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https://github.com/willmiao/ComfyUI-Lora-Manager.git
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Add OpenModelDB (openmodeldb.info) as a metadata and download source for
the existing upscaler model type.
Metadata:
- New OpenModelDBClient: fetches the site's bulk JSON dumps, caches them
on disk (24h TTL + ETag revalidation), and builds a local sha256 index
- New OpenModelDBModelMetadataProvider adapts catalogue entries to the
CivitAI-shaped version dict contract; registered in the fallback chain
behind the enable_openmodeldb_api setting (default on), gated to the
upscaler sub-type so other model types never trigger the dump download
- Persisted provenance uses metadata_source "openmodeldb" plus a nested
openmodeldb block (page URL, architecture, scale, license)
Images: paired-image LR/SR URLs are ephemeral imgdiff.net sessions, so
displayable images come from the site-hosted auto-generated thumbnails
(model-level cover leads images[], per-image thumbs for the rest); the
original comparison URL is kept in meta.comparisonUrl.
Downloads:
- New OpenModelDBSource (flat model ids, omdb: group prefix) with
resource filename derivation that recovers names hidden mid-path
(mediafire) or synthesizes {id}.{type} for folder links
- HTML-gateway mirrors (mediafire/mega/drive) are rejected with a clear
manual-download hint instead of silently saving an HTML page as .pth
- ModelSource base gains is_valid_source_id / default_subdir_parts /
resolve_download_url hooks so flat-id sources need no platform branches
UI: "View on OpenModelDB" link in the model modal (downloaded and
hash-enriched models), settings toggle next to the CivArchive one.
251 lines
9.1 KiB
JavaScript
251 lines
9.1 KiB
JavaScript
import { describe, it, expect, vi } from 'vitest';
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const { I18N_MODULE } = vi.hoisted(() => ({
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I18N_MODULE: new URL('../../../static/js/utils/i18nHelpers.js', import.meta.url).pathname,
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}));
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vi.mock(I18N_MODULE, () => ({
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translate: vi.fn((key, params, fallback) => (typeof fallback === 'string' ? fallback : key)),
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}));
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const {
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MODEL_SOURCES,
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parseModelSourceUrl,
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getModelSource,
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getModelSourceInfo,
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getModelSourceUrl,
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getModelSourceGroupKey,
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canEnrichModelSource,
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getModelSourceViewTitle,
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parseModelSourceGroupKey,
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isValidSourceId,
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openModelSource,
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} = await import('../../../static/js/utils/modelSourceHelpers.js');
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describe('modelSourceHelpers', () => {
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it('exposes one descriptor per supported platform', () => {
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expect(MODEL_SOURCES.map((s) => s.platform)).toEqual([
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'huggingface',
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'modelscope',
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'modelscope-ai',
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'tensorart',
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'openmodeldb',
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]);
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});
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describe('parseModelSourceUrl', () => {
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it('recognises Hugging Face URLs', () => {
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const info = parseModelSourceUrl('https://huggingface.co/user/repo');
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expect(info.platform).toBe('huggingface');
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expect(info.sourceId).toBe('user/repo');
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});
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it('recognises ModelScope URLs with view sub-paths', () => {
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const info = parseModelSourceUrl('https://modelscope.cn/models/user/repo/summary');
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expect(info.platform).toBe('modelscope');
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expect(info.sourceId).toBe('user/repo');
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expect(info.url).toBe('https://modelscope.cn/models/user/repo');
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});
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it('recognises ModelScope International as its own platform', () => {
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const info = parseModelSourceUrl(
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'https://www.modelscope.ai/models/referall13/EM1/files'
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);
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expect(info.platform).toBe('modelscope-ai');
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expect(info.groupPrefix).toBe('msai');
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expect(info.sourceId).toBe('referall13/EM1');
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expect(info.url).toBe('https://www.modelscope.ai/models/referall13/EM1');
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});
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it('recognises TensorArt URLs and keeps only the numeric id', () => {
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const info = parseModelSourceUrl(
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'https://tensor.art/models/827823520299086029/Vivid-Impressions-Storybook-Sstyle-V1.0'
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);
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expect(info.platform).toBe('tensorart');
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expect(info.sourceId).toBe('827823520299086029');
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expect(info.url).toBe('https://tensor.art/models/827823520299086029');
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});
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it('recognises OpenModelDB URLs with flat model ids', () => {
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const info = parseModelSourceUrl('https://openmodeldb.info/models/4x-UltraSharp');
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expect(info.platform).toBe('openmodeldb');
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expect(info.groupPrefix).toBe('omdb');
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expect(info.sourceId).toBe('4x-UltraSharp');
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expect(info.url).toBe('https://openmodeldb.info/models/4x-UltraSharp');
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expect(info.supportsDownload).toBe(true);
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expect(info.supportsEnrichment).toBe(true);
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});
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it('rejects unsupported URLs', () => {
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expect(parseModelSourceUrl('https://example.com/x')).toBeNull();
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expect(parseModelSourceUrl('')).toBeNull();
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expect(parseModelSourceUrl(null)).toBeNull();
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});
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});
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describe('getModelSourceInfo', () => {
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it('falls back to the legacy hf_url field', () => {
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const info = getModelSourceInfo({ hf_url: 'https://huggingface.co/user/repo' });
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expect(info.platform).toBe('huggingface');
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expect(info.sourceId).toBe('user/repo');
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});
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it('prefers the canonical source fields', () => {
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const info = getModelSourceInfo({
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source_platform: 'modelscope',
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source_url: 'https://modelscope.cn/models/user/repo',
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hf_url: 'https://huggingface.co/old/repo',
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});
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expect(info.platform).toBe('modelscope');
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});
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it('returns null when there is no source', () => {
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expect(getModelSourceInfo({})).toBeNull();
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expect(getModelSourceInfo({ hf_url: '' })).toBeNull();
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});
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});
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describe('getModelSourceUrl', () => {
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it('reads source_url then hf_url', () => {
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expect(getModelSourceUrl({ source_url: 'https://a.example/1' })).toBe('https://a.example/1');
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expect(getModelSourceUrl({ hf_url: 'https://huggingface.co/u/r' })).toBe(
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'https://huggingface.co/u/r'
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);
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expect(getModelSourceUrl({})).toBe('');
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});
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});
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describe('getModelSourceGroupKey', () => {
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it('matches the backend group-key shapes', () => {
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// TensorArt's numeric id already identifies a single model.
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expect(getModelSourceGroupKey({ source_url: 'https://tensor.art/models/123' })).toBe(
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'ta:123'
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);
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// OpenModelDB's flat model id is the published-model identity.
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expect(
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getModelSourceGroupKey({ source_url: 'https://openmodeldb.info/models/4x-UltraSharp' })
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).toBe('omdb:4x-UltraSharp');
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// ModelScope groups by the site-native published-model id.
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expect(
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getModelSourceGroupKey({
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source_url: 'https://modelscope.cn/models/u/r',
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source_model_id: '555',
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})
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).toBe('ms:555');
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expect(
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getModelSourceGroupKey({
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source_url: 'https://www.modelscope.ai/models/u/r',
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source_model_id: '678',
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})
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).toBe('msai:678');
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});
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it('returns an empty string for sources without a model identity', () => {
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// Hugging Face repos are not a model identity: never grouped.
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expect(getModelSourceGroupKey({ hf_url: 'https://huggingface.co/u/r' })).toBe('');
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// Unenriched ModelScope models stay standalone rather than collapsing
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// a whole collection repo into one group.
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expect(
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getModelSourceGroupKey({ source_url: 'https://modelscope.cn/models/u/r' })
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).toBe('');
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expect(
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getModelSourceGroupKey({
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source_url: 'https://modelscope.cn/models/u/r',
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source_model_id: ' ',
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})
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).toBe('');
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});
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it('returns an empty string without a source', () => {
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expect(getModelSourceGroupKey({})).toBe('');
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});
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});
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describe('canEnrichModelSource', () => {
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it('allows Hugging Face and ModelScope', () => {
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expect(canEnrichModelSource({ hf_url: 'https://huggingface.co/u/r' })).toBe(true);
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expect(
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canEnrichModelSource({ source_url: 'https://modelscope.cn/models/u/r' })
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).toBe(true);
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});
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it('disallows TensorArt and unlinked models', () => {
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expect(canEnrichModelSource({ source_url: 'https://tensor.art/models/123' })).toBe(false);
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expect(canEnrichModelSource({})).toBe(false);
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});
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});
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describe('getModelSourceViewTitle', () => {
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it('uses the branded label for non-HF sources', () => {
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expect(getModelSourceViewTitle(getModelSource('modelscope'))).toBe('View on ModelScope');
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expect(getModelSourceViewTitle(getModelSource('tensorart'))).toBe('View on TensorArt');
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});
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it('keeps the historical Hugging Face title', () => {
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expect(getModelSourceViewTitle(getModelSource('huggingface'))).toBe(
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'View on Hugging Face'
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);
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});
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});
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describe('parseModelSourceGroupKey', () => {
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it('parses every external group-key prefix', () => {
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expect(parseModelSourceGroupKey('hf:user/repo')).toEqual({
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platform: 'huggingface',
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label: 'Hugging Face',
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sourceId: 'user/repo',
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});
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expect(parseModelSourceGroupKey('ms:user/repo').platform).toBe('modelscope');
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expect(parseModelSourceGroupKey('ta:123').platform).toBe('tensorart');
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expect(parseModelSourceGroupKey('omdb:4x-UltraSharp')).toEqual({
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platform: 'openmodeldb',
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label: 'OpenModelDB',
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sourceId: '4x-UltraSharp',
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});
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});
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it('rejects numeric CivitAI model ids and unknown prefixes', () => {
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expect(parseModelSourceGroupKey(222)).toBeNull();
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expect(parseModelSourceGroupKey('222')).toBeNull();
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expect(parseModelSourceGroupKey('unknown:1')).toBeNull();
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expect(parseModelSourceGroupKey('')).toBeNull();
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expect(parseModelSourceGroupKey(null)).toBeNull();
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});
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});
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describe('isValidSourceId', () => {
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it('requires owner/name for repository sites', () => {
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expect(isValidSourceId('huggingface', 'user/repo')).toBe(true);
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expect(isValidSourceId('huggingface', '4x-UltraSharp')).toBe(false);
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expect(isValidSourceId('modelscope', 'u/..')).toBe(false);
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});
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it('accepts flat model ids for OpenModelDB', () => {
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expect(isValidSourceId('openmodeldb', '4x-UltraSharp')).toBe(true);
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expect(isValidSourceId('openmodeldb', 'owner/name')).toBe(false);
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expect(isValidSourceId('openmodeldb', '../escape')).toBe(false);
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expect(isValidSourceId('openmodeldb', '')).toBe(false);
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});
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});
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describe('openModelSource', () => {
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it('opens the URL in a new tab', () => {
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const openSpy = vi.spyOn(window, 'open').mockImplementation(() => {});
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openModelSource('https://modelscope.cn/models/u/r');
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expect(openSpy).toHaveBeenCalledWith(
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'https://modelscope.cn/models/u/r',
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'_blank',
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'noopener,noreferrer'
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);
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openSpy.mockRestore();
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});
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it('does nothing without a URL', () => {
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const openSpy = vi.spyOn(window, 'open').mockImplementation(() => {});
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openModelSource('');
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expect(openSpy).not.toHaveBeenCalled();
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openSpy.mockRestore();
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});
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});
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});
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