thzxx
2230bcec3f
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
594 lines
24 KiB
TypeScript
594 lines
24 KiB
TypeScript
/**
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* IPC Agent Handlers — Agent 交互域（P2-9 从 handlers.ts 拆分）
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*
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* 职责：
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* 1. agent:sendMessage — 消息发送编排（历史加载/记忆注入/注入检测/runStream/持久化）
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* 2. agent:abortSession — 中断会话（联动 SubAgent）
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* 3. 常驻引擎事件管道 — 流式转发（按会话节流）、状态广播、TRACE 录制（P1-6 补全 9 种事件）、
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* 压缩/死循环/Provider 切换通知
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*
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* P2-10: 事件监听从"每消息 attach/detach"改为常驻管道（按 sessionId 隔离状态），
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* 支持多会话并发流式与多窗口广播。
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*/
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import { ipcMain } from 'electron';
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import type { IPCContext } from './context';
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import { broadcast } from './context';
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import type { MetonaMessage, MetonaStreamEvent, MetonaError } from '../harness/types';
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import { MetonaErrorCode, MetonaStreamEventType } from '../harness/types';
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import { estimateMessagesTokens } from '../harness/utils/token-estimator';
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import log from 'electron-log';
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/** 单会话的 text_delta 节流状态 */
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interface ThrottleState {
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buffer: string;
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lastEventMeta: Pick<MetonaStreamEvent, 'requestId' | 'sessionId' | 'iteration' | 'seq' | 'timestamp' | 'runId'> | null;
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flushTimer: ReturnType<typeof setTimeout> | null;
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}
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/** 单会话的迭代录制状态（TRACE 层） */
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interface IterationTrace {
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iteration: number;
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startedAt: number;
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text: string;
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usage?: { input: number; output: number; total: number };
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responded: boolean; // 本轮 llm_response 是否已记录（PARSING 与下一轮 THINKING 去重）
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}
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export function registerAgentHandlers(ctx: IPCContext): void {
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const {
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agentEngineManager, sessionRecorder, configService, sessionService,
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workspaceService, contextBuilder, auditService, memoryManager,
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promptInjectionDefender, outputValidator, memoryConsolidator,
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sessionSummaryService, orchestrator, confirmationHook,
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} = ctx;
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// ===== 常驻事件管道：text_delta 按会话节流（F8） =====
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const throttleStates = new Map<string, ThrottleState>();
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const iterationTraces = new Map<string, IterationTrace>();
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const flushThrottle = (sessionId: string): void => {
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const st = throttleStates.get(sessionId);
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if (!st) return;
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st.flushTimer = null;
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if (!st.buffer || !st.lastEventMeta) {
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st.buffer = '';
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st.lastEventMeta = null;
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return;
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}
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// 构建合并的 text_delta 事件，保留最后一个 delta 的元数据
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const mergedEvent: MetonaStreamEvent = {
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...st.lastEventMeta,
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type: MetonaStreamEventType.TEXT_DELTA,
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delta: st.buffer,
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seq: st.lastEventMeta.seq,
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timestamp: Date.now(),
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};
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broadcast('agent:streamEvent', mergedEvent);
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st.buffer = '';
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st.lastEventMeta = null;
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};
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const cleanupSessionState = (sessionId: string): void => {
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const st = throttleStates.get(sessionId);
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if (st?.flushTimer) {
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clearTimeout(st.flushTimer);
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flushThrottle(sessionId);
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}
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throttleStates.delete(sessionId);
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iterationTraces.delete(sessionId);
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};
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// ===== 常驻监听：流式事件（节流转发 + TRACE 录制） =====
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agentEngineManager.on('streamEvent', (event: MetonaStreamEvent) => {
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if (!event.sessionId) return;
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const sessionId = event.sessionId;
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const trace = iterationTraces.get(sessionId);
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// F8: text_delta 聚合，其他事件立即转发（先 flush 保证顺序）
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if (event.type === MetonaStreamEventType.TEXT_DELTA && event.delta) {
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const st = throttleStates.get(sessionId) ?? {
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buffer: '', lastEventMeta: null, flushTimer: null,
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};
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throttleStates.set(sessionId, st);
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if (st.buffer === '') {
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st.lastEventMeta = {
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requestId: event.requestId,
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sessionId: event.sessionId,
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iteration: event.iteration,
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seq: event.seq,
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timestamp: event.timestamp,
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runId: event.runId,
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};
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} else if (st.lastEventMeta) {
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st.lastEventMeta = { ...st.lastEventMeta, seq: event.seq, timestamp: event.timestamp, runId: event.runId };
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}
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st.buffer += event.delta;
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if (st.flushTimer === null) {
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st.flushTimer = setTimeout(() => flushThrottle(sessionId), 32);
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}
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// TRACE: 累积本轮 LLM 文本（供 llm_response 记录）
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if (trace) trace.text += event.delta;
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return;
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}
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// 非 text_delta 事件：先 flush 缓冲区，再立即转发（保证事件顺序）
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const st = throttleStates.get(sessionId);
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if (st?.flushTimer) {
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clearTimeout(st.flushTimer);
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flushThrottle(sessionId);
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}
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// TRACE: 工具调用/结果/usage 录制（P1-6 补全）
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switch (event.type) {
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case MetonaStreamEventType.TOOL_CALL_COMPLETE:
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if (event.toolCall) {
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sessionRecorder.recordToolCall({
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sessionId,
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iteration: event.iteration,
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toolName: event.toolCall.name,
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args: event.toolCall.args,
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});
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}
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break;
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case MetonaStreamEventType.TOOL_RESULT:
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if (event.toolResult) {
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const resultPreview = typeof event.toolResult.result === 'string'
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? event.toolResult.result
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: JSON.stringify(event.toolResult.result);
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sessionRecorder.recordToolResult({
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sessionId,
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iteration: event.iteration,
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toolName: event.toolResult.toolName,
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success: event.toolResult.success,
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durationMs: event.toolResult.durationMs ?? 0,
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resultPreview,
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error: event.toolResult.error,
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});
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}
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break;
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case MetonaStreamEventType.USAGE:
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if (trace && event.usage) {
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trace.usage = {
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input: event.usage.inputTokens ?? 0,
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output: event.usage.outputTokens ?? 0,
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total: event.usage.totalTokens ?? 0,
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};
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}
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break;
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case MetonaStreamEventType.DONE:
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cleanupSessionState(sessionId);
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break;
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default:
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break;
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}
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broadcast('agent:streamEvent', event);
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});
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// ===== 常驻监听：状态变化（广播 + TRACE 迭代录制） =====
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agentEngineManager.on('stateChange', (data: {
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previous?: string; current?: string; state?: string;
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sessionId?: string; iteration?: number; runId?: string;
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}) => {
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if (data.previous) log.info(`[AGENT] State: ${data.previous} → ${data.current}`);
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broadcast('agent:stateChange', data);
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const sessionId = data.sessionId;
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if (!sessionId || data.iteration == null) return;
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const stateValue = data.state ?? data.current ?? '';
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const trace = iterationTraces.get(sessionId);
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// THINKING 且迭代号变化 → 新迭代开始（关闭上一迭代）
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if (stateValue === 'THINKING' && (!trace || trace.iteration !== data.iteration)) {
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if (trace && !trace.responded) {
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sessionRecorder.recordLLMResponse({
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sessionId,
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iteration: trace.iteration,
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content: trace.text,
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finishReason: 'stop',
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tokenUsage: trace.usage ?? { input: 0, output: 0, total: 0 },
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});
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}
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if (trace) {
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sessionRecorder.recordIterationEnd(sessionId, {
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iteration: trace.iteration,
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durationMs: Date.now() - trace.startedAt,
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});
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}
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iterationTraces.set(sessionId, {
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iteration: data.iteration,
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startedAt: Date.now(),
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text: '',
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responded: false,
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});
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sessionRecorder.recordIterationStart(sessionId, data.iteration);
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const provider = configService.get<string>('llm.provider') ?? '';
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const model = configService.get<string>('llm.model') ?? '';
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sessionRecorder.recordLLMRequest({
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sessionId,
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iteration: data.iteration,
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provider,
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model,
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messageCount: data.iteration + 1,
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});
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}
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// PARSING → 本轮流式结束，记录 llm_response
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if (stateValue === 'PARSING' && trace && trace.iteration === data.iteration && !trace.responded) {
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trace.responded = true;
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sessionRecorder.recordLLMResponse({
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sessionId,
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iteration: trace.iteration,
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content: trace.text,
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finishReason: 'stop',
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tokenUsage: trace.usage ?? { input: 0, output: 0, total: 0 },
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});
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}
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// TERMINATED → 补记最终迭代的 iteration_end（正常流程只在下一轮 THINKING 补记，
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// 最终轮无后续迭代，需在此补齐 TRACE 完整性）+ 兜底清理会话管道状态
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if (stateValue === 'TERMINATED') {
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if (trace) {
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sessionRecorder.recordIterationEnd(sessionId, {
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iteration: trace.iteration,
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durationMs: Date.now() - trace.startedAt,
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});
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}
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cleanupSessionState(sessionId);
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}
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});
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// ===== 常驻监听：上下文压缩（toast + streamEvent 通知） =====
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agentEngineManager.on('compressed', (data: {
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sessionId?: string; iteration?: number; originalTokens?: number; compressedTokens?: number;
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}) => {
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const savedTokens = Math.max(0, (data.originalTokens ?? 0) - (data.compressedTokens ?? 0));
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// toast 通知用户压缩已发生
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broadcast('toast:show', {
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type: 'info',
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message: `上下文压缩: ${data.originalTokens ?? '?'} → ${data.compressedTokens ?? '?'} tokens（节省 ${savedTokens}）`,
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});
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// 通过 streamEvent 转发，前端 useAgentStream 监听 'compressed' 类型后更新 store
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broadcast('agent:streamEvent', {
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type: 'compressed',
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sessionId: data.sessionId ?? '',
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iteration: data.iteration ?? 0,
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originalTokens: data.originalTokens,
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compressedTokens: data.compressedTokens,
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savedTokens,
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timestamp: Date.now(),
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});
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});
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// ===== 常驻监听：死循环检测（toast 警告） =====
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agentEngineManager.on('deadLoop', (data: { iteration?: number; sessionId?: string }) => {
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log.warn(`[AGENT] Dead loop detected at iteration ${data.iteration ?? '?'}`);
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broadcast('toast:show', {
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type: 'warning',
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message: `检测到死循环（第 ${data.iteration ?? '?'} 轮）：连续3轮重复相同工具调用，已自动终止`,
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});
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});
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// ===== 常驻监听：Provider 故障转移（P1，通知前端 + toast） =====
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agentEngineManager.on('providerSwitched', (data: {
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from?: string; to?: string; reason?: string; sessionId?: string;
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}) => {
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broadcast('agent:providerSwitched', {
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from: data.from,
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to: data.to,
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reason: data.reason ?? 'failover',
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sessionId: data.sessionId ?? '',
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});
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broadcast('toast:show', {
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type: 'warning',
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message: `Provider 故障转移: ${data.from ?? '?'} → ${data.to ?? '?'}（主 Provider 请求失败）`,
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});
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});
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// ===== Agent 消息发送 =====
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ipcMain.handle('agent:sendMessage', async (_event, userMessage: MetonaMessage, sessionId: string) => {
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// M-33 修复: 参数校验，防止 undefined/非字符串导致下游异常
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// P1-5 修复: 校验失败时也发 ERROR+DONE 流事件，防止 isStreaming 永久卡死
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const sendErrorEvent = (message: string, sid: string): void => {
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const errorEvent: MetonaStreamEvent = {
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type: MetonaStreamEventType.ERROR,
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requestId: '', sessionId: sid, iteration: 0, seq: 0, timestamp: Date.now(),
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error: { code: MetonaErrorCode.UNKNOWN, message, retryable: false },
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};
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broadcast('agent:streamEvent', errorEvent);
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broadcast('agent:streamEvent', { ...errorEvent, type: MetonaStreamEventType.DONE });
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};
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if (!sessionId || typeof sessionId !== 'string') {
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log.warn('[AGENT] sendMessage rejected: invalid sessionId');
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sendErrorEvent('无效的会话 ID', sessionId ?? '');
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return { success: false, error: 'Invalid sessionId' };
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}
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if (!userMessage || typeof userMessage !== 'object' || typeof userMessage.content !== 'string') {
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log.warn('[AGENT] sendMessage rejected: invalid userMessage');
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sendErrorEvent('无效的消息格式', sessionId);
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return { success: false, error: 'Invalid message format' };
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}
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log.info('[AGENT] sendMessage:', sessionId, (userMessage.content ?? '').slice(0, 80));
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// 发送消息前确保 Adapter 使用最新配置（失败则中止，防止用旧 Provider 的 adapter 发送）
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if (!ctx.reloadAdapter()) {
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const errorMsg = 'Adapter 加载失败，请检查 LLM 配置（Provider、API Key、Base URL、Model 是否完整）';
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log.error('[AGENT]', errorMsg);
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sendErrorEvent(errorMsg, sessionId);
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sessionRecorder.stopRecording(sessionId, { totalIterations: 0, totalTokens: 0, durationMs: 0, terminationReason: 'error' });
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return { success: false, error: errorMsg };
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}
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// TRACE 层：开始录制 / TOOL 层：记录会话开始
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sessionRecorder.startRecording(sessionId);
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auditService.logSessionStart(sessionId);
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// 保存用户消息到数据库
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sessionService.saveMessage({
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sessionId,
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role: 'user',
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content: userMessage.content,
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attachments: (userMessage as MetonaMessage & { attachments?: unknown[] }).attachments,
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});
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// P2-11: 分层加载历史——存在滚动摘要时只加载 [摘要 + 近期原文]
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const history = sessionSummaryService.buildHistoryMessages(sessionId).slice(0, -1);
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// 从工作空间文件构建 System Prompt
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const workspaceFiles = workspaceService.getFiles();
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const systemPrompt = contextBuilder.buildSystemPrompt(workspaceFiles, workspaceService.getPath());
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// v0.3.18 修复: SOUL.md 为空或不存在时降级到默认身份，向前端发 toast 提示用户
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if (contextBuilder.isUsingFallbackRole()) {
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broadcast('toast:show', {
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type: 'info',
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message: '未找到 SOUL.md 或内容为空，已使用默认 Metona 身份。可在工作空间根目录创建 SOUL.md 自定义 Agent 人格',
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});
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}
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// 检索与用户消息相关的记忆，注入到 System Prompt 动态区
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try {
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const memories = memoryManager.search(userMessage.content, { topK: 5, minImportance: 0.3 });
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if (memories.length > 0) {
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const memorySection = memories.map((m, i) =>
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`[${i + 1}] (${m.type}, 重要度: ${m.importance.toFixed(1)}) ${m.content.slice(0, 200)}`,
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).join('\n');
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const memoryBlock = `## Relevant Memories (Retrieved)\n${memorySection}`;
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systemPrompt.dynamicReminders = systemPrompt.dynamicReminders
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? `${systemPrompt.dynamicReminders}\n\n---\n\n${memoryBlock}`
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: memoryBlock;
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log.debug(`[AGENT] Injected ${memories.length} memories into system prompt`);
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}
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} catch (err) {
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log.warn('[AGENT] Memory retrieval failed, proceeding without memories:', err);
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}
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// 附件提示注入：用户直接上传的文件/图片，避免 LLM 误以为需要在工作空间查找
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const attachments = (userMessage as MetonaMessage & { attachments?: Array<{ name: string; type: string }> }).attachments;
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if (Array.isArray(attachments) && attachments.length > 0) {
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const attachmentList = attachments.map((att, i) => {
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const typeLabel = att.type === 'image' ? 'image' : att.type === 'text' ? 'text file' : 'file';
|
||
const note = att.type === 'image'
|
||
? 'already provided to you via vision capability — you can SEE it directly, do NOT call view_image or any tool to read it again'
|
||
: att.type === 'text'
|
||
? 'content already inlined in the user message, do NOT search in workspace or read it again'
|
||
: 'uploaded directly by user, do NOT search in workspace';
|
||
return `${i + 1}. [${typeLabel}] ${att.name} — ${note}`;
|
||
}).join('\n');
|
||
|
||
const attachmentBlock = `## User Attachments (Direct Upload)\nThe following files were uploaded directly by the user to this conversation. They are inline attachments, NOT workspace files:\n${attachmentList}\n\n**IMPORTANT**: Images listed above are already visible to you in this conversation. Do NOT call \`view_image\`, \`read_file\`, or any file tool to read them — doing so wastes a tool call and may fail (they are not workspace files).`;
|
||
|
||
systemPrompt.dynamicReminders = systemPrompt.dynamicReminders
|
||
? `${systemPrompt.dynamicReminders}\n\n---\n\n${attachmentBlock}`
|
||
: attachmentBlock;
|
||
|
||
log.debug(`[AGENT] Injected ${attachments.length} attachment hints into system prompt`);
|
||
}
|
||
|
||
try {
|
||
// 提示注入检测（安全模块）
|
||
const injectionResult = promptInjectionDefender.detect(userMessage.content);
|
||
if (injectionResult.riskScore >= 7) {
|
||
log.warn('[PromptInjectionDefender] Blocked message:', injectionResult.findings);
|
||
sendErrorEvent(`Message blocked by prompt injection defense: ${injectionResult.recommendation}`, sessionId);
|
||
sessionRecorder.stopRecording(sessionId, {
|
||
totalIterations: 0, totalTokens: 0, durationMs: 0, terminationReason: 'error',
|
||
});
|
||
return { success: false, error: 'Message blocked by prompt injection defense' };
|
||
}
|
||
if (injectionResult.riskScore >= 4) {
|
||
log.warn('[PromptInjectionDefender] Suspicious patterns detected:', injectionResult.findings);
|
||
}
|
||
|
||
// TRACE 层：记录上下文构建
|
||
sessionRecorder.recordContextBuilt(sessionId, {
|
||
tokenCount: estimateMessagesTokens(history),
|
||
usageRatio: 0,
|
||
});
|
||
|
||
// 启动 Agent Loop（P2-10: 每会话独立引擎）
|
||
const engine = agentEngineManager.getEngine(sessionId);
|
||
const output = await engine.runStream(userMessage, sessionId, history, systemPrompt);
|
||
|
||
// 输出验证（不阻塞响应，仅记录警告）
|
||
// v0.3.0 修复: 传入 toolResults 和 context，启用事实一致性检查和幻觉检测
|
||
try {
|
||
const toolResults = output.iterations
|
||
.flatMap((step) => step.toolResults ?? [])
|
||
.map((r) => (typeof r.result === 'string' ? r.result : JSON.stringify(r.result)));
|
||
const context = [...history, { role: 'user', content: userMessage.content }]
|
||
.map((m) => `${m.role}: ${m.content}`).join('\n');
|
||
const validation = await outputValidator.validate(output.finalAnswer, {
|
||
toolResults: toolResults.length > 0 ? toolResults : undefined,
|
||
context,
|
||
});
|
||
if (!validation.valid || validation.issues.length > 0) {
|
||
log.warn('[OutputValidator] Validation issues:', validation.issues);
|
||
}
|
||
log.debug(`[OutputValidator] Score: ${validation.score}, Valid: ${validation.valid}`);
|
||
} catch (err) {
|
||
log.error('[OutputValidator] Validation failed:', err);
|
||
}
|
||
|
||
// 保存每轮迭代的 assistant 消息到数据库（含思考内容和工具调用）
|
||
for (const step of output.iterations) {
|
||
if (!step.thought) continue;
|
||
|
||
const toolCallsWithResults = step.toolCalls?.map((tc) => {
|
||
const result = step.toolResults?.find((r) => r.toolCallId === tc.id);
|
||
return {
|
||
id: tc.id,
|
||
name: tc.name,
|
||
args: tc.args,
|
||
status: result?.success ? 'success' as const : 'error' as const,
|
||
result: result?.result,
|
||
durationMs: result?.durationMs,
|
||
error: result?.error,
|
||
};
|
||
});
|
||
|
||
// 只有当有内容、思考内容或工具调用时才保存
|
||
if (step.thought.content || step.thought.reasoningContent || toolCallsWithResults?.length) {
|
||
// C-6 修复: assistant 消息仅有 tool_calls 时 content 必须为 null（而非空字符串）
|
||
const assistantContent = (toolCallsWithResults?.length && !step.thought.content)
|
||
? null
|
||
: step.thought.content;
|
||
sessionService.saveMessage({
|
||
sessionId,
|
||
role: 'assistant',
|
||
content: assistantContent,
|
||
reasoningContent: step.thought.reasoningContent || undefined,
|
||
toolCalls: toolCallsWithResults,
|
||
iteration: step.iteration,
|
||
});
|
||
}
|
||
|
||
// v0.3.0 修复: 保存 tool 结果消息到数据库
|
||
// OpenAI 兼容 API 要求 assistant 消息有 tool_calls 时，后续必须有对应的 tool 结果消息
|
||
if (step.toolResults) {
|
||
for (const result of step.toolResults) {
|
||
const resultContent = typeof result.result === 'string'
|
||
? result.result
|
||
: JSON.stringify(result.result);
|
||
sessionService.saveMessage({
|
||
sessionId,
|
||
role: 'tool',
|
||
content: result.error ?? resultContent,
|
||
toolResult: result,
|
||
iteration: step.iteration,
|
||
});
|
||
}
|
||
}
|
||
}
|
||
|
||
// 更新 Token 统计
|
||
if (output.totalTokenUsage.totalTokens > 0) {
|
||
sessionService.updateTokenUsage(sessionId, output.totalTokenUsage.totalTokens);
|
||
}
|
||
|
||
// 更新 MEMORY.md 时间戳
|
||
workspaceService.updateMemoryTimestamp();
|
||
|
||
// 会话结束：AI 判断本次对话有哪些重要内容需要持久化到 MEMORY.md
|
||
// 异步执行，不阻塞主流程返回；失败仅记录日志
|
||
memoryConsolidator
|
||
.consolidate(userMessage.content, output.finalAnswer, output.iterations)
|
||
.then((result) => {
|
||
if (result.appended > 0) {
|
||
log.info(`[AGENT] Memory consolidated: ${result.appended} entries appended to MEMORY.md`);
|
||
broadcast('toast:show', {
|
||
type: 'info',
|
||
message: `AI 已将 ${result.appended} 条重要记忆写入 MEMORY.md`,
|
||
});
|
||
}
|
||
})
|
||
.catch((err) => {
|
||
log.warn('[AGENT] Memory consolidation failed:', err);
|
||
});
|
||
|
||
// TOOL 层：记录会话结束 / TRACE 层：停止录制
|
||
auditService.logSessionEnd({
|
||
sessionId,
|
||
totalIterations: output.iterations.length,
|
||
totalTokens: output.totalTokenUsage.totalTokens,
|
||
durationMs: output.durationMs,
|
||
terminationReason: output.terminationReason,
|
||
});
|
||
sessionRecorder.stopRecording(sessionId, {
|
||
totalIterations: output.iterations.length,
|
||
totalTokens: output.totalTokenUsage.totalTokens,
|
||
durationMs: output.durationMs,
|
||
terminationReason: output.terminationReason,
|
||
});
|
||
|
||
// P2-11: 会话结束后评估滚动摘要（fire-and-forget，失败仅记录）
|
||
sessionSummaryService.maybeSummarize(sessionId).catch((err) => {
|
||
log.warn('[AGENT] Session summary generation failed:', err);
|
||
});
|
||
|
||
log.info(`[AGENT] Completed: ${output.terminationReason}, ${output.iterations.length} iterations, ${output.durationMs}ms`);
|
||
|
||
return { success: true };
|
||
} catch (error) {
|
||
log.error('[AGENT] Error:', error);
|
||
|
||
// TOOL 层：记录错误
|
||
auditService.log({
|
||
sessionId,
|
||
eventType: 'error',
|
||
actor: 'agent',
|
||
target: 'agent_loop',
|
||
details: { error: (error as Error).message },
|
||
outcome: 'error',
|
||
});
|
||
|
||
// TRACE 层：停止录制
|
||
sessionRecorder.stopRecording(sessionId, {
|
||
totalIterations: 0, totalTokens: 0, durationMs: 0, terminationReason: 'error',
|
||
});
|
||
|
||
// 发送错误事件到 UI
|
||
const metonaError: MetonaError = {
|
||
code: MetonaErrorCode.UNKNOWN,
|
||
message: (error as Error).message,
|
||
retryable: false,
|
||
};
|
||
broadcast('agent:streamEvent', {
|
||
type: MetonaStreamEventType.ERROR,
|
||
requestId: '', sessionId, iteration: 0, seq: 0, timestamp: Date.now(),
|
||
error: metonaError,
|
||
} satisfies MetonaStreamEvent);
|
||
|
||
return { success: false, error: (error as Error).message };
|
||
}
|
||
});
|
||
|
||
// ===== 中断会话 =====
|
||
|
||
ipcMain.handle('agent:abortSession', async (_event, sessionId) => {
|
||
log.info('[AGENT] Abort:', sessionId);
|
||
// P2-10: 联动中断该会话派生的所有 SubAgent（消除"会话停了子任务还在跑"）
|
||
orchestrator.abortByParent(sessionId);
|
||
agentEngineManager.abort(sessionId);
|
||
// MT-1 修复: 等待当前 run 完全结束再返回，防止用户立即重发时新消息卡在等待中
|
||
await agentEngineManager.waitForAbort(sessionId);
|
||
// v0.3.0 修复: 清理所有等待中的工具确认，避免定时器泄漏和超时 toast 在新会话中弹出
|
||
confirmationHook.clearPending();
|
||
|
||
// TOOL 层：记录中断
|
||
auditService.log({
|
||
sessionId,
|
||
eventType: 'session_end',
|
||
actor: 'user',
|
||
target: 'session',
|
||
details: { reason: 'user_abort' },
|
||
outcome: 'denied',
|
||
});
|
||
|
||
return { success: true };
|
||
});
|
||
}
|