Dinh Long Nguyen a30eb7f968
feat: Jan Web (reusing Jan Desktop UI) (#6298)
* add platform guards

* add service management

* fix types

* move to zustand for servicehub

* update App Updater

* update tauri missing move

* update app updater

* refactor: move PlatformFeatures to separate const file

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* change tauri fetch name

* update implementation

* update extension fetch

* make web version run properly

* disabled unused web settings

* fix all tests

* fix lint

* fix tests

* add mock for extension

* fix build

* update make and mise

* fix tsconfig for web-extensions

* fix loader type

* cleanup

* fix test

* update error handling + mcp should be working

* Update mcp init

* use separate is_web_app build property

* Remove fixed model catalog url

* fix additional tests

* fix download issue (event emitter not implemented correctly)

* Update Title html

* fix app logs

* update root tsx render timing

---------

Co-authored-by: Claude <noreply@anthropic.com>
2025-09-05 01:47:46 +07:00

451 lines
14 KiB
TypeScript

/**
* Default Models Service - Web implementation
*/
import { sanitizeModelId } from '@/lib/utils'
import {
AIEngine,
EngineManager,
SessionInfo,
SettingComponentProps,
modelInfo,
} from '@janhq/core'
import { Model as CoreModel } from '@janhq/core'
import type { ModelsService, ModelCatalog, HuggingFaceRepo, CatalogModel } from './types'
// TODO: Replace this with the actual provider later
const defaultProvider = 'llamacpp'
export class DefaultModelsService implements ModelsService {
private getEngine(provider: string = defaultProvider) {
return EngineManager.instance().get(provider) as AIEngine | undefined
}
async fetchModels(): Promise<modelInfo[]> {
return this.getEngine()?.list() ?? []
}
async fetchModelCatalog(): Promise<ModelCatalog> {
try {
const response = await fetch(MODEL_CATALOG_URL)
if (!response.ok) {
throw new Error(
`Failed to fetch model catalog: ${response.status} ${response.statusText}`
)
}
const catalog: ModelCatalog = await response.json()
return catalog
} catch (error) {
console.error('Error fetching model catalog:', error)
throw new Error(
`Failed to fetch model catalog: ${error instanceof Error ? error.message : 'Unknown error'}`
)
}
}
async fetchHuggingFaceRepo(
repoId: string,
hfToken?: string
): Promise<HuggingFaceRepo | null> {
try {
// Clean the repo ID to handle various input formats
const cleanRepoId = repoId
.replace(/^https?:\/\/huggingface\.co\//, '')
.replace(/^huggingface\.co\//, '')
.replace(/\/$/, '') // Remove trailing slash
.trim()
if (!cleanRepoId || !cleanRepoId.includes('/')) {
return null
}
const response = await fetch(
`https://huggingface.co/api/models/${cleanRepoId}?blobs=true&files_metadata=true`,
{
headers: hfToken
? {
Authorization: `Bearer ${hfToken}`,
}
: {},
}
)
if (!response.ok) {
if (response.status === 404) {
return null // Repository not found
}
throw new Error(
`Failed to fetch HuggingFace repository: ${response.status} ${response.statusText}`
)
}
const repoData = await response.json()
return repoData
} catch (error) {
console.error('Error fetching HuggingFace repository:', error)
return null
}
}
convertHfRepoToCatalogModel(repo: HuggingFaceRepo): CatalogModel {
// Format file size helper
const formatFileSize = (size?: number) => {
if (!size) return 'Unknown size'
if (size < 1024 ** 3) return `${(size / 1024 ** 2).toFixed(1)} MB`
return `${(size / 1024 ** 3).toFixed(1)} GB`
}
// Extract GGUF files from the repository siblings
const ggufFiles =
repo.siblings?.filter((file) =>
file.rfilename.toLowerCase().endsWith('.gguf')
) || []
// Separate regular GGUF files from mmproj files
const regularGgufFiles = ggufFiles.filter(
(file) => !file.rfilename.toLowerCase().includes('mmproj')
)
const mmprojFiles = ggufFiles.filter((file) =>
file.rfilename.toLowerCase().includes('mmproj')
)
// Convert regular GGUF files to quants format
const quants = regularGgufFiles.map((file) => {
// Generate model_id from filename (remove .gguf extension, case-insensitive)
const modelId = file.rfilename.replace(/\.gguf$/i, '')
return {
model_id: sanitizeModelId(modelId),
path: `https://huggingface.co/${repo.modelId}/resolve/main/${file.rfilename}`,
file_size: formatFileSize(file.size),
}
})
// Convert mmproj files to mmproj_models format
const mmprojModels = mmprojFiles.map((file) => {
const modelId = file.rfilename.replace(/\.gguf$/i, '')
return {
model_id: sanitizeModelId(modelId),
path: `https://huggingface.co/${repo.modelId}/resolve/main/${file.rfilename}`,
file_size: formatFileSize(file.size),
}
})
return {
model_name: repo.modelId,
developer: repo.author,
downloads: repo.downloads || 0,
created_at: repo.createdAt,
num_quants: quants.length,
quants: quants,
num_mmproj: mmprojModels.length,
mmproj_models: mmprojModels,
readme: `https://huggingface.co/${repo.modelId}/resolve/main/README.md`,
description: `**Tags**: ${repo.tags?.join(', ')}`,
}
}
async updateModel(model: Partial<CoreModel>): Promise<void> {
if (model.settings)
this.getEngine()?.updateSettings(model.settings as SettingComponentProps[])
}
async pullModel(
id: string,
modelPath: string,
modelSha256?: string,
modelSize?: number,
mmprojPath?: string,
mmprojSha256?: string,
mmprojSize?: number
): Promise<void> {
return this.getEngine()?.import(id, {
modelPath,
mmprojPath,
modelSha256,
modelSize,
mmprojSha256,
mmprojSize,
})
}
async pullModelWithMetadata(
id: string,
modelPath: string,
mmprojPath?: string,
hfToken?: string
): Promise<void> {
let modelSha256: string | undefined
let modelSize: number | undefined
let mmprojSha256: string | undefined
let mmprojSize: number | undefined
// Extract repo ID from model URL
// URL format: https://huggingface.co/{repo}/resolve/main/{filename}
const modelUrlMatch = modelPath.match(
/https:\/\/huggingface\.co\/([^/]+\/[^/]+)\/resolve\/main\/(.+)/
)
if (modelUrlMatch) {
const [, repoId, modelFilename] = modelUrlMatch
try {
// Fetch real-time metadata from HuggingFace
const repoInfo = await this.fetchHuggingFaceRepo(repoId, hfToken)
if (repoInfo?.siblings) {
// Find the specific model file
const modelFile = repoInfo.siblings.find(
(file) => file.rfilename === modelFilename
)
if (modelFile?.lfs) {
modelSha256 = modelFile.lfs.sha256
modelSize = modelFile.lfs.size
}
// If mmproj path provided, extract its metadata too
if (mmprojPath) {
const mmprojUrlMatch = mmprojPath.match(
/https:\/\/huggingface\.co\/[^/]+\/[^/]+\/resolve\/main\/(.+)/
)
if (mmprojUrlMatch) {
const [, mmprojFilename] = mmprojUrlMatch
const mmprojFile = repoInfo.siblings.find(
(file) => file.rfilename === mmprojFilename
)
if (mmprojFile?.lfs) {
mmprojSha256 = mmprojFile.lfs.sha256
mmprojSize = mmprojFile.lfs.size
}
}
}
}
} catch (error) {
console.warn(
'Failed to fetch HuggingFace metadata, proceeding without hash verification:',
error
)
// Continue with download even if metadata fetch fails
}
}
// Call the original pullModel with the fetched metadata
return this.pullModel(
id,
modelPath,
modelSha256,
modelSize,
mmprojPath,
mmprojSha256,
mmprojSize
)
}
async abortDownload(id: string): Promise<void> {
return this.getEngine()?.abortImport(id)
}
async deleteModel(id: string): Promise<void> {
return this.getEngine()?.delete(id)
}
async getActiveModels(provider?: string): Promise<string[]> {
return this.getEngine(provider)?.getLoadedModels() ?? []
}
async stopModel(model: string, provider?: string): Promise<void> {
this.getEngine(provider)?.unload(model)
}
async stopAllModels(): Promise<void> {
const models = await this.getActiveModels()
if (models) await Promise.all(models.map((model) => this.stopModel(model)))
}
async startModel(provider: ProviderObject, model: string): Promise<SessionInfo | undefined> {
const engine = this.getEngine(provider.provider)
if (!engine) return undefined
const loadedModels = await engine.getLoadedModels()
if (loadedModels.includes(model)) return undefined
// Find the model configuration to get settings
const modelConfig = provider.models.find((m) => m.id === model)
// Key mapping function to transform setting keys
const mapSettingKey = (key: string): string => {
const keyMappings: Record<string, string> = {
ctx_len: 'ctx_size',
ngl: 'n_gpu_layers',
}
return keyMappings[key] || key
}
const settings = modelConfig?.settings
? Object.fromEntries(
Object.entries(modelConfig.settings).map(([key, value]) => [
mapSettingKey(key),
value.controller_props?.value,
])
)
: undefined
return engine.load(model, settings).catch((error) => {
console.error(
`Failed to start model ${model} for provider ${provider.provider}:`,
error
)
throw error
})
}
async isToolSupported(modelId: string): Promise<boolean> {
const engine = this.getEngine()
if (!engine) return false
return engine.isToolSupported(modelId)
}
async checkMmprojExistsAndUpdateOffloadMMprojSetting(
modelId: string,
updateProvider?: (providerName: string, data: Partial<ModelProvider>) => void,
getProviderByName?: (providerName: string) => ModelProvider | undefined
): Promise<{ exists: boolean; settingsUpdated: boolean }> {
let settingsUpdated = false
try {
const engine = this.getEngine('llamacpp') as AIEngine & {
checkMmprojExists?: (id: string) => Promise<boolean>
}
if (engine && typeof engine.checkMmprojExists === 'function') {
const exists = await engine.checkMmprojExists(modelId)
// If we have the store functions, use them; otherwise fall back to localStorage
if (updateProvider && getProviderByName) {
const provider = getProviderByName('llamacpp')
if (provider) {
const model = provider.models.find((m) => m.id === modelId)
if (model?.settings) {
const hasOffloadMmproj = 'offload_mmproj' in model.settings
// If mmproj exists, add offload_mmproj setting (only if it doesn't exist)
if (exists && !hasOffloadMmproj) {
// Create updated models array with the new setting
const updatedModels = provider.models.map((m) => {
if (m.id === modelId) {
return {
...m,
settings: {
...m.settings,
offload_mmproj: {
key: 'offload_mmproj',
title: 'Offload MMProj',
description:
'Offload multimodal projection model to GPU',
controller_type: 'checkbox',
controller_props: {
value: true,
},
},
},
}
}
return m
})
// Update the provider with the new models array
updateProvider('llamacpp', { models: updatedModels })
settingsUpdated = true
}
}
}
} else {
// Fall back to localStorage approach for backwards compatibility
try {
const modelProviderData = JSON.parse(
localStorage.getItem('model-provider') || '{}'
)
const llamacppProvider = modelProviderData.state?.providers?.find(
(p: { provider: string }) => p.provider === 'llamacpp'
)
const model = llamacppProvider?.models?.find(
(m: { id: string; settings?: Record<string, unknown> }) => m.id === modelId
)
if (model?.settings) {
// If mmproj exists, add offload_mmproj setting (only if it doesn't exist)
if (exists) {
if (!model.settings.offload_mmproj) {
model.settings.offload_mmproj = {
key: 'offload_mmproj',
title: 'Offload MMProj',
description: 'Offload multimodal projection layers to GPU',
controller_type: 'checkbox',
controller_props: {
value: true,
},
}
// Save updated settings back to localStorage
localStorage.setItem(
'model-provider',
JSON.stringify(modelProviderData)
)
settingsUpdated = true
}
}
}
} catch (localStorageError) {
console.error(
`Error checking localStorage for model ${modelId}:`,
localStorageError
)
}
}
return { exists, settingsUpdated }
}
} catch (error) {
console.error(`Error checking mmproj for model ${modelId}:`, error)
}
return { exists: false, settingsUpdated }
}
async checkMmprojExists(modelId: string): Promise<boolean> {
try {
const engine = this.getEngine('llamacpp') as AIEngine & {
checkMmprojExists?: (id: string) => Promise<boolean>
}
if (engine && typeof engine.checkMmprojExists === 'function') {
return await engine.checkMmprojExists(modelId)
}
} catch (error) {
console.error(`Error checking mmproj for model ${modelId}:`, error)
}
return false
}
async isModelSupported(modelPath: string, ctxSize?: number): Promise<'RED' | 'YELLOW' | 'GREEN' | 'GREY'> {
try {
const engine = this.getEngine('llamacpp') as AIEngine & {
isModelSupported?: (
path: string,
ctx_size?: number
) => Promise<'RED' | 'YELLOW' | 'GREEN'>
}
if (engine && typeof engine.isModelSupported === 'function') {
return await engine.isModelSupported(modelPath, ctxSize)
}
// Fallback if method is not available
console.warn('isModelSupported method not available in llamacpp engine')
return 'YELLOW' // Conservative fallback
} catch (error) {
console.error(`Error checking model support for ${modelPath}:`, error)
return 'GREY' // Error state, assume not supported
}
}
}