444 lines
13 KiB
TypeScript
444 lines
13 KiB
TypeScript
import { describe, expect, it, vi } from 'vitest';
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import type { CanvasLayer } from './ImageCanvasEditorTypes';
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import {
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buildAnimatedGifPreviewBytes,
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buildLayerExportMetadata,
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buildSpineImageSequenceJson,
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buildSpineImageSequenceReadme,
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dataUrlToBlob,
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formatExportDate,
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getImageExtensionFromTypeOrSrc,
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getLayerAssetExtensionFromTypeOrSrc,
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getLayerExportKey,
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readLayerAssetBlob,
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readLayerImageSequenceFrameBlob,
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sanitizeExportFilePart,
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} from './ImageCanvasExportModel';
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import {
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DEFAULT_ICON_DESCRIPTIONS,
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UI_DESIGN_ASSET_EXTRACTION_PROMPT,
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} from './ImageCanvasGenerationModel';
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describe('ImageCanvasExportModel', () => {
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it('builds a real animated GIF preview from sequence frames', () => {
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const gifBytes = buildAnimatedGifPreviewBytes({
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width: 2,
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height: 1,
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frameDelayCentiseconds: 12,
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frames: [
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{
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width: 2,
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height: 1,
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rgba: Uint8Array.from([255, 0, 0, 255, 0, 0, 0, 0]),
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},
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{
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width: 2,
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height: 1,
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rgba: Uint8Array.from([0, 255, 0, 255, 0, 0, 255, 255]),
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},
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],
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});
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expect(readAscii(gifBytes, 0, 6)).toBe('GIF89a');
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expect(readAscii(gifBytes, 0, gifBytes.length)).toContain('NETSCAPE2.0');
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expect(countGifImageDescriptors(gifBytes)).toBe(2);
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expect(gifBytes.at(-1)).toBe(0x3b);
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});
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it('rejects GIF preview frames with mismatched dimensions', () => {
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expect(() =>
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buildAnimatedGifPreviewBytes({
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width: 2,
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height: 2,
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frameDelayCentiseconds: 12,
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frames: [
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{
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width: 1,
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height: 2,
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rgba: Uint8Array.from([255, 0, 0, 255, 0, 0, 255, 255]),
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},
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],
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}),
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).toThrow('GIF 预览帧尺寸不一致');
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});
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it('normalizes export file names and dates', () => {
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expect(sanitizeExportFilePart(' 角色/草图:*? ', 'fallback')).toBe(
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'角色 草图',
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);
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expect(sanitizeExportFilePart(' ', 'fallback')).toBe('fallback');
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expect(formatExportDate(new Date('2026-06-17T01:02:03.000Z'))).toBe(
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'20260617',
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);
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});
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it('chooses stable image export keys by persistence identity', () => {
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expect(
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getLayerExportKey({
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...buildLayer(),
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assetObjectId: 'object-1',
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objectKey: 'object-key',
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sourceAssetId: 'asset-1',
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src: 'data:image/png;base64,one',
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}),
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).toBe('object-1');
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expect(
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getLayerExportKey({
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...buildLayer(),
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objectKey: 'object-key',
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sourceAssetId: 'asset-1',
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src: 'data:image/png;base64,one',
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}),
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).toBe('object-key');
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expect(
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getLayerExportKey({
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...buildLayer(),
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mediaType: 'image-sequence',
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taskId: 'sequence-task',
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imageSequenceFrames: [
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{
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frameIndex: 1,
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imageSrc: '/generated-character-drafts/editor/frame01.png',
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width: 1024,
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height: 1024,
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},
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],
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}),
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).toBe('image-sequence:sequence-task');
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});
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it('detects image extensions from content type before falling back to src', () => {
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expect(getImageExtensionFromTypeOrSrc('image/jpeg', '/image.png')).toBe(
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'jpg',
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);
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expect(getImageExtensionFromTypeOrSrc('', '/image.webp?x=1')).toBe('webp');
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expect(getImageExtensionFromTypeOrSrc('', '/image.unknown')).toBe('png');
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expect(
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getLayerAssetExtensionFromTypeOrSrc('video', 'video/mp4', '/video.png'),
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).toBe('mp4');
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expect(
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getLayerAssetExtensionFromTypeOrSrc(
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'video',
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'',
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'/generated-character-drafts/editor/preview.mp4',
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),
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).toBe('mp4');
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expect(
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getLayerAssetExtensionFromTypeOrSrc(
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'audio',
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'',
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'/generated-audios/effect.wav?token=1',
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),
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).toBe('wav');
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expect(
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getLayerAssetExtensionFromTypeOrSrc(
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'image-sequence',
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'',
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'/generated-character-drafts/editor/frame01.png',
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),
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).toBe('zip');
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});
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it('converts data URLs and builds layer metadata for manifest files', async () => {
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const blob = dataUrlToBlob('data:text/plain;base64,SGVsbG8=');
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expect(blob.type).toBe('text/plain');
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expect(await blob.text()).toBe('Hello');
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expect(
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buildLayerExportMetadata(buildLayer(), 'images/001-layer.png'),
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).toEqual({
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title: '导出图层',
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file: 'images/001-layer.png',
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visible: {
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type: '生成图片',
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generationInputs: {
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fields: [{ title: '生成提示词', value: '清爽游戏按钮' }],
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references: [
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{
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title: '参考图',
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label: '角色立绘',
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refType: 'project-resource',
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refId: 'resource-reference',
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},
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],
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},
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model: 'gpt-image-2',
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task: '1',
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object: 'generated/layer.png',
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resolution: '1024 x 1024 px',
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},
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exportError: undefined,
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});
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});
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it('filters built-in prompts from exported visible generation inputs', () => {
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const metadata = buildLayerExportMetadata(
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buildLayer({
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model: 'gpt-image-2',
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generationInputs: {
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fields: [
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{ title: '生成提示词', value: 'AI 生成图片' },
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{ title: '修改要求', value: '修改当前图片' },
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{ title: 'prompt', value: '游戏音效' },
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{
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title: 'gpt_description_prompt',
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value: '游戏背景音乐',
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},
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{
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title: '提取提示词',
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value: UI_DESIGN_ASSET_EXTRACTION_PROMPT,
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},
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{
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title: '素材描述',
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value: DEFAULT_ICON_DESCRIPTIONS.join('\n'),
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},
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{ title: '用户输入', value: '用户填写的视觉要求' },
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{ title: '游戏分类', value: '游戏音效' },
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{ title: 'duration', value: '5秒' },
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{ title: '处理模型', value: 'birefnet' },
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],
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references: [],
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},
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}),
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'images/001-layer.png',
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);
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expect(metadata.visible.generationInputs).toEqual({
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fields: [
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{ title: '用户输入', value: '用户填写的视觉要求' },
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{ title: '游戏分类', value: '游戏音效' },
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{ title: 'duration', value: '5秒' },
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],
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references: [],
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});
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expect(metadata.visible.model).toBe('gpt-image-2');
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});
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it('builds a Spine JSON attachment timeline from image sequence frames', () => {
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const layer = buildLayer({
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mediaType: 'image-sequence',
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originalWidth: 192,
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originalHeight: 256,
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durationSeconds: 0.5,
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});
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const spineJson = buildSpineImageSequenceJson({
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layer,
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frames: [
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{ frameIndex: 1, fileName: 'frame-01.png', width: 192, height: 256 },
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{ frameIndex: 2, fileName: 'frame-02.png', width: 192, height: 256 },
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{ frameIndex: 3, fileName: 'frame-03.png', width: 192, height: 256 },
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{ frameIndex: 4, fileName: 'frame-04.png', width: 192, height: 256 },
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],
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});
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expect(spineJson.skeleton).toMatchObject({
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images: './frames/',
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fps: 8,
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width: 192,
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height: 256,
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});
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expect(spineJson.bones).toEqual([{ name: 'root' }]);
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expect(spineJson.slots[0]).toEqual({
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name: 'character',
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bone: 'root',
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attachment: 'animation_0001',
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});
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expect(
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spineJson.skins[0]!.attachments.character.animation_0001,
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).toMatchObject({
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type: 'region',
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path: 'frame-01',
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y: 128,
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width: 192,
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height: 256,
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});
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expect(spineJson.animations.animation.slots.character.attachment).toEqual([
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{ time: 0, name: 'animation_0001' },
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{ time: 0.125, name: 'animation_0002' },
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{ time: 0.25, name: 'animation_0003' },
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{ time: 0.375, name: 'animation_0004' },
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{ time: 0.5, name: 'animation_0001' },
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]);
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expect(buildSpineImageSequenceReadme(layer)).toContain('skeleton.json');
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});
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it('reads private object-key assets through same-origin bytes before exporting', async () => {
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const originalFetch = globalThis.fetch;
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const fetchMock = vi.fn(async (url: string) => {
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if (url.startsWith('/api/assets/read-bytes?')) {
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return new Response(new Blob(['video'], { type: 'video/mp4' }));
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}
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return new Response(null, { status: 404 });
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});
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globalThis.fetch = fetchMock as typeof fetch;
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try {
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const blob = await readLayerAssetBlob(
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buildLayer({
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src: '/generated-editor-videos/video.mp4',
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mediaType: 'video',
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objectKey: 'generated/video.mp4',
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}),
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);
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expect(blob.type).toBe('video/mp4');
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expect(fetchMock).toHaveBeenCalledWith(
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expect.stringContaining(
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'/api/assets/read-bytes?objectKey=generated%2Fvideo.mp4',
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),
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expect.any(Object),
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);
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expect(fetchMock).not.toHaveBeenCalledWith(
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expect.stringContaining('x-oss-signature'),
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expect.anything(),
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);
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} finally {
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globalThis.fetch = originalFetch;
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}
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});
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it('reads private image-sequence frame object keys through same-origin bytes', async () => {
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const originalFetch = globalThis.fetch;
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const fetchMock = vi.fn(async (url: string) => {
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if (url.startsWith('/api/assets/read-bytes?')) {
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return new Response(new Blob(['frame'], { type: 'image/png' }));
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}
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return new Response(null, { status: 404 });
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});
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globalThis.fetch = fetchMock as typeof fetch;
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try {
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const blob = await readLayerImageSequenceFrameBlob(
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buildLayer({
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mediaType: 'image-sequence',
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imageSequenceFrames: [
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{
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frameIndex: 1,
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imageSrc: '/generated-editor-frames/frame-1.png',
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objectKey: 'generated/frame-1.png',
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width: 512,
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height: 512,
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},
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],
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}),
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{
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frameIndex: 1,
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imageSrc: '/generated-editor-frames/frame-1.png',
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objectKey: 'generated/frame-1.png',
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width: 512,
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height: 512,
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},
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);
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expect(blob).toBeTruthy();
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expect(fetchMock).toHaveBeenCalledWith(
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expect.stringContaining(
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'/api/assets/read-bytes?objectKey=generated%2Fframe-1.png',
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),
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expect.any(Object),
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);
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} finally {
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globalThis.fetch = originalFetch;
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}
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});
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});
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function readAscii(bytes: Uint8Array, start: number, end: number) {
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return Array.from(bytes.slice(start, end), (byte) =>
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String.fromCharCode(byte),
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).join('');
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}
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function skipGifDataSubBlocks(bytes: Uint8Array, offset: number) {
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let cursor = offset;
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while (cursor < bytes.length) {
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const blockLength = bytes[cursor] ?? 0;
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cursor += 1;
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if (blockLength === 0) {
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return cursor;
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}
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cursor += blockLength;
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}
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return cursor;
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}
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function countGifImageDescriptors(bytes: Uint8Array) {
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let cursor = 13 + 256 * 3;
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let count = 0;
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while (cursor < bytes.length) {
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const blockType = bytes[cursor];
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if (blockType === 0x3b) {
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return count;
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}
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if (blockType === 0x21) {
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const label = bytes[cursor + 1];
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if (label === 0xf9) {
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const blockLength = bytes[cursor + 2] ?? 0;
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cursor += 3 + blockLength + 1;
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continue;
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}
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cursor = skipGifDataSubBlocks(
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bytes,
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cursor + 3 + (bytes[cursor + 2] ?? 0),
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);
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continue;
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}
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if (blockType === 0x2c) {
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count += 1;
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const packed = bytes[cursor + 9] ?? 0;
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cursor += 10;
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if (packed & 0x80) {
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cursor += 3 * 2 ** ((packed & 0x07) + 1);
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}
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cursor += 1;
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cursor = skipGifDataSubBlocks(bytes, cursor);
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continue;
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}
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throw new Error(`Unknown GIF block: ${blockType}`);
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}
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return count;
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}
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function buildLayer(overrides: Partial<CanvasLayer> = {}): CanvasLayer {
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return {
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id: 'layer-1',
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resourceId: 'resource-1',
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title: '导出图层',
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src: 'data:image/png;base64,one',
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x: 10,
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y: 20,
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width: 512,
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height: 512,
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originalWidth: 1024,
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originalHeight: 1024,
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zIndex: 3,
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sourceType: 'generated',
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prompt: '生成提示',
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actualPrompt: '实际提示',
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model: 'gpt-image-2',
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provider: 'VectorEngine',
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taskId: 'task-1',
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objectKey: 'generated/layer.png',
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sourceResourceId: 'source-resource',
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sourceAssetId: 'asset-1',
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generationInputs: {
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fields: [{ title: '生成提示词', value: '清爽游戏按钮' }],
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references: [
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{
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title: '参考图',
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label: '角色立绘',
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refType: 'project-resource',
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refId: 'resource-reference',
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},
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],
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},
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groupId: 'group-1',
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hidden: true,
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locked: false,
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flipX: true,
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flipY: false,
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...overrides,
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};
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}
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