feat: add native runtime customization
OpenCode and Continue customization was previously planned but unavailable, and Runtime-native capabilities were not represented consistently across providers. GoodBuddy now provides secure Main-owned customization settings, truthful native inventories, OpenCode Agents and Commands, Continue Rules and Prompts, DSH Web Search/Fetch, MCP Prompt and Resource metadata, and manual compaction where supported. Native capabilities are presented in eleven accessible tabs with Tools separated from Commands, LSP, and Formatters. Tool source and Ask/Execute availability are explicit, external OpenCode remains connection-only, Continue reports unsupported static tool discovery instead of advertising unreachable Skills, and disposable inventory probes avoid retaining background runtimes. Ask remains read-only at the Runtime boundary, Execute keeps the existing authorization controls, and credentials remain confined to Main. Release note: 新增 OpenCode、Continue 与 DeepSeek Harness 的 Runtime 原生定制与真实能力清单；工具来源、Ask/Execute 可用性、上下文压缩和 MCP 元数据现在可清晰查看，同时继续保持 Main 进程凭据保护与现有权限边界。
This commit is contained in:
mesalogo
+263
-1
@@ -24,6 +24,7 @@ import {
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agentRequestSchema,
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browserInteractRequestSchema,
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browserStopRequestSchema,
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defaultRuntimeSettings,
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knowledgeCreateSchema,
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knowledgeEntityUpdateSchema,
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knowledgeIdSchema,
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@@ -31,10 +32,16 @@ import {
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knowledgeRelationInputSchema,
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knowledgeUpdateLibrarySchema,
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knowledgeUrlImportSchema,
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isAgentRuntimeModelProtocol,
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modelProfileIdSchema,
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pastedImageInputSchema,
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runtimeConversationCompactInputSchema,
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runtimeConversationCompactResultSchema,
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runtimeConfigActionInputSchema,
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runtimeCustomizationSettingsSchema,
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runtimeFileSelectionKindSchema,
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runtimeNativeSnapshotInputSchema,
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runtimeNativeSnapshotSchema,
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runtimeSettingsInputSchema,
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windowCaptureRequestSchema,
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workspaceDirectoryRequestSchema,
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@@ -113,6 +120,7 @@ import {
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documentParsingTestInputSchema
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} from '../shared/document-parsing-contracts'
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import {
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agentRuntimeSelectionKey,
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agentRuntimeSelectionSchema,
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type AgentRuntimeSelection
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} from '../shared/runtime-selection-contracts'
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@@ -161,7 +169,10 @@ import {
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createDefaultModelRuntime,
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createModelProfileRuntime
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} from './agent/create-runtime'
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import { resolveConfiguredAgentRuntimeSelection } from './agent/runtime-selection'
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import {
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applyRuntimeSelection,
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resolveConfiguredAgentRuntimeSelection
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} from './agent/runtime-selection'
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import { safeToolErrorDetail } from './agent/approval-summary'
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import { ReasoningTagStreamParser } from './agent/reasoning-stream'
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import {
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@@ -2361,6 +2372,9 @@ export function registerIpcHandlers(
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let executionRequest = request
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let preflightReferences: KnowledgeSearchReference[] = []
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let referencesPublished = false
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let runtimeMetricSettings:
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| Promise<Awaited<ReturnType<RuntimeSettingsStore['getResolvedSettings']>>>
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| undefined
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const persistedEventBuffer = new AgentEventBuffer({
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onError: (error) => controller.abort(error),
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onEvent: (event) => {
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@@ -2665,6 +2679,50 @@ export function registerIpcHandlers(
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for await (const agentEvent of splitTaggedReasoning(eventStream)) {
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if (agentEvent.type === 'model-usage') {
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persistModelUsage(agentEvent)
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if (agentEvent.runtime !== 'model') {
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runtimeMetricSettings ??=
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settingsStore.getResolvedSettings()
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const runtimeSettings = await runtimeMetricSettings
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const selectedSettings = request.runtimeSelection
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? applyRuntimeSelection(
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runtimeSettings,
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request.runtimeSelection
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).settings
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: runtimeSettings
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const profile =
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agentEvent.runtime === 'opencode'
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? selectedSettings.opencodeModelProfile
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: agentEvent.runtime === 'continue'
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? selectedSettings.continueModelProfile
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: selectedSettings.deepseekHarnessModelProfile
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const contextWindowTokens =
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profile?.contextWindowTokens
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const providerUsesSeparateCacheTokens =
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/anthropic/iu.test(agentEvent.provider)
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const contextTokens = Math.min(
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50_000_000,
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agentEvent.inputTokens +
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(providerUsesSeparateCacheTokens
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? agentEvent.cacheReadTokens +
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agentEvent.cacheWriteTokens
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: 0)
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)
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eventBuffer.push({
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requestId: request.requestId,
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type: 'context-metrics',
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contextTokens,
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effectiveTriggerTokens:
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contextWindowTokens ??
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selectedSettings.contextCompression?.triggerTokens ??
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defaultRuntimeSettings.contextCompression.triggerTokens,
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...(contextWindowTokens
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? { contextWindowTokens }
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: {}),
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compressionEnabled: false,
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source: 'provider',
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basis: 'model-call'
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})
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}
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continue
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}
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const publicEvent: AgentEvent =
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@@ -2843,6 +2901,161 @@ export function registerIpcHandlers(
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}
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)
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registerHandler(
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ipcChannels.agentCompactConversation,
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async (event, input: unknown) => {
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assertTrustedSender(event, window)
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if (executionPaused || shuttingDown) {
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throw new Error('本地数据维护期间暂不支持压缩上下文')
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}
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const request = runtimeConversationCompactInputSchema.parse(input)
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if (
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request.runtimeSelection.provider !== 'opencode' &&
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request.runtimeSelection.provider !== 'continue'
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) {
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throw new Error('当前 Runtime 不支持手动压缩')
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}
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if (activeRequests.has(request.requestId)) {
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throw new Error('上下文压缩请求正在执行')
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}
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const conversation = assistantDatabase.getConversation(
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request.conversationId
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)
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if (
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conversation.projectId !== request.projectId ||
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!conversation.runtimeSelection ||
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agentRuntimeSelectionKey(conversation.runtimeSelection) !==
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agentRuntimeSelectionKey(request.runtimeSelection)
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) {
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throw new Error('对话 Runtime 或 Project 已更改，请刷新后重试')
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}
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const persistedHistory = conversation.messages
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.filter(
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(message) =>
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message.state === 'complete' && message.content.trim()
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)
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.slice(-500)
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if (
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persistedHistory.length !== request.history.length ||
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persistedHistory.some(
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(message, index) =>
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message.id !== request.historyMessageIds[index] ||
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message.role !== request.history[index]?.role ||
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message.content !== request.history[index]?.content
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)
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) {
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throw new Error('对话历史已更改，请刷新后重试')
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}
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const trustedRequest = {
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...request,
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contextCompressionState:
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conversation.contextCompressionState
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}
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const settings = await settingsStore.getResolvedSettings()
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const selected = applyRuntimeSelection(
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settings,
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request.runtimeSelection
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)
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const workspacePath = request.projectId
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? assistantDatabase.getProject(request.projectId).rootPath
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: selected.settings.workspacePath
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const controller = new AbortController()
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const timeout = setTimeout(
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() =>
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controller.abort(
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new Error('上下文压缩超过 5 分钟安全时限')
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),
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5 * 60_000
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)
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activeRequests.set(request.requestId, controller)
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assistantDatabase.createTask({
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id: request.requestId,
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projectId: request.projectId,
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conversationId: request.conversationId,
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title: '压缩对话上下文',
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instructions: '手动压缩对话上下文',
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workMode: 'ask',
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visible: false
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})
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try {
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let outcome
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if (request.runtimeSelection.provider === 'opencode') {
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if (!selectedRuntimes) {
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throw new Error('OpenCode Runtime 管理器不可用')
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}
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outcome = await selectedRuntimes.compactConversation(
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trustedRequest,
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workspacePath,
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controller.signal
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)
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} else {
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const compressionSource =
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selected.settings.contextCompression?.modelSource
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const profile =
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(compressionSource?.kind === 'profile'
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? selected.settings.modelProfiles.find(
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(candidate) =>
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candidate.id === compressionSource.profileId
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)
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: selected.settings.continueModelProfile) ??
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selected.settings.modelProfiles.find(
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(candidate) =>
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candidate.id ===
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selected.settings.defaultModelProfileId &&
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isAgentRuntimeModelProtocol(candidate.protocol)
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) ??
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selected.settings.modelProfiles.find((candidate) =>
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isAgentRuntimeModelProtocol(candidate.protocol)
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)
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if (!profile) {
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throw new Error('没有可用于 Continue 上下文摘要的文本模型连接')
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}
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if (
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profile.authentication === 'api-key' &&
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!profile.apiKey
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) {
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throw new Error(
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`上下文摘要模型连接“${profile.name}”未配置 API Key`
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)
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}
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const compactor = createModelProfileRuntime(
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workspacePath,
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selected.settings,
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profile
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)
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try {
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outcome = await compactor.compactConversation(
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trustedRequest,
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controller.signal
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)
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} finally {
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await compactor.dispose()
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}
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}
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for (const usageEvent of outcome.usageEvents ?? []) {
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persistModelUsage(usageEvent)
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}
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assistantDatabase.updateTaskStatus(
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request.requestId,
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'completed'
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)
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return runtimeConversationCompactResultSchema.parse(
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outcome.result
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)
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} catch (error) {
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assistantDatabase.updateTaskStatus(
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request.requestId,
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controller.signal.aborted ? 'cancelled' : 'failed',
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safeRuntimeError(error, '上下文压缩失败')
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)
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throw error
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} finally {
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clearTimeout(timeout)
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activeRequests.delete(request.requestId)
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}
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}
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)
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registerHandler(
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ipcChannels.runtimeSettingsGet,
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(event): Promise<RuntimeSettings> => {
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@@ -2851,6 +3064,55 @@ export function registerIpcHandlers(
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}
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)
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registerHandler(
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ipcChannels.runtimeCustomizationGet,
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(event) => {
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assertTrustedSender(event, window)
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return settingsStore.getRuntimeCustomization()
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}
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)
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registerHandler(
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ipcChannels.runtimeCustomizationUpdate,
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async (event, input: unknown) => {
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assertTrustedSender(event, window)
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const settings =
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runtimeCustomizationSettingsSchema.parse(input)
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const saved =
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await settingsStore.updateRuntimeCustomization(settings)
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abortActiveRequests('Runtime 定制设置已更改')
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approvalBroker.clear()
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await onRuntimeSettingsChanged()
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return saved
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}
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)
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registerHandler(
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ipcChannels.runtimeNativeSnapshot,
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async (event, input: unknown) => {
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assertTrustedSender(event, window)
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if (!selectedRuntimes) {
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throw new Error('Runtime 管理器不可用')
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}
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const request = runtimeNativeSnapshotInputSchema.parse(input)
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const selection: AgentRuntimeSelection = {
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provider: request.provider,
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...(request.profileId
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? { profileId: request.profileId }
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: {})
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}
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const workspacePath = request.projectId
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? assistantDatabase.getProject(request.projectId).rootPath
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: (await settingsStore.getResolvedSettings()).workspacePath
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return runtimeNativeSnapshotSchema.parse(
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await selectedRuntimes.getNativeSnapshot(
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selection,
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workspacePath
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)
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)
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}
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)
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registerHandler(
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ipcChannels.runtimeSettingsUpdate,
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async (event, input: unknown): Promise<RuntimeSettings> => {
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