DemonGatanjieuandClaude Opus 5.5
9abd596186
- Each run keeps its shape read from the prompt ComfyUI queued (ai_run_map.py): boxes by role with their settings, typed links, plumbing wired through, and what changed since the task's run before. The run step shows a one-line summary, the changes as chips and the boxes (top down, fitted to the column, each locating its node); show_run_map puts it on the stage. - By default the AI works in a tab of the task's own (ai_task_canvas.py, mcp_task_tab.js): the open workflow is copied before its first change, the tab is brought back (a click on ComfyUI's tab) before later changes, reads and runs, and the user's tab stays untouched. Per-task switch in the header, default in the Gates window; the AI is told once. - Output pictures can be handed to the task an AI is on (gallery card menu, the inspector's ✦), with the user's words: the AI gets them attached with what made them (ai_pictures.py). search_images(with_pictures) attaches the first six. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
71 lines
3.5 KiB
JavaScript
71 lines
3.5 KiB
JavaScript
/**
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* A gallery card's right-click menu: put the picture on the canvas as a Load Image node, open
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* its parameters, or hand it to the AI (ui_ai_handoff.js). The picture is uploaded into the input folder the way a dropped file is
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* (ComfyUI keeps one copy of the same picture): a "name.png [output]" value would be flagged
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* as a missing file by ComfyUI's checks for any picture not made since ComfyUI started.
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*/
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import { app } from '../../../scripts/app.js';
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import { translate as t } from './locales.js';
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import { recordCanvasStep } from './canvas_history.js';
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import { showWorkbenchToast } from './ui_prompt_toast.js';
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import { canvasPoint, followPointer } from './notebook_canvas.js';
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import { openActionMenu } from './action_menu.js';
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import { handPicturesToAi } from './ui_ai_handoff.js';
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/** The output picture uploaded into the input folder; its name there for a Load Image node. */
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async function copyToInput(image) {
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const query = new URLSearchParams({ filename: image.filename, subfolder: image.subfolder || '', type: 'output' });
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const picture = await fetch(`/view?${query}`);
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if (!picture.ok) throw new Error(`view ${picture.status}`);
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const blob = await picture.blob();
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const form = new FormData();
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form.append('image', new File([blob], image.filename, { type: blob.type }));
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form.append('type', 'input');
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const response = await fetch('/upload/image', { method: 'POST', body: form });
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if (!response.ok) throw new Error(`upload ${response.status}`);
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const data = await response.json();
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return data.subfolder ? `${data.subfolder}/${data.name}` : data.name;
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}
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/**
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* A Load Image node showing `image`: the browser closes and the node follows the pointer until a
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* click puts it down (Esc takes it off again), like a combo's Put on canvas. `at` is the click
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* that chose it, where the node starts.
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*/
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export async function insertLoadImageNode(owner, image, at) {
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const node = globalThis.LiteGraph?.createNode('LoadImage');
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const widget = node?.widgets?.find(item => item.name === 'image');
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let file = null;
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try {
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if (node && widget && app.graph) file = await copyToInput(image);
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} catch (error) {
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console.error('[AMB] Could not copy the picture into the input folder:', error);
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}
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if (!file) {
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showWorkbenchToast(t('galleryInsertNodeFailed'));
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return;
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}
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const [x, y] = canvasPoint(at);
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node.pos = [x - node.size[0] / 2, y - 20];
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app.graph.add(node);
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const choices = widget.options?.values;
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if (Array.isArray(choices) && !choices.includes(file)) choices.push(file);
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widget.value = file;
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widget.callback?.(file); // shows the picture in the node
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app.graph.setDirtyCanvas(true, true);
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owner.close();
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followPointer(owner, [{ node, relX: 0, relY: 0 }], () => recordCanvasStep(app));
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showWorkbenchToast(t('galleryInsertNodeFollow'));
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}
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/** Opens the menu at the pointer; `openDetails()` opens the picture's parameters. */
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export function openGalleryCardMenu(event, image, { owner, openDetails }) {
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event.preventDefault();
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openActionMenu(event, [
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{ icon: '🖼️', label: t('galleryInsertAsNode'), run: (click) => insertLoadImageNode(owner, image, click) },
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{ icon: '🔍', label: t('materialViewParameters'), run: openDetails },
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...(image.type && image.type !== 'output' ? [] : [{ icon: '✦', label: t('aiPicturesMenu'), run: () => handPicturesToAi(owner, [[image.subfolder, image.filename].filter(Boolean).join('/')]) }]),
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]);
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}
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