jan/web-app/src/services/__tests__/models.test.ts
2025-08-19 19:51:33 +07:00

849 lines
23 KiB
TypeScript

import { describe, it, expect, vi, beforeEach } from 'vitest'
import {
fetchModels,
fetchModelCatalog,
fetchHuggingFaceRepo,
convertHfRepoToCatalogModel,
updateModel,
pullModel,
abortDownload,
deleteModel,
getActiveModels,
stopModel,
stopAllModels,
startModel,
HuggingFaceRepo,
CatalogModel,
} from '../models'
import { EngineManager, Model } from '@janhq/core'
// Mock EngineManager
vi.mock('@janhq/core', () => ({
EngineManager: {
instance: vi.fn(),
},
}))
// Mock fetch
global.fetch = vi.fn()
// Mock MODEL_CATALOG_URL
Object.defineProperty(global, 'MODEL_CATALOG_URL', {
value: 'https://example.com/models',
writable: true,
configurable: true,
})
describe('models service', () => {
const mockEngine = {
list: vi.fn(),
updateSettings: vi.fn(),
import: vi.fn(),
abortImport: vi.fn(),
delete: vi.fn(),
getLoadedModels: vi.fn(),
unload: vi.fn(),
load: vi.fn(),
}
const mockEngineManager = {
get: vi.fn().mockReturnValue(mockEngine),
}
beforeEach(() => {
vi.clearAllMocks()
;(EngineManager.instance as any).mockReturnValue(mockEngineManager)
})
describe('fetchModels', () => {
it('should fetch models successfully', async () => {
const mockModels = [
{ id: 'model1', name: 'Model 1' },
{ id: 'model2', name: 'Model 2' },
]
mockEngine.list.mockResolvedValue(mockModels)
const result = await fetchModels()
expect(result).toEqual(mockModels)
expect(mockEngine.list).toHaveBeenCalled()
})
})
describe('fetchModelCatalog', () => {
it('should fetch model catalog successfully', async () => {
const mockCatalog = [
{
model_name: 'GPT-4',
description: 'Large language model',
developer: 'OpenAI',
downloads: 1000,
num_quants: 5,
quants: [],
},
]
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockCatalog),
})
const result = await fetchModelCatalog()
expect(result).toEqual(mockCatalog)
})
it('should handle fetch error', async () => {
;(fetch as any).mockResolvedValue({
ok: false,
status: 404,
statusText: 'Not Found',
})
await expect(fetchModelCatalog()).rejects.toThrow(
'Failed to fetch model catalog: 404 Not Found'
)
})
it('should handle network error', async () => {
;(fetch as any).mockRejectedValue(new Error('Network error'))
await expect(fetchModelCatalog()).rejects.toThrow(
'Failed to fetch model catalog: Network error'
)
})
})
describe('updateModel', () => {
it('should update model settings', async () => {
const model = {
id: 'model1',
settings: [{ key: 'temperature', value: 0.7 }],
}
await updateModel(model as any)
expect(mockEngine.updateSettings).toHaveBeenCalledWith(model.settings)
})
it('should handle model without settings', async () => {
const model = { id: 'model1' }
await updateModel(model)
expect(mockEngine.updateSettings).not.toHaveBeenCalled()
})
})
describe('pullModel', () => {
it('should pull model successfully', async () => {
const id = 'model1'
const modelPath = '/path/to/model'
await pullModel(id, modelPath)
expect(mockEngine.import).toHaveBeenCalledWith(id, { modelPath })
})
})
describe('abortDownload', () => {
it('should abort download successfully', async () => {
const id = 'model1'
await abortDownload(id)
expect(mockEngine.abortImport).toHaveBeenCalledWith(id)
})
})
describe('deleteModel', () => {
it('should delete model successfully', async () => {
const id = 'model1'
await deleteModel(id)
expect(mockEngine.delete).toHaveBeenCalledWith(id)
})
})
describe('getActiveModels', () => {
it('should get active models successfully', async () => {
const mockActiveModels = ['model1', 'model2']
mockEngine.getLoadedModels.mockResolvedValue(mockActiveModels)
const result = await getActiveModels()
expect(result).toEqual(mockActiveModels)
expect(mockEngine.getLoadedModels).toHaveBeenCalled()
})
})
describe('stopModel', () => {
it('should stop model successfully', async () => {
const model = 'model1'
const provider = 'openai'
await stopModel(model, provider)
expect(mockEngine.unload).toHaveBeenCalledWith(model)
})
})
describe('stopAllModels', () => {
it('should stop all active models', async () => {
const mockActiveModels = ['model1', 'model2']
mockEngine.getLoadedModels.mockResolvedValue(mockActiveModels)
await stopAllModels()
expect(mockEngine.unload).toHaveBeenCalledTimes(2)
expect(mockEngine.unload).toHaveBeenCalledWith('model1')
expect(mockEngine.unload).toHaveBeenCalledWith('model2')
})
it('should handle empty active models', async () => {
mockEngine.getLoadedModels.mockResolvedValue(null)
await stopAllModels()
expect(mockEngine.unload).not.toHaveBeenCalled()
})
})
describe('startModel', () => {
it('should start model successfully', async () => {
const mockSettings = {
ctx_len: { controller_props: { value: 4096 } },
ngl: { controller_props: { value: 32 } },
}
const provider = {
provider: 'openai',
models: [{ id: 'model1', settings: mockSettings }],
} as any
const model = 'model1'
const mockSession = { id: 'session1' }
mockEngine.getLoadedModels.mockResolvedValue({
includes: () => false,
})
mockEngine.load.mockResolvedValue(mockSession)
const result = await startModel(provider, model)
expect(result).toEqual(mockSession)
expect(mockEngine.load).toHaveBeenCalledWith(model, {
ctx_size: 4096,
n_gpu_layers: 32,
})
})
it('should handle start model error', async () => {
const mockSettings = {
ctx_len: { controller_props: { value: 4096 } },
ngl: { controller_props: { value: 32 } },
}
const provider = {
provider: 'openai',
models: [{ id: 'model1', settings: mockSettings }],
} as any
const model = 'model1'
const error = new Error('Failed to start model')
mockEngine.getLoadedModels.mockResolvedValue({
includes: () => false,
})
mockEngine.load.mockRejectedValue(error)
await expect(startModel(provider, model)).rejects.toThrow(error)
})
it('should not load model again', async () => {
const mockSettings = {
ctx_len: { controller_props: { value: 4096 } },
ngl: { controller_props: { value: 32 } },
}
const provider = {
provider: 'openai',
models: [{ id: 'model1', settings: mockSettings }],
} as any
const model = 'model1'
mockEngine.getLoadedModels.mockResolvedValue({
includes: () => true,
})
expect(mockEngine.load).toBeCalledTimes(0)
await expect(startModel(provider, model)).resolves.toBe(undefined)
})
})
describe('fetchHuggingFaceRepo', () => {
beforeEach(() => {
vi.clearAllMocks()
})
it('should fetch HuggingFace repository successfully with blobs=true', async () => {
const mockRepoData = {
id: 'microsoft/DialoGPT-medium',
modelId: 'microsoft/DialoGPT-medium',
sha: 'abc123',
downloads: 5000,
likes: 100,
tags: ['conversational', 'pytorch'],
pipeline_tag: 'text-generation',
createdAt: '2023-01-01T00:00:00Z',
last_modified: '2023-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'microsoft',
siblings: [
{
rfilename: 'model-Q4_K_M.gguf',
size: 2147483648,
blobId: 'blob123',
},
{
rfilename: 'model-Q8_0.gguf',
size: 4294967296,
blobId: 'blob456',
},
{
rfilename: 'README.md',
size: 1024,
blobId: 'blob789',
},
],
readme: '# DialoGPT Model\nThis is a conversational AI model.',
}
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockRepoData),
})
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toEqual(mockRepoData)
expect(fetch).toHaveBeenCalledWith(
'https://huggingface.co/api/models/microsoft/DialoGPT-medium?blobs=true',
{
headers: {},
}
)
})
it('should clean repository ID from various input formats', async () => {
const mockRepoData = { modelId: 'microsoft/DialoGPT-medium' }
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockRepoData),
})
// Test with full URL
await fetchHuggingFaceRepo(
'https://huggingface.co/microsoft/DialoGPT-medium'
)
expect(fetch).toHaveBeenCalledWith(
'https://huggingface.co/api/models/microsoft/DialoGPT-medium?blobs=true',
{
headers: {},
}
)
// Test with domain prefix
await fetchHuggingFaceRepo('huggingface.co/microsoft/DialoGPT-medium')
expect(fetch).toHaveBeenCalledWith(
'https://huggingface.co/api/models/microsoft/DialoGPT-medium?blobs=true',
{
headers: {},
}
)
// Test with trailing slash
await fetchHuggingFaceRepo('microsoft/DialoGPT-medium/')
expect(fetch).toHaveBeenCalledWith(
'https://huggingface.co/api/models/microsoft/DialoGPT-medium?blobs=true',
{
headers: {},
}
)
})
it('should return null for invalid repository IDs', async () => {
// Test empty string
expect(await fetchHuggingFaceRepo('')).toBeNull()
// Test string without slash
expect(await fetchHuggingFaceRepo('invalid-repo')).toBeNull()
// Test whitespace only
expect(await fetchHuggingFaceRepo(' ')).toBeNull()
})
it('should return null for 404 responses', async () => {
;(fetch as any).mockResolvedValue({
ok: false,
status: 404,
statusText: 'Not Found',
})
const result = await fetchHuggingFaceRepo('nonexistent/model')
expect(result).toBeNull()
expect(fetch).toHaveBeenCalledWith(
'https://huggingface.co/api/models/nonexistent/model?blobs=true',
{
headers: {},
}
)
})
it('should handle other HTTP errors', async () => {
const consoleSpy = vi.spyOn(console, 'error').mockImplementation(() => {})
;(fetch as any).mockResolvedValue({
ok: false,
status: 500,
statusText: 'Internal Server Error',
})
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toBeNull()
expect(consoleSpy).toHaveBeenCalledWith(
'Error fetching HuggingFace repository:',
expect.any(Error)
)
consoleSpy.mockRestore()
})
it('should handle network errors', async () => {
const consoleSpy = vi.spyOn(console, 'error').mockImplementation(() => {})
;(fetch as any).mockRejectedValue(new Error('Network error'))
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toBeNull()
expect(consoleSpy).toHaveBeenCalledWith(
'Error fetching HuggingFace repository:',
expect.any(Error)
)
consoleSpy.mockRestore()
})
it('should handle repository with no siblings', async () => {
const mockRepoData = {
id: 'microsoft/DialoGPT-medium',
modelId: 'microsoft/DialoGPT-medium',
sha: 'abc123',
downloads: 5000,
likes: 100,
tags: ['conversational'],
pipeline_tag: 'text-generation',
createdAt: '2023-01-01T00:00:00Z',
last_modified: '2023-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'microsoft',
siblings: undefined,
}
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockRepoData),
})
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toEqual(mockRepoData)
})
it('should handle repository with no GGUF files', async () => {
const mockRepoData = {
id: 'microsoft/DialoGPT-medium',
modelId: 'microsoft/DialoGPT-medium',
sha: 'abc123',
downloads: 5000,
likes: 100,
tags: ['conversational'],
pipeline_tag: 'text-generation',
createdAt: '2023-01-01T00:00:00Z',
last_modified: '2023-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'microsoft',
siblings: [
{
rfilename: 'README.md',
size: 1024,
blobId: 'blob789',
},
{
rfilename: 'config.json',
size: 512,
blobId: 'blob101',
},
],
}
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockRepoData),
})
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toEqual(mockRepoData)
})
it('should handle repository with mixed file types including GGUF', async () => {
const mockRepoData = {
id: 'microsoft/DialoGPT-medium',
modelId: 'microsoft/DialoGPT-medium',
sha: 'abc123',
downloads: 5000,
likes: 100,
tags: ['conversational'],
pipeline_tag: 'text-generation',
createdAt: '2023-01-01T00:00:00Z',
last_modified: '2023-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'microsoft',
siblings: [
{
rfilename: 'model-Q4_K_M.gguf',
size: 2147483648, // 2GB
blobId: 'blob123',
},
{
rfilename: 'README.md',
size: 1024,
blobId: 'blob789',
},
{
rfilename: 'config.json',
size: 512,
blobId: 'blob101',
},
],
}
;(fetch as any).mockResolvedValue({
ok: true,
json: vi.fn().mockResolvedValue(mockRepoData),
})
const result = await fetchHuggingFaceRepo('microsoft/DialoGPT-medium')
expect(result).toEqual(mockRepoData)
// Verify the GGUF file is present in siblings
expect(result?.siblings?.some((s) => s.rfilename.endsWith('.gguf'))).toBe(
true
)
})
})
describe('convertHfRepoToCatalogModel', () => {
const mockHuggingFaceRepo: HuggingFaceRepo = {
id: 'microsoft/DialoGPT-medium',
modelId: 'microsoft/DialoGPT-medium',
sha: 'abc123',
downloads: 1500,
likes: 75,
tags: ['pytorch', 'transformers', 'text-generation'],
pipeline_tag: 'text-generation',
createdAt: '2021-01-01T00:00:00Z',
last_modified: '2021-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'microsoft',
siblings: [
{
rfilename: 'model-q4_0.gguf',
size: 2 * 1024 * 1024 * 1024, // 2GB
blobId: 'blob123',
},
{
rfilename: 'model-q8_0.GGUF', // Test case-insensitive matching
size: 4 * 1024 * 1024 * 1024, // 4GB
blobId: 'blob456',
},
{
rfilename: 'tokenizer.json', // Non-GGUF file (should be filtered out)
size: 1024 * 1024, // 1MB
blobId: 'blob789',
},
],
}
it('should convert HuggingFace repo to catalog model format', () => {
const result = convertHfRepoToCatalogModel(mockHuggingFaceRepo)
const expected: CatalogModel = {
model_name: 'microsoft/DialoGPT-medium',
description: '**Tags**: pytorch, transformers, text-generation',
developer: 'microsoft',
downloads: 1500,
num_quants: 2,
quants: [
{
model_id: 'model-q4_0',
path: 'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/model-q4_0.gguf',
file_size: '2.0 GB',
},
{
model_id: 'model-q8_0',
path: 'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/model-q8_0.GGUF',
file_size: '4.0 GB',
},
],
num_mmproj: 0,
mmproj_models: [],
created_at: '2021-01-01T00:00:00Z',
readme:
'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/README.md',
}
expect(result).toEqual(expected)
})
it('should handle repository with no GGUF files', () => {
const repoWithoutGGUF: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: [
{
rfilename: 'tokenizer.json',
size: 1024 * 1024,
blobId: 'blob789',
},
{
rfilename: 'config.json',
size: 2048,
blobId: 'blob101',
},
],
}
const result = convertHfRepoToCatalogModel(repoWithoutGGUF)
expect(result.num_quants).toBe(0)
expect(result.quants).toEqual([])
})
it('should handle repository with no siblings', () => {
const repoWithoutSiblings: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: undefined,
}
const result = convertHfRepoToCatalogModel(repoWithoutSiblings)
expect(result.num_quants).toBe(0)
expect(result.quants).toEqual([])
})
it('should format file sizes correctly', () => {
const repoWithVariousFileSizes: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: [
{
rfilename: 'small-model.gguf',
size: 500 * 1024 * 1024, // 500MB
blobId: 'blob1',
},
{
rfilename: 'large-model.gguf',
size: 3.5 * 1024 * 1024 * 1024, // 3.5GB
blobId: 'blob2',
},
{
rfilename: 'unknown-size.gguf',
// No size property
blobId: 'blob3',
},
],
}
const result = convertHfRepoToCatalogModel(repoWithVariousFileSizes)
expect(result.quants[0].file_size).toBe('500.0 MB')
expect(result.quants[1].file_size).toBe('3.5 GB')
expect(result.quants[2].file_size).toBe('Unknown size')
})
it('should handle empty or undefined tags', () => {
const repoWithEmptyTags: HuggingFaceRepo = {
...mockHuggingFaceRepo,
tags: [],
}
const result = convertHfRepoToCatalogModel(repoWithEmptyTags)
expect(result.description).toBe('**Tags**: ')
})
it('should handle missing downloads count', () => {
const repoWithoutDownloads: HuggingFaceRepo = {
...mockHuggingFaceRepo,
downloads: undefined as any,
}
const result = convertHfRepoToCatalogModel(repoWithoutDownloads)
expect(result.downloads).toBe(0)
})
it('should correctly remove .gguf extension from model IDs', () => {
const repoWithVariousGGUF: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: [
{
rfilename: 'model.gguf',
size: 1024,
blobId: 'blob1',
},
{
rfilename: 'MODEL.GGUF',
size: 1024,
blobId: 'blob2',
},
{
rfilename: 'complex-model-name.gguf',
size: 1024,
blobId: 'blob3',
},
],
}
const result = convertHfRepoToCatalogModel(repoWithVariousGGUF)
expect(result.quants[0].model_id).toBe('model')
expect(result.quants[1].model_id).toBe('MODEL')
expect(result.quants[2].model_id).toBe('complex-model-name')
})
it('should generate correct download paths', () => {
const result = convertHfRepoToCatalogModel(mockHuggingFaceRepo)
expect(result.quants[0].path).toBe(
'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/model-q4_0.gguf'
)
expect(result.quants[1].path).toBe(
'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/model-q8_0.GGUF'
)
})
it('should generate correct readme URL', () => {
const result = convertHfRepoToCatalogModel(mockHuggingFaceRepo)
expect(result.readme).toBe(
'https://huggingface.co/microsoft/DialoGPT-medium/resolve/main/README.md'
)
})
it('should handle GGUF files with case-insensitive extension matching', () => {
const repoWithMixedCase: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: [
{
rfilename: 'model-1.gguf',
size: 1024,
blobId: 'blob1',
},
{
rfilename: 'model-2.GGUF',
size: 1024,
blobId: 'blob2',
},
{
rfilename: 'model-3.GgUf',
size: 1024,
blobId: 'blob3',
},
{
rfilename: 'not-a-model.txt',
size: 1024,
blobId: 'blob4',
},
],
}
const result = convertHfRepoToCatalogModel(repoWithMixedCase)
expect(result.num_quants).toBe(3)
expect(result.quants).toHaveLength(3)
expect(result.quants[0].model_id).toBe('model-1')
expect(result.quants[1].model_id).toBe('model-2')
expect(result.quants[2].model_id).toBe('model-3')
})
it('should handle edge cases with file size formatting', () => {
const repoWithEdgeCases: HuggingFaceRepo = {
...mockHuggingFaceRepo,
siblings: [
{
rfilename: 'tiny.gguf',
size: 512, // < 1MB
blobId: 'blob1',
},
{
rfilename: 'exactly-1gb.gguf',
size: 1024 * 1024 * 1024, // Exactly 1GB
blobId: 'blob2',
},
{
rfilename: 'zero-size.gguf',
size: 0,
blobId: 'blob3',
},
],
}
const result = convertHfRepoToCatalogModel(repoWithEdgeCases)
expect(result.quants[0].file_size).toBe('0.0 MB')
expect(result.quants[1].file_size).toBe('1.0 GB')
expect(result.quants[2].file_size).toBe('Unknown size') // 0 is falsy, so it returns 'Unknown size'
})
it('should handle missing optional fields gracefully', () => {
const minimalRepo: HuggingFaceRepo = {
id: 'minimal/repo',
modelId: 'minimal/repo',
sha: 'abc123',
downloads: 0,
likes: 0,
tags: [],
createdAt: '2021-01-01T00:00:00Z',
last_modified: '2021-12-01T00:00:00Z',
private: false,
disabled: false,
gated: false,
author: 'minimal',
siblings: [
{
rfilename: 'model.gguf',
blobId: 'blob1',
},
],
}
const result = convertHfRepoToCatalogModel(minimalRepo)
expect(result.model_name).toBe('minimal/repo')
expect(result.developer).toBe('minimal')
expect(result.downloads).toBe(0)
expect(result.description).toBe('**Tags**: ')
expect(result.quants[0].file_size).toBe('Unknown size')
})
})
})