mirror of
https://github.com/Comfy-Org/ComfyUI_frontend.git
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5cb36fea91
Backport of #12061 to `cloud/1.44` Automatically created by backport workflow. ┆Issue is synchronized with this [Notion page](https://www.notion.so/PR-12079-backport-cloud-1-44-fix-remove-asset-hash-verification-35a6d73d36508157bec2d1259f32d142) by [Unito](https://www.unito.io) Co-authored-by: jaeone94 <89377375+jaeone94@users.noreply.github.com>
1630 lines
45 KiB
TypeScript
1630 lines
45 KiB
TypeScript
import { fromAny, fromPartial } from '@total-typescript/shoehorn'
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import { beforeEach, describe, expect, it, vi } from 'vitest'
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import type { LGraph } from '@/lib/litegraph/src/LGraph'
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import type { LGraphNode } from '@/lib/litegraph/src/LGraphNode'
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import type {
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IBaseWidget,
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IComboWidget
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} from '@/lib/litegraph/src/types/widgets'
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import {
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scanAllModelCandidates,
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scanNodeModelCandidates,
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isModelFileName,
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enrichWithEmbeddedMetadata,
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verifyAssetSupportedCandidates,
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MODEL_FILE_EXTENSIONS
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} from '@/platform/missingModel/missingModelScan'
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import activeSubgraphUnmatchedModel from '@/platform/missingModel/__fixtures__/activeSubgraphUnmatchedModel.json' with { type: 'json' }
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import bypassedSubgraphUnmatchedModel from '@/platform/missingModel/__fixtures__/bypassedSubgraphUnmatchedModel.json' with { type: 'json' }
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import type { MissingModelCandidate } from '@/platform/missingModel/types'
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import type { ComfyWorkflowJSON } from '@/platform/workflow/validation/schemas/workflowSchema'
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vi.mock('@/utils/graphTraversalUtil', () => ({
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collectAllNodes: (graph: { _testNodes: LGraphNode[] }) => graph._testNodes,
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getExecutionIdByNode: (
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_graph: unknown,
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node: { _testExecutionId?: string; id: number }
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) => node._testExecutionId ?? String(node.id)
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}))
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/** Helper: create a combo widget mock */
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function makeComboWidget(
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name: string,
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value: string | number,
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options: string[] = []
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): IComboWidget {
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return fromAny<IComboWidget, unknown>({
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type: 'combo',
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name,
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value,
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options: { values: options }
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})
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}
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/** Helper: create an asset widget mock (Cloud combo replacement) */
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function makeAssetWidget(name: string, value: unknown): IBaseWidget {
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return fromAny<IBaseWidget, unknown>({
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type: 'asset',
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name,
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value,
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options: {}
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})
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}
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/** Helper: create a non-combo widget mock */
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function makeOtherWidget(name: string, value: unknown): IBaseWidget {
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return fromAny<IBaseWidget, unknown>({
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type: 'number',
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name,
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value,
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options: {}
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})
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}
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/** Helper: create a mock LGraphNode with configured widgets */
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function makeNode(
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id: number,
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type: string,
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widgets: IBaseWidget[] = [],
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executionId?: string
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): LGraphNode {
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return fromAny<LGraphNode, unknown>({
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id,
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type,
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widgets,
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_testExecutionId: executionId
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})
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}
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/** Helper: create a mock LGraph containing given nodes */
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function makeGraph(nodes: LGraphNode[]): LGraph {
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return fromAny<LGraph, unknown>({ _testNodes: nodes })
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}
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const noAssetSupport = () => false
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describe('isModelFileName', () => {
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it('should return true for common model extensions', () => {
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expect(isModelFileName('model.safetensors')).toBe(true)
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expect(isModelFileName('model.ckpt')).toBe(true)
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expect(isModelFileName('model.pt')).toBe(true)
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expect(isModelFileName('model.pth')).toBe(true)
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expect(isModelFileName('model.bin')).toBe(true)
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expect(isModelFileName('model.gguf')).toBe(true)
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})
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it('should return false for non-model extensions', () => {
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expect(isModelFileName('image.png')).toBe(false)
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expect(isModelFileName('video.mp4')).toBe(false)
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expect(isModelFileName('config.json')).toBe(false)
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expect(isModelFileName('no_extension')).toBe(false)
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})
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it('should be case-insensitive', () => {
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expect(isModelFileName('MODEL.SAFETENSORS')).toBe(true)
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expect(isModelFileName('Model.Ckpt')).toBe(true)
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})
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})
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describe('MODEL_FILE_EXTENSIONS', () => {
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it('should contain standard extensions', () => {
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expect(MODEL_FILE_EXTENSIONS.has('.safetensors')).toBe(true)
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expect(MODEL_FILE_EXTENSIONS.has('.ckpt')).toBe(true)
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})
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})
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describe('scanNodeModelCandidates', () => {
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it('returns candidates for a node with a missing model combo widget', () => {
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const graph = makeGraph([])
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const node = makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'missing_model.safetensors', [
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'existing_model.safetensors'
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])
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])
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const result = scanNodeModelCandidates(graph, node, noAssetSupport)
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expect(result).toHaveLength(1)
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expect(result[0]).toEqual({
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nodeId: '1',
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nodeType: 'CheckpointLoaderSimple',
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widgetName: 'ckpt_name',
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isAssetSupported: false,
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name: 'missing_model.safetensors',
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isMissing: true
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})
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})
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it('returns empty array for node with no widgets', () => {
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const graph = makeGraph([])
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const node = makeNode(1, 'EmptyNode', [])
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const result = scanNodeModelCandidates(graph, node, noAssetSupport)
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expect(result).toEqual([])
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})
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it('returns empty array when executionId is null', () => {
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const graph = makeGraph([])
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const node = makeNode(
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1,
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'CheckpointLoaderSimple',
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[makeComboWidget('ckpt_name', 'model.safetensors', [])],
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''
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)
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const result = scanNodeModelCandidates(graph, node, noAssetSupport)
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expect(result).toEqual([])
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})
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it('enriches candidates with url/hash/directory from node.properties.models', () => {
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// Regression: bypass/un-bypass cycle previously lost url metadata
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// because realtime scan only reads widget values. Per-node embedded
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// metadata in `properties.models` persists across mode toggles, so
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// the scan now enriches candidates from that source.
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const graph = makeGraph([])
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const node = fromAny<LGraphNode, unknown>({
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id: 1,
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type: 'CheckpointLoaderSimple',
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widgets: [
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makeComboWidget('ckpt_name', 'missing_model.safetensors', [
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'other_model.safetensors'
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])
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],
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properties: {
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models: [
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{
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name: 'missing_model.safetensors',
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url: 'https://example.com/missing_model',
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directory: 'checkpoints',
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hash: 'abc123',
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hash_type: 'sha256'
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}
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]
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}
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})
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const result = scanNodeModelCandidates(graph, node, noAssetSupport)
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expect(result).toHaveLength(1)
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expect(result[0].url).toBe('https://example.com/missing_model')
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expect(result[0].directory).toBe('checkpoints')
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expect(result[0].hash).toBe('abc123')
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expect(result[0].hashType).toBe('sha256')
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})
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it('preserves existing candidate fields when enriching (no overwrite)', () => {
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const graph = makeGraph([])
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const node = fromAny<LGraphNode, unknown>({
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id: 1,
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type: 'CheckpointLoaderSimple',
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widgets: [makeComboWidget('ckpt_name', 'missing_model.safetensors', [])],
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properties: {
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models: [
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{
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name: 'missing_model.safetensors',
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url: 'https://example.com/new_url',
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directory: 'checkpoints'
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}
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]
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}
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})
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const result = scanNodeModelCandidates(
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graph,
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node,
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noAssetSupport,
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() => 'checkpoints'
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)
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expect(result).toHaveLength(1)
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// scanComboWidget already sets directory via getDirectory; enrichment
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// does not overwrite it.
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expect(result[0].directory).toBe('checkpoints')
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// url was not set by scan, so enrichment fills it in.
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expect(result[0].url).toBe('https://example.com/new_url')
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})
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it('skips enrichment when candidate and embedded model directories differ', () => {
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// A node can list the same model name under multiple directories
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// (e.g. a LoRA present in both `loras` and `loras/subdir`). Name-only
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// matching would stamp the wrong url/hash onto the candidate, so
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// enrichment must agree on directory when the candidate already has
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// one.
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const graph = makeGraph([])
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const node = fromAny<LGraphNode, unknown>({
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id: 1,
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type: 'CheckpointLoaderSimple',
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widgets: [
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makeComboWidget('ckpt_name', 'collision_model.safetensors', [])
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],
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properties: {
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models: [
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{
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name: 'collision_model.safetensors',
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url: 'https://example.com/wrong_dir_url',
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directory: 'wrong_dir'
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}
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]
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}
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})
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const result = scanNodeModelCandidates(
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graph,
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node,
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noAssetSupport,
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() => 'checkpoints'
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)
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expect(result).toHaveLength(1)
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expect(result[0].directory).toBe('checkpoints')
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// Directory mismatch — enrichment should not stamp the wrong url.
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expect(result[0].url).toBeUndefined()
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})
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it('does not enrich candidates with mismatched model names', () => {
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const graph = makeGraph([])
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const node = fromAny<LGraphNode, unknown>({
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id: 1,
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type: 'CheckpointLoaderSimple',
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widgets: [makeComboWidget('ckpt_name', 'missing_model.safetensors', [])],
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properties: {
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models: [
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{
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name: 'different_model.safetensors',
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url: 'https://example.com/different',
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directory: 'checkpoints'
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}
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]
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}
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})
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const result = scanNodeModelCandidates(graph, node, noAssetSupport)
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expect(result).toHaveLength(1)
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expect(result[0].url).toBeUndefined()
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})
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})
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describe('scanAllModelCandidates', () => {
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it('should detect a missing model from a combo widget', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'missing_model.safetensors', [
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'existing_model.safetensors'
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])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([
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{
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nodeId: '1',
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nodeType: 'CheckpointLoaderSimple',
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widgetName: 'ckpt_name',
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isAssetSupported: false,
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name: 'missing_model.safetensors',
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isMissing: true
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}
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])
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})
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it('should not report models that exist in combo options', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'sd_xl_base_1.0.safetensors', [
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'sd_xl_base_1.0.safetensors'
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])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([
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{
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nodeId: '1',
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nodeType: 'CheckpointLoaderSimple',
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widgetName: 'ckpt_name',
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isAssetSupported: false,
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name: 'sd_xl_base_1.0.safetensors',
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isMissing: false
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}
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])
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})
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it('should skip non-model values (no model extension)', () => {
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const graph = makeGraph([
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makeNode(1, 'SomeNode', [
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makeComboWidget('mode', 'custom_mode', ['fast', 'slow'])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([])
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})
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it('should skip non-combo widgets', () => {
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const graph = makeGraph([
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makeNode(1, 'SomeNode', [
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makeOtherWidget('steps', 20),
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makeOtherWidget('cfg', 7.5)
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([])
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})
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it('should produce separate entries for same model in different nodes', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'missing.safetensors', [])
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]),
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makeNode(2, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'missing.safetensors', [])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toHaveLength(2)
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expect(result[0].nodeId).toBe('1')
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expect(result[1].nodeId).toBe('2')
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})
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it('should use correct widget name for each combo widget', () => {
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const graph = makeGraph([
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makeNode(1, 'LoraLoader', [
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makeComboWidget('lora_name', 'custom_lora.safetensors', [
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'existing.safetensors'
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]),
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makeOtherWidget('strength', 0.8)
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([
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{
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nodeId: '1',
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nodeType: 'LoraLoader',
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widgetName: 'lora_name',
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isAssetSupported: false,
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name: 'custom_lora.safetensors',
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isMissing: true
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}
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])
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})
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it('should skip nodes with no widgets', () => {
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const graph = makeGraph([makeNode(1, 'EmptyNode', [])])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([])
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})
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it('should detect missing models from custom nodes', () => {
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const graph = makeGraph([
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makeNode(1, 'WanVideoModelLoader', [
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makeComboWidget('model', 'Wan2_1-I2V-14B-480P_fp8_e4m3fn.safetensors', [
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'Wan2_1-I2V-14B.safetensors'
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])
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]),
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makeNode(2, 'WanVideoLoraSelect', [
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makeComboWidget('lora', 'SquishSquish_18.safetensors', [
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'default_lora.safetensors'
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])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toHaveLength(2)
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expect(result.map((r) => r.name)).toEqual([
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'Wan2_1-I2V-14B-480P_fp8_e4m3fn.safetensors',
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'SquishSquish_18.safetensors'
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])
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})
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it('should detect multiple missing models from different nodes', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'model_a.safetensors', [])
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]),
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makeNode(2, 'LoraLoader', [
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makeComboWidget('lora_name', 'lora_b.safetensors', []),
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makeOtherWidget('strength', 0.8)
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]),
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makeNode(3, 'VAELoader', [
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makeComboWidget('vae_name', 'vae_c.safetensors', [])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toHaveLength(3)
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})
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it('should handle whitespace-only widget values', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', ' ', []),
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makeComboWidget('other', '', [])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toEqual([])
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})
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it('should set isMissing=undefined for asset-supported nodes', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'missing.safetensors', [])
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])
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])
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const result = scanAllModelCandidates(graph, () => true)
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expect(result).toHaveLength(1)
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expect(result[0].isAssetSupported).toBe(true)
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expect(result[0].isMissing).toBeUndefined()
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})
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it('should set isMissing=true for non-asset nodes with missing model', () => {
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const graph = makeGraph([
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makeNode(1, 'CustomLoader', [
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makeComboWidget('model', 'custom.safetensors', [])
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])
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toHaveLength(1)
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expect(result[0].isAssetSupported).toBe(false)
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expect(result[0].isMissing).toBe(true)
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})
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it('should pass directory from getDirectory callback', () => {
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const graph = makeGraph([
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makeNode(1, 'CheckpointLoaderSimple', [
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makeComboWidget('ckpt_name', 'model.safetensors', [])
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])
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])
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const result = scanAllModelCandidates(
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graph,
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noAssetSupport,
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() => 'checkpoints'
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)
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expect(result[0].directory).toBe('checkpoints')
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})
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it('should use execution ID from graph traversal for subgraph nodes', () => {
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const graph = makeGraph([
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makeNode(
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99,
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'CheckpointLoaderSimple',
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[makeComboWidget('ckpt_name', 'subgraph_model.safetensors', [])],
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'10:99'
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)
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])
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const result = scanAllModelCandidates(graph, noAssetSupport)
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expect(result).toHaveLength(1)
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expect(result[0].nodeId).toBe('10:99')
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expect(result[0].name).toBe('subgraph_model.safetensors')
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})
|
|
|
|
it('should detect missing models from asset widgets (Cloud combo replacement)', () => {
|
|
const graph = makeGraph([
|
|
makeNode(1, 'CheckpointLoaderSimple', [
|
|
makeAssetWidget('ckpt_name', 'missing_model.safetensors')
|
|
])
|
|
])
|
|
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].isAssetSupported).toBe(true)
|
|
expect(result[0].isMissing).toBeUndefined()
|
|
expect(result[0].name).toBe('missing_model.safetensors')
|
|
expect(result[0].widgetName).toBe('ckpt_name')
|
|
})
|
|
|
|
it('should skip asset widgets with non-model values', () => {
|
|
const graph = makeGraph([
|
|
makeNode(1, 'SomeNode', [makeAssetWidget('mode', 'not_a_model')])
|
|
])
|
|
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toEqual([])
|
|
})
|
|
|
|
it('should skip asset widgets with non-string values', () => {
|
|
const graph = makeGraph([
|
|
makeNode(1, 'SomeNode', [makeAssetWidget('ckpt_name', 123)])
|
|
])
|
|
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toEqual([])
|
|
})
|
|
|
|
it('should scan both combo and asset widgets on the same node', () => {
|
|
const graph = makeGraph([
|
|
makeNode(1, 'DualLoaderNode', [
|
|
makeAssetWidget('ckpt_name', 'cloud_model.safetensors'),
|
|
makeComboWidget('vae_name', 'local_vae.safetensors', [])
|
|
])
|
|
])
|
|
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(2)
|
|
expect(result[0].widgetName).toBe('ckpt_name')
|
|
expect(result[0].isAssetSupported).toBe(true)
|
|
expect(result[1].widgetName).toBe('vae_name')
|
|
})
|
|
|
|
it('skips muted nodes (mode === NEVER)', () => {
|
|
const mutedNode = fromAny<LGraphNode, unknown>({
|
|
id: 10,
|
|
type: 'CheckpointLoaderSimple',
|
|
widgets: [
|
|
makeComboWidget('ckpt_name', 'model.safetensors', ['other.safetensors'])
|
|
],
|
|
mode: 2, // LGraphEventMode.NEVER
|
|
_testExecutionId: '10'
|
|
})
|
|
|
|
const graph = makeGraph([mutedNode])
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('skips bypassed nodes (mode === BYPASS)', () => {
|
|
const bypassedNode = fromAny<LGraphNode, unknown>({
|
|
id: 11,
|
|
type: 'CheckpointLoaderSimple',
|
|
widgets: [
|
|
makeComboWidget('ckpt_name', 'model.safetensors', ['other.safetensors'])
|
|
],
|
|
mode: 4, // LGraphEventMode.BYPASS
|
|
_testExecutionId: '11'
|
|
})
|
|
|
|
const graph = makeGraph([bypassedNode])
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('includes active nodes (mode === ALWAYS)', () => {
|
|
const activeNode = fromAny<LGraphNode, unknown>({
|
|
id: 12,
|
|
type: 'CheckpointLoaderSimple',
|
|
widgets: [
|
|
makeComboWidget('ckpt_name', 'model.safetensors', ['other.safetensors'])
|
|
],
|
|
mode: 0, // LGraphEventMode.ALWAYS
|
|
_testExecutionId: '12'
|
|
})
|
|
|
|
const graph = makeGraph([activeNode])
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].isMissing).toBe(true)
|
|
})
|
|
|
|
it('skips subgraph container nodes whose promoted widgets are already scanned via interior nodes', () => {
|
|
const containerNode = fromAny<LGraphNode, unknown>({
|
|
id: 65,
|
|
type: 'abc-def-uuid',
|
|
widgets: [makeComboWidget('ckpt_name', 'model.safetensors', [])],
|
|
isSubgraphNode: () => true,
|
|
_testExecutionId: '65'
|
|
})
|
|
|
|
const interiorNode = makeNode(
|
|
42,
|
|
'CheckpointLoaderSimple',
|
|
[
|
|
makeComboWidget('ckpt_name', 'model.safetensors', ['model.safetensors'])
|
|
],
|
|
'65:42'
|
|
)
|
|
|
|
const graph = makeGraph([containerNode, interiorNode])
|
|
const result = scanAllModelCandidates(graph, noAssetSupport)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].nodeId).toBe('65:42')
|
|
expect(result[0].nodeType).toBe('CheckpointLoaderSimple')
|
|
})
|
|
})
|
|
|
|
function makeCandidate(
|
|
name: string,
|
|
opts: Partial<MissingModelCandidate> = {}
|
|
): MissingModelCandidate {
|
|
return {
|
|
nodeId: opts.nodeId ?? 1,
|
|
nodeType: opts.nodeType ?? 'CheckpointLoaderSimple',
|
|
widgetName: opts.widgetName ?? 'ckpt_name',
|
|
isAssetSupported: opts.isAssetSupported ?? false,
|
|
name,
|
|
isMissing: opts.isMissing ?? true,
|
|
...opts
|
|
}
|
|
}
|
|
|
|
const alwaysMissing = async () => false
|
|
const alwaysInstalled = async () => true
|
|
|
|
describe('enrichWithEmbeddedMetadata', () => {
|
|
it('enriches existing candidate with url and directory from embedded metadata', async () => {
|
|
const candidates = [makeCandidate('model_a.safetensors')]
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model_a.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model_a.safetensors',
|
|
url: 'https://example.com/model_a',
|
|
directory: 'checkpoints',
|
|
hash: 'abc123',
|
|
hash_type: 'sha256'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result[0].url).toBe('https://example.com/model_a')
|
|
expect(result[0].directory).toBe('checkpoints')
|
|
expect(result[0].hash).toBe('abc123')
|
|
})
|
|
|
|
it('does not overwrite existing fields on candidate', async () => {
|
|
const candidates = [
|
|
makeCandidate('model_a.safetensors', {
|
|
directory: 'existing_dir',
|
|
url: 'https://existing.com'
|
|
})
|
|
]
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model_a.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model_a.safetensors',
|
|
url: 'https://new.com',
|
|
directory: 'new_dir'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
// ??= should not overwrite existing values
|
|
expect(result[0].url).toBe('https://existing.com')
|
|
expect(result[0].directory).toBe('existing_dir')
|
|
})
|
|
|
|
it('does not mutate the original candidates array', async () => {
|
|
const candidates = [makeCandidate('model_a.safetensors')]
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model_a.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model_a.safetensors',
|
|
url: 'https://example.com/model_a',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const originalUrl = candidates[0].url
|
|
await enrichWithEmbeddedMetadata(candidates, graphData, alwaysMissing)
|
|
|
|
expect(candidates[0].url).toBe(originalUrl)
|
|
})
|
|
|
|
it('adds new candidate for embedded model not found by COMBO scan', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model_a.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model_a.safetensors',
|
|
url: 'https://example.com/model_a',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].name).toBe('model_a.safetensors')
|
|
expect(result[0].isMissing).toBe(true)
|
|
})
|
|
|
|
it('does not add candidate when model is already installed', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 0,
|
|
last_link_id: 0,
|
|
nodes: [],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'installed_model.safetensors',
|
|
url: 'https://example.com',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysInstalled
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('skips embedded models from muted nodes', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 2, // NEVER (muted)
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('drops workflow-level model entries when only referencing nodes are bypassed (other active nodes present)', async () => {
|
|
// Regression: a previous `hasActiveNodes` check kept workflow-level
|
|
// models in a mixed graph if ANY active node existed, even when every
|
|
// node that actually referenced the model was bypassed. The correct
|
|
// check drops unmatched workflow-level entries since candidates are
|
|
// derived from active-node widgets.
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 2,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 4, // BYPASS — only node referencing the model
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model.safetensors' }
|
|
},
|
|
{
|
|
id: 2,
|
|
type: 'KSampler',
|
|
pos: [200, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 1,
|
|
mode: 0, // ALWAYS — unrelated active node
|
|
properties: {},
|
|
widgets_values: {}
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('keeps unmatched node-sourced entries in a mixed graph', async () => {
|
|
// A node-sourced unmatched entry (sourceNodeType !== '') must survive
|
|
// the workflow-level filter. This ensures the simplification does not
|
|
// over-filter legitimate per-node missing models.
|
|
const candidates = [
|
|
makeCandidate('node_model.safetensors', { nodeId: '1' })
|
|
]
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {
|
|
models: [
|
|
{
|
|
name: 'node_model.safetensors',
|
|
url: 'https://example.com/node_model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
},
|
|
widgets_values: { ckpt_name: 'node_model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: []
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].name).toBe('node_model.safetensors')
|
|
})
|
|
|
|
it('skips embedded models from bypassed nodes', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 4, // BYPASS
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('drops workflow-level entries when only reference is in a bypassed subgraph interior', async () => {
|
|
// Interior properties.models references the workflow-level model
|
|
// but its widget value does not — forcing the workflow-level entry
|
|
// down the unmatched path where isModelReferencedByActiveNode
|
|
// decides. Previously the helper ignored the bypassed container.
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
[],
|
|
fromAny<ComfyWorkflowJSON, unknown>(bypassedSubgraphUnmatchedModel),
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
|
|
it('keeps workflow-level entries when reference is in an active subgraph interior', async () => {
|
|
// Positive control for the bypassed case above: identical fixture
|
|
// with container mode=0 must still surface the unmatched workflow-
|
|
// level model. Guards against a regression where the ancestor gate
|
|
// drops every workflow-level entry regardless of context.
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
[],
|
|
fromAny<ComfyWorkflowJSON, unknown>(activeSubgraphUnmatchedModel),
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].name).toBe('rare_model.safetensors')
|
|
})
|
|
|
|
it('drops workflow-level entries when interior reference is under a different directory', async () => {
|
|
// Same name, different directory: the interior's properties.models
|
|
// entry is not the same asset as the workflow-level entry, so the
|
|
// fallback helper must not treat it as a reference that keeps the
|
|
// workflow-level model alive.
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {
|
|
models: [
|
|
{
|
|
name: 'collide_model.safetensors',
|
|
directory: 'loras'
|
|
}
|
|
]
|
|
},
|
|
widgets_values: ['unrelated_widget.safetensors']
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'collide_model.safetensors',
|
|
url: 'https://example.com/collide',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
[],
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(0)
|
|
})
|
|
})
|
|
|
|
describe('OSS missing model detection (non-Cloud path)', () => {
|
|
it('scanAllModelCandidates returns empty array when not called (simulating isCloud === false guard)', () => {
|
|
// In the app, when isCloud is false, scanAllModelCandidates is not called
|
|
// and an empty array is used instead. This test verifies the OSS path
|
|
// starts with an empty candidates list.
|
|
const isCloud = false
|
|
const graph = makeGraph([
|
|
makeNode(1, 'CheckpointLoaderSimple', [
|
|
makeComboWidget('ckpt_name', 'missing_model.safetensors', [])
|
|
])
|
|
])
|
|
|
|
const modelCandidates = isCloud
|
|
? scanAllModelCandidates(graph, noAssetSupport)
|
|
: []
|
|
|
|
expect(modelCandidates).toEqual([])
|
|
})
|
|
|
|
it('enrichWithEmbeddedMetadata detects missing embedded models without prior COMBO scan (OSS dialog path)', async () => {
|
|
// OSS path: candidates start empty, enrichWithEmbeddedMetadata adds
|
|
// missing embedded models so the dialog can show them.
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 2,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'sd_xl_base_1.0.safetensors' }
|
|
},
|
|
{
|
|
id: 2,
|
|
type: 'LoraLoader',
|
|
pos: [200, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 1,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { lora_name: 'detail_enhancer.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'sd_xl_base_1.0.safetensors',
|
|
url: 'https://example.com/sdxl',
|
|
directory: 'checkpoints'
|
|
},
|
|
{
|
|
name: 'detail_enhancer.safetensors',
|
|
url: 'https://example.com/lora',
|
|
directory: 'loras'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(2)
|
|
expect(result.every((c) => c.isMissing === true)).toBe(true)
|
|
expect(result.map((c) => c.name)).toEqual([
|
|
'sd_xl_base_1.0.safetensors',
|
|
'detail_enhancer.safetensors'
|
|
])
|
|
})
|
|
|
|
it('enrichWithEmbeddedMetadata sets isMissing=true when isAssetSupported is not provided (OSS)', async () => {
|
|
// When isAssetSupported is omitted (OSS), unmatched embedded models
|
|
// should have isMissing=true (not undefined), enabling the dialog.
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'missing_model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'missing_model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing
|
|
)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].isMissing).toBe(true)
|
|
expect(result[0].isAssetSupported).toBe(false)
|
|
})
|
|
|
|
it('enrichWithEmbeddedMetadata correctly filters for dialog: only isMissing=true with url', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'missing_model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'missing_model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
},
|
|
{
|
|
name: 'installed_model.safetensors',
|
|
url: 'https://example.com/installed',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const selectiveInstallCheck = async (name: string) =>
|
|
name === 'installed_model.safetensors'
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
selectiveInstallCheck
|
|
)
|
|
|
|
const dialogModels = result.filter((c) => c.isMissing === true && c.url)
|
|
expect(dialogModels).toHaveLength(1)
|
|
expect(dialogModels[0].name).toBe('missing_model.safetensors')
|
|
expect(dialogModels[0].url).toBe('https://example.com/model')
|
|
})
|
|
|
|
it('enrichWithEmbeddedMetadata with isAssetSupported leaves isMissing undefined for asset-supported models (Cloud path)', async () => {
|
|
const candidates: MissingModelCandidate[] = []
|
|
const graphData = fromPartial<ComfyWorkflowJSON>({
|
|
last_node_id: 1,
|
|
last_link_id: 0,
|
|
nodes: [
|
|
{
|
|
id: 1,
|
|
type: 'CheckpointLoaderSimple',
|
|
pos: [0, 0],
|
|
size: [100, 100],
|
|
flags: {},
|
|
order: 0,
|
|
mode: 0,
|
|
properties: {},
|
|
widgets_values: { ckpt_name: 'model.safetensors' }
|
|
}
|
|
],
|
|
links: [],
|
|
groups: [],
|
|
config: {},
|
|
extra: {},
|
|
version: 0.4,
|
|
models: [
|
|
{
|
|
name: 'model.safetensors',
|
|
url: 'https://example.com/model',
|
|
directory: 'checkpoints'
|
|
}
|
|
]
|
|
})
|
|
|
|
const result = await enrichWithEmbeddedMetadata(
|
|
candidates,
|
|
graphData,
|
|
alwaysMissing,
|
|
() => true
|
|
)
|
|
|
|
expect(result).toHaveLength(1)
|
|
expect(result[0].isMissing).toBeUndefined()
|
|
expect(result[0].isAssetSupported).toBe(true)
|
|
})
|
|
})
|
|
|
|
const { mockUpdateModelsForNodeType, mockGetAssets } = vi.hoisted(() => ({
|
|
mockUpdateModelsForNodeType: vi.fn().mockResolvedValue(undefined),
|
|
mockGetAssets: vi.fn().mockReturnValue([])
|
|
}))
|
|
|
|
vi.mock('@/stores/assetsStore', () => ({
|
|
useAssetsStore: () => ({
|
|
updateModelsForNodeType: mockUpdateModelsForNodeType,
|
|
getAssets: mockGetAssets
|
|
})
|
|
}))
|
|
|
|
vi.mock('@/platform/updates/common/toastStore', () => ({
|
|
useToastStore: () => ({
|
|
add: vi.fn()
|
|
})
|
|
}))
|
|
|
|
vi.mock('@/i18n', () => ({
|
|
st: (_key: string, fallback: string) => fallback
|
|
}))
|
|
|
|
function makeAssetCandidate(
|
|
name: string,
|
|
opts: Partial<MissingModelCandidate> = {}
|
|
): MissingModelCandidate {
|
|
return {
|
|
nodeId: opts.nodeId ?? 1,
|
|
nodeType: opts.nodeType ?? 'CheckpointLoaderSimple',
|
|
widgetName: opts.widgetName ?? 'ckpt_name',
|
|
isAssetSupported: opts.isAssetSupported ?? true,
|
|
name,
|
|
isMissing: opts.isMissing,
|
|
...opts
|
|
}
|
|
}
|
|
|
|
describe('verifyAssetSupportedCandidates', () => {
|
|
beforeEach(() => {
|
|
vi.clearAllMocks()
|
|
mockUpdateModelsForNodeType.mockResolvedValue(undefined)
|
|
mockGetAssets.mockReturnValue([])
|
|
})
|
|
|
|
it('should resolve isMissing=true for candidates not found in asset store', async () => {
|
|
const candidates = [makeAssetCandidate('missing_model.safetensors')]
|
|
mockGetAssets.mockReturnValue([])
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(true)
|
|
expect(mockUpdateModelsForNodeType).toHaveBeenCalledWith(
|
|
'CheckpointLoaderSimple'
|
|
)
|
|
})
|
|
|
|
it('should match filenames regardless of hash metadata shape', async () => {
|
|
const hash =
|
|
'2222222222222222222222222222222222222222222222222222222222222222'
|
|
const candidates = [
|
|
makeAssetCandidate('my_model.safetensors', {
|
|
hash,
|
|
hashType: 'blake3'
|
|
}),
|
|
makeAssetCandidate('other_model.safetensors', {
|
|
hash: 'abc123',
|
|
hashType: 'blake3'
|
|
})
|
|
]
|
|
mockGetAssets.mockReturnValue([
|
|
{
|
|
id: '1',
|
|
name: 'my_model.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'my_model.safetensors' }
|
|
},
|
|
{
|
|
id: '2',
|
|
name: 'other_model.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'other_model.safetensors' }
|
|
}
|
|
])
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
expect(candidates[1].isMissing).toBe(false)
|
|
expect(mockUpdateModelsForNodeType).toHaveBeenCalledWith(
|
|
'CheckpointLoaderSimple'
|
|
)
|
|
})
|
|
|
|
it('should resolve isMissing=false when asset with matching asset_hash exists', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('model.safetensors', {
|
|
hash: 'abc123',
|
|
hashType: 'sha256'
|
|
})
|
|
]
|
|
mockGetAssets.mockReturnValue([
|
|
{ id: '1', name: 'model.safetensors', asset_hash: 'sha256:abc123' }
|
|
])
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
})
|
|
|
|
it('should resolve isMissing=false when asset with matching filename exists', async () => {
|
|
const candidates = [makeAssetCandidate('my_model.safetensors')]
|
|
mockGetAssets.mockReturnValue([
|
|
{
|
|
id: '1',
|
|
name: 'my_model.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'my_model.safetensors' }
|
|
}
|
|
])
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
})
|
|
|
|
it('should return immediately when signal is already aborted', async () => {
|
|
const candidates = [makeAssetCandidate('model.safetensors')]
|
|
const controller = new AbortController()
|
|
controller.abort()
|
|
|
|
await verifyAssetSupportedCandidates(candidates, controller.signal)
|
|
|
|
// isMissing should remain undefined since we aborted before resolving
|
|
expect(candidates[0].isMissing).toBeUndefined()
|
|
})
|
|
|
|
it('should return immediately when no asset-supported candidates exist', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('model.safetensors', {
|
|
isAssetSupported: false,
|
|
isMissing: true
|
|
})
|
|
]
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(mockUpdateModelsForNodeType).not.toHaveBeenCalled()
|
|
expect(candidates[0].isMissing).toBe(true)
|
|
})
|
|
|
|
it('should skip candidates with isMissing already resolved', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('found.safetensors', { isMissing: false }),
|
|
makeAssetCandidate('missing.safetensors', { isMissing: true })
|
|
]
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(mockUpdateModelsForNodeType).not.toHaveBeenCalled()
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
expect(candidates[1].isMissing).toBe(true)
|
|
})
|
|
|
|
it('should deduplicate nodeType calls to updateModelsForNodeType', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('model_a.safetensors'),
|
|
makeAssetCandidate('model_b.safetensors')
|
|
]
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(mockUpdateModelsForNodeType).toHaveBeenCalledTimes(1)
|
|
})
|
|
|
|
it('should call updateModelsForNodeType for each unique nodeType', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('model_a.safetensors', {
|
|
nodeType: 'CheckpointLoaderSimple'
|
|
}),
|
|
makeAssetCandidate('model_b.safetensors', { nodeType: 'LoraLoader' })
|
|
]
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(mockUpdateModelsForNodeType).toHaveBeenCalledWith(
|
|
'CheckpointLoaderSimple'
|
|
)
|
|
expect(mockUpdateModelsForNodeType).toHaveBeenCalledWith('LoraLoader')
|
|
})
|
|
|
|
it('should leave candidates unresolved when their node type fails to load', async () => {
|
|
const candidates = [
|
|
makeAssetCandidate('checkpoint.safetensors', {
|
|
nodeType: 'CheckpointLoaderSimple'
|
|
}),
|
|
makeAssetCandidate('lora.safetensors', { nodeType: 'LoraLoader' })
|
|
]
|
|
mockUpdateModelsForNodeType.mockImplementation(async (nodeType: string) => {
|
|
if (nodeType === 'LoraLoader') throw new Error('load failed')
|
|
})
|
|
mockGetAssets.mockImplementation((nodeType: string) =>
|
|
nodeType === 'CheckpointLoaderSimple'
|
|
? [
|
|
{
|
|
id: '1',
|
|
name: 'checkpoint.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'checkpoint.safetensors' }
|
|
}
|
|
]
|
|
: []
|
|
)
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
expect(candidates[1].isMissing).toBeUndefined()
|
|
})
|
|
|
|
it('should leave candidates unresolved when aborted after asset loads settle', async () => {
|
|
const controller = new AbortController()
|
|
const candidates = [makeAssetCandidate('model.safetensors')]
|
|
mockUpdateModelsForNodeType.mockImplementation(async () => {
|
|
controller.abort()
|
|
})
|
|
mockGetAssets.mockReturnValue([
|
|
{
|
|
id: '1',
|
|
name: 'model.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'model.safetensors' }
|
|
}
|
|
])
|
|
|
|
await verifyAssetSupportedCandidates(candidates, controller.signal)
|
|
|
|
expect(candidates[0].isMissing).toBeUndefined()
|
|
})
|
|
|
|
it('should match filename with path prefix normalization', async () => {
|
|
const candidates = [makeAssetCandidate('subfolder/my_model.safetensors')]
|
|
mockGetAssets.mockReturnValue([
|
|
{
|
|
id: '1',
|
|
name: 'my_model.safetensors',
|
|
asset_hash: null,
|
|
metadata: { filename: 'subfolder/my_model.safetensors' }
|
|
}
|
|
])
|
|
|
|
await verifyAssetSupportedCandidates(candidates)
|
|
|
|
expect(candidates[0].isMissing).toBe(false)
|
|
})
|
|
})
|