refactor: 全面清理死代码 — 删除 348 行无用代码
删除文件: - training-export.ts: 训练数据导出（零引用，UI 已移除） 删除函数: - workspace.ts: isProcessAlive, getActiveProcessCount, execWorkspaceCommand, terminateWorkspaceCommand - sqlite.ts: deleteMessagesBySession, getSkill, closeDatabase - tool-registry.ts: isToolEnabled - cron-manager.ts: clearAllTimers - workspace-panel.ts: setOnToolTerminated, setWorkspaceDirPath 删除 UI: - index.html: 训练数据导出按钮及说明 - settings-modal.ts: 训练数据导出事件绑定
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thzxx
@@ -151,15 +151,6 @@ export function initSettingsModal(): void {
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logSetting('检查间隔', `${ms / 60000} 分钟`);
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});
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// ── v5.0 训练数据导出 ──
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document.querySelector('#btnExportTraining')!.addEventListener('click', async () => {
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const { saveTrainingData } = await import('../services/training-export.js');
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showToast('正在导出训练数据...', 'info');
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const ok = await saveTrainingData();
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if (ok) showToast('训练数据导出成功', 'success');
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else showToast('导出取消或无数据', 'warning');
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});
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// ── v5.0 Cron 定时任务 ──
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document.querySelector('#btnAddCronTask')!.addEventListener('click', async () => {
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const name = (document.querySelector('#inputCronName') as HTMLInputElement).value.trim();
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@@ -44,10 +44,6 @@ let currentAiCommand: string | null = null;
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/** 终止通知回调（由外部设置） */
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let onToolTerminated: ((command: string) => void) | null = null;
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/** 设置终止通知回调 */
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export function setOnToolTerminated(cb: (command: string) => void): void {
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onToolTerminated = cb;
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}
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function genId(): string {
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return `ws_${Date.now()}_${++_counter}`;
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@@ -628,17 +624,3 @@ export function getWorkspaceDirPath(): string {
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return workspaceDir;
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}
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/** 设置工作空间目录 */
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export async function setWorkspaceDirPath(dir: string): Promise<boolean> {
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const bridge = window.metonaDesktop;
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if (!bridge?.isDesktop) return false;
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const result = await bridge.workspace.setDir(dir);
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if (result.success && result.dir) {
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workspaceDir = result.dir;
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currentFileDir = workspaceDir;
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logInfo('工作空间目录已更新', workspaceDir);
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return true;
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}
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return false;
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}
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@@ -347,11 +347,6 @@
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<button class="btn btn-outline" id="btnDoctor" style="margin-bottom:8px;">🩺 一键诊断</button>
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<div id="doctorResults" style="display:none;margin-top:8px;padding:10px;background:var(--bg-layer);border-radius:var(--radius-control);font-size:12px;max-height:200px;overflow-y:auto;"></div>
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</div>
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<div class="setting-group">
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<label class="setting-label">📚 训练数据导出</label>
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<button class="btn btn-outline" id="btnExportTraining" style="margin-bottom:4px;">📥 导出训练数据 (JSONL)</button>
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<p class="text-muted" style="margin-top:4px;font-size:11px;">将 Agent 执行轨迹导出为 SFT 格式，可用于模型微调训练。包含成功的工具调用链和对话记录。</p>
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</div>
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<div class="setting-group">
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<label class="setting-label">⏰ 定时任务 (Cron)</label>
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<div style="display:flex;gap:8px;margin-bottom:8px;">
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@@ -183,12 +183,3 @@ export async function restoreCronTasks(): Promise<void> {
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logInfo(`定时任务已恢复: ${scheduled} 个任务`);
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}
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}
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/**
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* 清理所有定时器（应用退出时调用）
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*/
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export function clearAllTimers(): void {
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for (const [id] of activeTimers) {
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clearTimer(id);
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}
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}
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@@ -572,9 +572,6 @@ export function setToolEnabled(toolName: string, enabled: boolean): void {
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else enabledTools.delete(toolName);
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}
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export function isToolEnabled(toolName: string): boolean {
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return enabledTools.has(toolName);
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}
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export function getEnabledToolDefinitions(): ToolDefinition[] {
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const builtIn = TOOL_DEFINITIONS.filter(def => enabledTools.has(def.function.name));
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@@ -1,130 +0,0 @@
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/**
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* TrainingExport - 训练数据导出 (v5.0)
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* 将 Agent 执行轨迹转换为 SFT 训练数据格式
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*/
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import { state, KEYS } from '../state/state.js';
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import { logInfo, logSuccess, logError } from './log-service.js';
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interface SFTRecord {
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instruction: string;
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input: string;
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output: string;
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tools?: Array<{ name: string; arguments: Record<string, unknown> }>;
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observations?: string[];
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metadata?: {
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session_id: string;
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session_title: string;
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timestamp: number;
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model: string;
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eval_count?: number;
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total_duration?: number;
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};
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}
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/**
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* 导出所有会话的训练数据
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* 从 traces + messages 中提取成功的工具调用链
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*/
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export async function exportTrainingData(): Promise<string | null> {
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const bridge = (window as any).metonaDesktop;
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if (!bridge?.db) return null;
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try {
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const sessions = await bridge.db.getAllSessions();
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const records: SFTRecord[] = [];
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for (const session of sessions) {
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const messages = await bridge.db.getMessages(session.id);
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const traces = await bridge.db.getTraces(session.id);
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// 遍历消息对（user → assistant）
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for (let i = 0; i < messages.length - 1; i++) {
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const userMsg = messages[i];
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const asstMsg = messages[i + 1];
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if (userMsg.role !== 'user' || asstMsg.role !== 'assistant') continue;
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if (!userMsg.content || !asstMsg.content) continue;
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// 解析工具调用
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let tools: Array<{ name: string; arguments: Record<string, unknown> }> | undefined;
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let observations: string[] | undefined;
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if (asstMsg.tool_calls) {
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try {
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const toolCalls = JSON.parse(asstMsg.tool_calls);
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if (Array.isArray(toolCalls) && toolCalls.length > 0) {
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tools = toolCalls.map((tc: any) => ({
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name: tc.name || tc.function?.name || 'unknown',
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arguments: tc.arguments || tc.function?.arguments || {}
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}));
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}
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} catch { /* ignore */ }
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}
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// 从 traces 中提取 observation
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const sessionTraces = traces.filter(t =>
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t.created_at >= userMsg.created_at && t.created_at <= asstMsg.created_at
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);
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if (sessionTraces.length > 0) {
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observations = sessionTraces.map(t => t.observation || '').filter(Boolean);
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}
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records.push({
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instruction: userMsg.content,
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input: '',
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output: asstMsg.content,
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...(tools && { tools }),
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...(observations?.length && { observations }),
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metadata: {
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session_id: session.id,
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session_title: session.title,
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timestamp: userMsg.created_at,
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model: session.model,
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...(asstMsg.eval_count && { eval_count: asstMsg.eval_count }),
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...(asstMsg.total_duration && { total_duration: asstMsg.total_duration })
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}
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});
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i++; // 跳过 assistant 消息
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}
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}
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if (records.length === 0) {
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logInfo('训练数据导出: 无可导出数据');
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return null;
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}
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logSuccess(`训练数据导出完成: ${records.length} 条记录`);
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return records.map(r => JSON.stringify(r)).join('\n');
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} catch (err) {
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logError('训练数据导出失败', (err as Error).message);
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return null;
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}
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}
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/**
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* 保存训练数据到文件
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*/
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export async function saveTrainingData(): Promise<boolean> {
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const bridge = (window as any).metonaDesktop;
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if (!bridge?.dialog?.saveFile) return false;
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const data = await exportTrainingData();
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if (!data) return false;
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try {
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const filePath = await bridge.dialog.saveFile({
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defaultPath: `metona-training-data-${new Date().toISOString().slice(0, 10)}.jsonl`,
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filters: [{ name: 'JSONL', extensions: ['jsonl'] }, { name: 'JSON', extensions: ['json'] }]
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});
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if (!filePath) return false;
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await bridge.fs.writeFile(filePath, data);
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logSuccess(`训练数据已保存: ${filePath}`);
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return true;
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} catch (err) {
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logError('保存训练数据失败', (err as Error).message);
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return false;
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}
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}
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