lofyerandfactory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
b3fdf96962
Harden runtime execution and add local knowledge, Smart Heartbeat, usage visibility, responsive product surfaces, and cross-platform packaging support. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
880 lines
25 KiB
TypeScript
880 lines
25 KiB
TypeScript
import { z } from 'zod'
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import type {
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CapabilityAssignments,
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CapabilitySnapshot,
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McpServerInput,
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McpServerTestResult
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} from './capability-contracts'
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import {
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workModeSchema,
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type AssistantProject,
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type AssistantArtifact,
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type AssistantMemory,
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type AssistantSchedule,
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type AssistantHeartbeatConfig,
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type AssistantHeartbeatEntry,
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type AssistantHeartbeatRun,
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type AssistantExpert,
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type AssistantTask,
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type TokenUsageSummary,
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type ConversationSnapshot,
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type WorkspaceChanges,
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type ProjectCreateInput,
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type MemoryCreateInput,
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type ScheduleCreateInput,
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type HeartbeatCreateInput,
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type HeartbeatUpdateInput,
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type ExpertCreateInput
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} from './assistant-contracts'
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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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conversationId: z.string().min(1).max(128),
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projectId: z.string().uuid().optional(),
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expertId: z.string().uuid().optional(),
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teamMode: z.boolean().optional(),
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workMode: workModeSchema.optional(),
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prompt: z.string().trim().min(1).max(100_000),
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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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z
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.object({
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role: z.enum(['user', 'assistant']),
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content: z.string().max(100_000)
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})
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.strict()
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)
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.max(40)
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.optional()
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})
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.strict()
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.superRefine((request, context) => {
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const historyLength =
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request.history?.reduce(
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(total, message) => total + message.content.length,
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0
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) ?? 0
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if (historyLength > 500_000) {
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context.addIssue({
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code: 'custom',
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path: ['history'],
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message: '会话历史总长度不能超过 500,000 个字符'
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})
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}
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})
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export type AgentRequest = z.infer<typeof agentRequestSchema>
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export const runtimeProviderSchema = z.enum([
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'auto',
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'model',
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'opencode',
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'continue'
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])
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export const toolApprovalPolicySchema = z.enum([
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'always',
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'session',
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'workspace',
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'policy'
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])
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export const continueModeSchema = z.enum(['chat', 'agent'])
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export const runtimeSandboxModeSchema = z.enum(['off', 'auto', 'strict'])
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export const modelProtocolSchema = z.enum([
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'anthropic-messages',
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'openai-chat-completions',
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'openai-images-generations'
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])
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export const modelAuthenticationSchema = z.enum(['api-key', 'none'])
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export type ModelProtocol = z.infer<typeof modelProtocolSchema>
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export type ModelAuthentication = z.infer<
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typeof modelAuthenticationSchema
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>
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export const defaultModelProfileId =
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'00000000-0000-4000-8000-000000000001'
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export const defaultRuntimeSettings = {
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provider: 'auto',
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modelBaseUrl: 'https://bigtoken.ai',
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modelName: 'sonnet-5',
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modelProtocol: 'anthropic-messages',
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modelAuthentication: 'api-key',
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opencodeBaseUrl: '',
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opencodeEmbedded: false,
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opencodeBinaryPath: '',
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opencodeConfigPath: '',
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continueBinaryPath: '',
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continueConfigPath: '',
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continueMode: 'chat',
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runtimeSandboxMode: 'auto',
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knowledgeEmbeddingEnabled: false,
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knowledgeEmbeddingBaseUrl: 'http://127.0.0.1:11434',
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knowledgeEmbeddingModel: 'nomic-embed-text',
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workspacePath: '',
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toolApproval: 'always'
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} as const
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export const runtimePathSchema = z
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.string()
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.max(4_096)
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.refine(
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(value) =>
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[...value].every((character) => {
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const code = character.charCodeAt(0)
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return code > 31 && code !== 127
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}),
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'Runtime 路径包含控制字符'
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)
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export const runtimeFileSelectionKindSchema = z.enum([
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'opencodeBinary',
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'opencodeConfig',
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'continueBinary',
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'continueConfig'
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])
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export type RuntimeFileSelectionKind = z.infer<
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typeof runtimeFileSelectionKindSchema
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>
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const modelApiKeyUpdateSchema = z.discriminatedUnion('action', [
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z.object({ action: z.literal('keep') }).strict(),
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z
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.object({
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action: z.literal('replace'),
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value: z
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.string()
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.trim()
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.min(1)
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.max(8_192)
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.refine(
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(value) =>
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[...value].every((character) => {
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const code = character.charCodeAt(0)
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return code > 31 && code !== 127
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}),
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{
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message: 'API Key 包含控制字符'
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}
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)
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})
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.strict(),
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z.object({ action: z.literal('clear') }).strict()
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])
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const modelProfileInputSchema = z
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.object({
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id: z.string().uuid(),
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name: z.string().trim().min(1).max(64),
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baseUrl: z.string().url().max(2_048),
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modelName: z
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.string()
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.trim()
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.min(1)
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.max(128)
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.regex(/^[\w./:-]+$/, '模型名称包含不支持的字符'),
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protocol: modelProtocolSchema,
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authentication: modelAuthenticationSchema,
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apiKey: modelApiKeyUpdateSchema
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})
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.strict()
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export const runtimeModelSourceSchema = z.discriminatedUnion('kind', [
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z.object({ kind: z.literal('platform') }).strict(),
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z
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.object({
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kind: z.literal('profile'),
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profileId: z.string().uuid()
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})
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.strict()
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])
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export const runtimeSettingsInputSchema = z
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.object({
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provider: runtimeProviderSchema,
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modelBaseUrl: z.string().url().max(2_048),
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modelName: z
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.string()
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.trim()
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.min(1)
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.max(128)
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.regex(/^[\w./:-]+$/, '模型名称包含不支持的字符'),
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modelProtocol: modelProtocolSchema,
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modelAuthentication: modelAuthenticationSchema,
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opencodeBaseUrl: z.union([
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z.literal(''),
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z.string().url().max(2_048)
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]),
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opencodeEmbedded: z.boolean(),
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opencodeBinaryPath: runtimePathSchema,
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opencodeConfigPath: runtimePathSchema,
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continueBinaryPath: runtimePathSchema,
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continueConfigPath: runtimePathSchema,
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continueMode: continueModeSchema,
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runtimeSandboxMode: runtimeSandboxModeSchema,
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knowledgeEmbeddingEnabled: z.boolean(),
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knowledgeEmbeddingBaseUrl: z.string().url().max(2_048),
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knowledgeEmbeddingModel: 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./:-]+$/, '向量模型名称包含不支持的字符'),
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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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defaultModelProfileId: z.string().uuid().optional(),
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opencodeModelSource: runtimeModelSourceSchema.optional(),
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continueModelSource: runtimeModelSourceSchema.optional(),
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toolApproval: toolApprovalPolicySchema
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}).strict()
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.superRefine((settings, context) => {
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if (
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!settings.modelProfiles &&
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settings.modelAuthentication === 'none' &&
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settings.apiKey.action === 'replace'
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) {
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context.addIssue({
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code: 'custom',
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path: ['apiKey'],
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message: '无认证模型连接不得配置 API Key'
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})
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}
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const endpoints = settings.modelProfiles?.map((profile, index) => ({
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path: ['modelProfiles', index, 'baseUrl'] as (string | number)[],
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value: profile.baseUrl
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})) ?? [{ path: ['modelBaseUrl'], value: settings.modelBaseUrl }]
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for (const endpoint of endpoints) {
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const url = new URL(endpoint.value)
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const hostname = url.hostname.toLowerCase()
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const loopback =
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hostname === 'localhost' ||
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hostname === '::1' ||
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hostname === '[::1]' ||
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/^127(?:\.\d{1,3}){3}$/u.test(hostname)
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if (
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(url.protocol !== 'https:' &&
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!(url.protocol === 'http:' && loopback)) ||
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url.username ||
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url.password ||
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url.search ||
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url.hash
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) {
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context.addIssue({
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code: 'custom',
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path: endpoint.path,
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message:
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'模型服务地址必须使用 HTTPS；仅本机回环地址可使用 HTTP，且不得包含凭据、查询参数或片段'
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})
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}
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}
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if (settings.modelProfiles) {
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for (const [index, profile] of settings.modelProfiles.entries()) {
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if (
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profile.authentication === 'none' &&
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profile.apiKey.action === 'replace'
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) {
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context.addIssue({
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code: 'custom',
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path: ['modelProfiles', index, 'apiKey'],
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message: '无认证模型连接不得配置 API Key'
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})
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}
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}
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const ids = new Set(settings.modelProfiles.map((profile) => profile.id))
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const names = new Set(
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settings.modelProfiles.map((profile) => profile.name.toLowerCase())
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)
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if (
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ids.size !== settings.modelProfiles.length ||
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names.size !== settings.modelProfiles.length
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) {
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context.addIssue({
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code: 'custom',
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path: ['modelProfiles'],
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message: '模型连接的 ID 和名称必须唯一'
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})
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}
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const defaultId =
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settings.defaultModelProfileId ?? settings.modelProfiles[0]?.id
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if (!defaultId || !ids.has(defaultId)) {
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context.addIssue({
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code: 'custom',
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path: ['defaultModelProfileId'],
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message: '默认模型连接不存在'
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})
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}
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for (const [key, source] of [
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['opencodeModelSource', settings.opencodeModelSource],
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['continueModelSource', settings.continueModelSource]
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] as const) {
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if (source?.kind === 'profile' && !ids.has(source.profileId)) {
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context.addIssue({
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code: 'custom',
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path: [key],
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message: 'Runtime 引用的模型连接不存在'
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})
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}
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}
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const opencodeSource = settings.opencodeModelSource
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const opencodeProfile =
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opencodeSource?.kind === 'profile'
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? settings.modelProfiles.find(
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(profile) => profile.id === opencodeSource.profileId
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)
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: undefined
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if (
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opencodeProfile &&
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(opencodeProfile.protocol !== 'anthropic-messages' ||
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opencodeProfile.authentication !== 'api-key')
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) {
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context.addIssue({
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code: 'custom',
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path: ['opencodeModelSource'],
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message:
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'OpenCode 独立模型连接仅支持需要 API Key 的 Anthropic Messages 协议'
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})
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}
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const continueSource = settings.continueModelSource
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const continueProfile =
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continueSource?.kind === 'profile'
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? settings.modelProfiles.find(
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(profile) => profile.id === continueSource.profileId
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)
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: undefined
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if (continueProfile?.protocol === 'openai-images-generations') {
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context.addIssue({
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code: 'custom',
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path: ['continueModelSource'],
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message: 'Continue 不支持图像生成模型连接'
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})
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}
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}
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if (settings.opencodeBaseUrl) {
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const opencodeUrl = new URL(settings.opencodeBaseUrl)
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if (
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!['http:', 'https:'].includes(opencodeUrl.protocol) ||
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opencodeUrl.username ||
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opencodeUrl.password ||
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opencodeUrl.search ||
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opencodeUrl.hash ||
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(opencodeUrl.pathname !== '/' && opencodeUrl.pathname !== '')
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) {
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context.addIssue({
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code: 'custom',
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path: ['opencodeBaseUrl'],
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message: 'OpenCode 地址必须是无凭据和路径的 HTTP(S) origin'
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})
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}
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}
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const embeddingUrl = new URL(settings.knowledgeEmbeddingBaseUrl)
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const embeddingHost = embeddingUrl.hostname.toLowerCase()
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const privateIpv4 =
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/^10(?:\.\d{1,3}){3}$/u.test(embeddingHost) ||
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/^192\.168(?:\.\d{1,3}){2}$/u.test(embeddingHost) ||
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/^172\.(?:1[6-9]|2\d|3[01])(?:\.\d{1,3}){2}$/u.test(
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embeddingHost
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)
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const loopback =
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embeddingHost === 'localhost' ||
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embeddingHost === '::1' ||
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embeddingHost === '[::1]' ||
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/^127(?:\.\d{1,3}){3}$/u.test(embeddingHost)
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if (
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(embeddingUrl.protocol !== 'https:' &&
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!(
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embeddingUrl.protocol === 'http:' &&
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(loopback || privateIpv4)
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)) ||
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embeddingUrl.username ||
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embeddingUrl.password ||
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embeddingUrl.search ||
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embeddingUrl.hash ||
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(embeddingUrl.pathname !== '/' && embeddingUrl.pathname !== '')
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) {
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context.addIssue({
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code: 'custom',
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path: ['knowledgeEmbeddingBaseUrl'],
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message:
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'Ollama 向量地址必须使用 HTTPS，或使用本机/私有网络 HTTP origin，且不得包含凭据、路径、查询参数或片段'
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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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export type RuntimeModelSource = z.infer<typeof runtimeModelSourceSchema>
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export type ModelConnectionSettings = {
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id: string
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name: string
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baseUrl: string
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modelName: string
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protocol: ModelProtocol
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authentication: ModelAuthentication
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apiKeyConfigured: boolean
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credentialSource: 'none' | 'encrypted' | 'environment'
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}
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export type RuntimeSettings = {
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provider: RuntimeSettingsInput['provider']
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modelBaseUrl: string
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modelName: string
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modelProtocol: ModelProtocol
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modelAuthentication: ModelAuthentication
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opencodeBaseUrl: string
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opencodeEmbedded: boolean
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opencodeBinaryPath: string
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opencodeConfigPath: string
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continueBinaryPath: string
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continueConfigPath: string
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continueMode: RuntimeSettingsInput['continueMode']
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runtimeSandboxMode: RuntimeSettingsInput['runtimeSandboxMode']
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knowledgeEmbeddingEnabled: boolean
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knowledgeEmbeddingBaseUrl: string
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knowledgeEmbeddingModel: string
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workspacePath: string
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apiKeyConfigured: boolean
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credentialSource: 'none' | 'encrypted' | 'environment'
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modelProfiles: ModelConnectionSettings[]
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defaultModelProfileId: string
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opencodeModelSource: RuntimeModelSource
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continueModelSource: RuntimeModelSource
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secureStorageAvailable: boolean
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toolApproval: RuntimeSettingsInput['toolApproval']
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warning?: string
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}
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export type ContextAttachment = {
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id: string
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name: string
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size: number
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preview: string
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kind: 'text' | 'image'
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thumbnailUrl?: string
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}
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export type AgentRuntimeStatus = {
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id: 'setup' | 'model' | 'opencode' | 'continue'
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label: string
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available: boolean
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detail: string
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capability?: 'chat' | 'image-generation'
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supportsToolExecution: boolean
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}
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export type RuntimeBinaryDetection =
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| {
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available: true
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path: string
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version?: string
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detail: string
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}
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| {
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available: false
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path?: never
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version?: never
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detail: string
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}
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export type AgentRuntimeDetection = {
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opencode: RuntimeBinaryDetection
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continue: RuntimeBinaryDetection
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}
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export const approvalDecisionSchema = z.enum([
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'deny',
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'once',
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'session',
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'permanent'
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])
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export type ApprovalDecision = z.infer<typeof approvalDecisionSchema>
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export type AgentEvent =
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| {
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requestId: string
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type: 'status'
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message: string
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}
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| {
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requestId: string
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type: 'text'
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delta: string
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}
|
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| {
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requestId: string
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type: 'tool'
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callId: string
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name: string
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state: 'pending' | 'running' | 'completed' | 'failed'
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summary: string
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}
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| {
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requestId: string
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type: 'approval'
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approvalId: string
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title: string
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description: string
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toolName?: string
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argumentSummary?: string
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allowPermanent?: boolean
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}
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| {
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requestId: string
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type: 'artifact'
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artifactId: string
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kind: 'image'
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title: 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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sessionId?: string
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}
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| {
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requestId: string
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type: 'error'
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status: 'failed' | 'cancelled'
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message: string
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}
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export type AppInfo = {
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name: string
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version: string
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platform: string
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arch: string
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shortcut: string
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}
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export const knowledgeIdSchema = z.string().uuid()
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export const knowledgeCreateSchema = z
|
|
.object({
|
|
name: z.string().trim().min(1).max(120),
|
|
description: z.string().trim().max(1_000),
|
|
storageMode: z.enum(['reference', 'managed']),
|
|
graphEnabled: z.boolean(),
|
|
graphStrategy: z.enum(['rules', 'model', 'hybrid', 'ask'])
|
|
})
|
|
.strict()
|
|
export const knowledgeImportPathsSchema = z
|
|
.object({
|
|
libraryId: knowledgeIdSchema,
|
|
paths: z.array(z.string().trim().min(1).max(4_096)).min(1).max(20),
|
|
graphStrategy: z.enum(['rules', 'model', 'hybrid']).optional()
|
|
})
|
|
.strict()
|
|
export const knowledgeUrlImportSchema = z
|
|
.object({
|
|
libraryId: knowledgeIdSchema,
|
|
url: z.string().url().max(2_048),
|
|
graphStrategy: z.enum(['rules', 'model', 'hybrid']).optional()
|
|
})
|
|
.strict()
|
|
export const knowledgeUpdateLibrarySchema = z
|
|
.object({
|
|
libraryId: knowledgeIdSchema,
|
|
graphEnabled: z.boolean(),
|
|
graphStrategy: z.enum(['rules', 'model', 'hybrid', 'ask'])
|
|
})
|
|
.strict()
|
|
export const knowledgeEntityUpdateSchema = z
|
|
.object({
|
|
label: z.string().trim().min(1).max(120),
|
|
type: z.string().trim().min(1).max(120),
|
|
description: z.string().trim().max(2_000),
|
|
aliases: z.array(z.string().trim().min(1).max(120)).max(50)
|
|
})
|
|
.strict()
|
|
export const knowledgeRelationInputSchema = z
|
|
.object({
|
|
sourceId: knowledgeIdSchema,
|
|
targetId: knowledgeIdSchema,
|
|
type: z.string().trim().min(1).max(120),
|
|
description: z.string().trim().max(2_000)
|
|
})
|
|
.strict()
|
|
|
|
export type KnowledgeLibrary = z.infer<typeof knowledgeCreateSchema> & {
|
|
id: string
|
|
sourceCount: number
|
|
documentCount: number
|
|
indexedDocumentCount: number
|
|
updatedAt?: string
|
|
}
|
|
|
|
export type KnowledgeSourceItem = {
|
|
id: string
|
|
libraryId: string
|
|
name: string
|
|
kind: 'file' | 'directory' | 'url'
|
|
location?: string
|
|
status: 'queued' | 'syncing' | 'paused' | 'ready' | 'failed'
|
|
progress?: number
|
|
documentCount: number
|
|
lastSyncedAt?: string
|
|
error?: string
|
|
}
|
|
|
|
export type KnowledgeDocumentItem = {
|
|
id: string
|
|
libraryId: string
|
|
sourceId?: string
|
|
name: string
|
|
path?: string
|
|
status: 'queued' | 'parsing' | 'indexing' | 'ready' | 'failed'
|
|
indexProgress?: number
|
|
chunkCount?: number
|
|
size?: number
|
|
updatedAt?: string
|
|
error?: string
|
|
}
|
|
|
|
export type KnowledgeGraphNode = {
|
|
id: string
|
|
label: string
|
|
type: string
|
|
description?: string
|
|
aliases?: string[]
|
|
x: number
|
|
y: number
|
|
evidenceIds?: string[]
|
|
}
|
|
|
|
export type KnowledgeGraphRelation = {
|
|
id: string
|
|
sourceId: string
|
|
targetId: string
|
|
type: string
|
|
description?: string
|
|
evidenceIds?: string[]
|
|
}
|
|
|
|
export type KnowledgeEvidence = {
|
|
id: string
|
|
documentId: string
|
|
documentName: string
|
|
excerpt: string
|
|
location?: string
|
|
}
|
|
|
|
export type KnowledgeSnapshot = {
|
|
libraries: KnowledgeLibrary[]
|
|
selectedLibraryId?: string
|
|
sources: KnowledgeSourceItem[]
|
|
documents: KnowledgeDocumentItem[]
|
|
graphNodes: KnowledgeGraphNode[]
|
|
graphRelations: KnowledgeGraphRelation[]
|
|
evidence: KnowledgeEvidence[]
|
|
}
|
|
|
|
export type KnowledgeSearchReference = {
|
|
libraryId: string
|
|
libraryName: string
|
|
documentId: string
|
|
documentName: string
|
|
sourceName: string
|
|
sourceLocation?: string
|
|
locator?: string
|
|
snippet: string
|
|
rank: number
|
|
retrievalChannels?: Array<'fts' | 'vector' | 'graph'>
|
|
evidenceIds?: string[]
|
|
}
|
|
|
|
export type DesktopApi = {
|
|
app: {
|
|
getInfo: () => Promise<AppInfo>
|
|
show: () => Promise<void>
|
|
hide: () => Promise<void>
|
|
clearLocalData: () => Promise<void>
|
|
onNewConversation: (listener: () => void) => () => void
|
|
onOpenSettings: (listener: () => void) => () => void
|
|
}
|
|
agent: {
|
|
getStatus: () => Promise<AgentRuntimeStatus>
|
|
run: (request: AgentRequest) => Promise<void>
|
|
cancel: (requestId: string) => Promise<void>
|
|
respondApproval: (
|
|
approvalId: string,
|
|
decision: ApprovalDecision
|
|
) => Promise<void>
|
|
onEvent: (listener: (event: AgentEvent) => void) => () => void
|
|
}
|
|
settings: {
|
|
getRuntime: () => Promise<RuntimeSettings>
|
|
updateRuntime: (input: RuntimeSettingsInput) => Promise<RuntimeSettings>
|
|
selectWorkspace: () => Promise<string | undefined>
|
|
detectAgentRuntimes: () => Promise<AgentRuntimeDetection>
|
|
selectRuntimeFile: (
|
|
kind: RuntimeFileSelectionKind
|
|
) => Promise<string | undefined>
|
|
testRuntime: () => Promise<AgentRuntimeStatus>
|
|
}
|
|
projects: {
|
|
list: (includeArchived?: boolean) => Promise<AssistantProject[]>
|
|
create: (input: ProjectCreateInput) => Promise<AssistantProject>
|
|
update: (
|
|
projectId: string,
|
|
input: ProjectCreateInput
|
|
) => Promise<AssistantProject>
|
|
setArchived: (projectId: string, archived: boolean) => Promise<void>
|
|
}
|
|
conversations: {
|
|
list: () => Promise<ConversationSnapshot[]>
|
|
replace: (conversations: ConversationSnapshot[]) => Promise<void>
|
|
}
|
|
workspace: {
|
|
getChanges: (projectId: string) => Promise<WorkspaceChanges>
|
|
}
|
|
tasks: {
|
|
list: () => Promise<AssistantTask[]>
|
|
setStatus: (
|
|
taskId: string,
|
|
status: Extract<AssistantTask['status'], 'completed' | 'cancelled'>
|
|
) => Promise<void>
|
|
}
|
|
usage: {
|
|
getTokenSummary: () => Promise<TokenUsageSummary>
|
|
}
|
|
artifacts: {
|
|
list: (projectId?: string) => Promise<AssistantArtifact[]>
|
|
get: (artifactId: string) => Promise<AssistantArtifact>
|
|
importFiles: (projectId?: string) => Promise<AssistantArtifact[]>
|
|
}
|
|
memory: {
|
|
list: (scopeId?: string) => Promise<AssistantMemory[]>
|
|
create: (input: MemoryCreateInput) => Promise<AssistantMemory>
|
|
setStatus: (
|
|
memoryId: string,
|
|
status: AssistantMemory['status']
|
|
) => Promise<void>
|
|
remove: (memoryId: string) => Promise<void>
|
|
}
|
|
schedules: {
|
|
list: (projectId?: string) => Promise<AssistantSchedule[]>
|
|
create: (input: ScheduleCreateInput) => Promise<AssistantSchedule>
|
|
setEnabled: (scheduleId: string, enabled: boolean) => Promise<void>
|
|
remove: (scheduleId: string) => Promise<void>
|
|
runNow: (scheduleId: string) => Promise<void>
|
|
}
|
|
heartbeats: {
|
|
list: (projectId?: string) => Promise<AssistantHeartbeatConfig[]>
|
|
create: (
|
|
input: HeartbeatCreateInput
|
|
) => Promise<AssistantHeartbeatConfig>
|
|
update: (
|
|
heartbeatId: string,
|
|
input: HeartbeatUpdateInput
|
|
) => Promise<AssistantHeartbeatConfig>
|
|
setPaused: (heartbeatId: string, paused: boolean) => Promise<void>
|
|
remove: (heartbeatId: string) => Promise<void>
|
|
runNow: (heartbeatId: string) => Promise<AssistantHeartbeatRun>
|
|
history: (
|
|
heartbeatId?: string
|
|
) => Promise<{
|
|
runs: AssistantHeartbeatRun[]
|
|
entries: AssistantHeartbeatEntry[]
|
|
}>
|
|
}
|
|
experts: {
|
|
list: () => Promise<AssistantExpert[]>
|
|
create: (input: ExpertCreateInput) => Promise<AssistantExpert>
|
|
}
|
|
capabilities: {
|
|
getSnapshot: () => Promise<CapabilitySnapshot>
|
|
importSkill: () => Promise<CapabilitySnapshot>
|
|
removeSkill: (skillId: string) => Promise<CapabilitySnapshot>
|
|
setSkillEnabled: (
|
|
skillId: string,
|
|
enabled: boolean
|
|
) => Promise<CapabilitySnapshot>
|
|
setSkillAssignments: (
|
|
skillId: string,
|
|
assignments: CapabilityAssignments
|
|
) => Promise<CapabilitySnapshot>
|
|
saveMcpServer: (
|
|
serverId: string | undefined,
|
|
input: McpServerInput
|
|
) => Promise<CapabilitySnapshot>
|
|
removeMcpServer: (serverId: string) => Promise<CapabilitySnapshot>
|
|
testMcpServer: (serverId: string) => Promise<McpServerTestResult>
|
|
}
|
|
context: {
|
|
selectFiles: () => Promise<ContextAttachment[]>
|
|
captureScreen: () => Promise<ContextAttachment>
|
|
captureWindow: () => Promise<ContextAttachment>
|
|
readClipboard: () => Promise<ContextAttachment>
|
|
remove: (contextId: string) => Promise<void>
|
|
}
|
|
knowledge: {
|
|
getSnapshot: (libraryId?: string) => Promise<KnowledgeSnapshot>
|
|
createLibrary: (
|
|
input: z.infer<typeof knowledgeCreateSchema>
|
|
) => Promise<KnowledgeLibrary>
|
|
updateLibrary: (
|
|
libraryId: string,
|
|
update: {
|
|
graphEnabled: boolean
|
|
graphStrategy: 'rules' | 'model' | 'hybrid' | 'ask'
|
|
}
|
|
) => Promise<void>
|
|
deleteLibrary: (libraryId: string) => Promise<void>
|
|
selectFiles: (
|
|
libraryId: string,
|
|
graphStrategy?: 'rules' | 'model' | 'hybrid'
|
|
) => Promise<void>
|
|
selectDirectory: (
|
|
libraryId: string,
|
|
graphStrategy?: 'rules' | 'model' | 'hybrid'
|
|
) => Promise<void>
|
|
importDroppedFiles: (
|
|
libraryId: string,
|
|
files: File[],
|
|
graphStrategy?: 'rules' | 'model' | 'hybrid'
|
|
) => Promise<void>
|
|
importUrl: (
|
|
libraryId: string,
|
|
url: string,
|
|
graphStrategy?: 'rules' | 'model' | 'hybrid'
|
|
) => Promise<void>
|
|
syncSource: (sourceId: string) => Promise<void>
|
|
pauseSource: (sourceId: string) => Promise<void>
|
|
retrySource: (sourceId: string) => Promise<void>
|
|
removeSource: (sourceId: string) => Promise<void>
|
|
search: (
|
|
libraryIds: string[],
|
|
query: string
|
|
) => Promise<KnowledgeSearchReference[]>
|
|
createEntity: (
|
|
libraryId: string,
|
|
input: z.infer<typeof knowledgeEntityUpdateSchema>
|
|
) => Promise<void>
|
|
updateEntity: (
|
|
entityId: string,
|
|
update: z.infer<typeof knowledgeEntityUpdateSchema>
|
|
) => Promise<void>
|
|
moveEntity: (
|
|
entityId: string,
|
|
position: { x: number; y: number }
|
|
) => Promise<void>
|
|
deleteEntity: (entityId: string) => Promise<void>
|
|
mergeEntities: (
|
|
sourceEntityId: string,
|
|
targetEntityId: string
|
|
) => Promise<void>
|
|
createRelation: (
|
|
libraryId: string,
|
|
input: z.infer<typeof knowledgeRelationInputSchema>
|
|
) => Promise<void>
|
|
updateRelation: (
|
|
relationId: string,
|
|
input: z.infer<typeof knowledgeRelationInputSchema>
|
|
) => Promise<void>
|
|
deleteRelation: (relationId: string) => Promise<void>
|
|
}
|
|
}
|