mirror of
https://github.com/hellodigua/ChatLab.git
synced 2026-05-18 12:28:56 +08:00
digua
823 lines
24 KiB
TypeScript
823 lines
24 KiB
TypeScript
// electron/main/ipc/ai.ts
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import { ipcMain, BrowserWindow, shell } from 'electron'
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import * as fs from 'fs'
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import * as path from 'path'
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import * as aiConversations from '../ai/conversations'
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import * as llm from '../ai/llm'
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import * as rag from '../ai/rag'
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import { aiLogger } from '../ai/logger'
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import { getLogsDir } from '../paths'
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import { Agent, type AgentStreamChunk, type PromptConfig } from '../ai/agent'
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import { t } from '../i18n'
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import type { ToolContext } from '../ai/tools/types'
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import type { IpcContext } from './types'
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// ==================== AI Agent 请求追踪 ====================
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// 用于跟踪活跃的 Agent 请求，支持中止操作
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const activeAgentRequests = new Map<string, AbortController>()
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/**
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* 格式化 AI 报错信息，输出更友好的提示
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*/
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function formatAIError(error: unknown): string {
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const candidates: unknown[] = []
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if (error) {
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candidates.push(error)
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}
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const errorObj = error as {
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lastError?: unknown
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errors?: unknown[]
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}
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if (errorObj?.lastError) {
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candidates.push(errorObj.lastError)
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}
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if (Array.isArray(errorObj?.errors)) {
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candidates.push(...errorObj.errors)
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}
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let rawMessage = ''
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let statusCode: number | undefined
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let retrySeconds: number | undefined
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for (const candidate of candidates) {
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if (!candidate || typeof candidate !== 'object') {
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if (!rawMessage && typeof candidate === 'string') {
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rawMessage = candidate
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}
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continue
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}
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const record = candidate as Record<string, unknown>
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if (typeof record.statusCode === 'number') {
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statusCode = record.statusCode
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}
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if (!rawMessage && typeof record.message === 'string') {
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rawMessage = record.message
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}
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if (!rawMessage && record.data && typeof record.data === 'object') {
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const data = record.data as { error?: { message?: string } }
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if (data.error?.message) {
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rawMessage = data.error.message
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}
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}
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if (record.responseBody && typeof record.responseBody === 'string') {
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const responseBody = record.responseBody
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try {
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const parsed = JSON.parse(responseBody) as { error?: { message?: string } }
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if (!rawMessage && parsed.error?.message) {
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rawMessage = parsed.error.message
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}
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} catch {
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if (!rawMessage) {
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rawMessage = responseBody
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}
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}
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}
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if (rawMessage) {
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const retryMatch = rawMessage.match(/retry in ([0-9.]+)s/i)
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if (retryMatch) {
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retrySeconds = Math.ceil(Number(retryMatch[1]))
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}
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}
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}
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const fallbackMessage = rawMessage || String(error)
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const lowerMessage = fallbackMessage.toLowerCase()
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if (statusCode === 429 || lowerMessage.includes('quota') || lowerMessage.includes('resource_exhausted')) {
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return retrySeconds
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? `Gemini 配额已用尽，请等待 ${retrySeconds} 秒后重试，或更换/升级配额。`
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: 'Gemini 配额已用尽，请稍后重试或更换/升级配额。'
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}
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if (statusCode === 503 || lowerMessage.includes('overloaded') || lowerMessage.includes('unavailable')) {
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return 'Gemini 模型繁忙，请稍后重试。'
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}
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if (fallbackMessage.length > 300) {
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return `${fallbackMessage.slice(0, 300)}...`
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}
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return fallbackMessage
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}
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export function registerAIHandlers({ win }: IpcContext): void {
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console.log('[IPC] Registering AI handlers...')
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// ==================== AI 对话管理 ====================
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/**
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* 创建新的 AI 对话
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*/
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ipcMain.handle(
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'ai:createConversation',
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async (
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_,
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title: string,
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sessionId?: string,
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dataSource?: { type: 'chat' | 'member'; id: string; name?: string }
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) => {
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try {
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return aiConversations.createConversation(title, sessionId, dataSource)
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} catch (error) {
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console.error('创建 AI 对话失败：', error)
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throw error
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}
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}
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)
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/**
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* 获取所有 AI 对话列表
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*/
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ipcMain.handle('ai:getConversations', async (_, sessionId?: string) => {
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try {
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return aiConversations.getConversations(sessionId)
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} catch (error) {
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console.error('获取 AI 对话列表失败：', error)
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return []
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}
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})
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/**
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* 打开当前 AI 日志文件并定位到文件
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*/
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ipcMain.handle('ai:showLogFile', async () => {
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try {
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// 优先使用当前已存在的日志文件，避免创建新的空日志
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const existingLogPath = aiLogger.getExistingLogPath()
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if (existingLogPath) {
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shell.showItemInFolder(existingLogPath)
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return { success: true, path: existingLogPath }
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}
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const logDir = path.join(getLogsDir(), 'ai')
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if (!fs.existsSync(logDir)) {
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return { success: false, error: '暂无 AI 日志文件' }
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}
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const logFiles = fs.readdirSync(logDir).filter((name) => name.startsWith('ai_') && name.endsWith('.log'))
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if (logFiles.length === 0) {
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return { success: false, error: '暂无 AI 日志文件' }
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}
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// 选择最近修改的日志文件
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const latestLog = logFiles
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.map((name) => {
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const filePath = path.join(logDir, name)
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const stat = fs.statSync(filePath)
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return { path: filePath, mtimeMs: stat.mtimeMs }
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})
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.sort((a, b) => b.mtimeMs - a.mtimeMs)[0]
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shell.showItemInFolder(latestLog.path)
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return { success: true, path: latestLog.path }
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} catch (error) {
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console.error('打开 AI 日志文件失败：', error)
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return { success: false, error: String(error) }
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}
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})
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/**
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* 获取单个对话详情
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*/
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ipcMain.handle('ai:getConversation', async (_, conversationId: string) => {
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try {
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return aiConversations.getConversation(conversationId)
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} catch (error) {
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console.error('获取 AI 对话详情失败：', error)
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return null
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}
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})
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/**
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* 更新 AI 对话标题
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*/
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ipcMain.handle('ai:updateConversationTitle', async (_, conversationId: string, title: string) => {
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try {
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return aiConversations.updateConversationTitle(conversationId, title)
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} catch (error) {
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console.error('更新 AI 对话标题失败：', error)
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return false
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}
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})
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/**
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* 删除 AI 对话
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*/
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ipcMain.handle('ai:deleteConversation', async (_, conversationId: string) => {
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try {
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return aiConversations.deleteConversation(conversationId)
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} catch (error) {
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console.error('删除 AI 对话失败：', error)
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return false
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}
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})
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/**
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* 添加 AI 消息
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*/
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ipcMain.handle(
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'ai:addMessage',
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async (
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_,
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conversationId: string,
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role: 'user' | 'assistant',
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content: string,
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dataKeywords?: string[],
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dataMessageCount?: number,
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contentBlocks?: aiConversations.ContentBlock[]
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) => {
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try {
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return aiConversations.addMessage(conversationId, role, content, dataKeywords, dataMessageCount, contentBlocks)
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} catch (error) {
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console.error('添加 AI 消息失败：', error)
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throw error
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}
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}
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)
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/**
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* 获取 AI 对话的所有消息
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*/
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ipcMain.handle('ai:getMessages', async (_, conversationId: string) => {
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try {
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return aiConversations.getMessages(conversationId)
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} catch (error) {
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console.error('获取 AI 消息失败：', error)
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return []
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}
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})
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/**
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* 删除 AI 消息
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*/
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ipcMain.handle('ai:deleteMessage', async (_, messageId: string) => {
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try {
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return aiConversations.deleteMessage(messageId)
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} catch (error) {
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console.error('删除 AI 消息失败：', error)
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return false
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}
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})
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// ==================== LLM 服务（多配置管理）====================
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/**
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* 获取所有支持的 LLM 提供商
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*/
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ipcMain.handle('llm:getProviders', async () => {
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return llm.PROVIDERS
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})
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/**
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* 获取所有配置列表
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*/
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ipcMain.handle('llm:getAllConfigs', async () => {
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const configs = llm.getAllConfigs()
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// 返回 API Key
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return configs.map((c) => ({
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...c,
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apiKeySet: !!c.apiKey,
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}))
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})
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/**
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* 获取当前激活的配置 ID
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*/
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ipcMain.handle('llm:getActiveConfigId', async () => {
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const config = llm.getActiveConfig()
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return config?.id || null
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})
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/**
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* 添加新配置
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*/
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ipcMain.handle(
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'llm:addConfig',
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async (
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_,
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config: {
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name: string
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provider: llm.LLMProvider
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apiKey: string
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model?: string
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baseUrl?: string
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maxTokens?: number
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}
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) => {
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try {
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const result = llm.addConfig(config)
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if (result.success && result.config) {
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return {
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success: true,
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config: {
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...result.config,
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apiKeySet: !!result.config.apiKey,
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},
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}
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}
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return result
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} catch (error) {
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console.error('添加 LLM 配置失败：', error)
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return { success: false, error: String(error) }
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}
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}
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)
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/**
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* 更新配置
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*/
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ipcMain.handle(
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'llm:updateConfig',
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async (
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_,
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id: string,
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updates: {
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name?: string
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provider?: llm.LLMProvider
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apiKey?: string
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model?: string
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baseUrl?: string
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maxTokens?: number
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}
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) => {
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try {
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// 如果 apiKey 为空字符串，表示不更新 API Key
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const cleanUpdates = { ...updates }
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if (cleanUpdates.apiKey === '') {
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delete cleanUpdates.apiKey
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}
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return llm.updateConfig(id, cleanUpdates)
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} catch (error) {
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console.error('更新 LLM 配置失败：', error)
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return { success: false, error: String(error) }
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}
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}
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)
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/**
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* 删除配置
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*/
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ipcMain.handle('llm:deleteConfig', async (_, id?: string) => {
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try {
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// 如果没有传 id，删除当前激活的配置
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if (!id) {
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const activeConfig = llm.getActiveConfig()
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if (activeConfig) {
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return llm.deleteConfig(activeConfig.id)
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}
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return { success: false, error: t('llm.noActiveConfig') }
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}
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return llm.deleteConfig(id)
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} catch (error) {
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console.error('删除 LLM 配置失败：', error)
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return { success: false, error: String(error) }
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}
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})
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/**
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* 设置激活的配置
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*/
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ipcMain.handle('llm:setActiveConfig', async (_, id: string) => {
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try {
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return llm.setActiveConfig(id)
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} catch (error) {
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console.error('设置激活配置失败：', error)
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return { success: false, error: String(error) }
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}
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})
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/**
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* 验证 API Key（支持自定义 baseUrl 和 model）
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* 返回对象格式：{ success: boolean, error?: string }
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*/
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ipcMain.handle(
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'llm:validateApiKey',
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async (_, provider: llm.LLMProvider, apiKey: string, baseUrl?: string, model?: string) => {
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console.log('[LLM:validateApiKey] 开始验证:', { provider, baseUrl, model, apiKeyLength: apiKey?.length })
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try {
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const service = llm.createLLMService({ provider, apiKey, baseUrl, model })
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const result = await service.validateApiKey()
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console.log('[LLM:validateApiKey] 验证结果:', result)
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return { success: result.success, error: result.error }
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} catch (error) {
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console.error('[LLM:validateApiKey] 验证失败：', error)
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// 提取有意义的错误信息
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const errorMessage = error instanceof Error ? error.message : String(error)
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return { success: false, error: errorMessage }
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}
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}
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)
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/**
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* 检查是否已配置 LLM（是否有激活的配置）
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*/
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ipcMain.handle('llm:hasConfig', async () => {
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return llm.hasActiveConfig()
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})
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/**
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* 发送 LLM 聊天请求（非流式）
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*/
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ipcMain.handle('llm:chat', async (_, messages: llm.ChatMessage[], options?: llm.ChatOptions) => {
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aiLogger.info('IPC', '收到非流式 LLM 请求', {
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messagesCount: messages.length,
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firstMsgRole: messages[0]?.role,
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firstMsgContentLen: messages[0]?.content?.length,
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options,
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})
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try {
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const response = await llm.chat(messages, options)
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aiLogger.info('IPC', '非流式 LLM 请求成功', { responseLength: response.length })
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return { success: true, content: response }
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} catch (error) {
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aiLogger.error('IPC', '非流式 LLM 请求失败', { error: String(error) })
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console.error('LLM 聊天失败：', error)
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return { success: false, error: String(error) }
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}
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})
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/**
|
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* 发送 LLM 聊天请求（流式）
|
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* 使用 IPC 事件发送流式数据
|
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*/
|
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ipcMain.handle(
|
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'llm:chatStream',
|
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async (_, requestId: string, messages: llm.ChatMessage[], options?: llm.ChatOptions) => {
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aiLogger.info('IPC', `收到流式聊天请求: ${requestId}`, {
|
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messagesCount: messages.length,
|
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options,
|
||
})
|
||
|
||
try {
|
||
const generator = llm.chatStream(messages, options)
|
||
aiLogger.info('IPC', `创建流式生成器: ${requestId}`)
|
||
|
||
// 异步处理流式响应
|
||
;(async () => {
|
||
let chunkIndex = 0
|
||
try {
|
||
aiLogger.info('IPC', `开始迭代流式响应: ${requestId}`)
|
||
for await (const chunk of generator) {
|
||
chunkIndex++
|
||
aiLogger.debug('IPC', `发送 chunk #${chunkIndex}: ${requestId}`, {
|
||
contentLength: chunk.content?.length,
|
||
isFinished: chunk.isFinished,
|
||
finishReason: chunk.finishReason,
|
||
})
|
||
win.webContents.send('llm:streamChunk', { requestId, chunk })
|
||
}
|
||
aiLogger.info('IPC', `流式响应完成: ${requestId}`, { totalChunks: chunkIndex })
|
||
} catch (error) {
|
||
aiLogger.error('IPC', `流式响应出错: ${requestId}`, {
|
||
error: String(error),
|
||
chunkIndex,
|
||
})
|
||
win.webContents.send('llm:streamChunk', {
|
||
requestId,
|
||
chunk: { content: '', isFinished: true, finishReason: 'error' },
|
||
error: String(error),
|
||
})
|
||
}
|
||
})()
|
||
|
||
return { success: true }
|
||
} catch (error) {
|
||
aiLogger.error('IPC', `创建流式请求失败: ${requestId}`, { error: String(error) })
|
||
console.error('LLM 流式聊天失败：', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
}
|
||
)
|
||
|
||
// ==================== AI Agent API ====================
|
||
|
||
/**
|
||
* 执行 Agent 对话（流式）
|
||
* Agent 会自动调用工具并返回最终结果
|
||
* @param historyMessages 对话历史（可选，用于上下文关联）
|
||
* @param chatType 聊天类型（'group' | 'private'）
|
||
* @param promptConfig 用户自定义提示词配置（可选）
|
||
* @param locale 语言设置（可选，默认 'zh-CN'）
|
||
*/
|
||
ipcMain.handle(
|
||
'agent:runStream',
|
||
async (
|
||
_,
|
||
requestId: string,
|
||
userMessage: string,
|
||
context: ToolContext,
|
||
historyMessages?: Array<{ role: 'user' | 'assistant'; content: string }>,
|
||
chatType?: 'group' | 'private',
|
||
promptConfig?: PromptConfig,
|
||
locale?: string
|
||
) => {
|
||
aiLogger.info('IPC', `收到 Agent 流式请求: ${requestId}`, {
|
||
userMessage: userMessage.slice(0, 100),
|
||
sessionId: context.sessionId,
|
||
historyLength: historyMessages?.length ?? 0,
|
||
chatType: chatType ?? 'group',
|
||
hasPromptConfig: !!promptConfig,
|
||
})
|
||
|
||
try {
|
||
// 创建 AbortController 并存储
|
||
const abortController = new AbortController()
|
||
activeAgentRequests.set(requestId, abortController)
|
||
|
||
// 转换历史消息格式
|
||
const formattedHistory =
|
||
historyMessages?.map((msg) => ({
|
||
role: msg.role as 'user' | 'assistant',
|
||
content: msg.content,
|
||
})) ?? []
|
||
|
||
const agent = new Agent(
|
||
context,
|
||
{ abortSignal: abortController.signal },
|
||
formattedHistory,
|
||
chatType ?? 'group',
|
||
promptConfig,
|
||
locale ?? 'zh-CN'
|
||
)
|
||
|
||
// 异步执行，通过事件发送流式数据
|
||
;(async () => {
|
||
try {
|
||
const result = await agent.executeStream(userMessage, (chunk: AgentStreamChunk) => {
|
||
// 如果已中止，不再发送
|
||
if (abortController.signal.aborted) {
|
||
return
|
||
}
|
||
// 减少日志噪音：只在工具调用时记录
|
||
if (chunk.type === 'tool_start' || chunk.type === 'tool_result') {
|
||
aiLogger.debug('IPC', `Agent chunk: ${requestId}`, {
|
||
type: chunk.type,
|
||
toolName: chunk.toolName,
|
||
})
|
||
}
|
||
win.webContents.send('agent:streamChunk', { requestId, chunk })
|
||
})
|
||
|
||
// 如果已中止，不发送完成信息
|
||
if (abortController.signal.aborted) {
|
||
aiLogger.info('IPC', `Agent 已中止，跳过完成信息: ${requestId}`)
|
||
return
|
||
}
|
||
|
||
// 发送完成信息
|
||
win.webContents.send('agent:complete', {
|
||
requestId,
|
||
result: {
|
||
content: result.content,
|
||
toolsUsed: result.toolsUsed,
|
||
toolRounds: result.toolRounds,
|
||
totalUsage: result.totalUsage,
|
||
},
|
||
})
|
||
|
||
aiLogger.info('IPC', `Agent 执行完成: ${requestId}`, {
|
||
toolsUsed: result.toolsUsed,
|
||
toolRounds: result.toolRounds,
|
||
contentLength: result.content.length,
|
||
totalUsage: result.totalUsage,
|
||
})
|
||
} catch (error) {
|
||
// 如果是中止错误，不报告为错误
|
||
if (error instanceof Error && error.name === 'AbortError') {
|
||
aiLogger.info('IPC', `Agent 请求已中止: ${requestId}`)
|
||
return
|
||
}
|
||
const friendlyError = formatAIError(error)
|
||
aiLogger.error('IPC', `Agent 执行出错: ${requestId}`, {
|
||
error: String(error),
|
||
friendlyError,
|
||
})
|
||
// 发送错误 chunk
|
||
win.webContents.send('agent:streamChunk', {
|
||
requestId,
|
||
chunk: { type: 'error', error: friendlyError, isFinished: true },
|
||
})
|
||
// 发送完成事件（带错误信息），确保前端 promise 能 resolve
|
||
win.webContents.send('agent:complete', {
|
||
requestId,
|
||
result: {
|
||
content: '',
|
||
toolsUsed: [],
|
||
toolRounds: 0,
|
||
totalUsage: { promptTokens: 0, completionTokens: 0, totalTokens: 0 },
|
||
error: friendlyError,
|
||
},
|
||
})
|
||
} finally {
|
||
// 清理请求追踪
|
||
activeAgentRequests.delete(requestId)
|
||
}
|
||
})()
|
||
|
||
return { success: true }
|
||
} catch (error) {
|
||
aiLogger.error('IPC', `创建 Agent 请求失败: ${requestId}`, { error: String(error) })
|
||
return { success: false, error: String(error) }
|
||
}
|
||
}
|
||
)
|
||
|
||
/**
|
||
* 中止 Agent 请求
|
||
*/
|
||
ipcMain.handle('agent:abort', async (_, requestId: string) => {
|
||
aiLogger.info('IPC', `收到中止请求: ${requestId}`)
|
||
|
||
const abortController = activeAgentRequests.get(requestId)
|
||
if (abortController) {
|
||
abortController.abort()
|
||
activeAgentRequests.delete(requestId)
|
||
aiLogger.info('IPC', `已中止 Agent 请求: ${requestId}`)
|
||
return { success: true }
|
||
} else {
|
||
aiLogger.warn('IPC', `未找到 Agent 请求: ${requestId}`)
|
||
return { success: false, error: '未找到该请求' }
|
||
}
|
||
})
|
||
|
||
// ==================== Embedding 多配置管理 ====================
|
||
|
||
/**
|
||
* 获取所有 Embedding 配置（展示用，隐藏 apiKey）
|
||
*/
|
||
ipcMain.handle('embedding:getAllConfigs', async () => {
|
||
try {
|
||
const configs = rag.getAllEmbeddingConfigs()
|
||
// 隐藏敏感信息
|
||
return configs.map((c) => ({
|
||
...c,
|
||
apiKey: undefined,
|
||
apiKeySet: !!c.apiKey,
|
||
}))
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '获取 Embedding 配置失败', error)
|
||
return []
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 获取单个 Embedding 配置（用于编辑，包含完整信息）
|
||
*/
|
||
ipcMain.handle('embedding:getConfig', async (_, id: string) => {
|
||
try {
|
||
return rag.getEmbeddingConfigById(id)
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '获取 Embedding 配置失败', error)
|
||
return null
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 获取激活的 Embedding 配置 ID
|
||
*/
|
||
ipcMain.handle('embedding:getActiveConfigId', async () => {
|
||
try {
|
||
return rag.getActiveEmbeddingConfigId()
|
||
} catch (error) {
|
||
return null
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 检查语义搜索是否启用
|
||
*/
|
||
ipcMain.handle('embedding:isEnabled', async () => {
|
||
try {
|
||
return rag.isEmbeddingEnabled()
|
||
} catch (error) {
|
||
return false
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 添加 Embedding 配置
|
||
*/
|
||
ipcMain.handle(
|
||
'embedding:addConfig',
|
||
async (_, config: Omit<rag.EmbeddingServiceConfig, 'id' | 'createdAt' | 'updatedAt'>) => {
|
||
try {
|
||
aiLogger.info('IPC', '添加 Embedding 配置', { name: config.name, model: config.model })
|
||
const result = rag.addEmbeddingConfig(config)
|
||
if (result.success) {
|
||
await rag.resetEmbeddingService()
|
||
}
|
||
return result
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '添加 Embedding 配置失败', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
}
|
||
)
|
||
|
||
/**
|
||
* 更新 Embedding 配置
|
||
*/
|
||
ipcMain.handle(
|
||
'embedding:updateConfig',
|
||
async (_, id: string, updates: Partial<Omit<rag.EmbeddingServiceConfig, 'id' | 'createdAt' | 'updatedAt'>>) => {
|
||
try {
|
||
aiLogger.info('IPC', '更新 Embedding 配置', { id })
|
||
const result = rag.updateEmbeddingConfig(id, updates)
|
||
if (result.success) {
|
||
await rag.resetEmbeddingService()
|
||
}
|
||
return result
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '更新 Embedding 配置失败', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
}
|
||
)
|
||
|
||
/**
|
||
* 删除 Embedding 配置
|
||
*/
|
||
ipcMain.handle('embedding:deleteConfig', async (_, id: string) => {
|
||
try {
|
||
aiLogger.info('IPC', '删除 Embedding 配置', { id })
|
||
const result = rag.deleteEmbeddingConfig(id)
|
||
if (result.success) {
|
||
await rag.resetEmbeddingService()
|
||
}
|
||
return result
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '删除 Embedding 配置失败', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 设置激活的 Embedding 配置
|
||
*/
|
||
ipcMain.handle('embedding:setActiveConfig', async (_, id: string) => {
|
||
try {
|
||
aiLogger.info('IPC', '设置激活 Embedding 配置', { id })
|
||
const result = rag.setActiveEmbeddingConfig(id)
|
||
if (result.success) {
|
||
await rag.resetEmbeddingService()
|
||
}
|
||
return result
|
||
} catch (error) {
|
||
aiLogger.error('IPC', '设置激活 Embedding 配置失败', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 验证 Embedding 配置
|
||
*/
|
||
ipcMain.handle('embedding:validateConfig', async (_, config: rag.EmbeddingServiceConfig) => {
|
||
try {
|
||
return await rag.validateEmbeddingConfig(config)
|
||
} catch (error) {
|
||
return { success: false, error: String(error) }
|
||
}
|
||
})
|
||
|
||
// ==================== 向量存储管理 ====================
|
||
|
||
/**
|
||
* 获取向量存储统计信息
|
||
*/
|
||
ipcMain.handle('rag:getVectorStoreStats', async () => {
|
||
try {
|
||
return await rag.getVectorStoreStats()
|
||
} catch (error) {
|
||
console.error('获取向量存储统计失败：', error)
|
||
return { enabled: false, error: String(error) }
|
||
}
|
||
})
|
||
|
||
/**
|
||
* 清空向量存储
|
||
*/
|
||
ipcMain.handle('rag:clearVectorStore', async () => {
|
||
try {
|
||
const store = await rag.getVectorStore()
|
||
if (store) {
|
||
await store.clear()
|
||
return { success: true }
|
||
}
|
||
return { success: false, error: '向量存储未启用' }
|
||
} catch (error) {
|
||
console.error('清空向量存储失败：', error)
|
||
return { success: false, error: String(error) }
|
||
}
|
||
})
|
||
}
|