root/goodbuddy
1
0
Fork 0
Code Issues Pull Requests Actions 3 Packages Projects Releases Wiki Activity

feat: add managed Granite embedding models

Browse Source 
GoodBuddy previously required an external OpenAI-compatible endpoint for vector retrieval. It can now install, verify, import, remove, and run the built-in Granite multilingual embedding model in an isolated local inference process, while retaining custom embedding connections and migrating existing settings.

The model connection UI now manages built-in and custom vector connections consistently, reports the actual retrieval path, preserves credentials across failed saves, and renders the vector tab synchronously. Related settings copy, switch styling, metadata typography, and renderer bundle guardrails are aligned with the resulting workflow.

Release note: 新增可管理的内置 Granite 多语言向量模型，支持本地下载、离线导入、连接切换与诊断；同时优化向量设置及相关界面的文案、开关和状态显示。
This commit is contained in:
mesalogo
2026-08-23 11:26:44 +08:00
parent 58d774ae0c
commit 076b3aaa7b
90 changed files with 7820 additions and 1446 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/renderer/src/SettingsPanel.tsx
+319 -141
View File
@@ -34,6 +34,7 @@ import type {
} from '../../shared/contracts'
import {
defaultContextCompressionSettings,
builtinEmbeddingConnectionId,
defaultModelProfileId as builtInDefaultModelProfileId,
defaultRuntimeSettings,
isAgentRuntimeModelProtocol,
@@ -46,7 +47,6 @@ import { ChannelSettingsSection } from './ChannelSettingsSection'
import { UpdateSettingsSection } from './UpdateSettingsSection'
import { PlatformFeaturesSettingsSection } from './PlatformFeaturesSettingsSection'
import { SpeechModelSettingsSection } from './SpeechModelSettingsSection'
import { EmbeddingSettingsSection } from './EmbeddingSettingsSection'
import { DocumentParsingSettingsSection } from './DocumentParsingSettingsSection'
import { DshMarketplaceSection } from './DshMarketplaceSection'
import {
@@ -66,8 +66,10 @@ import type { AppearanceTheme } from './theme'
import type { AppNotificationInput } from './notifications'
import type {
EmbeddingDiagnosticResult,
EmbeddingConfigurationSummary
EmbeddingModelSnapshot,
EmbeddingSettingsSnapshot
} from '../../shared/embedding-contracts'
import { EmbeddingSettingsSection } from './EmbeddingSettingsSection'
import { useUiLocale } from './i18n/UiLocaleProvider'
import type { GlobalShortcutSettingsSnapshot } from '../../shared/shortcut'
import { findPreferredCompatibleModelProfile } from './model-profile-selection'
@@ -81,6 +83,36 @@ type ModelProfileDraft = RuntimeSettings['modelProfiles'][number] & {
apiKey: string
clearApiKey: boolean
}
type EmbeddingConnectionDraft =
Omit<
Exclude<
NonNullable<RuntimeSettings['embeddingConnections']>[number],
{ kind: 'builtin' }
>,
'apiKey'
> & {
apiKey: string
clearApiKey: boolean
}
function toEmbeddingConnectionDrafts(
settings: RuntimeSettings
): EmbeddingConnectionDraft[] {
return (settings.embeddingConnections ?? [])
.filter(
(
connection
): connection is Exclude<
NonNullable<RuntimeSettings['embeddingConnections']>[number],
{ kind: 'builtin' }
> => connection.kind === 'openai-compatible'
)
.map((connection) => ({
...connection,
apiKey: '',
clearApiKey: false
}))
}
const settingsTabs = settingsCategoryList.map(({ id }) => id)
const contextCompressionTokenScale = 1_000
@@ -276,6 +308,8 @@ function hydrateRuntimeSettings(
knowledgeEmbeddingModel: (value: string) => void
knowledgeEmbeddingApiKey: (value: string) => void
clearKnowledgeEmbeddingApiKey: (value: boolean) => void
embeddingConnections: (value: EmbeddingConnectionDraft[]) => void
activeEmbeddingConnectionId: (value: string) => void
knowledgeRerankEnabled: (value: boolean) => void
knowledgeRerankEndpoint: (value: string) => void
knowledgeRerankModel: (value: string) => void
@@ -324,6 +358,10 @@ function hydrateRuntimeSettings(
setters.knowledgeEmbeddingModel(value.knowledgeEmbeddingModel)
setters.knowledgeEmbeddingApiKey('')
setters.clearKnowledgeEmbeddingApiKey(false)
setters.embeddingConnections(toEmbeddingConnectionDrafts(value))
setters.activeEmbeddingConnectionId(
value.activeEmbeddingConnectionId ?? builtinEmbeddingConnectionId
)
setters.knowledgeRerankEnabled(
value.knowledgeRerankEnabled ??
defaultRuntimeSettings.knowledgeRerankEnabled
@@ -600,6 +638,15 @@ export function SettingsPanel({
clearKnowledgeEmbeddingApiKey,
setClearKnowledgeEmbeddingApiKey
] = useState(false)
const [embeddingConnections, setEmbeddingConnections] = useState<
EmbeddingConnectionDraft[]
>([])
const [
activeEmbeddingConnectionId,
setActiveEmbeddingConnectionId
] = useState(builtinEmbeddingConnectionId)
const [editingEmbeddingConnectionId, setEditingEmbeddingConnectionId] =
useState<string>()
const [knowledgeRerankEnabled, setKnowledgeRerankEnabled] =
useState<boolean>(defaultRuntimeSettings.knowledgeRerankEnabled)
const [knowledgeRerankEndpoint, setKnowledgeRerankEndpoint] =
@@ -642,12 +689,16 @@ export function SettingsPanel({
: profile.name
const [saving, setSaving] = useState(false)
const [testing, setTesting] = useState(false)
const [embeddingConfiguration, setEmbeddingConfiguration] =
useState<EmbeddingConfigurationSummary>()
const [embeddingSnapshot, setEmbeddingSnapshot] =
useState<EmbeddingSettingsSnapshot>()
const [embeddingModels, setEmbeddingModels] =
useState<EmbeddingModelSnapshot>()
const [embeddingDiagnostic, setEmbeddingDiagnostic] =
useState<EmbeddingDiagnosticResult>()
const [embeddingDiagnosticRunning, setEmbeddingDiagnosticRunning] =
useState(false)
const [embeddingModelActionRunning, setEmbeddingModelActionRunning] =
useState(false)
const [error, setError] = useState<string>()
const [confirmingClear, setConfirmingClear] = useState(false)
const [clearingLocalData, setClearingLocalData] = useState(false)
@@ -721,6 +772,9 @@ export function SettingsPanel({
knowledgeEmbeddingModel: setKnowledgeEmbeddingModel,
knowledgeEmbeddingApiKey: setKnowledgeEmbeddingApiKey,
clearKnowledgeEmbeddingApiKey: setClearKnowledgeEmbeddingApiKey,
embeddingConnections: setEmbeddingConnections,
activeEmbeddingConnectionId:
setActiveEmbeddingConnectionId,
knowledgeRerankEnabled: setKnowledgeRerankEnabled,
knowledgeRerankEndpoint: setKnowledgeRerankEndpoint,
knowledgeRerankModel: setKnowledgeRerankModel,
@@ -779,6 +833,8 @@ export function SettingsPanel({
knowledgeEmbeddingModel,
knowledgeEmbeddingApiKey,
clearKnowledgeEmbeddingApiKey,
embeddingConnections,
activeEmbeddingConnectionId,
knowledgeRerankEnabled,
knowledgeRerankEndpoint,
knowledgeRerankModel,
@@ -819,6 +875,10 @@ export function SettingsPanel({
knowledgeEmbeddingModel: settings.knowledgeEmbeddingModel,
knowledgeEmbeddingApiKey: '',
clearKnowledgeEmbeddingApiKey: false,
embeddingConnections: toEmbeddingConnectionDrafts(settings),
activeEmbeddingConnectionId:
settings.activeEmbeddingConnectionId ??
builtinEmbeddingConnectionId,
knowledgeRerankEnabled:
settings.knowledgeRerankEnabled ??
defaultRuntimeSettings.knowledgeRerankEnabled,
@@ -981,7 +1041,8 @@ export function SettingsPanel({
.then((snapshot) => {
if (active) {
setEmbeddingDiagnostic(undefined)
setEmbeddingConfiguration(snapshot.configuration)
setEmbeddingSnapshot(snapshot)
setEmbeddingModels(snapshot.models)
}
})
.catch((reason: unknown) => {
@@ -1001,6 +1062,27 @@ export function SettingsPanel({
}
}, [i18n, open])
useEffect(() => {
const embeddings = window.goodbuddy.embeddings
if (
!open ||
!embeddings ||
!embeddingModels?.operations.length
) {
return
}
const timer = window.setInterval(() => {
void embeddings.getSnapshot().then(
(snapshot) => {
setEmbeddingSnapshot(snapshot)
setEmbeddingModels(snapshot.models)
},
() => undefined
)
}, 300)
return () => window.clearInterval(timer)
}, [embeddingModels?.operations.length, open])
const normalizedContextCompression =
normalizeContextCompressionTokenDrafts(
contextCompression,
@@ -1035,6 +1117,14 @@ export function SettingsPanel({
)
setKnowledgeEmbeddingApiKey('')
setClearKnowledgeEmbeddingApiKey(false)
setEmbeddingConnections((connections) =>
connections.map((connection) => ({
...connection,
apiKey: '',
clearApiKey: false
}))
)
setEditingEmbeddingConnectionId(undefined)
setKnowledgeRerankApiKey('')
setClearKnowledgeRerankApiKey(false)
setSpeechModelDraftId(undefined)
@@ -1187,6 +1277,31 @@ export function SettingsPanel({
value: knowledgeEmbeddingApiKey.trim()
}
: { action: 'keep' },
embeddingConnections: [
{
id: builtinEmbeddingConnectionId,
name: 'GoodBuddy 内置向量模型',
kind: 'builtin'
},
...embeddingConnections.map((connection) => ({
id: connection.id,
name: connection.name,
kind: connection.kind,
baseUrl: connection.baseUrl,
modelName: connection.modelName,
authentication: connection.authentication,
apiKey: connection.clearApiKey
? ({ action: 'clear' } as const)
: connection.authentication === 'api-key' &&
connection.apiKey.trim()
? ({
action: 'replace',
value: connection.apiKey.trim()
} as const)
: ({ action: 'keep' } as const)
}))
],
activeEmbeddingConnectionId,
knowledgeRerankEnabled,
knowledgeRerankEndpoint,
knowledgeRerankModel,
@@ -1231,9 +1346,9 @@ export function SettingsPanel({
const embeddings = window.goodbuddy.embeddings
if (embeddings) {
try {
setEmbeddingConfiguration(
(await embeddings.getSnapshot()).configuration
)
const snapshot = await embeddings.getSnapshot()
setEmbeddingSnapshot(snapshot)
setEmbeddingModels(snapshot.models)
} catch (reason) {
setError(
settingsErrorMessage(
@@ -1325,7 +1440,9 @@ export function SettingsPanel({
}
}
const runEmbeddingDiagnostic = async (): Promise<void> => {
const runEmbeddingDiagnostic = async (
connectionId: string
): Promise<void> => {
const embeddings = window.goodbuddy.embeddings
if (!embeddings) {
setError(t('errors.embeddingDiagnosticUnavailable'))
@@ -1338,11 +1455,11 @@ export function SettingsPanel({
if (!(await save(false))) {
return
}
const diagnostic = await embeddings.diagnose()
const diagnostic = await embeddings.diagnose(connectionId)
setEmbeddingDiagnostic(diagnostic)
setEmbeddingConfiguration(
(await embeddings.getSnapshot()).configuration
)
const snapshot = await embeddings.getSnapshot()
setEmbeddingSnapshot(snapshot)
setEmbeddingModels(snapshot.models)
} catch (reason) {
setError(settingsErrorMessage(reason, t('errors.testEmbedding')))
} finally {
@@ -1350,6 +1467,51 @@ export function SettingsPanel({
}
}
const runEmbeddingModelOperation = async (
operation: (
api: NonNullable<typeof window.goodbuddy.embeddings>
) => Promise<EmbeddingModelSnapshot | undefined>
): Promise<void> => {
const embeddings = window.goodbuddy.embeddings
if (!embeddings) {
setError(t('errors.embeddingDiagnosticUnavailable'))
return
}
setEmbeddingModelActionRunning(true)
setError(undefined)
try {
const models = await operation(embeddings)
if (models) {
setEmbeddingModels(models)
const snapshot = await embeddings.getSnapshot()
setEmbeddingSnapshot(snapshot)
}
} catch (reason) {
setError(settingsErrorMessage(reason, t('errors.saveSettings')))
} finally {
setEmbeddingModelActionRunning(false)
}
}
const cancelEmbeddingModelOperation = async (
modelId: string
): Promise<void> => {
const embeddings = window.goodbuddy.embeddings
if (!embeddings) {
setError(t('errors.embeddingDiagnosticUnavailable'))
return
}
setError(undefined)
try {
await embeddings.cancelModelOperation(modelId)
const snapshot = await embeddings.getSnapshot()
setEmbeddingSnapshot(snapshot)
setEmbeddingModels(snapshot.models)
} catch (reason) {
setError(settingsErrorMessage(reason, t('errors.saveSettings')))
}
}
const selectRuntimeFile = async (
kind: RuntimeFileSelectionKind,
setValue: (value: string) => void
@@ -1633,8 +1795,6 @@ export function SettingsPanel({
<X aria-hidden="true" size={19} />
</button>
}
description={t('center.description')}
eyebrow={t('center.eyebrow')}
headingId="settings-title"
title={t('center.title')}
/>
@@ -1670,11 +1830,6 @@ export function SettingsPanel({
<strong>
{t(`categories.${category.translationKey}.label`)}
</strong>
<small>
{t(
`categories.${category.translationKey}.navigationDescription`
)}
</small>
</button>
))}
</nav>
@@ -1974,9 +2129,6 @@ export function SettingsPanel({
</div>
<details className="settings-section">
<summary>{t('runtime.advanced')}</summary>
<p className="settings-panel__description">
{t('runtime.opencode.advancedDescription')}
</p>
<fieldset className="runtime-source-options">
<legend>{t('runtime.sourceLegend')}</legend>
<label>
@@ -2205,9 +2357,6 @@ export function SettingsPanel({
</div>
<details className="settings-section">
<summary>{t('runtime.advanced')}</summary>
<p className="settings-panel__description">
{t('runtime.continue.advancedDescription')}
</p>
<fieldset className="runtime-source-options">
<legend>{t('runtime.sourceLegend')}</legend>
<label>
@@ -2508,15 +2657,6 @@ export function SettingsPanel({
]}
value={modelType}
/>
<small>
{modelType === 'llm'
? t('model.types.llm.description')
: modelType === 'embedding'
? t('model.types.embedding.description')
: modelType === 'rerank'
? t('model.types.rerank.description')
: t('model.types.speech.description')}
</small>
</div>
{modelType === 'llm' && (
<div className="settings-section">
@@ -2963,115 +3103,153 @@ export function SettingsPanel({
</div>
)}
{modelType === 'embedding' && (
<div className="settings-section">
<div className="settings-section__title">
<KeyRound size={17} />
<div>
<strong>{t('model.embedding.title')}</strong>
<small>{t('model.embedding.description')}</small>
</div>
</div>
<div className="runtime-note model-service-form">
<label className="toggle-row">
<input
checked={knowledgeEmbeddingEnabled}
onChange={(event) =>
setKnowledgeEmbeddingEnabled(event.target.checked)
}
role="switch"
type="checkbox"
/>
<span>{t('model.embedding.enabled')}</span>
</label>
<label className="field">
<span>{t('model.embedding.endpoint')}</span>
<input
aria-label={t('model.embedding.endpoint')}
disabled={!knowledgeEmbeddingEnabled}
inputMode="url"
onChange={(event) =>
setKnowledgeEmbeddingBaseUrl(event.target.value)
}
placeholder="https://provider.example/v1/embeddings"
value={knowledgeEmbeddingBaseUrl}
/>
<small>
{t('model.embedding.endpointDescription')}
</small>
</label>
<label className="field">
<span>{t('model.embedding.modelName')}</span>
<input
aria-label={t('model.embedding.modelName')}
disabled={!knowledgeEmbeddingEnabled}
onChange={(event) =>
setKnowledgeEmbeddingModel(event.target.value)
}
value={knowledgeEmbeddingModel}
/>
</label>
<label className="field">
<span>{t('model.embedding.optionalApiKey')}</span>
<input
aria-label={t('model.embedding.optionalApiKey')}
autoComplete="off"
disabled={
!knowledgeEmbeddingEnabled ||
settings?.knowledgeEmbeddingCredentialSource ===
'environment' ||
!settings?.secureStorageAvailable
}
onChange={(event) => {
setKnowledgeEmbeddingApiKey(event.target.value)
setClearKnowledgeEmbeddingApiKey(false)
}}
placeholder={
settings?.knowledgeEmbeddingApiKeyConfigured
? t('credentials.configuredPlaceholder')
: t('model.embedding.optionalApiKeyPlaceholder')
}
type="password"
value={knowledgeEmbeddingApiKey}
/>
</label>
<div className="credential-state">
<LockKeyhole size={15} />
<span>
{settings
? t(
`credentials.${settings.knowledgeEmbeddingCredentialSource}`
)
: t('credentials.none')}
</span>
{settings?.knowledgeEmbeddingCredentialSource ===
'encrypted' && (
<button
onClick={() => {
setKnowledgeEmbeddingApiKey('')
setClearKnowledgeEmbeddingApiKey(true)
}}
type="button"
>
{clearKnowledgeEmbeddingApiKey
? t('actions.clearAfterSave')
: t('actions.clearCredential')}
</button>
)}
</div>
<small>
{t('model.embedding.privacyDescription')}
</small>
</div>
</div>
)}
{modelType === 'embedding' && embeddingConfiguration && (
<EmbeddingSettingsSection
configuration={embeddingConfiguration}
connections={[
...(embeddingSnapshot?.connections ?? [])
.filter((connection) => connection.kind === 'builtin')
.map((connection) => {
const installed = embeddingModels?.installed.some(
(candidate) => candidate.id === connection.model
)
const operation = embeddingModels?.operations.find(
(candidate) =>
candidate.modelId === connection.model
)
const progress =
operation?.totalBytes &&
Math.round(
(operation.completedBytes /
operation.totalBytes) *
100
)
return {
...connection,
installed,
operationActive: Boolean(operation),
statusText: operation
? t('model.embedding.progress', {
percent: progress ?? 0
})
: installed
? t('model.embedding.installed')
: t('model.embedding.notInstalled')
}
}),
...embeddingConnections.map((connection) => ({
...connection,
model: connection.modelName,
endpoint: connection.baseUrl
}))
]}
currentConnectionId={activeEmbeddingConnectionId}
diagnostic={embeddingDiagnostic}
diagnosticRunning={embeddingDiagnosticRunning}
disabled={saving || !knowledgeEmbeddingEnabled}
onTest={() => {
void runEmbeddingDiagnostic()
enabled={knowledgeEmbeddingEnabled}
busy={saving || embeddingModelActionRunning}
secureStorageAvailable={
settings?.secureStorageAvailable ?? false
}
selectedConnectionId={editingEmbeddingConnectionId}
onAddConnection={() => {
const id = crypto.randomUUID()
setEmbeddingConnections((connections) => [
...connections,
{
id,
name: t('model.embedding.newConnectionName'),
kind: 'openai-compatible',
baseUrl:
'https://provider.example/v1/embeddings',
modelName: 'text-embedding-3-small',
authentication: 'api-key',
apiKeyConfigured: false,
credentialSource: 'none',
apiKey: '',
clearApiKey: false
}
])
setEditingEmbeddingConnectionId(id)
}}
onCancelBuiltin={(modelId) => {
void cancelEmbeddingModelOperation(modelId)
}}
onDeleteConnection={(connectionId) => {
setEmbeddingConnections((connections) =>
connections.filter(
(connection) => connection.id !== connectionId
)
)
if (activeEmbeddingConnectionId === connectionId) {
setActiveEmbeddingConnectionId(
builtinEmbeddingConnectionId
)
}
setEditingEmbeddingConnectionId(
builtinEmbeddingConnectionId
)
}}
onDownloadBuiltin={(modelId) => {
const model = embeddingModels?.catalog.find(
(candidate) => candidate.id === modelId
)
if (model && embeddingModels) {
void runEmbeddingModelOperation((api) =>
api.installModel(
model.id,
embeddingModels.selectedDownloadSource
)
)
}
}}
onEnabledChange={setKnowledgeEmbeddingEnabled}
onImportBuiltin={(modelId) => {
void runEmbeddingModelOperation((api) =>
api.importModelArchive(modelId)
)
}}
onRemoveBuiltin={(modelId) => {
void runEmbeddingModelOperation((api) =>
api.removeModel(modelId)
)
}}
onSelectConnection={setEditingEmbeddingConnectionId}
onSetCurrent={setActiveEmbeddingConnectionId}
onTestConnection={(connectionId) => {
void runEmbeddingDiagnostic(connectionId)
}}
onUpdateConnection={(connectionId, changes) => {
setEmbeddingConnections((connections) =>
connections.map((connection) =>
connection.id === connectionId
? {
...connection,
...(changes.name === undefined
? {}
: { name: changes.name }),
...(changes.endpoint === undefined
? {}
: { baseUrl: changes.endpoint }),
...(changes.model === undefined
? {}
: { modelName: changes.model }),
...(changes.authentication === undefined
? {}
: {
authentication:
changes.authentication
}),
...(changes.apiKey === undefined
? {}
: { apiKey: changes.apiKey }),
...(changes.clearApiKey === undefined
? {}
: {
clearApiKey: changes.clearApiKey
})
}
: connection
)
)
}}
/>
)}