+    }
+    async loadCatalog(fetchApi) {
+        this.catalogController?.abort();const controller=this.catalogController=new AbortController(),timer=setTimeout(()=>controller.abort(),15000);
+        const get = async path => {const r=await fetchApi(path,{signal:controller.signal});if(!r.ok)throw Error(T("Model list request failed ({status})",{status:r.status}));return r.json();};
+        const sources=[['checkpoints','/object_info/CheckpointLoaderSimple','CheckpointLoaderSimple','ckpt_name'],
+            ['unets','/object_info/UNETLoader','UNETLoader','unet_name'],
+            ['clips','/object_info/CLIPLoader','CLIPLoader','clip_name'],
+            ['vaes','/object_info/VAELoader','VAELoader','vae_name'],['loras','/models/loras']];
+        let results;try{results=await Promise.allSettled(sources.map(([,path])=>get(path)));}finally{clearTimeout(timer);}
+        if(this.destroyed || this.catalogController!==controller)return;
+        results.forEach((result,i)=>{if(result.status!=='fulfilled')return;const [key,,type,input]=sources[i];
+            const values=type?result.value?.[type]?.input?.required?.[input]?.[0]:result.value;
+            if(Array.isArray(values)){this.catalog[key]=values.map(String);this.catalogReady.add(key);}
+        });
+        this.catalogError=results.some(r=>r.status==='rejected')?T("Some model lists are unavailable; existing workflow selections remain usable"):'';
+        this.render();
+    }
+    createPanel() { this.root=document.createElement('section');this.root.className='aw-bindings';this.render();return this.root; }
+    render() {
+        if(!this.root || this.destroyed)return;
+        const doc=this.root.ownerDocument;
+        const active=doc.activeElement;
+        const focus=active?.tagName==='TEXTAREA' && this.root.contains(active)?{
+            id:active.dataset.executionId,field:active.dataset.widget,
+            start:active.selectionStart,end:active.selectionEnd,direction:active.selectionDirection,scroll:active.scrollTop,
+        }:null;
+        const el=(tag,text)=>{const e=doc.createElement(tag);if(text)e.textContent=text;return e;};
+        const row=(label,control)=>{const l=el('label',label);l.append(control);return l;};
+        const select=(values,current,change)=>{const s=el('select');for(const [value,label] of values){const o=el('option',label);o.value=value;s.append(o);}s.value=current;s.onchange=()=>change(s.value);return s;};
+        this.root.replaceChildren();
+        const presets=el('div');presets.className='aw-presets';
+        const controllerActive = this.controller && this.controller.node.mode === 0;
+        if (!controllerActive) {const multiple=this.nodes.filter(n=>n.type==='AdachiGroupPresets'&&n.mode===0).length>1;const warning=el('p',multiple?T("Multiple group preset controllers found; choose one in Workflow connections."):T("No enabled Group Bypass Presets node; using the current workflow settings."));warning.className='aw-profile-warning';warning.setAttribute('role','status');this.root.append(warning);}
+        for(const p of controllerActive ? this.profiles : []){const b=el('button',p.name);b.type='button';b.setAttribute('aria-pressed',String(p.id===this.profileId));b.onclick=()=>this.selectProfile(p.id);presets.append(b);}
+        this.root.append(presets);
+        const missing=this.missingDependencies();
+        if(missing.length){const warning=el('details'),head=el('summary',T("Missing {count} model files",{count:missing.length}));warning.className='aw-model-warning';warning.title=missing.map(d=>T("{label}: {value}",{label:d.label,value:d.widget.value})).join('\n');warning.append(head);
+            const list=el('ul');for(const d of missing){const item=el('li',T("{label}: {value}",{label:d.label,value:d.widget.value}));item.append(el('small',`ComfyUI/models/${d.folder}/`));list.append(item);}warning.append(list);this.root.append(warning);}
+        const details=el('details'),summary=el('summary',T("Main model and LoRA"));details.append(summary);details.open=!!this.detailsOpen;details.ontoggle=()=>{this.detailsOpen=details.open;};
+        const dependencies=this.modelDependencies();
+        for(const d of dependencies){const w=d.widget,current=String(w.value||'');const values=[...new Set([...valueList(w),...this.catalog[d.key],current])].filter(Boolean);
+            const label=dependencies.filter(x=>x.label===d.label).length>1?`${d.label} · ${d.node.title||d.node.type} #${d.id}`:d.label;const field=row(label,select(values.map(v=>[v,v]),current,v=>{w.value=v;w.callback?.(v,this.canvas,d.node);this.render();this.changed();}));field.title=`ComfyUI/models/${d.folder}/`;details.append(field);}
+        if(!dependencies.some(d=>d.node===this.model))details.append(el('p',T("This profile uses the model from the workflow")));
+        const loraTitle=el('div','LoRA');details.append(loraTitle);
+        const inherit=el('input');inherit.type='checkbox';inherit.checked=this.settings.loraMode==='inherit';inherit.onchange=()=>{this.settings.loraMode=inherit.checked?'inherit':'override';this.render();this.changed();};const inheritRow=row(T("Inherit workflow LoRAs"),inherit);inheritRow.title=T("Keep existing LoRA nodes and both CLIP branches; uncheck to use the custom list below. An empty custom list disables recognized LoRAs.");details.append(inheritRow);
+        if(inherit.checked){
+            const active=[];for(const entry of this.flow?.loras||[]){const input=entry.api.inputs||{};if(entry.api.class_type==='Power Lora Loader (rgthree)'){for(const value of Object.values(input))if(value?.on && value.lora)active.push(`${value.lora} · ${value.strength??1}`);}else if(input.lora_name && (Number(input.strength_model)||Number(input.strength_clip)))active.push(`${input.lora_name} · ${input.strength_model??1}`);}
+            const info=el('small',active.length?active.join(' / '):T("No active LoRAs in the original workflow"));info.title=active.join('\n');details.append(info);
+        }
+        const customLoras=el('div');customLoras.hidden=inherit.checked;details.append(customLoras);
+
+        if(!this.settings.loras.length)customLoras.append(el('small',T("No LoRA")));
+        this.settings.loras.forEach((l,index)=>{
+            const line=el('div');line.className='aw-lora-row';
+            const names=[...new Set([...this.catalog.loras,l.name].filter(Boolean))];
+            const pick=select([['',T("None")],...names.map(n=>[n,n])],l.name||'',v=>{l.name=v;this.changed();});pick.setAttribute('aria-label',T("LoRA {index}",{index:index+1}));
+            const strength=el('input');strength.type='number';strength.min='-10';strength.max='10';strength.step='0.05';strength.value=l.strength??1;strength.setAttribute('aria-label',T("LoRA {index} strength",{index:index+1}));strength.onchange=()=>{const n=Number(strength.value);if(Number.isFinite(n)){l.strength=Math.max(-10,Math.min(10,n));strength.value=l.strength;this.changed();}};
+            const remove=el('button','×');remove.type='button';remove.title=T("Remove this LoRA");remove.onclick=()=>{this.settings.loras.splice(index,1);this.render();this.changed();};
+            line.append(pick,strength,remove);customLoras.append(line);
+        });
+        const add=el('button',T("＋ Add LoRA"));add.type='button';add.disabled=!this.flow?.refs.model;add.onclick=()=>{this.settings.loras.push({name:'',strength:1});this.render();this.changed();};customLoras.append(add);
+        const refiner=el('input');refiner.type='checkbox';refiner.checked=!!this.settings.useRefiner;
+        refiner.onchange=()=>{this.settings.useRefiner=refiner.checked;this.changed();};
+        details.append(row(T("Use the workflow Refiner (must be compatible with the main model)"),refiner));
+        if(this.catalogError)details.append(el('small',this.catalogError));
+        this.root.append(details);
+        for(const [kind,label] of [['positive',T("Positive prompt")],['negative',T("Negative prompt")]]) {
+            const entries=this.flow?.encoders[kind]||[];
+            const container=el('details');container.className='aw-prompt-section';container.dataset.promptKind=kind;
+            container.append(el('summary',entries.length>1?T("{label} · {count} encoders",{label,count:entries.length}):label));
+            const savedOpen=this.sampler.properties?.adachi_workspace_ui?.promptOpen?.[kind];
+            let lastOpen=typeof savedOpen==='boolean'?savedOpen:entries.length<=1;
+            container.open=lastOpen;
+            container.ontoggle=()=>{
+                // Native <details> emits asynchronous toggle events even when
+                // open is initialized programmatically or an old panel is removed.
+                if(!container.isConnected || container.open===lastOpen)return;
+                lastOpen=container.open;this.sampler.properties??={};
+                let ui=this.sampler.properties.adachi_workspace_ui;
+                if(!ui || typeof ui!=='object' || Array.isArray(ui))ui=this.sampler.properties.adachi_workspace_ui={};
+                if(!ui.promptOpen || typeof ui.promptOpen!=='object' || Array.isArray(ui.promptOpen))ui.promptOpen={};
+                ui.promptOpen[kind]=lastOpen;this.markChanged();
+            };
+            this.root.append(container);
+            if(!entries.length){const info=el('p',this.flow?T("Controlled by the original workflow"):T("Reading connections…"));info.title=T("Encoders are identified from the execution graph; unrecognized conditioning stays controlled by the original workflow");container.append(info);continue;}
+            for(const entry of entries)for(const name of entry.fields){
+                const w=widget(entry.node,name),linked=Array.isArray(entry.api.inputs?.[name]);
+                const saved=this.settings.textOverrides[entry.id]||{},legacy=entries.length===1&&name==='text'?this.settings[kind]:undefined;
+                const text=el('textarea');text.rows=kind==='positive'?6:3;
+                text.value=saved[name]??legacy??(linked?'':w?.value??entry.api.inputs?.[name]??'');
+                text.placeholder=linked?T("Inherit upstream dynamic text; type to override"):'';
+                text.dataset.executionId=entry.id;text.dataset.widget=name;
+                text.oninput=()=>{this.settings.textOverrides[entry.id]??={};this.settings.textOverrides[entry.id][name]=text.value;this.changed();};
+                const title=entries.length>1||entry.fields.length>1?`${label} · ${entry.node?.title||entry.api.class_type} · ${name}`:label;
+                text.setAttribute('aria-label',title);const field=row(entries.length===1&&entry.fields.length===1?'':title,text);
+                field.title=T("Actual sampler connections · {node} #{id} · {field}. {description}",{node:entry.node?.title||entry.api.class_type,id:entry.id,field:name,description:linked?T("Text comes from upstream; typing creates an override."):T("Changes affect only this encoder; downstream conditioning is preserved.")});
+                const reset=el('button','↶');reset.type='button';reset.title=T("Restore {label} from the workflow",{label:title});reset.onclick=()=>{delete this.settings.textOverrides[entry.id]?.[name];if(entries.length===1&&name==='text')delete this.settings[kind];this.render();this.changed();};field.append(reset);container.append(field);
+            }
+        }
+        // Catalog and route discovery can re-render the panel asynchronously.
+        // Restore the active prompt and caret only when that field still exists
+        // and is visible; switching profile or closing a fold must not steal focus.
+        if(focus){
+            const target=[...this.root.querySelectorAll('textarea')].find(el=>el.dataset.executionId===focus.id && el.dataset.widget===focus.field);
+            if(target && !target.closest('details:not([open])')){
+                target.focus({preventScroll:true});
+                target.setSelectionRange(focus.start,focus.end,focus.direction);target.scrollTop=focus.scroll;
+            }
+        }
+    }
+    destroy() {this.destroyed=true;this.catalogController?.abort();this.root?.remove();}
+}

web/workspace_execution.js

@@ -0,0 +1,48 @@
+import {T} from './i18n.js';
+import {app} from '../../scripts/app.js';
+import {api} from '../../scripts/api.js';
+import {workspaceRequest} from './workspace_transport.js';
+import {workspaceRoutingNodes} from './workspace_activation.js';
+import {applyExecutionBinding,graphNodeEntries,executionId,executionNode} from './workspace_flow.js';
+const graphTasks=new WeakMap();
+const link=value=>Array.isArray(value)&&value.length===2&&typeof value[0]==='string'&&Number.isInteger(value[1]);
+function depends(prompt,ref,target,seen=new Set()) {
+ if(!link(ref)||seen.has(ref[0]))return false;if(ref[0]===target)return true;seen.add(ref[0]);
+ return Object.values(prompt[ref[0]]?.inputs||{}).some(input=>depends(prompt,input,target,seen));
+}
+export function prepareWorkspacePrompt(options) {
+ const graph=app.rootGraph||app.graph;
+ const previous=graphTasks.get(graph)||Promise.resolve();
+ const task=previous.catch(()=>{}).then(()=>prepareSnapshot(graph,options));graphTasks.set(graph,task);return task;
+}
+async function prepareSnapshot(graph,{editorNode,samplerNode,compareNode,binding={},getBinding,allowEmpty=false,controller}) {
+ if(!editorNode?.adachiEditor?.ready && !allowEmpty)throw Error(T("Upload a source image first"));
+ const entries=graphNodeEntries(graph),roots=[editorNode,samplerNode,compareNode];
+ if(graph!==(app.rootGraph||app.graph)||roots.some(n=>!entries.some(e=>e.node===n)))throw Error(T("The workflow changed; reopen the workbench"));
+ const ids=roots.map(n=>executionId(graph,n)),[editorId,samplerId,compareId]=ids;
+ const parents=roots.flatMap(node=>{const path=executionId(graph,node).split(':');return path.slice(0,-1).map((_,i)=>executionNode(graph,path.slice(0,i+1).join(':'))).filter(Boolean);});
+ const routers=workspaceRoutingNodes(roots,controller),modes=new Map([...parents,...roots,...routers].map(n=>[n,n.mode]));
+ if(editorNode.adachiEditor.ready)editorNode.adachiEditor.flush();let prepared;
+ try {
+  for(const node of modes.keys())node.mode=0;
+  prepared=typeof app.ue_modified_prompt==='function'?await app.ue_modified_prompt():await app.graphToPrompt();
+  if(!prepared?.output)throw Error(T("Workflow connections could not be resolved; check bypass states, Get/Set and broadcast connections"));
+ } finally {for(const [node,mode]of modes)node.mode=mode;}
+ if(graph!==(app.rootGraph||app.graph))throw Error(T("The workflow changed; check connections again"));
+ const output=prepared.output,sampler=output[samplerId],compare=output[compareId];
+ if(!sampler||!compare||!output[editorId])throw Error(T("The selected image, inpaint or comparison node is missing from the execution graph"));
+ // Existing image processors and result postprocessing remain connected. An
+ // unconnected workbench can use its explicitly selected inline source/output.
+ if(!depends(output,sampler.inputs.image,editorId)){sampler.inputs.image=[editorId,0];sampler.inputs.mask=[editorId,1];}
+ else if(!link(sampler.inputs.mask))sampler.inputs.mask=[editorId,1];
+ if(!link(compare.inputs.original))compare.inputs.original=[editorId,0];
+ if(!depends(output,compare.inputs.result,samplerId))compare.inputs.result=[samplerId,0];
+ const resolved=getBinding?await getBinding(output,samplerId):binding;
+ const prompt=applyExecutionBinding(output,samplerId,resolved);
+ // Keep the editable workflow, including ignored groups and original routers,
+ // in PNG metadata. Only the separate API execution graph is specialized.
+ const workflow=JSON.parse(JSON.stringify(graph.serialize()));
+ return {prompt,compare_id:compareId,client_id:api.clientId||'',extra_data:{extra_pnginfo:{workflow},auth_token_comfy_org:api.authToken,api_key_comfy_org:api.apiKey}};
+}
+export const validateWorkspace=(prepared,options)=>workspaceRequest(api,'validate',prepared,options);
+export const submitWorkspace=prepared=>workspaceRequest(api,'submit',prepared);

web/workspace_flow.js

@@ -0,0 +1,133 @@
+import {T} from './i18n.js';
+const link=value=>Array.isArray(value) && value.length===2 && ['string','number'].includes(typeof value[0]) && Number.isInteger(value[1]);
+const asRef=value=>link(value)?[String(value[0]),value[1]]:null;
+const loraTypes=new Set(['LoraLoader','LoraLoaderModelOnly','Power Lora Loader (rgthree)']);
+const staticRouter=api=>api.class_type==='AdachiExclusiveSwitch'||(['ComfySwitchNode','ComfySoftSwitchNode'].includes(api.class_type)&&typeof api.inputs?.switch==='boolean');
+const loaderTypes={MODEL:new Set(['CheckpointLoaderSimple','CheckpointLoader','UNETLoader','UNETLoaderGGUF','CheckpointLoaderNF4']),
+    CLIP:new Set(['CheckpointLoaderSimple','CheckpointLoader','CLIPLoader','DualCLIPLoader','TripleCLIPLoader','CLIPLoaderGGUF','DualCLIPLoaderGGUF']),
+    VAE:new Set(['CheckpointLoaderSimple','CheckpointLoader','VAELoader'])};
+
+function sourceInputs(api) {
+    if(['ComfySwitchNode','ComfySoftSwitchNode'].includes(api.class_type)&&typeof api.inputs?.switch==='boolean'){
+        const inputs=api.inputs;if(api.class_type==='ComfySoftSwitchNode'){
+            if(!Object.hasOwn(inputs,'on_false'))return [inputs.on_true];if(!Object.hasOwn(inputs,'on_true'))return [inputs.on_false];
+        }
+        return [inputs[inputs.switch?'on_true':'on_false']];
+    }
+    if(api.class_type==='AdachiExclusiveSwitch') {
+        const mask=Number(api.inputs?.active_inputs);
+        if(mask===1)return [api.inputs.input_a];if(mask===2)return [api.inputs.input_b];
+    }
+    return Object.values(api.inputs||{});
+}
+function ancestors(prompt,refs) {
+    const found=new Set(),queue=refs.map(asRef).filter(Boolean);
+    while(queue.length){const [id]=queue.pop();if(found.has(id)||!prompt[id])continue;found.add(id);queue.push(...sourceInputs(prompt[id]).map(asRef).filter(Boolean));}
+    return found;
+}
+function origins(prompt,start,type,lookup) {
+    const found=[],seen=new Set(),queue=[asRef(start)].filter(Boolean);
+    while(queue.length){const [id,slot]=queue.shift(),key=`${id}:${slot}`;if(seen.has(key))continue;seen.add(key);
+        const api=prompt[id],node=lookup(id);if(!api)continue;
+        if(loaderTypes[type].has(api.class_type)){found.push({id,node,api});continue;}
+        if(staticRouter(api)){queue.push(...sourceInputs(api).map(asRef).filter(Boolean));continue;}
+        if(loraTypes.has(api.class_type)){const ref=asRef(api.inputs?.[type==='MODEL'?'model':type==='CLIP'?'clip':'vae']);if(ref)queue.push(ref);continue;}
+        const typed=(node?.inputs||[]).filter(i=>i.type===type).map(i=>i.name);
+        const names=typed.length?typed:Object.keys(api.inputs||{}).filter(name=>new RegExp(`^${type.toLowerCase()}(?:$|[_\\d])`,'i').test(name));
+        queue.push(...names.map(name=>asRef(api.inputs[name])).filter(Boolean));
+    }
+    return found.filter((item,i,all)=>all.findIndex(x=>x.id===item.id)===i);
+}
+function encoders(prompt,start,lookup) {
+    const found=[],seen=new Set(),queue=[asRef(start)].filter(Boolean);
+    while(queue.length){const [id,slot]=queue.shift(),key=`${id}:${slot}`;if(seen.has(key))continue;seen.add(key);
+        const api=prompt[id],node=lookup(id);if(!api)continue;
+        const fields=(node?.widgets||[]).filter(w=>/^(text(?:_[gl])?|prompt)$/i.test(w.name) && typeof w.value==='string').map(w=>w.name);
+        const output=node?.outputs?.[slot];
+        if(fields.length && (output?.type==='CONDITIONING'||/^CLIPTextEncode/.test(api.class_type))){found.push({id,node,api,fields});continue;}
+        if(staticRouter(api)){queue.push(...sourceInputs(api).map(asRef).filter(Boolean));continue;}
+        const selected=output?.name && /^(positive|negative)$/i.test(output.name) && asRef(api.inputs?.[output.name]);
+        if(selected){queue.push(selected);continue;}
+        const names=(node?.inputs||[]).filter(i=>i.type==='CONDITIONING').map(i=>i.name);
+        const fallback=Object.keys(api.inputs||{}).filter(name=>/^(positive|negative|conditioning(?:_\d+)?)$/i.test(name));
+        queue.push(...(names.length?names:fallback).map(name=>asRef(api.inputs[name])).filter(Boolean));
+    }
+    return found.filter((item,i,all)=>all.findIndex(x=>x.id===item.id)===i);
+}
+
+export function inspectExecutionFlow(prompt,samplerId,lookup=()=>null) {
+    const api=prompt[String(samplerId)],refs={};
+    for(const name of ['model','positive','negative','vae'])refs[name]=asRef(api?.inputs?.[name]);
+    const positive=encoders(prompt,refs.positive,lookup),negative=encoders(prompt,refs.negative,lookup);
+    const allEncoders=[...positive,...negative].filter((item,i,all)=>all.findIndex(x=>x.id===item.id)===i);
+    const consumers=allEncoders.filter(e=>asRef(e.api.inputs?.clip)).map(e=>({id:e.id,input:'clip'}));
+    const clipNodes=consumers.flatMap(e=>origins(prompt,prompt[e.id].inputs[e.input],'CLIP',lookup)).filter((e,i,all)=>all.findIndex(x=>x.id===e.id)===i);
+    return {refs,modelNodes:origins(prompt,refs.model,'MODEL',lookup),clipNodes,
+        vaeNodes:origins(prompt,refs.vae,'VAE',lookup),encoders:{positive,negative},clipConsumers:consumers,
+        loras:[...ancestors(prompt,Object.values(refs))].filter(id=>loraTypes.has(prompt[id].class_type)).map(id=>({id,node:lookup(id),api:prompt[id]}))};
+}
+
+export function executionNode(graph,id) {
+    const path=String(id).split(':');let node;
+    for(let i=0;i<path.length;i++){node=graph?.getNodeById(path[i]);if(!node && /^-?\d+$/.test(path[i]))node=graph?.getNodeById(Number(path[i]));if(!node)return null;if(i<path.length-1)graph=node.subgraph;}
+    return node;
+}
+
+export function graphNodeEntries(graph,prefix=[],seen=new Set()) {
+    if(!graph || seen.has(graph))return [];seen.add(graph);
+    return Array.from(graph._nodes||[]).flatMap(node=>{
+        const path=[...prefix,String(node.id)];
+        return [{id:path.join(':'),node,graph},...graphNodeEntries(node.subgraph,path,seen)];
+    });
+}
+export const executionId=(graph,node)=>graphNodeEntries(graph).find(entry=>entry.node===node)?.id;
+
+// Rewrite only the chosen sampler's ancestry. Other output branches keep their
+// graph definitions; the backend subsequently queues only the comparison target.
+export function applyExecutionBinding(original,samplerId,binding={}) {
+    // Native widget values can be Vue proxies (for example rgthree LoRA
+    // rows). Copy using the same JSON boundary as ComfyUI's queue request.
+    const prompt=JSON.parse(JSON.stringify(original)),id=String(samplerId),sampler=prompt[id];
+    if(!sampler)throw Error(T("The selected inpaint node is missing from the execution graph"));
+    Object.assign(sampler.inputs,binding.samplerInputs||{});
+    for(const [key,inputs] of Object.entries(binding.inputOverrides||{})){
+        if(!prompt[key])throw Error(T("The selected parameter node is missing from the execution graph #{id}",{id:key}));Object.assign(prompt[key].inputs,inputs);
+    }
+    for(const [key,names] of Object.entries(binding.removeInputs||{}))for(const name of names)if(prompt[key])delete prompt[key].inputs[name];
+    const scope=()=>new Set([id,...ancestors(prompt,Object.values(sampler.inputs))]);
+    const collapse=(candidates,choose)=>{
+        const resolve=(value,seen=new Set())=>{
+            const ref=asRef(value);if(!ref || !candidates.has(ref[0]))return ref;
+            if(seen.has(ref[0]))return null;seen=new Set(seen);seen.add(ref[0]);
+            const next=choose(prompt[ref[0]],ref[1]);return next?resolve(next,seen):null;
+        };
+        for(const key of scope())if(!candidates.has(key))for(const [name,value] of Object.entries(prompt[key]?.inputs||{})){
+            const ref=asRef(value);if(ref && candidates.has(ref[0])){const result=resolve(ref);if(result && prompt[result[0]])prompt[key].inputs[name]=result;}
+        }
+    };
+    const switches=new Set([...scope()].filter(key=>prompt[key]?.class_type==='AdachiExclusiveSwitch' && [1,2].includes(Number(prompt[key].inputs.active_inputs))));
+    collapse(switches,(api,slot)=>slot===0?api.inputs[Number(api.inputs.active_inputs)===1?'input_a':'input_b']:null);
+    if(binding.loraMode==='override') {
+        const loras=new Set([...scope()].filter(key=>loraTypes.has(prompt[key]?.class_type)));
+        collapse(loras,(api,slot)=>slot===0?api.inputs.model:slot===1?api.inputs.clip:null);
+        const selected=(binding.loras||[]).filter(l=>l.name && l.on!==false);
+        if(selected.length){
+            const baseModel=asRef(sampler.inputs.model);if(!baseModel)throw Error(T("Connect a main model before adding LoRAs"));
+            let nextId=-1000000;
+            const fresh=()=>{while(prompt[String(nextId)])nextId--;return String(nextId--);};
+            const consumers=(binding.clipConsumers||[]).filter(c=>asRef(prompt[c.id]?.inputs?.[c.input]));
+            const unique=new Map();for(const c of consumers){const ref=asRef(prompt[c.id].inputs[c.input]),key=JSON.stringify(ref);if(!unique.has(key))unique.set(key,{ref,consumers:[]});unique.get(key).consumers.push(c);}
+            const chains=unique.size?[...unique.values()]:[{ref:null,consumers:[]}];
+            chains.forEach((chain,index)=>{
+                let model=baseModel,clip=chain.ref;
+                for(const l of selected){const key=fresh(),inputs={model,lora_name:l.name,strength_model:Number(l.strength??1)};
+                    if(clip)Object.assign(inputs,{clip,strength_clip:Number(l.clipStrength??l.strength??1)});
+                    prompt[key]={class_type:clip?'LoraLoader':'LoraLoaderModelOnly',inputs};model=[key,0];if(clip)clip=[key,1];
+                }
+                if(index===0)sampler.inputs.model=model;
+                for(const c of chain.consumers)prompt[c.id].inputs[c.input]=clip;
+            });
+        }
+    }
+    return prompt;
+}

web/workspace_history.js

@@ -0,0 +1,167 @@
+import {T} from './i18n.js';
+// Session-only source checkpoints for the full-screen workspace. Capturing and
+// restoring never uploads a new image or serializes the rest of the workflow.
+const WIDGETS = ["image", "mask_data", "source_data", "edit_mode", "crop_state", "blend_data", "layer_image", "paint_data"];
+const copyCommands = commands => (commands || []).map(command => ({ ...command,
+    ...(command.points ? {points: command.points.map(point => ({...point}))} : {}),
+}));
+
+function contextSnapshot(context) {
+    return {
+        mask: context.mask.toDataURL("image/png"),
+        baseMask: context.baseMask.toDataURL("image/png"),
+        history: copyCommands(context.history), future: copyCommands(context.future),
+        lastMask: context.lastMask || "", dirty: !!context.dirty,
+    };
+}
+
+async function decodeCanvas(data) {
+    const image = new Image(); image.src = data;
+    await image.decode();
+    const canvas = document.createElement("canvas");
+    canvas.width = image.naturalWidth || image.width; canvas.height = image.naturalHeight || image.height;
+    canvas.getContext("2d").drawImage(image, 0, 0);
+    return canvas;
+}
+
+export function captureSourceState(node) {
+    const editor = node.adachiEditor, crop = node.adachiCrop;
+    if (!editor?.ready || !editor.image || editor.destroyed) throw Error(T("Load a source image first"));
+    if (editor.stroke || editor.pointerId != null || crop?.busy || node.adachiColorPaint?.drawing || node.adachiColorPaint?.restoring) throw Error(T("Finish the current edit first"));
+    editor.flush();
+    const target = crop?.target || "mask", contexts = {};
+    for (const [name, context] of Object.entries(crop?.contexts || {})) {
+        if (name !== target && context?.mask && context?.baseMask) contexts[name] = contextSnapshot(context);
+    }
+    contexts[target] = contextSnapshot(editor);
+    const state = {
+        widgets: Object.fromEntries(WIDGETS.map(name => [name, node.widgets?.find(widget => widget.name === name)?.value])),
+        image: editor.image, layer: crop?.layer || null, contexts, target,
+        cropWidth: crop?.cropWidth, cropHeight: crop?.cropHeight,
+        filename: editor.filename?.textContent || "", embed: !!editor.embed?.checked,
+        view: editor.view, zoom: editor.zoom, pan: {...editor.pan}, keepFit: !!editor.keepFit,
+    };
+    state.key = JSON.stringify([state.widgets, state.image.src, state.layer?.src, state.contexts, state.target]);
+    return state;
+}
+
+function releaseContexts(contexts, active) {
+    const canvases = new Set();
+    for (const context of Object.values(contexts || {})) for (const name of ["mask", "baseMask"]) {
+        if (context?.[name] && context[name] !== active?.mask && context[name] !== active?.baseMask) canvases.add(context[name]);
+    }
+    for (const canvas of canvases) canvas.width = canvas.height = 0;
+}
+
+export async function restoreSourceState(node, state, {decode = decodeCanvas, onRestore} = {}) {
+    const editor = node.adachiEditor, crop = node.adachiCrop;
+    if (!editor || editor.destroyed || !node.graph) throw Error(T("The source image node was removed"));
+    if (editor.stroke || editor.pointerId != null || crop?.busy || node.adachiColorPaint?.drawing || node.adachiColorPaint?.restoring) throw Error(T("Finish the current edit first"));
+    const loadVersion = editor.loadVersion, maskRevision = editor.maskRevision, cropRevision=crop?.revision, paintRevision=node.adachiColorPaint?.revision;
+    const contexts = {};
+    let paintSnapshot;
+    try {
+        // Decode all masks before altering live state. A failed decode leaves
+        // the working image, mask and crop completely untouched.
+        for (const [name, context] of Object.entries(state.contexts)) {
+            const decoded=await Promise.allSettled([decode(context.mask), decode(context.baseMask)]);
+            const failed=decoded.find(item=>item.status==='rejected');
+            if(failed){for(const item of decoded)if(item.status==='fulfilled')item.value.width=item.value.height=0;throw failed.reason;}
+            const [mask,baseMask]=decoded.map(item=>item.value);
+            contexts[name] = {...context, mask, baseMask, history:copyCommands(context.history), future:copyCommands(context.future)};
+        }
+        if(node.adachiColorPaint?.prepareRestore) paintSnapshot = await node.adachiColorPaint.prepareRestore(state.widgets.paint_data || "",state.image.width,state.image.height);
+        if (editor.destroyed || !node.graph || editor.loadVersion !== loadVersion || editor.maskRevision !== maskRevision || crop?.revision !== cropRevision || node.adachiColorPaint?.revision !== paintRevision || editor.stroke || editor.pointerId != null || crop?.busy || node.adachiColorPaint?.drawing || node.adachiColorPaint?.restoring) {
+            throw Error(T("The image changed during restoration; try again"));
+        }
+    } catch (error) { releaseContexts(contexts); throw error; }
+    const active = contexts[state.target];
+    if (!active) { releaseContexts(contexts); throw Error(T("The saved mask state is invalid")); }
+    const oldContexts = {...(crop?.contexts || {}), live: {mask:editor.mask, baseMask:editor.baseMask}};
+    crop?.stopOriginalPreview?.();
+    for (const [name, value] of Object.entries(state.widgets)) {
+        const widget = node.widgets?.find(widget => widget.name === name);
+        if (widget && value !== undefined) widget.value = value;
+    }
+    editor.loadVersion++;
+    editor.image = state.image;
+    Object.assign(editor, active);
+    editor.view = state.view; editor.zoom = state.zoom; editor.pan = {...state.pan};
+    editor.keepFit = state.keepFit; editor.ready = true;
+    editor.stroke = null; editor.pointerId = null; editor.drag = null; editor.cursor = null;
+    editor.sceneKey = null; editor.maskRevision++;
+    if (editor.filename) { editor.filename.textContent = state.filename; editor.filename.title = state.filename; }
+    if (editor.sizeLabel) editor.sizeLabel.textContent = `${state.image.width} × ${state.image.height}`;
+    if (editor.embed) editor.embed.checked = state.embed;
+    node.properties ??= {}; node.properties.adachi_keep_fit = state.keepFit;
+    if (editor.empty) editor.empty.hidden = true;
+    if (crop) {
+        clearTimeout(crop.resultTimer); crop.pendingResult = null; crop.acceptVersion++;
+        crop.contexts = contexts; crop.target = state.target; crop.layer = state.layer;
+        crop.cropWidth = state.cropWidth; crop.cropHeight = state.cropHeight;
+        crop.hover = null; crop.revision++; crop.patchKey = null;
+        crop.syncPreset?.(); crop.sync?.();
+    }
+    if(node.adachiColorPaint?.commitRestore) node.adachiColorPaint.commitRestore(paintSnapshot,state.image.width,state.image.height);
+    releaseContexts(oldContexts, active);
+    editor.updateButtons?.(); editor.schedule?.();
+    node.graph.setDirtyCanvas?.(true, true);
+    await onRestore?.(state);
+    return state;
+}
+
+function estimateBytes(entries) {
+    const images = new Set(); let bytes = 0;
+    for (const {state} of entries) {
+        bytes += state.key.length * 2;
+        for (const image of [state.image, state.layer]) if (image && !images.has(image)) {
+            images.add(image); bytes += image.width * image.height * 4;
+        }
+    }
+    return bytes;
+}
+
+export class WorkspaceHistory {
+    constructor(node, {maxEntries = 12, maxBytes = 256 * 1024 * 1024, onChange, onRestore} = {}) {
+        Object.assign(this, {node, maxEntries:Math.max(2,maxEntries), maxBytes, onChange, onRestore});
+        this.entries = []; this.index = -1; this.busy = false;
+    }
+    get current() { return this.entries[this.index] || null; }
+    get canUndo() { return this.index > 0 && !this.busy; }
+    checkpoint(label = T("Source image")) {
+        const state = captureSourceState(this.node);
+        if (this.current?.state.key === state.key) return this.current;
+        this.entries.splice(this.index + 1);
+        const entry = {id:crypto.randomUUID(), label:String(label), state};
+        this.entries.push(entry); this.index = this.entries.length - 1;
+        // Keep the original and current source reachable; discard intermediate
+        // checkpoints first when the session history reaches its budget.
+        while (this.entries.length > 2 && (this.entries.length > this.maxEntries || estimateBytes(this.entries) > this.maxBytes)) {
+            this.entries.splice(1,1); this.index--;
+        }
+        this.onChange?.(this); return entry;
+    }
+    async transact(label, operation) {
+        if (this.busy) throw Error(T("Processing the source image; please wait"));
+        this.busy = true; this.onChange?.(this);
+        try {
+            this.checkpoint(this.entries.length ? T("Edited source") : T("Initial source"));
+            const result = await operation();
+            this.checkpoint(label);
+            return result;
+        } finally { this.busy = false; this.onChange?.(this); }
+    }
+    async restore(index) {
+        if (this.busy) throw Error(T("Processing the source image; please wait"));
+        if (!Number.isInteger(index) || !this.entries[index]) throw Error(T("The source image history entry no longer exists"));
+        this.busy = true; this.onChange?.(this);
+        try {
+            await restoreSourceState(this.node, this.entries[index].state, {onRestore:this.onRestore});
+            this.index = index;
+            return this.current;
+        } finally { this.busy = false; this.onChange?.(this); }
+    }
+    undo() { return this.restore(this.index - 1); }
+    original() { return this.restore(0); }
+    clear() { this.entries = []; this.index = -1; this.onChange?.(this); }
+}

web/workspace_progress.js

@@ -0,0 +1,71 @@
+import {T} from './i18n.js';
+const stageNames={
+    CheckpointLoaderSimple:"Loading main model",UNETLoader:"Loading main model",UNETLoaderGGUF:"Loading main model",
+    CLIPLoader:"Loading text encoder",DualCLIPLoader:"Loading text encoder",VAELoader:"Loading VAE",
+    CLIPTextEncode:"Encoding prompts",LoraLoader:"Loading LoRA",'Power Lora Loader (rgthree)':"Loading LoRA",
+    AdachiInlineMask:"Reading source image and mask",AdachiWebUIInpaint:"Preparing inpaint sampling",
+    KSampler:"KSampler",KSamplerAdvanced:"KSampler",SamplerCustom:"Sampler",
+    VAEDecode:"VAE decode",VAEEncode:"VAE encode",AdachiImageCompare:"Preparing comparison images",
+};
+
+// Percentages describe the current node's reported steps, not invented overall
+// job progress. Nodes without numeric progress use an indeterminate bar.
+export class WorkspaceProgress {
+    constructor(onChange=()=>{}) {this.onChange=onChange;this.state='idle';this.buffer=[];}
+    begin(nodes={},promptId=null) {
+        this.nodes=nodes;this.promptId=promptId;this.state='queued';this.label=T("Queued…");
+        this.nodeId=null;this.value=null;this.max=null;this.buffer=[];this.emit();
+    }
+    attach(promptId) {
+        this.promptId=promptId;const events=this.buffer;this.buffer=[];
+        for(const [name,data] of events)if(data?.prompt_id===promptId)this.handle(name,data);
+    }
+    emit(){this.onChange(this);}
+    stage(id) {
+        const node=this.nodes?.[String(id)],type=node?.class_type;
+        return stageNames[type]?T(stageNames[type]):node?._meta?.title||type||T("Executing workflow");
+    }
+    finish(success,message) {
+        this.state=success?'complete':'error';this.label=message||(success?T("Generation complete"):T("Generation stopped"));
+        this.value=success?1:null;this.max=success?1:null;this.emit();
+    }
+    connection(connected) {
+        if(!['queued','running'].includes(this.state))return;
+        this.label=connected?T("Reconnected; waiting for execution progress…"):T("Connection lost; recovering execution progress…");this.value=this.max=null;this.emit();
+    }
+    handle(name,data={}) {
+        // Older frontends reduce executing payloads to a scalar node ID and
+        // dispatch null at completion, including before the submit HTTP reply.
+        if(data==null)return false;
+        if(name==='executing' && ['string','number'].includes(typeof data))data={node:String(data)};
+        if(typeof data!=='object')return false;
+        if(!['queued','running'].includes(this.state))return false;
+        if(!this.promptId){this.buffer.push([name,data]);if(this.buffer.length>64)this.buffer.shift();return false;}
+        if(data.prompt_id && data.prompt_id!==this.promptId)return false;
+        if(name==='execution_success'){this.finish(true);return true;}
+        if(['execution_error','execution_interrupted'].includes(name)){this.finish(false,data.exception_message||T("Generation stopped"));return true;}
+        if(name==='execution_start'){this.state='running';this.label=T("Starting execution…");this.emit();return true;}
+        if(name==='execution_cached'){
+            if(this.state==='queued'){this.label=T("Reading cache · {count} nodes",{count:data.nodes?.length||0});this.emit();}return true;
+        }
+        if(name==='progress_state') {
+            const running=Object.entries(data.nodes||{}).filter(([,n])=>n.state==='running');
+            if(!running.length)return false;
+            const [id,node]=running.at(-1);
+            return this.handle('progress',{...node,prompt_id:this.promptId,node:id,
+                max:Number(node.max)>1?node.max:0});
+        }
+        if(name==='executing' && data.node==null && data.node_id==null)return false;
+        const id=data.node ?? data.node_id ?? this.nodeId;
+        if(id==null || !this.nodes?.[String(id)])return false;
+        const changed=String(id)!==this.nodeId;this.nodeId=String(id);this.state='running';
+        if(changed || name==='executing'){this.value=this.max=null;}
+        const max=Number(data.max),value=Number(data.value);
+        if(name==='progress' && Number.isFinite(max) && max>0 && Number.isFinite(value)){
+            this.max=max;this.value=Math.max(0,Math.min(max,value));
+            const type=this.nodes[this.nodeId]?.class_type;
+            this.label=`${type==='AdachiWebUIInpaint'?T("Inpaint sampling (KSampler)"):this.stage(id)} · ${this.value} / ${this.max}`;
+        } else this.label=this.stage(id);
+        this.emit();return true;
+    }
+}

web/workspace_routes.js

@@ -0,0 +1,35 @@
+const linkAt = (graph, input) => input?.link == null ? null
+    : graph.getLink?.(input.link) ?? graph.links?.get?.(input.link) ?? graph.links?.[input.link];
+// Follow the actual sampler conditioning inputs, including KJ Get/Set routes.
+// Ambiguous processing graphs are left under the workflow's control.
+export function conditioningSource(graph, sampler, inputName, modes = new Map()) {
+    const mode = node => modes.get(node) ?? node.mode ?? 0;
+    const visit = (node, slot, seen = new Set()) => {
+        if (!node || seen.has(node) || mode(node) === 2) return null;
+        seen = new Set(seen); seen.add(node);
+        const follow = input => {
+            const link = linkAt(node.graph || graph, input);
+            return link ? visit((node.graph || graph).getNodeById(link.origin_id), link.origin_slot, seen) : null;
+        };
+        if (node.type === 'AdachiExclusiveSwitch') {
+            const sources = (node.inputs || []).filter(i=>['input_a','input_b'].includes(i.name)).map(follow).filter(Boolean);
+            return sources.length === 1 ? sources[0] : null;
+        }
+        if (node.type === 'GetNode') {
+            if (mode(node) !== 0) return null;
+            const name = node.widgets?.[0]?.value;
+            const setter = node.findSetter?.(node.graph || graph) || Array.from(graph._nodes || []).find(n=>n.type === 'SetNode' && n.widgets?.[0]?.value === name);
+            return setter ? visit(setter,slot,seen) : null;
+        }
+        if (node.type === 'SetNode' || node.type === 'Reroute') {
+            if (mode(node) !== 0) return null;
+            return follow(node.inputs?.[0]);
+        }
+        if (node.type === 'CLIPTextEncode') return mode(node) === 0 ? node : null;
+        const resolved = node.resolveVirtualOutput?.(slot);
+        if (resolved?.node) return visit(resolved.node,resolved.slot ?? 0,seen);
+        return null;
+    };
+    const link = linkAt(graph, sampler.inputs?.find(i=>i.name===inputName));
+    return link ? visit(graph.getNodeById(link.origin_id),link.origin_slot) : null;
+}

web/workspace_splitter.js

@@ -0,0 +1,48 @@
+import {T} from './i18n.js';
+export function installWorkspaceSplitter(root,main,divider) {
+    const key='adachi-workspace-sidebar-width',minimum=280,canvasMinimum=320;
+    let requested=360,drag=null;
+    try {const saved=Number(localStorage.getItem(key));if(Number.isFinite(saved) && saved>=minimum)requested=saved;}catch{}
+    const bounds=()=>{
+        const style=getComputedStyle(main),width=main.clientWidth-parseFloat(style.paddingLeft)-parseFloat(style.paddingRight);
+        return {width,max:Math.max(minimum,Math.min(760,width-canvasMinimum-10))};
+    };
+    const render=()=>{
+        const {width,max}=bounds(),actual=Math.min(max,Math.max(minimum,requested));
+        root.style.setProperty('--aw-sidebar-width',`${actual}px`);
+        divider.setAttribute('aria-valuemin',String(Math.min(canvasMinimum,width-minimum-10)));
+        divider.setAttribute('aria-valuemax',String(Math.max(0,width-minimum-10)));
+        divider.setAttribute('aria-valuenow',String(Math.max(0,width-actual-10)));
+        divider.setAttribute('aria-valuetext',T("Settings panel {width} pixels wide",{width:Math.round(actual)}));
+        return actual;
+    };
+    const save=()=>{try{localStorage.setItem(key,String(requested));}catch{}};
+    const change=value=>{requested=Math.min(bounds().max,Math.max(minimum,value));render();};
+    divider.setAttribute('role','separator');divider.setAttribute('aria-orientation','vertical');
+    divider.setAttribute('aria-label',T("Resize canvas and settings"));divider.tabIndex=0;
+    divider.title=T("Drag to resize the canvas and settings; double-click to reset, or use arrow keys for fine adjustments");
+    divider.onpointerdown=e=>{
+        if(e.button!==0)return;e.preventDefault();e.stopPropagation();
+        drag={id:e.pointerId,x:e.clientX,width:render()};divider.setPointerCapture(e.pointerId);
+        root.dataset.resizing='true';divider.focus({preventScroll:true});
+    };
+    divider.onpointermove=e=>{if(drag?.id!==e.pointerId)return;e.preventDefault();change(drag.width+drag.x-e.clientX);};
+    const finish=e=>{
+        if(drag?.id!==e.pointerId)return;drag=null;delete root.dataset.resizing;
+        if(divider.hasPointerCapture(e.pointerId))divider.releasePointerCapture(e.pointerId);save();
+    };
+    divider.onpointerup=finish;divider.onpointercancel=finish;divider.onlostpointercapture=finish;
+    divider.ondblclick=e=>{e.preventDefault();requested=360;render();save();};
+    divider.onkeydown=e=>{
+        const step=e.shiftKey?48:16;
+        if(e.key==='ArrowLeft')change(render()+step);
+        else if(e.key==='ArrowRight')change(render()-step);
+        else if(e.key==='Home')change(bounds().max);
+        else if(e.key==='End')change(minimum);
+        else if(e.key==='Enter'){requested=360;render();}
+        else return;
+        e.preventDefault();e.stopPropagation();save();
+    };
+    const observer=new ResizeObserver(render);observer.observe(main);render();
+    return ()=>{observer.disconnect();delete root.dataset.resizing;};
+}

web/workspace_transport.js

@@ -0,0 +1,44 @@
+import {T} from './i18n.js';
+// Check protocol support before POSTing: old ComfyUI processes may serve the
+// updated JavaScript while still running the previous Python node package.
+const unavailable = () => new Error(T("The workbench backend is not loaded. Stop and restart ComfyUI, then check connections again; refreshing the browser is not enough."));
+export async function workspaceRequest(api, path, prepared, {signal}={}) {
+    const controller = new AbortController();
+    const abort=()=>controller.abort();
+    if(signal?.aborted)controller.abort();else signal?.addEventListener('abort',abort,{once:true});
+    const timer = setTimeout(() => controller.abort(), path === 'submit' ? 60000 : 20000);
+    try {
+        controller.signal.throwIfAborted();
+        let base;
+        for (const candidate of ['/adachi-inpaint/workspace', '/api/adachi-inpaint/workspace']) {
+            const probe = await api.fetchApi(`${candidate}/capabilities`, {signal:controller.signal});
+            if (!probe.ok) continue;
+            let info; try { info = await probe.json(); } catch { continue; }
+            if (info.api_version === 1 && info.can_validate) { base = candidate; break; }
+        }
+        if (!base) throw unavailable();
+        const response = await api.fetchApi(`${base}/${path}`, {
+            method:'POST', headers:{'Content-Type':'application/json'},
+            body:JSON.stringify(prepared), signal:controller.signal,
+        });
+        if ([404,405].includes(response.status)) throw unavailable();
+        let data;
+        try { data = await response.json(); } catch { throw new Error(T("Invalid workbench response ({status}); check your proxy settings or restart ComfyUI",{status:response.status})); }
+        if (!response.ok || !data.valid) {
+            const errors = Object.entries(data.node_errors || {}).flatMap(([id,node]) =>
+                (node.errors || []).map(e => {
+                    const labels={ckpt_name:T("Main model"),unet_name:T("Main model"),clip_name:T("Text encoder"),vae_name:'VAE',lora_name:'LoRA'};
+                    const field=e.extra_info?.input_name,value=e.extra_info?.received_value;
+                    if(e.type==='value_not_in_list' && labels[field] && typeof value==='string')return T("{label} not found: {value}",{label:labels[field],value});
+                    return `#${id} ${e.message || ''}: ${e.details || ''}`;
+                }));
+            const error = new Error(errors.join('\n') || data.error?.message || T("Workflow validation failed"));
+            error.nodeErrors = data.node_errors || {}; throw error;
+        }
+        return data;
+    } catch (error) {
+        if(signal?.aborted)throw error;
+        if (error.name === 'AbortError') throw new Error(path === 'submit' ? T("Submission timed out. Check the task queue before retrying to avoid duplicate generations.") : T("Connection check timed out; check your network and retry"));
+        throw error;
+    } finally {clearTimeout(timer);signal?.removeEventListener('abort',abort);controller.abort();}
+}

web/workspace_ui.js

@@ -0,0 +1,224 @@
+import {T} from './i18n.js';
+import { app } from '../../scripts/app.js';
+import { api } from '../../scripts/api.js';
+import {selectWorkbenchPipeline} from './workbench_analysis.js';
+import {executionId} from './workspace_flow.js';
+import { WorkspaceBindings } from './workspace_bindings.js';
+import { WorkspaceHistory } from './workspace_history.js';
+import { WorkspaceProgress } from './workspace_progress.js';
+import { installWorkspaceSplitter } from './workspace_splitter.js';
+import { prepareWorkspacePrompt, validateWorkspace, submitWorkspace } from './workspace_execution.js';
+import { syncCurrentDimensions } from './parameter_bridge.js?v=0.8.2';
+const el=(tag,text,cls)=>{const e=document.createElement(tag);if(text)e.textContent=text;if(cls)e.className=cls;return e;};
+const btn=(text,fn)=>{const b=el('button',text);b.type='button';b.onclick=fn;return b;};
+const icons={edit:'<path d="m14 3 7 7-11 11H3v-7L14 3Z"/><path d="m11 6 7 7"/>',compare:'<rect x="3" y="4" width="18" height="16" rx="2"/><path d="M12 2v20M3 8h9M3 13h9M3 18h9"/>',side:'<rect x="3" y="4" width="18" height="16" rx="2"/><path d="M12 4v16M6 12h12m-3-3 3 3-3 3"/>',theme:'<path d="M20 15.5A9 9 0 0 1 8.5 4 9 9 0 1 0 20 15.5Z"/>',check:'<circle cx="12" cy="12" r="9"/><path d="m8 12 3 3 5-6"/>',back:'<path d="m9 5-7 7 7 7M3 12h19"/>',fit:'<path d="M4 9V4h5M15 4h5v5M20 15v5h-5M9 20H4v-5"/>'};
+const iconButton=(label,kind,fn)=>{const b=btn('',fn);b.title=label;b.setAttribute('aria-label',label);b.innerHTML=`<svg width="18" height="18" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.7" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true">${icons[kind]}</svg>`;b.className='aw-icon';return b;};
+let currentWorkspace=null;
+export class Workspace {
+ constructor(samplerNode=null,options={}){
+  this.preferredSampler=samplerNode;this.pipelineOptions=options;this.mounts=[];this.disposers=[];this.closed=false;this.running=false;this.checkVersion=0;
+  this.sessionController=new AbortController();
+  this.root=el('div','','adachi-workspace');this.root.adachiWorkspace=this;this.root.setAttribute('role','dialog');this.root.setAttribute('aria-label','Adachi Workbench');
+  const head=el('header'),title=el('h1','Adachi Workbench');head.append(title);
+  this.status=el('span',T("Reading the current workflow…"),'aw-status');this.themeButton=iconButton(T("Switch theme"),'theme',()=>this.toggleTheme());head.append(this.status,this.themeButton,iconButton(T("Check connections"),'check',()=>this.check()),iconButton(T("Return to workflow"),'back',()=>this.close()));this.root.append(head);
+  const main=el('main'),canvas=el('section','','aw-canvas'),toolbar=el('div','','aw-toolbar');
+  this.tabs={edit:iconButton(T("Edit mask"),'edit',()=>this.show('edit')),compare:iconButton(T("Slide to compare"),'compare',()=>this.show('compare'))};
+  this.sideButton=iconButton(T("Show before"),'side',()=>this.show(this.view==='before'?'after':'before'));
+  this.fitCompareButton=iconButton(T("Fit comparison image"),'fit',()=>this.compare?.fitView());this.fitCompareButton.disabled=true;toolbar.append(this.tabs.edit,this.tabs.compare,this.sideButton,this.fitCompareButton);
+  toolbar.append(el('span','','spacer'));this.adoptButton=btn(T("Adopt"),()=>this.adopt());this.adoptButton.title=T("Use this result as the next source image and keep the mask; restore earlier images below");this.adoptButton.className='primary';toolbar.append(this.adoptButton);
+  this.surface=el('div','','aw-surface');this.still=el('img','','aw-result-image');this.still.alt=T("Selected source image or generated result");this.still.hidden=true;this.surface.append(this.still);
+  const foot=el('div','','aw-footer');this.undoButton=btn(T("↶ Undo"),()=>this.restoreHistory('undo'));this.originalButton=btn(T("Initial source"),()=>this.restoreHistory('original'));this.historySelect=el('select');this.historySelect.setAttribute('aria-label',T("Choose an adopted source image"));this.historySelect.onchange=()=>this.restoreHistory(Number(this.historySelect.value));foot.append(this.undoButton,this.originalButton,this.historySelect);
+  this.footer=foot;this.undoButton.title=T("Restore the previous source image, mask and crop");this.originalButton.title=T("Restore the initial source image of this session");this.historySelect.title=T("Choose an earlier adopted or uploaded source image");this.note=el('div','','aw-note');canvas.append(toolbar,this.surface,foot,this.note);
+  this.side=el('aside');this.generationPanel=el('div','','aw-generation-progress');this.generationPanel.hidden=true;this.generationLabel=el('span');this.generationBar=el('progress');this.generationBar.max=1;this.generationBar.setAttribute('aria-label',T("Current stage progress"));this.generationPanel.title=T("Actual progress from the current node; stages without step counts show an indeterminate bar");this.generationPanel.append(this.generationLabel,this.generationBar);this.side.append(this.generationPanel,el('h2',T("Workflow settings")));this.settings=el('div');this.params=el('div','','aw-parameters');this.quickParams=el('div','','dd-inpaint aw-quick-params');this.runButton=btn(T("Generate"),()=>this.run());this.runButton.disabled=true;this.runButton.className='primary';this.runButton.style.width='100%';this.side.append(this.runButton,this.quickParams,this.settings,this.params);this.divider=el('div','','aw-splitter');main.append(canvas,this.divider,this.side);this.root.append(main);
+  this.root.addEventListener('keydown',e=>{if(e.key==='Escape'&&e.target===this.root)this.close();});
+  this.root.addEventListener('pointerdown',e=>e.stopPropagation());document.body.append(this.root);document.body.classList.add('adachi-workspace-open');this.stopSplitter=installWorkspaceSplitter(this.root,main,this.divider);
+  // Render first. Discovery/catalog and actual server validation run afterward.
+  let theme='light';try{theme=localStorage.getItem('adachi-workspace-theme')||theme;}catch{}this.setTheme(theme);
+  setTimeout(()=>this.initialize().catch(e=>this.setStatus(e.message,'error')),0);
+ }
+ setTheme(theme){this.root.dataset.theme=theme==='dark'?'dark':'light';const label=this.root.dataset.theme==='dark'?T("Switch to light theme"):T("Switch to dark theme");this.themeButton.title=label;this.themeButton.setAttribute('aria-label',label);try{localStorage.setItem('adachi-workspace-theme',this.root.dataset.theme);}catch{}}
+ toggleTheme(){this.setTheme(this.root.dataset.theme==='dark'?'light':'dark');}
+ setStatus(text,state='pending'){if(this.closed)return;this.status.textContent=text;this.status.title=text;this.status.dataset.state=state;}
+ renderTaskProgress(){
+  const p=this.taskProgress;if(!p || this.closed)return;
+  this.generationPanel.hidden=p.state==='idle';this.generationPanel.dataset.state=p.state;
+  const known=p.max>0 && p.value!=null;
+  this.generationLabel.textContent=p.label+(known && p.max>1?` · ${Math.round(p.value/p.max*100)}%`:'');
+  this.generationBar.setAttribute('aria-valuetext',this.generationLabel.textContent);
+  if(known)this.generationBar.value=p.value/p.max;else this.generationBar.removeAttribute('value');
+  if(this.running && p.state!=='idle')this.setStatus(p.state==='complete'?T("Generation complete"):p.state==='error'?p.label:T("Generating"),p.state==='error'?'error':p.state==='complete'?'ok':'pending');
+ }
+ showGeneratedResult(){if(this.editor?.stroke || this.editor?.drag || this.editor?.pointerId!=null){this.pendingResultView=true;return;}this.pendingResultView=false;this.show('compare');}
+ mount(element,target,canvas=false){
+  if(!element?.parentNode)throw Error(T("Controls are not ready; reopen the workbench shortly"));
+  const marker=document.createComment('workspace');element.before(marker);this.mounts.push({element,marker,style:element.getAttribute('style')});target.append(element);if(canvas)element.classList.add('aw-embedded');
+ }
+ async initialize(){
+  if(this.closed)return;this.graph=app.rootGraph||app.graph;this.nodes=selectWorkbenchPipeline(this.graph,this.preferredSampler,this.pipelineOptions);
+  this.editorNode=this.nodes.editor;this.sampler=this.nodes.sampler;this.compareNode=this.nodes.compare;this.connectionsConfirmed=!this.nodes.ambiguous||!!this.pipelineOptions.confirmed;
+  this.editor=this.editorNode?.adachiEditor;this.compare=this.compareNode?.adachiCompare;
+  if(!this.editor||!this.sampler?.adachiWorkbench||!this.compare)throw Error(T("This workflow needs Inline Mask, Adachi Inpaint Workbench and Image Compare nodes"));
+  this.taskProgress=this.sampler.adachiWorkspaceProgress ||= new WorkspaceProgress();this.taskProgress.onChange=()=>this.renderTaskProgress();this.renderTaskProgress();
+  this.history=this.editorNode.adachiWorkspaceHistory ||= new WorkspaceHistory(this.editorNode);
+  this.history.onChange=()=>this.syncHistory();
+  this.history.onRestore=()=>{syncCurrentDimensions(this.editorNode);app.canvas?.emitBeforeChange?.();app.canvas?.emitAfterChange?.();this.show('edit');this.scheduleCheck();};
+  if(this.editor.ready)await this.history.checkpoint(T("Source when opened"));
+  if(this.closed)return;
+  if((app.rootGraph||app.graph)!==this.graph){this.close();return;}
+  const originalTargets=this.compare.options.getTargets,originalManual=this.compare.manualTarget,originalTarget=this.compare.targetSelect.value;
+  this.compare.options.getTargets=()=>({...originalTargets(),preferred:executionId(this.graph,this.editorNode)});this.compare.manualTarget=false;this.compare.refreshTargets();
+  this.disposers.push(()=>{this.compare.options.getTargets=originalTargets;this.compare.manualTarget=originalManual;this.compare.targetSelect.value=originalTarget;this.compare.refreshTargets();});
+  this.mount(this.editor.root,this.surface,true);this.mount(this.compare.root,this.surface,true);this.mount(this.sampler.adachiWorkbench.root,this.params);
+  // Move the existing controls, rather than copying widgets: linked inputs,
+  // source-size synchronization and sampler updates keep their native wiring.
+  this.sampler.adachiParameters.refresh();
+  for(const name of ['area','resolution','width','height','denoise']){
+   const field=this.sampler.adachiParameters.body.querySelector(`:scope > [data-adachi-param="${name}"]`);
+   if(field)this.mount(field,this.quickParams);
+  }
+  // The dock can wrap on narrow screens or with long history labels. Keep
+  // crop/result controls above its measured height instead of a fixed offset.
+  const dockObserver=new ResizeObserver(()=>{
+   this.root.style.setProperty('--aw-history-height',`${this.footer.getBoundingClientRect().height}px`);
+   const crop=this.editorNode.adachiCrop?.bar;
+   if(crop)this.root.style.setProperty('--aw-crop-height',`${crop.getBoundingClientRect().height}px`);
+  });
+  dockObserver.observe(this.footer);if(this.editorNode.adachiCrop?.bar)dockObserver.observe(this.editorNode.adachiCrop.bar);
+  this.disposers.push(()=>dockObserver.disconnect());
+  const editorWheel=this.editor.options.onGraphWheel,compareWheel=this.compare.options.onGraphWheel;
+  this.editor.options.onGraphWheel=()=>{};this.compare.options.onGraphWheel=()=>{};
+  this.disposers.push(()=>{this.editor.options.onGraphWheel=editorWheel;this.compare.options.onGraphWheel=compareWheel;});
+  this.compare.enableWorkspaceZoom(true);this.disposers.push(()=>{this.compare.setDisplayMode('compare');this.compare.enableWorkspaceZoom(false);});
+  this.bindings=new WorkspaceBindings({graph:this.graph,sampler:this.sampler,canvas:app.canvas,onChange:()=>this.scheduleCheck(),markChanged:()=>{app.canvas?.emitBeforeChange?.();app.canvas?.emitAfterChange?.();}});
+  this.settings.append(this.connectionPicker(),this.bindings.createPanel());
+  this.prepare(true).catch(e=>this.setStatus(e.message,'error'));
+  this.bindings.loadCatalog(api.fetchApi.bind(api)).then(()=>this.scheduleCheck()).catch(e=>this.setStatus(e.message,'error'));
+  const oldAdopt=this.compare.options.onAdopt;
+  this.compare.options.onAdopt=async(...args)=>{const result=await this.history.transact(T("Adopted result"),()=>oldAdopt(...args));if(!this.closed && this.editorNode.adachiCrop?.mode==='crop')this.show('edit');return result;};
+  this.disposers.push(()=>{this.compare.options.onAdopt=oldAdopt;});
+  const oldLoad=this.compare.loadSelected;
+  this.compare.loadSelected=async(...args)=>{const result=await oldLoad.apply(this.compare,args);if(!this.closed){this.show(this.view||'edit');this.updateButtons();}return result;};
+  this.disposers.push(()=>{this.compare.loadSelected=oldLoad;});
+  const oldUpload=this.editor.upload;
+  this.editor.upload=async(...args)=>{const previous=this.editor.image;await oldUpload(...args);if(this.editor.ready&&this.editor.image!==previous&&!this.closed){await this.history.checkpoint(T("Uploaded source"));this.syncHistory();this.scheduleCheck();}};
+  this.disposers.push(()=>{this.editor.upload=oldUpload;});
+  const onExecuted=this.compareNode.onExecuted;
+  this.compareNode.onExecuted=(output)=>{const ret=onExecuted?.call(this.compareNode,output);if(output?.adachi_results?.length){this.showGeneratedResult();this.note.textContent='';this.updateButtons();}return ret;};
+  this.disposers.push(()=>{this.compareNode.onExecuted=onExecuted;});
+  const event=(name,fn)=>{api.addEventListener(name,fn);this.disposers.push(()=>api.removeEventListener(name,fn));};
+  for(const name of ['execution_start','executing','execution_cached','progress','progress_state','execution_success','execution_error','execution_interrupted'])event(name,e=>this.taskProgress.handle(name,e.detail));
+  event('reconnecting',()=>this.taskProgress.connection(false));event('reconnected',()=>this.taskProgress.connection(true));
+  const queued=e=>{if(e.detail.sampler!==this.sampler)return;this.promptId=e.detail.promptId;this.running=!['complete','error'].includes(this.taskProgress.state);this.runButton.textContent=this.running?T("Generating…"):T("Generate");this.renderTaskProgress();this.updateButtons();};
+  document.addEventListener('adachi-workspace-queued',queued);this.disposers.push(()=>document.removeEventListener('adachi-workspace-queued',queued));
+  const recovered=e=>{if(e.detail.node!==this.compareNode || e.detail.promptId!==this.promptId)return;if(e.detail.entry.outputs?.[executionId(this.graph,this.compareNode)]?.adachi_results?.length)this.showGeneratedResult();this.taskProgress.finish(e.detail.entry.status?.status_str==='success');this.running=false;this.sampler.adachiWorkspaceTask=null;this.runButton.disabled=false;this.runButton.textContent=T("Generate");this.setStatus(e.detail.entry.status?.status_str==='success'?T("Generation complete"):T("Generation failed; check the ComfyUI task history"),e.detail.entry.status?.status_str==='success'?'ok':'error');this.updateButtons();};
+  document.addEventListener('adachi-result-recovered',recovered);this.disposers.push(()=>document.removeEventListener('adachi-result-recovered',recovered));
+  for(const name of ['execution_success','execution_error','execution_interrupted'])event(name,e=>{if(e.detail.prompt_id===this.promptId){this.running=false;this.sampler.adachiWorkspaceTask=null;this.runButton.disabled=false;this.runButton.textContent=T("Generate");this.setStatus(name==='execution_success'?T("Generation complete"):e.detail.exception_message||T("Generation stopped"),name==='execution_success'?'ok':'error');}});
+  this.timer=setInterval(()=>{if((app.rootGraph||app.graph)!==this.graph||this.editor.destroyed||!this.sampler?.graph||!this.compareNode?.graph)this.close();else{this.updateButtons();if(this.pendingResultView)this.showGeneratedResult();}},500);
+  // The comparison's exact-task recovery also serves the workspace. A second
+  // history poller doubled weak-network traffic and could replay old results.
+  this.promptId=this.sampler.adachiWorkspaceTask;this.running=!!this.promptId;if(this.running){if(this.taskProgress.state==='idle')this.taskProgress.begin({},this.promptId);this.compareNode.adachiTrackPrompt?.(this.promptId);this.runButton.disabled=true;this.runButton.textContent=T("Generating…");}this.show('edit');this.syncHistory();this.scheduleCheck();
+ }
+ connectionPicker(){
+  const panel=el('details','','aw-connections');panel.open=!this.connectionsConfirmed;panel.append(el('summary',T("Workflow connections")));
+  if(!this.connectionsConfirmed)panel.append(el('p',T("Multiple candidates found; select the nodes to use")));
+  const controls={};
+  for(const [name,label,list,current]of [['sampler',T("Inpaint node"),this.nodes.samplers,this.sampler],['editor',T("Image editor"),this.nodes.editors,this.editorNode],['compare',T("Image comparison"),this.nodes.comparisons,this.compareNode]]){
+   const row=el('label',label),select=el('select');for(const node of list){const id=executionId(this.graph,node),option=el('option',`${node.title||node.type} #${id}`);option.value=id;select.append(option);}select.value=executionId(this.graph,current);row.append(select);panel.append(row);controls[name]=select;
+  }
+  const presetRow=el('label',T("Group presets")),preset=el('select'),none=el('option',T("No preset controller"));none.value='';preset.append(none);
+  for(const node of this.nodes.presets.filter(n=>n.mode===0)){const id=executionId(this.graph,node),option=el('option',`${node.title||node.type} #${id}`);option.value=id;preset.append(option);}preset.value=this.bindings.controller?executionId(this.graph,this.bindings.controller.node):'';presetRow.append(preset);panel.append(presetRow);
+  const apply=btn(T("Use these connections"),()=>{
+   const find=(list,value)=>list.find(node=>executionId(this.graph,node)===value),sampler=find(this.nodes.samplers,controls.sampler.value),editor=find(this.nodes.editors,controls.editor.value),compare=find(this.nodes.comparisons,controls.compare.value);
+   if(!sampler||!editor||!compare)return;sampler.properties.adachi_workspace_connections={editorId:executionId(this.graph,editor),compareId:executionId(this.graph,compare),controllerId:preset.value};
+   this.close();currentWorkspace=new Workspace(sampler,{editorNode:editor,compareNode:compare,confirmed:true});
+  });apply.title=T("Select nodes from this workflow; this inpaint node remembers your choices");panel.append(apply);return panel;
+ }
+ syncHistory(){if(!this.history)return;this.historySelect.replaceChildren();this.history.entries.forEach((item,i)=>{const o=el('option',`${i+1} · ${item.label}`);o.value=i;this.historySelect.append(o);});this.historySelect.value=String(this.history.index);this.undoButton.disabled=!this.history.canUndo;this.originalButton.disabled=this.history.index===0;}
+ updateButtons(){const busy=this.running||this.preparing||this.submitting||this.sampler?.adachiWorkspaceSubmitting;this.runButton.disabled=!!(this.running||this.submitting||this.sampler?.adachiWorkspaceSubmitting);this.adoptButton.disabled=!this.compare?.ready||!!this.compare?.busy||this.compare?.pendingOutputs>0||busy;this.tabs.compare.disabled=!this.compare?.ready;this.sideButton.disabled=!this.compare?.ready;this.fitCompareButton.disabled=!this.compare?.ready||!['compare','before','after'].includes(this.view);if(!this.preparing)this.bindings?.refreshProfiles();if(this.editor)this.editor.root.inert=(!this.connectionsConfirmed)||!!this.preparing&&!this.discovering;this.settings.inert=!!this.preparing;this.params.inert=!!this.preparing;this.quickParams.inert=!!this.preparing;this.historySelect.disabled=this.preparing||!!this.history?.busy;this.undoButton.disabled=this.preparing||!this.history?.canUndo;this.originalButton.disabled=this.preparing||this.history?.index<=0;if(this.compare?.adoptButton)this.compare.adoptButton.disabled=this.adoptButton.disabled;}
+ show(which){
+  this.view=which;
+  if(this.editor)this.editor.root.hidden=which!=='edit';
+  const comparing=['compare','before','after'].includes(which);
+  if(this.compare){this.compare.root.hidden=!comparing;if(comparing)this.compare.setDisplayMode(which);}
+  this.still.hidden=true;
+  for(const [id,b]of Object.entries(this.tabs)){b.classList.toggle('active',id===which);b.setAttribute('aria-pressed',String(id===which));}
+  this.sideButton.classList.toggle('active',['before','after'].includes(which));this.sideButton.setAttribute('aria-pressed',String(which==='before'));
+  this.sideButton.title=which==='before'?T("Show after"):T("Show before");this.sideButton.setAttribute('aria-label',this.sideButton.title);
+  this.fitCompareButton.disabled=!this.compare?.ready||!comparing;
+  this.editor?.schedule();this.compare?.schedule();
+ }
+ async adopt(){if(!this.compare?.ready||this.running)return;await this.compare.adopt();this.syncHistory();this.updateButtons();if(!this.compare.message.classList.contains('dd-error')){this.show(this.editorNode.adachiCrop?.mode==='crop'?'edit':'compare');this.note.textContent='';this.scheduleCheck();}}
+ async restoreHistory(which){try{if(this.preparing||this.history?.busy)return;if(which==='undo')await this.history.undo();else if(which==='original')await this.history.original();else await this.history.restore(which);this.syncHistory();}catch(e){this.setStatus(e.message,'error');}}
+ scheduleCheck(){++this.checkVersion;this.checkController?.abort();clearTimeout(this.checkTimer);if(!this.closed)this.checkTimer=setTimeout(()=>this.check(),200);}
+ prepare(discovery=false){
+  const task=(this.prepareTask||Promise.resolve()).catch(()=>{}).then(async()=>{
+   if(this.closed||(app.rootGraph||app.graph)!==this.graph)throw Error(T("The workflow changed"));
+   if(!this.connectionsConfirmed&&!discovery)throw Error(T("Select the nodes to use in Workflow connections first"));
+   if(!this.editor?.ready&&!discovery)throw Error(T("Upload a source image first"));
+   this.preparing=true;this.discovering=discovery;this.updateButtons();
+   try{return await prepareWorkspacePrompt({editorNode:this.editorNode,samplerNode:this.sampler,compareNode:this.compareNode,allowEmpty:discovery,controller:this.bindings.controller,getBinding:(output,id)=>{this.bindings.updateExecutionGraph(output,id);return this.bindings.getExecutionBinding();}});}
+   finally{this.preparing=false;this.discovering=false;if(!this.closed)this.updateButtons();}
+  });
+  this.prepareTask=task;return task;
+ }
+ async check(){
+  if(this.closed||this.running||this.submitting||this.sampler?.adachiWorkspaceSubmitting)return false;
+  if(this.checking){this.recheck=true;return false;}
+  const version=++this.checkVersion,controller=this.checkController=new AbortController();this.checking=true;
+  this.setStatus(T("Checking in the background…"));
+  try{
+   const prepared=await this.prepare();
+   if(this.closed||this.recheck||version!==this.checkVersion)return false;
+   const result=await validateWorkspace(prepared,{signal:controller.signal});
+   if(this.closed||this.running||this.recheck||version!==this.checkVersion)return false;
+   if(result.valid===false||result.ok===false)throw Error(result.error?.message||result.error||T("Workflow validation failed"));
+   this.setStatus(T("Ready to generate"),'ok');return true;
+  }catch(e){if(version===this.checkVersion&&!this.running)this.setStatus(e.message||String(e),'error');return false;}
+  finally{this.checking=false;if(this.recheck){this.recheck=false;this.scheduleCheck();}}
+ }
+
+ async run() {
+  if(this.closed||this.running||this.submitting||this.sampler?.adachiWorkspaceSubmitting)return;
+  if(!this.sampler||!this.taskProgress){this.setStatus(T("Controls are not ready; reopen the workbench shortly"),'error');return;}
+  this.submitting=true;this.sampler.adachiWorkspaceSubmitting=true;
+  ++this.checkVersion;this.checkController?.abort();clearTimeout(this.checkTimer);
+  this.runButton.disabled=true; this.runButton.textContent=T("Checking…");
+  const seed=this.sampler?.widgets?.find(w=>w.name==='seed'), oldSeed=seed?.value;
+  let queuedSeed=oldSeed;
+  try {
+   for(const widget of this.sampler.widgets || []) widget.beforeQueued?.();
+   queuedSeed=seed?.value;
+   const prepared=structuredClone(await this.prepare());
+   await validateWorkspace(prepared,{signal:this.sessionController.signal});
+   if(this.closed)return;
+   if((app.rootGraph||app.graph)!==this.graph||!this.sampler.graph||!this.compareNode.graph||this.editor.destroyed)throw Error(T("The workflow changed; check connections again"));
+   this.running=true;this.taskProgress.begin(prepared.prompt);this.promptId=null; this.updateButtons();
+   const queued=await submitWorkspace(prepared);
+   this.promptId=queued.prompt_id;this.taskProgress.attach(this.promptId);
+   for(const widget of this.sampler.widgets || []) widget.afterQueued?.();
+   this.sampler.adachiParameters.refresh();
+   this.running=!['complete','error'].includes(this.taskProgress.state);
+   this.sampler.adachiWorkspaceTask=this.running?this.promptId:null;
+   document.dispatchEvent(new CustomEvent('adachi-workspace-queued',{detail:{sampler:this.sampler,promptId:this.promptId}}));
+   this.compareNode.adachiTrackPrompt?.(this.promptId,this.graph);
+   if(this.closed)return;
+   this.runButton.textContent=this.running?T("Generating…"):T("Generate");
+   this.setStatus(this.running?T("Queued for generation"):this.taskProgress.label,this.running?'pending':this.taskProgress.state==='error'?'error':'ok');
+  } catch(e) {
+   this.running=false;
+   if(['queued','running'].includes(this.taskProgress.state))this.taskProgress.finish(false,e.message||String(e));
+   if(seed && seed.value===queuedSeed)seed.value=oldSeed;
+   this.setStatus(e.message||String(e),'error');
+  } finally {
+   this.submitting=false;this.sampler.adachiWorkspaceSubmitting=false;
+   if(!this.running){this.runButton.disabled=false;this.runButton.textContent=T("Generate");}
+   if(!this.closed)this.updateButtons();
+  }
+ }
+
+ close(){if(this.closed)return;this.closed=true;this.sessionController.abort();this.checkController?.abort();++this.checkVersion;clearInterval(this.timer);clearInterval(this.pollTimer);clearTimeout(this.checkTimer);this.stopSplitter?.();for(const dispose of this.disposers.reverse())dispose();if(this.history){this.history.onChange=null;this.history.onRestore=null;}if(this.taskProgress)this.taskProgress.onChange=()=>{};this.bindings?.destroy();for(const {element,marker,style}of this.mounts.reverse()){element.classList.remove('aw-embedded');const removed=(element===this.editor?.root&&(this.editor.destroyed||!this.editorNode?.graph))||(element===this.compare?.root&&!this.compareNode?.graph)||(element===this.sampler?.adachiWorkbench?.root&&!this.sampler?.graph);if(removed){marker.remove();element.remove();continue;}element.hidden=false;element.inert=false;if(marker.parentNode)marker.replaceWith(element);if(style===null)element.removeAttribute('style');else element.setAttribute('style',style);}this.root.remove();document.body.classList.remove('adachi-workspace-open');this.editor?.schedule();this.compare?.schedule();this.compare?.updateButton();currentWorkspace=null;}
+}
+app.registerExtension({name:'Adachi.InpaintWorkspace',setup(){
+ const css=document.createElement('link');css.rel='stylesheet';css.href=new URL('./workspace.css?v=toolbar-layout-20261112',import.meta.url).href;document.head.append(css);
+ document.addEventListener('adachi-open-workspace',event=>{if(!currentWorkspace)currentWorkspace=new Workspace(event.detail?.sampler||null);});
+}});

workspace_execution.py

@@ -0,0 +1,124 @@
+"""Validate and queue only the selected inpainting output, without a test render."""
+
+from copy import deepcopy
+import inspect
+import time
+import uuid
+
+
+def validate_input_mappings(prompt):
+    # Core replacement hooks inspect inputs before validate_prompt runs. Reject
+    # malformed mappings here so a bad request cannot crash those hooks first.
+    for key, node in prompt.items():
+        if not isinstance(node, dict) or not isinstance(node.get("inputs", {}), dict):
+            raise ValueError(f"Invalid input mapping for execution node: {key}")
+
+
+def dependency_prompt(prompt, output_id):
+    """Keep one output and its dependencies, including references into subgraphs."""
+    output_id = str(output_id)
+    if not isinstance(prompt, dict) or not isinstance(prompt.get(output_id), dict):
+        raise ValueError("The selected comparison is not present in the execution graph.")
+    if prompt[output_id].get("class_type") != "AdachiImageCompare":
+        raise ValueError("The workspace output must be an Adachi Image Compare node.")
+    found, pending = set(), [output_id]
+    while pending:
+        key = pending.pop()
+        if key in found:
+            continue
+        found.add(key)
+        node = prompt.get(key)
+        if not isinstance(node, dict):
+            raise ValueError(f"The execution graph references a missing node: {key}")
+        inputs = node.get("inputs", {})
+        if not isinstance(inputs, dict):
+            raise ValueError(f"Invalid input mapping for execution node: {key}")
+        for value in inputs.values():
+            if isinstance(value, list) and len(value) == 2 and isinstance(value[0], str) and isinstance(value[1], int):
+                pending.append(value[0])
+    return {key: value for key, value in prompt.items() if key in found}
+
+
+async def prepare_workspace(server, execution, payload):
+    """Use the same hooks, replacements and validation as ComfyUI /prompt."""
+    if not isinstance(payload, dict) or not isinstance(payload.get("prompt"), dict):
+        raise ValueError("No workflow execution graph was provided.")
+    target = str(payload.get("compare_id", ""))
+    data = deepcopy(payload)
+    validate_input_mappings(data["prompt"])
+    # Hooks may restore Get/Set or subgraph links; prune only after they ran.
+    data = server.trigger_on_prompt(data)
+    if not isinstance(data, dict) or not isinstance(data.get("prompt"), dict):
+        raise ValueError("A workflow extension rejected the execution graph.")
+    validate_input_mappings(data["prompt"])
+    replacements = getattr(server, "node_replace_manager", None)
+    if replacements is not None:
+        replacements.apply_replacements(data["prompt"])
+    data["prompt"] = dependency_prompt(data["prompt"], target)
+    data["partial_execution_targets"] = [target]
+    prompt_id = str(uuid.uuid4())
+    # Older supported ComfyUI builds have validate_prompt(prompt), newer builds
+    # include prompt_id and optional partial execution targets.
+    count = len(inspect.signature(execution.validate_prompt).parameters)
+    if count >= 3:
+        checked = execution.validate_prompt(prompt_id, data["prompt"], [target])
+    elif count == 2:
+        checked = execution.validate_prompt(prompt_id, data["prompt"])
+    else:
+        checked = execution.validate_prompt(data["prompt"])
+    valid = await checked if inspect.isawaitable(checked) else checked
+    return data, prompt_id, valid
+
+
+def register_workspace_routes(server):
+    if getattr(server, "_adachi_workspace_execution_routes", False):
+        return
+    from aiohttp import web
+    import execution
+
+    @server.routes.get("/adachi-inpaint/workspace/capabilities")
+    async def capabilities(request):
+        return web.json_response({"api_version": 1, "can_validate": True})
+
+    async def handle(request, submit):
+        try:
+            payload = await request.json()
+            data, prompt_id, valid = await prepare_workspace(server, execution, payload)
+            response = {"valid": bool(valid[0]), "error": valid[1], "node_errors": valid[3]}
+            if not valid[0]:
+                return web.json_response(response, status=400 if submit else 200)
+            if submit:
+                extra = data.get("extra_data", {})
+                if not isinstance(extra, dict):
+                    raise ValueError("Invalid workflow metadata.")
+                if isinstance(data.get("client_id"), str):
+                    extra["client_id"] = data["client_id"]
+                extra["create_time"] = int(time.time() * 1000)
+                sensitive = {}
+                sensitive_keys = getattr(execution, "SENSITIVE_EXTRA_DATA_KEYS", None)
+                for key in sensitive_keys or ():
+                    if key in extra:
+                        sensitive[key] = extra.pop(key)
+                number = server.number
+                server.number += 1
+                item = (number, prompt_id, data["prompt"], extra, valid[2])
+                if sensitive_keys is not None:
+                    item += (sensitive,)
+                server.prompt_queue.put(item)
+                response.update(prompt_id=prompt_id, number=number)
+            else:
+                response["outputs"] = valid[2]
+                response["node_count"] = len(data["prompt"])
+            return web.json_response(response)
+        except (ValueError, TypeError, KeyError) as exc:
+            return web.json_response({"valid": False, "error": {"message": str(exc)}, "node_errors": {}}, status=400)
+
+    @server.routes.post("/adachi-inpaint/workspace/validate")
+    async def validate(request):
+        return await handle(request, False)
+
+    @server.routes.post("/adachi-inpaint/workspace/submit")
+    async def submit(request):
+        return await handle(request, True)
+
+    server._adachi_workspace_execution_routes = True