feat: v0.4.0 四阶段迭代 — 安全加固 + 工程基线 + 架构重构 + 双 Provider 扩展
P0 安全修复: - API Key 加密存储（safeStorage 密钥链，版本化前缀，历史明文平滑兼容） - 间接提示注入防护（SecurityScanHook 工具结果深扫描，网络工具脱敏/本地工具警示分级） - error:report IPC 断链修复（渲染进程错误上报落 electron-log + 审计） - abort 信号贯通工具层（run_command/dev-tools 子进程随会话中断终止） - run_command 沙箱加固（cd 系统目录/敏感文件读取拦截 + chcp 前缀剥离防解析退化） - .env 真实生效（dotenv 回退加载，应用内配置优先） P1 工程基础: - ESLint 9 flat config + 全部 34 条存量 warnings 清零（零容忍基线） - 测试基线 118 用例 11 文件（token/文件防护/权限/沙箱/注入/命令/引擎/注册表/审计链/摘要分层） - test:electron 双模式（ELECTRON_RUN_AS_NODE 跑 Electron ABI，SQLite 套件全执行） - SessionRecorder 多会话隔离 + 9 种 TRACE 事件补全（含最终轮 iteration_end） - Provider 故障转移（重试耗尽/不可重试一次性切换 fallback + 前端通知） - MCP 真就绪（等待全部连接完成再广播 tools:ready） - SLO/HealthChecker 真实接入（60s 巡检 + 托盘状态） - CONFIG_DEFAULTS 单一来源（消除 SEED 双源漂移） P2 架构升级: - handlers.ts 1940 行拆分为 13 个 IPC 域模块（防重入注册 + 多窗口广播） - AgentEngineManager 每会话独立引擎（LRU 30 + adapter 工厂隔离 abort 信号） - TaskOrchestrator EngineProvider 改造 + abortByParent 联动中断 SubAgent - 会话摘要分层上下文（session_summaries 滚动摘要 + 截断游标清理防因果污染） - 消息编辑重发/重新生成（truncateAfter IPC + store 动作 + UI） - Markdown 导出 / WebSearch 并行抓取（并发 3）/ 记忆 TF 缓存 / 版本构建期注入 P3 能力扩展: - OpenAI Adapter（o 系列推理模型 reasoning_effort/max_completion_tokens） - Anthropic Adapter（原生 Messages API：tool_use 块/角色合并/thinking budget/图片 base64/SSE 事件机） - 设置页/Onboarding 六 Provider 全链路接入
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/**
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* Session Summary Service — 会话摘要分层上下文（P2-11）
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*
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* 解决"历史消息全量加载"问题：sendMessage 原实现从 DB 加载全部历史消息进 LLM
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* 上下文，超长会话（数百条消息）token 成本线性膨胀，只能依赖运行时压缩兜底。
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*
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* 分层策略（DB 层持久化，跨 run 生效）：
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* 1. 会话消息数超过阈值（50 条）后，将较早消息（保留尾部 20 条原文）交由 LLM
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* 生成滚动摘要，持久化到 session_summaries 表（含 summarized_until_rowid 游标）
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* 2. 下次 sendMessage 只加载：[摘要消息] + [rowid > 游标的近期原文消息]
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* 3. 摘要随新消息增量滚动更新（旧摘要作为上下文参与新一轮总结）
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*
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* 与 engine 运行时压缩（compressMessages）的关系：
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* 运行时压缩处理"单次 run 内"的上下文膨胀；本服务处理"跨 run"的 DB 历史分层，
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* 两者互补，运行时压缩触发频率将显著下降。
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*
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* @see electron/services/database.service.ts — session_summaries 表结构
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*/
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import { nanoid } from 'nanoid';
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import type Database from 'better-sqlite3';
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import log from 'electron-log';
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import type { IMetonaProviderAdapter, MetonaMessage, MetonaRequest } from '../harness/types';
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import type { SessionService } from './session.service';
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/** 触发摘要的最小消息总数（低于此值保持全量加载） */
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const MIN_MESSAGES_TO_SUMMARIZE = 50;
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/** 摘要后保留的尾部原文条数 */
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const TAIL_KEEP = 20;
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/** 每次摘要需新增的最小未总结消息数（避免每条消息都触发 LLM 摘要） */
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const MIN_NEW_TO_SUMMARIZE = 15;
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/** LLM 摘要调用超时 */
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const SUMMARY_TIMEOUT_MS = 30_000;
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/** 传给 LLM 的单条消息内容截断 */
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const PER_MESSAGE_TRUNCATE = 600;
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/** 传给 LLM 的总字符上限 */
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const MAX_DIGEST_CHARS = 24_000;
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export class SessionSummaryService {
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constructor(
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private getDB: () => Database.Database,
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private sessionService: SessionService,
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private adapterGetter: () => IMetonaProviderAdapter,
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) {}
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/**
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* 构建分层历史消息（sendMessage 的加载入口）
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*
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* @returns MetonaMessage 数组：存在摘要时为 [摘要消息, 近期原文...]，否则全量原文
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*/
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buildHistoryMessages(sessionId: string): MetonaMessage[] {
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const existing = this.getSummary(sessionId);
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const tail = this.sessionService.getMessages(sessionId, {
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afterRowid: existing?.summarizedUntilRowid ?? 0,
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});
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const messages: MetonaMessage[] = tail
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.filter((m) => m.role !== 'system')
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.map((m) => ({
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role: m.role as MetonaMessage['role'],
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content: m.content,
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reasoningContent: m.reasoningContent,
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toolCalls: m.toolCalls as MetonaMessage['toolCalls'],
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toolResult: m.toolResult as MetonaMessage['toolResult'],
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timestamp: m.timestamp,
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iteration: m.iteration,
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}));
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if (existing && messages.length > 0) {
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// 摘要以 assistant 角色注入（与 engine 运行时压缩的注入策略一致）
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const summaryMessage: MetonaMessage = {
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role: 'assistant',
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content: `[Context Summary] The following is a rolling summary of earlier conversation history:\n\n${existing.summary}`,
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timestamp: 0,
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};
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return [summaryMessage, ...messages];
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}
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return messages;
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}
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/**
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* 会话结束后评估并生成滚动摘要（fire-and-forget 调用，失败仅记录日志）
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*/
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async maybeSummarize(sessionId: string): Promise<void> {
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const rows = this.sessionService.getMessages(sessionId);
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if (rows.length < MIN_MESSAGES_TO_SUMMARIZE) return;
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const existing = this.getSummary(sessionId);
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const lastSummarized = existing?.summarizedUntilRowid ?? 0;
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const unsummarized = rows.filter((r) => (r.rowId ?? 0) > lastSummarized);
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// 未总结增量不足（保留尾部 TAIL_KEEP 后仍需 ≥ MIN_NEW_TO_SUMMARIZE 条）
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if (unsummarized.length <= TAIL_KEEP + MIN_NEW_TO_SUMMARIZE) return;
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const toSummarize = unsummarized.slice(0, unsummarized.length - TAIL_KEEP);
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if (toSummarize.length < MIN_NEW_TO_SUMMARIZE) return;
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const summary = await this.summarizeViaLLM(existing?.summary ?? '', toSummarize);
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if (!summary) return;
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const untilRowid = toSummarize[toSummarize.length - 1].rowId ?? 0;
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this.saveSummary(sessionId, summary, untilRowid);
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log.info(
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`[SessionSummary] session ${sessionId}: summarized ${toSummarize.length} messages (up to rowid ${untilRowid}), kept ${TAIL_KEEP} recent`,
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);
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}
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// ===== 摘要表 CRUD =====
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getSummary(sessionId: string): { summary: string; summarizedUntilRowid: number } | null {
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const db = this.getDB();
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const row = db
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.prepare('SELECT summary, summarized_until_rowid FROM session_summaries WHERE session_id = ?')
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.get(sessionId) as { summary: string; summarized_until_rowid: number } | undefined;
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return row ? { summary: row.summary, summarizedUntilRowid: row.summarized_until_rowid } : null;
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}
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saveSummary(sessionId: string, summary: string, untilRowid: number): void {
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const db = this.getDB();
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db.prepare(`
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INSERT INTO session_summaries (session_id, summary, summarized_until_rowid, updated_at)
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VALUES (?, ?, ?, ?)
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ON CONFLICT(session_id) DO UPDATE SET
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summary = excluded.summary,
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summarized_until_rowid = excluded.summarized_until_rowid,
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updated_at = excluded.updated_at
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`).run(sessionId, summary, untilRowid, Date.now());
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}
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// ===== LLM 摘要 =====
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/**
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* 调用 LLM 生成滚动摘要（复用主 Provider adapter）
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*
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* @param priorSummary 既有摘要（滚动总结上下文，可为空）
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* @param messages 本轮待总结的消息
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*/
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private async summarizeViaLLM(
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priorSummary: string,
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messages: Array<{ role: string; content: string | null }>,
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): Promise<string | null> {
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let total = 0;
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const transcript = messages
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.map((m) => {
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const content = (m.content ?? '').slice(0, PER_MESSAGE_TRUNCATE);
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if (total < MAX_DIGEST_CHARS) {
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total += content.length;
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return `[${m.role.toUpperCase()}] ${content}`;
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}
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return null;
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})
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.filter((s): s is string => s !== null)
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.join('\n\n');
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const request: MetonaRequest = {
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meta: {
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sessionId: 'session-summary',
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iteration: 0,
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requestId: `ss_${nanoid(12)}`,
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timestamp: Date.now(),
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agentVersion: '1.0.0',
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},
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systemPrompt: {
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roleDefinition: 'You are a conversation summarizer for an AI agent application.',
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outputConstraints:
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'Produce a rolling summary of the conversation history below. ' +
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'If a prior summary exists, merge it with the new content into one updated summary. ' +
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'Preserve key facts, decisions, tool outcomes, file paths, and open questions needed for future reasoning. ' +
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'Output in the same language as the conversation. Maximum 400 words. Output ONLY the summary text.',
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safetyGuidelines: 'Do not include sensitive data like passwords or API keys in the summary.',
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},
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messages: [
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{
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role: 'user',
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content: `${priorSummary ? `## Prior summary (merge and update):\n\n${priorSummary}\n\n` : ''}## New messages to summarize:\n\n${transcript}`,
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timestamp: Date.now(),
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},
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],
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params: {
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maxTokens: 2048,
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temperature: 0.0,
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stream: false,
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thinkingEnabled: false,
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thinkingEffort: 'low',
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},
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};
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try {
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const timeoutPromise = new Promise<never>((_, reject) => {
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setTimeout(() => reject(new Error('summary timeout')), SUMMARY_TIMEOUT_MS);
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});
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const response = await Promise.race([this.adapterGetter().send(request), timeoutPromise]);
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const summary = response.content.trim();
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return summary || null;
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} catch (err) {
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log.warn('[SessionSummary] LLM summarization failed:', (err as Error).message);
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return null;
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}
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}
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}
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