mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-09-20 18:51:26 -03:00
5ab0e88abc
A model file could only ever be linked to huggingface.co: `set_hf_url` validated the URL with a huggingface-only regex, the agent fetched the card from a hardcoded HF URL, and the readme processor built every relative image path off `https://huggingface.co/{repo}/resolve/main`. ModelScope publishes the same model-card convention (README.md + YAML frontmatter, often carrying `base_model:` and `trigger_words:`) behind a public, key-less API, so the enrichment pipeline could already serve it - it was the plumbing that was HF-shaped, not the idea. Make the external source a first-class, provider-driven concept: - New `py/services/model_sources/` registry. A `ModelSource` owns URL recognition (lenient for stored values, strict for user input), the canonical page URL, model-card fetching, the asset base URL and the capability flags. `HuggingFaceSource` is the previous logic relocated; `ModelScopeSource` reads `/models/{o}/{n}/resolve/{master|main}/README.md` and falls back to `/api/v1/models/{o}/{n}/repo`. `TensorArtSource` is link-only on purpose: tensor.art answers plain HTTP clients with a Cloudflare challenge and its internal API (ap-east-1.tensorart.cloud / cn.tensorart.net) rejects every /v1/model/* route with "invalid authorization header", so it declares supports_enrichment=False rather than failing silently later. - Metadata gains `source_platform` + `source_url`; `hf_url` stays as a read/write alias, written only for Hugging Face, so existing sidecars, cached rows and third-party consumers keep working. Normalisation runs at the scanner, the persistent cache (both directions, plus two new columns behind an ALTER migration) and the linking handler - which is what stops a user who switches sources from leaving a stale `hf_url` on a ModelScope model. - The agent pipeline keys off the provider instead of `hf_url`: the fast-fail gate now explains *why* a model is skipped (no source / unknown source / source without a reachable card), the prompt context exposes source_url/source_id/source_label/asset_base_url while still filling the legacy hf_url/repo aliases, and the four README image extractors take a base_url (defaulting to HF) so relative paths resolve against the right site. Version grouping generalises to hf: / ms: / ta: keys. - `POST /api/lm/set-hf-url` keeps its path and its legacy payload keys but accepts `source_url`, validates against every provider and returns the platform. `GET /api/lm/model-sources` lets the UI render the supported-site list from the server. - Frontend: a `modelSourceHelpers` mirror of the registry drives the link dialog, the card/modal globe (branded "View on ModelScope/TensorArt"), the version-group key and the enrichment gate; the versions tab no longer sends ms:/ta: keys to the CivitAI API. TensorArt stays in the list because provenance is worth keeping even when the card is unreadable - the dialog says so plainly ("Sites that don't expose one (currently TensorArt) can only be linked") and the context menu disables enrichment with a matching tooltip, instead of the user getting "Unsupported URL". Verified against the real ModelScope API: jj3550945163/Krea-2-LORA returns a 1882-byte card whose frontmatter carries base_model/tags/trigger_words, and relative images resolve to .../resolve/master/.... Tests: backend 2815 passed; frontend 1130 JS + 91 Vue passed; pytest tests/i18n and a Jinja compile pass over templates/. The nine locales carry [TODO: Translate] for the new strings, completed in the next commit.
251 lines
7.7 KiB
JavaScript
251 lines
7.7 KiB
JavaScript
import { describe, it, expect, vi, beforeEach } from 'vitest';
|
|
|
|
const {
|
|
MODEL_CARD_MODULE,
|
|
STATE_MODULE,
|
|
UI_HELPERS_MODULE,
|
|
I18N_MODULE,
|
|
API_CONFIG_MODULE,
|
|
API_FACTORY_MODULE,
|
|
} = vi.hoisted(() => ({
|
|
MODEL_CARD_MODULE: new URL('../../../static/js/components/shared/ModelCard.js', import.meta.url).pathname,
|
|
STATE_MODULE: new URL('../../../static/js/state/index.js', import.meta.url).pathname,
|
|
UI_HELPERS_MODULE: new URL('../../../static/js/utils/uiHelpers.js', import.meta.url).pathname,
|
|
I18N_MODULE: new URL('../../../static/js/utils/i18nHelpers.js', import.meta.url).pathname,
|
|
API_CONFIG_MODULE: new URL('../../../static/js/api/apiConfig.js', import.meta.url).pathname,
|
|
API_FACTORY_MODULE: new URL('../../../static/js/api/modelApiFactory.js', import.meta.url).pathname,
|
|
}));
|
|
|
|
vi.mock(STATE_MODULE, () => ({
|
|
state: {
|
|
settings: {
|
|
blur_mature_content: false,
|
|
model_name_display: 'model_name',
|
|
},
|
|
global: {
|
|
settings: {
|
|
model_name_display: 'model_name',
|
|
group_by_model: false,
|
|
display_density: 'default',
|
|
model_card_footer_action: 'example_images',
|
|
},
|
|
},
|
|
pages: {
|
|
other: {
|
|
previewVersions: new Map(),
|
|
sortBy: 'name',
|
|
},
|
|
},
|
|
bulkMode: false,
|
|
selectedModels: new Set(),
|
|
selectedLoras: new Set(),
|
|
},
|
|
getCurrentPageState: vi.fn(() => ({
|
|
sortBy: 'name',
|
|
previewVersions: new Map(),
|
|
})),
|
|
}));
|
|
|
|
vi.mock(UI_HELPERS_MODULE, () => ({
|
|
showToast: vi.fn(),
|
|
openCivitai: vi.fn(),
|
|
openHuggingFace: vi.fn(),
|
|
copyToClipboard: vi.fn(),
|
|
copyLoraSyntax: vi.fn(),
|
|
sendLoraToWorkflow: vi.fn(),
|
|
sendEmbeddingToWorkflow: vi.fn(),
|
|
openExampleImagesFolder: vi.fn(),
|
|
buildLoraSyntax: vi.fn(),
|
|
sendModelPathToWorkflow: vi.fn(),
|
|
}));
|
|
|
|
vi.mock(I18N_MODULE, () => ({
|
|
translate: vi.fn((key, params, fallback) => (typeof fallback === 'string' ? fallback : key)),
|
|
}));
|
|
|
|
vi.mock(API_CONFIG_MODULE, () => ({
|
|
MODEL_TYPES: { LORA: 'loras', CHECKPOINT: 'checkpoints', EMBEDDING: 'embeddings', OTHER: 'other' },
|
|
}));
|
|
|
|
vi.mock(API_FACTORY_MODULE, () => ({
|
|
getModelApiClient: vi.fn(() => ({})),
|
|
}));
|
|
|
|
function makeModel(overrides = {}) {
|
|
return {
|
|
sha256: 'abc123',
|
|
file_path: '/models/loras/linked.safetensors',
|
|
model_name: 'Linked LoRA',
|
|
file_name: 'linked',
|
|
folder: '',
|
|
modified: 1234567890,
|
|
file_size: 1024,
|
|
notes: '',
|
|
base_model: '',
|
|
favorite: false,
|
|
exclude: false,
|
|
from_civitai: true,
|
|
hf_url: '',
|
|
update_available: false,
|
|
skip_metadata_refresh: false,
|
|
preview_url: '',
|
|
preview_nsfw_level: 0,
|
|
tags: [],
|
|
civitai: {},
|
|
...overrides,
|
|
};
|
|
}
|
|
|
|
function mountCard(createModelCard, model) {
|
|
document.body.innerHTML = '<div id="modelGrid"></div>';
|
|
const card = createModelCard(model, 'loras');
|
|
document.getElementById('modelGrid').appendChild(card);
|
|
return card;
|
|
}
|
|
|
|
describe('ModelCard source globe (#1094)', () => {
|
|
let createModelCard;
|
|
let setupModelCardEventDelegation;
|
|
let openCivitai;
|
|
let openHuggingFace;
|
|
|
|
beforeEach(async () => {
|
|
document.body.innerHTML = '';
|
|
({ createModelCard, setupModelCardEventDelegation } = await import(MODEL_CARD_MODULE));
|
|
({ openCivitai, openHuggingFace } = await import(UI_HELPERS_MODULE));
|
|
openCivitai.mockReset();
|
|
openHuggingFace.mockReset();
|
|
});
|
|
|
|
it('points the globe at CivitAI when CivitAI data is present alongside an HF link', () => {
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({
|
|
civitai: { id: 111, modelId: 222, name: 'v1' },
|
|
hf_url: 'https://huggingface.co/user/repo',
|
|
})
|
|
);
|
|
|
|
expect(card.dataset.has_civitai).toBe('true');
|
|
expect(card.querySelector('.fa-globe').getAttribute('title')).toBe('View on Civitai');
|
|
});
|
|
|
|
it('keeps the CivitAI globe target when from_civitai is false but CivitAI data exists', () => {
|
|
// Regression for case 1: linking HF no longer hides CivitAI.
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({
|
|
from_civitai: false,
|
|
civitai: { id: 111, modelId: 222 },
|
|
hf_url: 'https://huggingface.co/user/repo',
|
|
})
|
|
);
|
|
|
|
expect(card.dataset.has_civitai).toBe('true');
|
|
expect(card.querySelector('.fa-globe').getAttribute('title')).toBe('View on Civitai');
|
|
});
|
|
|
|
it('points the globe at HuggingFace for an HF-only model', () => {
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({ from_civitai: false, civitai: {}, hf_url: 'https://huggingface.co/user/repo' })
|
|
);
|
|
|
|
expect(card.dataset.has_civitai).toBe('false');
|
|
expect(card.querySelector('.fa-globe').getAttribute('title')).toBe('View on Hugging Face');
|
|
});
|
|
|
|
it('disables the globe when there is no CivitAI data and no HF link', () => {
|
|
const card = mountCard(createModelCard, makeModel({ civitai: {} }));
|
|
const globe = card.querySelector('.fa-globe');
|
|
|
|
expect(card.dataset.has_civitai).toBe('false');
|
|
expect(globe.getAttribute('style')).toContain('cursor: not-allowed');
|
|
});
|
|
|
|
it('opens CivitAI when the globe is clicked on a dual-source model', () => {
|
|
const model = makeModel({
|
|
civitai: { id: 111, modelId: 222 },
|
|
hf_url: 'https://huggingface.co/user/repo',
|
|
});
|
|
const card = mountCard(createModelCard, model);
|
|
setupModelCardEventDelegation('loras');
|
|
|
|
card.querySelector('.fa-globe').dispatchEvent(new MouseEvent('click', { bubbles: true }));
|
|
|
|
expect(openCivitai).toHaveBeenCalledWith(model.file_path);
|
|
expect(openHuggingFace).not.toHaveBeenCalled();
|
|
});
|
|
|
|
it('opens HuggingFace when the globe is clicked on an HF-only model', () => {
|
|
const model = makeModel({
|
|
from_civitai: false,
|
|
civitai: {},
|
|
hf_url: 'https://huggingface.co/user/repo',
|
|
});
|
|
const card = mountCard(createModelCard, model);
|
|
setupModelCardEventDelegation('loras');
|
|
|
|
card.querySelector('.fa-globe').dispatchEvent(new MouseEvent('click', { bubbles: true }));
|
|
|
|
expect(openHuggingFace).toHaveBeenCalledWith('https://huggingface.co/user/repo');
|
|
expect(openCivitai).not.toHaveBeenCalled();
|
|
});
|
|
|
|
it('points the globe at ModelScope for a ModelScope-linked model', () => {
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({
|
|
from_civitai: false,
|
|
civitai: {},
|
|
source_platform: 'modelscope',
|
|
source_url: 'https://modelscope.cn/models/user/repo',
|
|
})
|
|
);
|
|
|
|
expect(card.dataset.has_civitai).toBe('false');
|
|
expect(card.dataset.source_platform).toBe('modelscope');
|
|
expect(card.dataset.hf_url).toBe('');
|
|
expect(card.querySelector('.fa-globe').getAttribute('title')).toBe('View on ModelScope');
|
|
});
|
|
|
|
it('opens the ModelScope page when the globe is clicked', () => {
|
|
const openSpy = vi.spyOn(window, 'open').mockImplementation(() => {});
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({
|
|
from_civitai: false,
|
|
civitai: {},
|
|
source_platform: 'modelscope',
|
|
source_url: 'https://modelscope.cn/models/user/repo',
|
|
})
|
|
);
|
|
setupModelCardEventDelegation('loras');
|
|
|
|
card.querySelector('.fa-globe').dispatchEvent(new MouseEvent('click', { bubbles: true }));
|
|
|
|
expect(openSpy).toHaveBeenCalledWith(
|
|
'https://modelscope.cn/models/user/repo',
|
|
'_blank',
|
|
'noopener,noreferrer'
|
|
);
|
|
expect(openCivitai).not.toHaveBeenCalled();
|
|
expect(openHuggingFace).not.toHaveBeenCalled();
|
|
openSpy.mockRestore();
|
|
});
|
|
|
|
it('points the globe at TensorArt for a TensorArt-linked model', () => {
|
|
const card = mountCard(
|
|
createModelCard,
|
|
makeModel({
|
|
from_civitai: false,
|
|
civitai: {},
|
|
source_platform: 'tensorart',
|
|
source_url: 'https://tensor.art/models/827823520299086029',
|
|
})
|
|
);
|
|
|
|
expect(card.querySelector('.fa-globe').getAttribute('title')).toBe('View on TensorArt');
|
|
});
|
|
});
|