feat: enhance local knowledge retrieval
This commit is contained in:
lofyer
+135
-25
@@ -13,7 +13,7 @@ import type {
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} from './capability-contracts'
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import {
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assistantIdSchema,
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workModeSchema,
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legacyWorkModeSchema,
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type AssistantProject,
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type AssistantArtifact,
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type AssistantMemory,
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@@ -73,8 +73,8 @@ import type {
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} from './speech-model-contracts'
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import type {
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EmbeddingDiagnosticResult,
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EmbeddingIndexStatus,
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EmbeddingSettingsSnapshot
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EmbeddingSettingsSnapshot,
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KnowledgeEmbeddingIndexSnapshot
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} from './embedding-contracts'
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import type {
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DocumentOcrAssets,
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@@ -85,6 +85,34 @@ import type {
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DocumentParsingSettings,
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DocumentParsingSnapshot
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} from './document-parsing-contracts'
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import type {
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KnowledgeChunkDeleteInput,
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KnowledgeChunkPage,
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KnowledgeChunkUpdateInput,
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KnowledgeChunksListInput,
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KnowledgeDocumentRebuildInput,
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KnowledgeLibraryRebuildInput,
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KnowledgeReferenceContext,
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KnowledgeReferenceContextInput,
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KnowledgeReferenceOpenInput,
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KnowledgeRetrievalResponse,
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KnowledgeRetrievalSettings,
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KnowledgeRetrieveInput,
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KnowledgeSettingsUpdateInput,
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KnowledgeChunkingSettings
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} from './knowledge-contracts'
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import type { KnowledgeOntologySettings } from './knowledge-ontology'
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import type {
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KnowledgeTaskItem
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} from './knowledge-task-contracts'
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export type {
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KnowledgeTaskError,
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KnowledgeTaskItem,
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KnowledgeTaskKind,
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KnowledgeTaskScope,
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KnowledgeTaskStage,
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KnowledgeTaskStatus
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} from './knowledge-task-contracts'
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import type { WeixinBindingSnapshot } from './weixin-channel-contracts'
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import type { RemoteChannelActivity } from './remote-channel-contracts'
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import {
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@@ -148,6 +176,11 @@ export type AgentQuestionAnswer = z.infer<
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export const conversationIdSchema = z.string().min(1).max(128)
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export const knowledgeRetrievalModeSchema = z.enum(['auto', 'always'])
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export type KnowledgeRetrievalMode = z.infer<
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typeof knowledgeRetrievalModeSchema
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>
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export const agentRequestSchema = z
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.object({
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requestId: z.string().uuid(),
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@@ -157,12 +190,13 @@ export const agentRequestSchema = z
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teamMode: z.boolean().optional(),
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smartRouting: z.boolean().optional(),
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runtimeSelection: agentRuntimeSelectionSchema.optional(),
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workMode: workModeSchema.optional(),
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workMode: legacyWorkModeSchema.optional(),
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prompt: z.string().trim().min(1).max(100_000),
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knowledgeLibraryIds: z
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.array(z.string().uuid())
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.max(20)
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.default([]),
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knowledgeRetrievalMode: knowledgeRetrievalModeSchema.default('auto'),
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contextIds: z.array(z.string().uuid()).max(8).optional(),
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history: z
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.array(
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@@ -260,6 +294,9 @@ export const defaultRuntimeSettings = {
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knowledgeEmbeddingBaseUrl:
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'http://127.0.0.1:11434/v1/embeddings',
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knowledgeEmbeddingModel: 'nomic-embed-text',
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knowledgeRerankEnabled: false,
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knowledgeRerankEndpoint: 'https://api.cohere.com/v1/rerank',
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knowledgeRerankModel: 'rerank-v3.5',
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workspacePath: '',
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toolApproval: 'always'
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} as const
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@@ -386,6 +423,15 @@ export const runtimeSettingsInputSchema = z
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.max(256)
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.regex(/^[\w./:-]+$/, '向量模型名称包含不支持的字符'),
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knowledgeEmbeddingApiKey: modelApiKeyUpdateSchema.optional(),
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knowledgeRerankEnabled: z.boolean(),
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knowledgeRerankEndpoint: z.string().url().max(2_048),
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knowledgeRerankModel: z
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.string()
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.trim()
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.min(1)
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.max(256)
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.regex(/^[\w./:-]+$/, '重排模型名称包含不支持的字符'),
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knowledgeRerankApiKey: modelApiKeyUpdateSchema.optional(),
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workspacePath: z.string().trim().min(1).max(4_096),
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apiKey: modelApiKeyUpdateSchema,
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modelProfiles: z.array(modelProfileInputSchema).min(1).max(20).optional(),
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@@ -527,6 +573,17 @@ export const runtimeSettingsInputSchema = z
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message: '向量接口 URL 必须使用 HTTP 或 HTTPS'
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})
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}
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if (
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!['http:', 'https:'].includes(
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new URL(settings.knowledgeRerankEndpoint).protocol
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)
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) {
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context.addIssue({
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code: 'custom',
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path: ['knowledgeRerankEndpoint'],
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message: '重排接口 URL 必须使用 HTTP 或 HTTPS'
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})
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}
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})
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export type RuntimeSettingsInput = z.infer<typeof runtimeSettingsInputSchema>
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@@ -568,6 +625,11 @@ export type RuntimeSettings = {
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knowledgeEmbeddingModel: string
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knowledgeEmbeddingApiKeyConfigured: boolean
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knowledgeEmbeddingCredentialSource: 'none' | 'encrypted' | 'environment'
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knowledgeRerankEnabled?: boolean
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knowledgeRerankEndpoint?: string
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knowledgeRerankModel?: string
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knowledgeRerankApiKeyConfigured?: boolean
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knowledgeRerankCredentialSource?: 'none' | 'encrypted' | 'environment'
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workspacePath: string
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apiKeyConfigured: boolean
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credentialSource: 'none' | 'encrypted' | 'environment'
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@@ -758,6 +820,23 @@ export type AgentEvent =
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type: 'source-references'
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references: KnowledgeSearchReference[]
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}
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| {
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requestId: string
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type: 'knowledge-retrieval'
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mode: 'always'
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state:
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| 'searching'
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| 'succeeded'
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| 'zero'
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| 'degraded'
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| 'failed'
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| 'cancelled'
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libraryCount: number
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resultCount: number
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durationMs?: number
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usedChannels: Array<'fts' | 'cjk' | 'vector' | 'graph'>
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warnings: string[]
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}
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| {
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requestId: string
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type: 'done'
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@@ -870,6 +949,11 @@ export type KnowledgeLibrary = z.infer<typeof knowledgeCreateSchema> & {
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sourceCount: number
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documentCount: number
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indexedDocumentCount: number
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retrievalSettings?: KnowledgeRetrievalSettings
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chunkingSettings?: KnowledgeChunkingSettings
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chunkingRebuildRequired?: boolean
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ontologySettings?: KnowledgeOntologySettings
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ontologyRebuildRequired?: boolean
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updatedAt?: string
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}
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@@ -900,21 +984,6 @@ export type KnowledgeDocumentItem = {
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error?: string
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}
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export type KnowledgeTaskItem = {
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id: string
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libraryId: string
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sourceId?: string
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documentId?: string
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documentName: string
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kind: 'parsing' | 'embedding' | 'graph'
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status: 'queued' | 'running' | 'succeeded' | 'failed' | 'skipped'
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progress: number
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message?: string
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createdAt: string
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startedAt?: string
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completedAt?: string
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}
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export type KnowledgeGraphNode = {
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id: string
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label: string
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@@ -958,13 +1027,19 @@ export type KnowledgeSearchReference = {
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libraryId: string
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libraryName: string
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documentId: string
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chunkId?: string
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documentName: string
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sourceName: string
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sourceLocation?: string
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locator?: string
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snippet: string
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rank: number
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retrievalChannels?: Array<'fts' | 'vector' | 'graph'>
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score?: number
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lexicalRank?: number
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vectorRank?: number
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graphRank?: number
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similarity?: number
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retrievalChannels?: Array<'fts' | 'cjk' | 'vector' | 'graph'>
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evidenceIds?: string[]
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}
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@@ -1078,11 +1153,6 @@ export type DesktopApi = {
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embeddings?: {
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getSnapshot: () => Promise<EmbeddingSettingsSnapshot>
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diagnose: () => Promise<EmbeddingDiagnosticResult>
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rebuild: () => Promise<EmbeddingIndexStatus>
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cancel: (jobId: string) => Promise<boolean>
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onStatus: (
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listener: (status: EmbeddingIndexStatus) => void
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) => () => void
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}
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documentParsing?: {
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getSnapshot: () => Promise<DocumentParsingSnapshot>
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@@ -1341,6 +1411,46 @@ export type DesktopApi = {
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libraryIds: string[],
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query: string
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) => Promise<KnowledgeSearchReference[]>
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retrieve: (
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input: KnowledgeRetrieveInput
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) => Promise<KnowledgeRetrievalResponse>
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updateSettings: (
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input: KnowledgeSettingsUpdateInput
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) => Promise<KnowledgeLibrary>
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listChunks: (
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input: KnowledgeChunksListInput
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) => Promise<KnowledgeChunkPage>
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updateChunk: (
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input: KnowledgeChunkUpdateInput
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) => Promise<void>
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deleteChunk: (
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input: KnowledgeChunkDeleteInput
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) => Promise<void>
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rebuildDocument: (
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input: KnowledgeDocumentRebuildInput
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) => Promise<KnowledgeSnapshot>
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rebuildLibrary: (
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input: KnowledgeLibraryRebuildInput
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) => Promise<{ rebuilt: number; failed: number }>
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cancelRebuild: (knowledgeBaseId: string) => Promise<boolean>
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getEmbeddingIndex: (
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knowledgeBaseId: string
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) => Promise<KnowledgeEmbeddingIndexSnapshot>
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rebuildEmbeddingIndex: (
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knowledgeBaseId: string
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) => Promise<KnowledgeEmbeddingIndexSnapshot>
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cancelEmbeddingIndex: (
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knowledgeBaseId: string,
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jobId: string
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) => Promise<boolean>
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cancelTask: (taskId: string) => Promise<boolean>
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retryTask: (taskId: string) => Promise<void>
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getReferenceContext: (
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input: KnowledgeReferenceContextInput
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) => Promise<KnowledgeReferenceContext>
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openReferenceSource: (
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input: KnowledgeReferenceOpenInput
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) => Promise<void>
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createEntity: (
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libraryId: string,
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input: z.infer<typeof knowledgeEntityUpdateSchema>
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