// electron/main/ipc/ai.ts
import { ipcMain, shell } from 'electron'
import * as fs from 'fs'
import * as path from 'path'
import * as aiConversations from '../ai/conversations'
import * as llm from '../ai/llm'
import * as rag from '../ai/rag'
import { aiLogger, setDebugMode } from '../ai/logger'
import { serializeError } from '../ai/serialize-error'
import { getLogsDir } from '../paths'
import { Agent, type AgentStreamChunk, type SkillContext } from '../ai/agent'
import { getDefaultGeneralAssistantId } from '../ai/assistant/defaultGeneral'
import { getDefaultAssistantConfig, buildPiModel } from '../ai/llm'
import { checkAndCompress, manualCompress, type CompressionConfig } from '../ai/compression'
import { countMessagesTokens } from '../ai/tokenizer'
import * as assistantManager from '../ai/assistant'
import type { AssistantConfig } from '../ai/assistant/types'
import * as skillManager from '../ai/skills'
import {
  completeSimple,
  streamSimple,
  type Message as PiMessage,
  type TextContent as PiTextContent,
} from '@mariozechner/pi-ai'
import { t } from '../i18n'
import type { ToolContext } from '../ai/tools/types'
import { TOOL_REGISTRY } from '../ai/tools/definitions'
import { getDefaultRulesForLocale, mergeRulesForLocale } from '../ai/preprocessor/builtin-rules'
import type { IpcContext } from './types'

function toPiSimpleMessages(messages: Array<{ role: string; content: string }>, timestamp: number): PiMessage[] {
  // pi-ai 的 simple API 在类型上要求完整 Message 联合，这里沿用现有轻量消息格式并集中做兼容转换。
  return messages.map((message) => ({
    role: message.role as 'user' | 'assistant',
    content: message.content,
    timestamp,
  })) as unknown as PiMessage[]
}

// ==================== AI Agent 请求追踪 ====================
// 用于跟踪活跃的 Agent 请求，支持中止操作
const activeAgentRequests = new Map<string, AbortController>()

/**
 * 格式化 AI 报错信息，输出更友好的提示
 */
function formatAIError(error: unknown, provider?: llm.LLMProvider): string {
  const candidates: unknown[] = []
  if (error) {
    candidates.push(error)
  }

  const errorObj = error as {
    lastError?: unknown
    errors?: unknown[]
  }

  if (errorObj?.lastError) {
    candidates.push(errorObj.lastError)
  }

  if (Array.isArray(errorObj?.errors)) {
    candidates.push(...errorObj.errors)
  }

  let rawMessage = ''
  let statusCode: number | undefined
  let retrySeconds: number | undefined

  for (const candidate of candidates) {
    if (!candidate || typeof candidate !== 'object') {
      if (!rawMessage && typeof candidate === 'string') {
        rawMessage = candidate
      }
      continue
    }

    const record = candidate as Record<string, unknown>
    if (typeof record.statusCode === 'number') {
      statusCode = record.statusCode
    }

    if (!rawMessage && typeof record.message === 'string') {
      rawMessage = record.message
    }

    if (!rawMessage && record.data && typeof record.data === 'object') {
      const data = record.data as { error?: { message?: string } }
      if (data.error?.message) {
        rawMessage = data.error.message
      }
    }

    if (record.responseBody && typeof record.responseBody === 'string') {
      const responseBody = record.responseBody
      try {
        const parsed = JSON.parse(responseBody) as { error?: { message?: string } }
        if (!rawMessage && parsed.error?.message) {
          rawMessage = parsed.error.message
        }
      } catch {
        if (!rawMessage) {
          rawMessage = responseBody
        }
      }
    }

    if (rawMessage) {
      const retryMatch = rawMessage.match(/retry in ([0-9.]+)s/i)
      if (retryMatch) {
        retrySeconds = Math.ceil(Number(retryMatch[1]))
      }
    }
  }

  const fallbackMessage = rawMessage || String(error)
  const lowerMessage = fallbackMessage.toLowerCase()
  const providerName =
    provider === 'openai-compatible'
      ? t('llm.genericProviderName')
      : provider
        ? llm.getProviderInfo(provider)?.name || provider
        : t('llm.genericProviderName')

  let friendlyMessage = ''

  if (statusCode === 429 || lowerMessage.includes('quota') || lowerMessage.includes('resource_exhausted')) {
    friendlyMessage = retrySeconds
      ? `${providerName} quota exhausted, please retry after ${retrySeconds}s or upgrade your quota.`
      : `${providerName} quota exhausted, please retry later or upgrade your quota.`
  } else if (
    statusCode === 403 &&
    (lowerMessage.includes('quota') || lowerMessage.includes('not enough') || lowerMessage.includes('insufficient'))
  ) {
    friendlyMessage = `${providerName} rejected the request due to insufficient quota or balance.`
  } else if (statusCode === 503 || lowerMessage.includes('overloaded') || lowerMessage.includes('unavailable')) {
    friendlyMessage = `${providerName} model is overloaded, please retry later.`
  } else if (fallbackMessage.length > 300) {
    friendlyMessage = `${fallbackMessage.slice(0, 300)}...`
  } else {
    friendlyMessage = fallbackMessage
  }

  const details = [statusCode ? `status=${statusCode}` : null, fallbackMessage].filter(Boolean).join('; ')

  // 同时返回封装提示和原始错误详情，便于用户定位第三方平台问题。
  if (friendlyMessage !== fallbackMessage) {
    return `${friendlyMessage}\n\n${t('llm.rawErrorLabel')}: ${details}`
  }

  return friendlyMessage
}

/**
 * 递归剥离对象中的 avatar/senderAvatar 字段（base64 大数据）
 * 用于工具测试场景，避免传输和序列化大量无用头像数据
 */
function stripAvatarFields(obj: unknown): void {
  if (!obj || typeof obj !== 'object') return
  if (Array.isArray(obj)) {
    for (const item of obj) stripAvatarFields(item)
    return
  }
  const record = obj as Record<string, unknown>
  for (const key of Object.keys(record)) {
    if ((key === 'avatar' || key === 'senderAvatar') && typeof record[key] === 'string') {
      const val = record[key] as string
      if (val.length > 200) {
        record[key] = '[stripped]'
      }
    } else if (typeof record[key] === 'object' && record[key] !== null) {
      stripAvatarFields(record[key])
    }
  }
}

export function registerAIHandlers({ win }: IpcContext): void {
  console.log('[IPC] Registering AI handlers...')

  // 初始化助手管理器（同步内置助手、加载用户助手）
  try {
    assistantManager.initAssistantManager()
    console.log('[IPC] Assistant manager initialized')
  } catch (error) {
    console.error('[IPC] Failed to initialize assistant manager:', error)
  }

  // 初始化技能管理器（扫描用户技能文件）
  try {
    skillManager.initSkillManager()
    console.log('[IPC] Skill manager initialized')
  } catch (error) {
    console.error('[IPC] Failed to initialize skill manager:', error)
  }

  // ==================== Debug 模式 ====================

  ipcMain.on('app:setDebugMode', (_, enabled: boolean) => {
    setDebugMode(enabled)
    aiLogger.info('Config', `Debug mode ${enabled ? 'enabled' : 'disabled'}`)
  })

  // ==================== AI 对话管理 ====================

  /**
   * 创建新的 AI 对话
   * 参数契约与 preload / 数据层保持一致：(sessionId, title?)
   */
  ipcMain.handle(
    'ai:createConversation',
    async (_, sessionId: string, title: string | undefined, assistantId: string) => {
      try {
        return aiConversations.createConversation(sessionId, title, assistantId)
      } catch (error) {
        console.error('Failed to create AI conversation:', error)
        throw error
      }
    }
  )

  /**
   * 获取所有 AI 对话列表
   */
  ipcMain.handle('ai:getConversations', async (_, sessionId: string) => {
    try {
      return aiConversations.getConversations(sessionId)
    } catch (error) {
      console.error('Failed to get AI conversations:', error)
      return []
    }
  })

  /**
   * 打开当前 AI 日志文件并定位到文件
   */
  ipcMain.handle('ai:showLogFile', async () => {
    try {
      // 优先使用当前已存在的日志文件，避免创建新的空日志
      const existingLogPath = aiLogger.getExistingLogPath()
      if (existingLogPath) {
        shell.showItemInFolder(existingLogPath)
        return { success: true, path: existingLogPath }
      }

      const logDir = path.join(getLogsDir(), 'ai')
      if (!fs.existsSync(logDir)) {
        return { success: false, error: 'No AI log files found' }
      }

      const logFiles = fs.readdirSync(logDir).filter((name) => name.startsWith('ai_') && name.endsWith('.log'))

      if (logFiles.length === 0) {
        return { success: false, error: 'No AI log files found' }
      }

      // 选择最近修改的日志文件
      const latestLog = logFiles
        .map((name) => {
          const filePath = path.join(logDir, name)
          const stat = fs.statSync(filePath)
          return { path: filePath, mtimeMs: stat.mtimeMs }
        })
        .sort((a, b) => b.mtimeMs - a.mtimeMs)[0]

      shell.showItemInFolder(latestLog.path)
      return { success: true, path: latestLog.path }
    } catch (error) {
      console.error('Failed to open AI log file:', error)
      return { success: false, error: String(error) }
    }
  })

  /**
   * 获取单个对话详情
   */
  ipcMain.handle('ai:getConversation', async (_, conversationId: string) => {
    try {
      return aiConversations.getConversation(conversationId)
    } catch (error) {
      console.error('Failed to get AI conversation details:', error)
      return null
    }
  })

  /**
   * 更新 AI 对话标题
   */
  ipcMain.handle('ai:updateConversationTitle', async (_, conversationId: string, title: string) => {
    try {
      return aiConversations.updateConversationTitle(conversationId, title)
    } catch (error) {
      console.error('Failed to update AI conversation title:', error)
      return false
    }
  })

  /**
   * 删除 AI 对话
   */
  ipcMain.handle('ai:deleteConversation', async (_, conversationId: string) => {
    try {
      return aiConversations.deleteConversation(conversationId)
    } catch (error) {
      console.error('Failed to delete AI conversation:', error)
      return false
    }
  })

  /**
   * 添加 AI 消息
   */
  ipcMain.handle(
    'ai:addMessage',
    async (
      _,
      conversationId: string,
      role: aiConversations.AIMessageRole,
      content: string,
      dataKeywords?: string[],
      dataMessageCount?: number,
      contentBlocks?: aiConversations.ContentBlock[],
      tokenUsage?: aiConversations.TokenUsageData
    ) => {
      try {
        return aiConversations.addMessage(
          conversationId,
          role,
          content,
          dataKeywords,
          dataMessageCount,
          contentBlocks,
          tokenUsage
        )
      } catch (error) {
        console.error('Failed to add AI message:', error)
        throw error
      }
    }
  )

  /**
   * 获取 AI 对话的所有消息
   */
  ipcMain.handle('ai:getMessages', async (_, conversationId: string) => {
    try {
      return aiConversations.getMessages(conversationId)
    } catch (error) {
      console.error('Failed to get AI messages:', error)
      return []
    }
  })

  /**
   * 获取对话的累计 token 使用量
   */
  ipcMain.handle('ai:getConversationTokenUsage', async (_, conversationId: string) => {
    try {
      return aiConversations.getConversationTokenUsage(conversationId)
    } catch (error) {
      console.error('Failed to get conversation token usage:', error)
      return { promptTokens: 0, completionTokens: 0, totalTokens: 0 }
    }
  })

  /**
   * 删除 AI 消息
   */
  ipcMain.handle('ai:deleteMessage', async (_, messageId: string) => {
    try {
      return aiConversations.deleteMessage(messageId)
    } catch (error) {
      console.error('Failed to delete AI message:', error)
      return false
    }
  })

  // ==================== 脱敏规则 ====================

  ipcMain.handle('ai:getDefaultDesensitizeRules', (_, locale: string) => {
    return getDefaultRulesForLocale(locale)
  })

  ipcMain.handle('ai:mergeDesensitizeRules', (_, existingRules: unknown[], locale: string) => {
    return mergeRulesForLocale(existingRules as any[], locale)
  })

  // ==================== LLM 服务（多配置管理）====================

  /**
   * 获取所有支持的 LLM 提供商
   */
  ipcMain.handle('llm:getProviders', async () => {
    return llm.PROVIDERS
  })

  /**
   * 获取所有配置列表
   */
  ipcMain.handle('llm:getAllConfigs', async () => {
    const configs = llm.getAllConfigs()
    // 返回 API Key
    return configs.map((c) => ({
      ...c,
      apiKeySet: !!c.apiKey,
    }))
  })

  /**
   * 获取默认助手 slot
   */
  ipcMain.handle('llm:getDefaultAssistantSlot', async () => {
    return llm.getDefaultAssistantSlot()
  })

  /**
   * 获取快速模型 slot
   */
  ipcMain.handle('llm:getFastModelSlot', async () => {
    return llm.getFastModelSlot()
  })

  /**
   * 添加新配置
   */
  ipcMain.handle(
    'llm:addConfig',
    async (
      _,
      config: {
        name: string
        provider: llm.LLMProvider
        apiKey: string
        model?: string
        baseUrl?: string
        maxTokens?: number
        apiFormat?: string
        customModels?: Array<{ id: string; name: string }>
      }
    ) => {
      try {
        const result = llm.addConfig(config)
        if (result.success && result.config) {
          return {
            success: true,
            config: {
              ...result.config,
              apiKeySet: !!result.config.apiKey,
            },
          }
        }
        return result
      } catch (error) {
        console.error('Failed to add LLM config:', error)
        return { success: false, error: String(error) }
      }
    }
  )

  /**
   * 更新配置
   */
  ipcMain.handle(
    'llm:updateConfig',
    async (
      _,
      id: string,
      updates: {
        name?: string
        provider?: llm.LLMProvider
        apiKey?: string
        model?: string
        baseUrl?: string
        maxTokens?: number
        apiFormat?: string
        customModels?: Array<{ id: string; name: string }>
      }
    ) => {
      try {
        // 如果 apiKey 为空字符串，表示不更新 API Key
        const cleanUpdates = { ...updates }
        if (cleanUpdates.apiKey === '') {
          delete cleanUpdates.apiKey
        }

        return llm.updateConfig(id, cleanUpdates)
      } catch (error) {
        console.error('Failed to update LLM config:', error)
        return { success: false, error: String(error) }
      }
    }
  )

  /**
   * 删除配置
   */
  ipcMain.handle('llm:deleteConfig', async (_, id?: string) => {
    try {
      if (!id) {
        const defaultConfig = llm.getDefaultAssistantConfig()
        if (defaultConfig) {
          return llm.deleteConfig(defaultConfig.id)
        }
        return { success: false, error: t('llm.noActiveConfig') }
      }
      return llm.deleteConfig(id)
    } catch (error) {
      console.error('Failed to delete LLM config:', error)
      return { success: false, error: String(error) }
    }
  })

  /**
   * 设置默认助手模型（configId + modelId）
   */
  ipcMain.handle('llm:setDefaultAssistantModel', async (_, configId: string, modelId: string) => {
    try {
      return llm.setDefaultAssistantModel(configId, modelId)
    } catch (error) {
      console.error('Failed to set default assistant model:', error)
      return { success: false, error: String(error) }
    }
  })

  /**
   * 设置快速模型
   */
  ipcMain.handle('llm:setFastModel', async (_, slot: { configId: string; modelId: string } | null) => {
    try {
      return llm.setFastModel(slot)
    } catch (error) {
      console.error('Failed to set fast model:', error)
      return { success: false, error: String(error) }
    }
  })

  /**
   * 验证 API Key（支持自定义 baseUrl 和 model）
   * 返回对象格式：{ success: boolean, error?: string }
   */
  ipcMain.handle(
    'llm:validateApiKey',
    async (_, provider: llm.LLMProvider, apiKey: string, baseUrl?: string, model?: string) => {
      aiLogger.info('IPC', 'llm:validateApiKey validating', {
        provider,
        baseUrl,
        model,
        apiKeyLength: apiKey?.length,
      })
      try {
        const result = await llm.validateApiKey(provider, apiKey, baseUrl, model)
        aiLogger.info('IPC', 'llm:validateApiKey result', result)
        return result
      } catch (error) {
        aiLogger.error('IPC', 'llm:validateApiKey failed', { error: String(error), provider, baseUrl, model })
        const errorMessage = error instanceof Error ? error.message : String(error)
        return { success: false, error: errorMessage }
      }
    }
  )

  /**
   * 获取远程模型列表
   */
  ipcMain.handle(
    'llm:fetchRemoteModels',
    async (_, provider: string, apiKey: string, baseUrl?: string, apiFormat?: string) => {
      aiLogger.info('IPC', 'llm:fetchRemoteModels', { provider, baseUrl, apiFormat })
      try {
        return await llm.fetchRemoteModels(provider, apiKey, baseUrl, apiFormat)
      } catch (error) {
        aiLogger.error('IPC', 'llm:fetchRemoteModels failed', { error: String(error) })
        return { success: false, error: error instanceof Error ? error.message : String(error) }
      }
    }
  )

  /**
   * 检查是否已配置 LLM（是否有激活的配置）
   */
  ipcMain.handle('llm:hasConfig', async () => {
    return llm.hasActiveConfig()
  })

  // ==================== Provider Registry / Model Catalog ====================

  ipcMain.handle('llm:getProviderRegistry', async () => {
    return llm.getProviderRegistry()
  })

  ipcMain.handle('llm:getModelCatalog', async () => {
    return llm.getModelCatalog()
  })

  ipcMain.handle('llm:addCustomProvider', async (_, input) => {
    try {
      const provider = llm.addCustomProvider(input)
      return { success: true, provider }
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('llm:updateCustomProvider', async (_, id: string, updates) => {
    try {
      return llm.updateCustomProvider(id, updates)
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('llm:deleteCustomProvider', async (_, id: string) => {
    try {
      return llm.deleteCustomProvider(id)
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('llm:addCustomModel', async (_, input) => {
    try {
      const model = llm.addCustomModel(input)
      return { success: true, model }
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('llm:updateCustomModel', async (_, providerId: string, modelId: string, updates) => {
    try {
      return llm.updateCustomModel(providerId, modelId, updates)
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('llm:deleteCustomModel', async (_, providerId: string, modelId: string) => {
    try {
      return llm.deleteCustomModel(providerId, modelId)
    } catch (error) {
      return { success: false, error: String(error) }
    }
  })

  // ==================== LLM 直接调用 API（SQLLab 等非 Agent 场景使用） ====================

  /**
   * 非流式 LLM 调用
   */
  ipcMain.handle(
    'llm:chat',
    async (
      _,
      messages: Array<{ role: string; content: string }>,
      options?: { temperature?: number; maxTokens?: number }
    ) => {
      try {
        const activeConfig = getDefaultAssistantConfig()
        if (!activeConfig) {
          return { success: false, error: t('llm.notConfigured') }
        }
        const piModel = buildPiModel(activeConfig)
        const now = Date.now()
        const systemMsg = messages.find((m) => m.role === 'system')
        const nonSystemMsgs = messages.filter((m) => m.role !== 'system')

        const result = await completeSimple(
          piModel,
          {
            systemPrompt: systemMsg?.content,
            messages: toPiSimpleMessages(nonSystemMsgs, now),
          },
          {
            apiKey: activeConfig.apiKey,
            temperature: options?.temperature,
            maxTokens: options?.maxTokens,
          }
        )

        const content = result.content
          .filter((item): item is PiTextContent => item.type === 'text')
          .map((item) => item.text)
          .join('')

        return { success: true, content }
      } catch (error) {
        aiLogger.error('IPC', 'llm:chat error', { error: String(error) })
        return { success: false, error: String(error) }
      }
    }
  )

  /**
   * 流式 LLM 调用（SQLLab AI 生成 / 结果总结等场景使用）
   */
  ipcMain.handle(
    'llm:chatStream',
    async (
      _,
      requestId: string,
      messages: Array<{ role: string; content: string }>,
      options?: { temperature?: number; maxTokens?: number }
    ) => {
      try {
        const activeConfig = getDefaultAssistantConfig()
        if (!activeConfig) {
          return { success: false, error: t('llm.notConfigured') }
        }
        const piModel = buildPiModel(activeConfig)
        const now = Date.now()
        const systemMsg = messages.find((m) => m.role === 'system')
        const nonSystemMsgs = messages.filter((m) => m.role !== 'system')

        const eventStream = streamSimple(
          piModel,
          {
            systemPrompt: systemMsg?.content,
            messages: toPiSimpleMessages(nonSystemMsgs, now),
          },
          {
            apiKey: activeConfig.apiKey,
            temperature: options?.temperature,
            maxTokens: options?.maxTokens,
          }
        )

        // 异步消费流，通过事件发送 chunks
        ;(async () => {
          let hasTerminalChunk = false
          try {
            for await (const event of eventStream) {
              if (event.type === 'text_delta') {
                win.webContents.send('llm:streamChunk', {
                  requestId,
                  chunk: { content: event.delta, isFinished: false },
                })
                continue
              }

              if (event.type === 'done') {
                hasTerminalChunk = true
                win.webContents.send('llm:streamChunk', {
                  requestId,
                  chunk: { content: '', isFinished: true, finishReason: event.reason === 'length' ? 'length' : 'stop' },
                })
                return
              }

              if (event.type === 'error') {
                hasTerminalChunk = true
                const errorMsg =
                  event.error?.errorMessage || formatAIError(event.error, activeConfig.provider) || 'Unknown LLM error'
                aiLogger.error('IPC', 'llm:chatStream LLM error', { requestId, error: errorMsg })
                win.webContents.send('llm:streamChunk', {
                  requestId,
                  error: errorMsg,
                  chunk: { content: '', isFinished: true, finishReason: 'error' },
                })
                return
              }
            }

            if (!hasTerminalChunk) {
              win.webContents.send('llm:streamChunk', {
                requestId,
                chunk: { content: '', isFinished: true, finishReason: 'stop' },
              })
            }
          } catch (error) {
            if (!hasTerminalChunk) {
              const friendlyError = formatAIError(error, activeConfig.provider)
              aiLogger.error('IPC', 'llm:chatStream stream error', { requestId, error: String(error) })
              win.webContents.send('llm:streamChunk', {
                requestId,
                error: friendlyError,
                chunk: { content: '', isFinished: true, finishReason: 'error' },
              })
            }
          }
        })()

        return { success: true }
      } catch (error) {
        aiLogger.error('IPC', 'llm:chatStream error', { error: String(error) })
        return { success: false, error: String(error) }
      }
    }
  )

  // ==================== 助手管理 API ====================

  ipcMain.handle('assistant:getAll', async () => {
    try {
      return assistantManager.getAllAssistants()
    } catch (error) {
      console.error('Failed to get assistants:', error)
      return []
    }
  })

  ipcMain.handle('assistant:getConfig', async (_, id: string) => {
    try {
      return assistantManager.getAssistantConfig(id)
    } catch (error) {
      console.error('Failed to get assistant config:', error)
      return null
    }
  })

  ipcMain.handle('assistant:update', async (_, id: string, updates: Partial<AssistantConfig>) => {
    try {
      return assistantManager.updateAssistant(id, updates)
    } catch (error) {
      console.error('Failed to update assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:create', async (_, config: Omit<AssistantConfig, 'id' | 'version'>) => {
    try {
      return assistantManager.createAssistant(config)
    } catch (error) {
      console.error('Failed to create assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:delete', async (_, id: string) => {
    try {
      return assistantManager.deleteAssistant(id)
    } catch (error) {
      console.error('Failed to delete assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:reset', async (_, id: string) => {
    try {
      return assistantManager.resetAssistant(id)
    } catch (error) {
      console.error('Failed to reset assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:getBuiltinToolCatalog', async () => {
    try {
      return assistantManager.getBuiltinToolCatalog()
    } catch (error) {
      console.error('Failed to get builtin tool catalog:', error)
      return []
    }
  })

  ipcMain.handle('assistant:getBuiltinCatalog', async () => {
    try {
      return assistantManager.getBuiltinCatalog()
    } catch (error) {
      console.error('Failed to get builtin catalog:', error)
      return []
    }
  })

  ipcMain.handle('assistant:import', async (_, builtinId: string) => {
    try {
      return assistantManager.importAssistant(builtinId)
    } catch (error) {
      console.error('Failed to import assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:reimport', async (_, id: string) => {
    try {
      return assistantManager.reimportAssistant(id)
    } catch (error) {
      console.error('Failed to reimport assistant:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('assistant:importFromMd', async (_, rawMd: string) => {
    try {
      return assistantManager.importAssistantFromMd(rawMd)
    } catch (error) {
      console.error('Failed to import assistant from markdown:', error)
      return { success: false, error: String(error) }
    }
  })

  // ==================== 技能管理 API ====================

  ipcMain.handle('skill:getAll', async () => {
    try {
      return skillManager.getAllSkills()
    } catch (error) {
      console.error('Failed to get skills:', error)
      return []
    }
  })

  ipcMain.handle('skill:getConfig', async (_, id: string) => {
    try {
      return skillManager.getSkillConfig(id)
    } catch (error) {
      console.error('Failed to get skill config:', error)
      return null
    }
  })

  ipcMain.handle('skill:update', async (_, id: string, rawMd: string) => {
    try {
      return skillManager.updateSkill(id, rawMd)
    } catch (error) {
      console.error('Failed to update skill:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('skill:create', async (_, rawMd: string) => {
    try {
      return skillManager.createSkill(rawMd)
    } catch (error) {
      console.error('Failed to create skill:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('skill:delete', async (_, id: string) => {
    try {
      return skillManager.deleteSkill(id)
    } catch (error) {
      console.error('Failed to delete skill:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('skill:getBuiltinCatalog', async () => {
    try {
      return skillManager.getBuiltinCatalog()
    } catch (error) {
      console.error('Failed to get builtin catalog:', error)
      return []
    }
  })

  ipcMain.handle('skill:import', async (_, builtinId: string) => {
    try {
      return skillManager.importSkill(builtinId)
    } catch (error) {
      console.error('Failed to import skill:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('skill:reimport', async (_, id: string) => {
    try {
      return skillManager.reimportSkill(id)
    } catch (error) {
      console.error('Failed to reimport skill:', error)
      return { success: false, error: String(error) }
    }
  })

  ipcMain.handle('skill:importFromMd', async (_, rawMd: string) => {
    try {
      return skillManager.importSkillFromMd(rawMd)
    } catch (error) {
      console.error('Failed to import skill from markdown:', error)
      return { success: false, error: String(error) }
    }
  })

  // ==================== 工具测试 API（实验室 - 基础工具） ====================

  const activeToolTests = new Map<string, AbortController>()

  ipcMain.handle('ai:getToolCatalog', async () => {
    try {
      return TOOL_REGISTRY.map((entry) => {
        const dummyContext: ToolContext = { sessionId: '__catalog__' }
        const tool = entry.factory(dummyContext)
        const descKey = `ai.tools.${entry.name}.desc`
        const translated = t(descKey)
        return {
          name: entry.name,
          category: entry.category,
          description: translated !== descKey ? translated : (tool.description ?? ''),
          parameters: tool.parameters ?? {},
        }
      })
    } catch (error) {
      console.error('Failed to get tool catalog:', error)
      return []
    }
  })

  ipcMain.handle(
    'ai:executeTool',
    async (_, testId: string, toolName: string, params: Record<string, unknown>, sessionId: string) => {
      const MAX_RESULT_CHARS = 500_000
      const abortController = new AbortController()
      activeToolTests.set(testId, abortController)

      try {
        const entry = TOOL_REGISTRY.find((e) => e.name === toolName)
        if (!entry) {
          return { success: false, error: `Tool not found: ${toolName}` }
        }

        const context: ToolContext = { sessionId }
        const tool = entry.factory(context)
        const startTime = Date.now()
        const result = await tool.execute(`test_${Date.now()}`, params)
        const elapsed = Date.now() - startTime

        if (abortController.signal.aborted) {
          return { success: false, error: 'cancelled' }
        }

        let details = result.details as Record<string, unknown> | undefined
        let truncated = false

        if (details) {
          stripAvatarFields(details)
          const raw = JSON.stringify(details)
          if (raw.length > MAX_RESULT_CHARS) {
            truncated = true
            details = { _truncated: true, _originalSize: raw.length, _preview: raw.slice(0, MAX_RESULT_CHARS) }
          }
        }

        return {
          success: true,
          elapsed,
          content: result.content,
          details,
          truncated,
        }
      } catch (error) {
        if (abortController.signal.aborted) {
          return { success: false, error: 'cancelled' }
        }
        console.error(`Failed to execute tool ${toolName}:`, error)
        return { success: false, error: String(error) }
      } finally {
        activeToolTests.delete(testId)
      }
    }
  )

  ipcMain.handle('ai:cancelToolTest', async (_, testId: string) => {
    const controller = activeToolTests.get(testId)
    if (controller) {
      controller.abort()
      activeToolTests.delete(testId)
      return { success: true }
    }
    return { success: false }
  })

  // ==================== 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
   * Agent 通过 context.conversationId 从 SQLite 读取对话历史（数据流倒置）
   * @param chatType 聊天类型（'group' | 'private'）
   * @param locale 语言设置（可选，默认 'zh-CN'）
   * @param assistantId 助手 ID（可选，传入时从 AssistantManager 获取配置）
   */
  ipcMain.handle(
    'agent:runStream',
    async (
      _,
      requestId: string,
      userMessage: string,
      context: ToolContext,
      chatType?: 'group' | 'private',
      locale?: string,
      assistantId?: string,
      skillId?: string | null,
      enableAutoSkill?: boolean,
      compressionConfig?: CompressionConfig
    ) => {
      aiLogger.info('IPC', `Agent stream request received: ${requestId}`, {
        userMessage: userMessage.slice(0, 100),
        sessionId: context.sessionId,
        conversationId: context.conversationId,
        chatType: chatType ?? 'group',
        assistantId: assistantId ?? '(none)',
        skillId: skillId ?? '(none)',
        enableAutoSkill: enableAutoSkill ?? false,
      })

      try {
        const abortController = new AbortController()
        activeAgentRequests.set(requestId, abortController)

        const activeAIConfig = getDefaultAssistantConfig()
        if (!activeAIConfig) {
          return { success: false, error: t('llm.notConfigured') }
        }
        const piModel = buildPiModel(activeAIConfig)

        // 上下文压缩前置步骤（在 Agent 创建之前执行）
        if (compressionConfig?.enabled && context.conversationId) {
          try {
            win.webContents.send('agent:streamChunk', {
              requestId,
              chunk: {
                type: 'status',
                status: {
                  phase: 'compressing',
                  round: 0,
                  toolsUsed: 0,
                  contextTokens: 0,
                  totalUsage: { promptTokens: 0, completionTokens: 0, totalTokens: 0 },
                  updatedAt: Date.now(),
                } satisfies import('@electron/shared/types').AgentRuntimeStatus,
              },
            })

            // 获取助手 systemPrompt 用于 token 计算
            const tempAssistantConfig = assistantId
              ? (assistantManager.getAssistantConfig(assistantId) ?? undefined)
              : undefined
            const systemPromptForCompression = tempAssistantConfig?.systemPrompt || ''

            const compressionResult = await checkAndCompress(
              context.conversationId,
              compressionConfig,
              systemPromptForCompression,
              activeAIConfig
            )

            aiLogger.info('IPC', `Compression result for ${requestId}`, compressionResult)

            if (compressionResult.compressed && compressionResult.summaryContent) {
              win.webContents.send('agent:streamChunk', {
                requestId,
                chunk: {
                  type: 'compression_done',
                  compressionResult: {
                    summaryContent: compressionResult.summaryContent,
                    tokensBefore: compressionResult.tokensBefore ?? 0,
                    tokensAfter: compressionResult.tokensAfter ?? 0,
                    timestamp: Date.now(),
                  },
                },
              })
            }
          } catch (error) {
            aiLogger.error('IPC', `Compression failed for ${requestId}, continuing without compression`, {
              error: String(error),
            })
          }
        }

        const pp = context.preprocessConfig
        aiLogger.info('IPC', `Agent context: ${requestId}`, {
          model: activeAIConfig.model,
          provider: activeAIConfig.provider,
          baseUrl: activeAIConfig.baseUrl || '(default)',
          maxMessagesLimit: context.maxMessagesLimit,
          hasTimeFilter: !!context.timeFilter,
          mentionedMembersCount: context.mentionedMembers?.length ?? 0,
          preprocess: pp
            ? {
                dataCleaning: pp.dataCleaning ?? true,
                mergeConsecutive: pp.mergeConsecutive,
                denoise: pp.denoise,
                desensitize: pp.desensitize,
                anonymizeNames: pp.anonymizeNames,
              }
            : '(disabled)',
        })

        // 提示词系统已退场，主流程统一从助手配置获取 systemPrompt。
        const defaultAssistantId = getDefaultGeneralAssistantId(locale)
        let resolvedAssistantId = assistantId || defaultAssistantId
        let assistantConfig: AssistantConfig | undefined =
          assistantManager.getAssistantConfig(resolvedAssistantId) ?? undefined
        if (!assistantConfig && resolvedAssistantId !== defaultAssistantId) {
          aiLogger.warn('IPC', `Assistant not found: ${resolvedAssistantId}, falling back to ${defaultAssistantId}`, {
            requestedAssistantId: assistantId ?? null,
            locale: locale ?? null,
          })
          resolvedAssistantId = defaultAssistantId
          assistantConfig = assistantManager.getAssistantConfig(defaultAssistantId) ?? undefined
        }

        // 构建技能上下文
        let skillCtx: SkillContext | undefined
        if (skillId) {
          const skillDef = skillManager.getSkillConfig(skillId) ?? undefined
          if (skillDef) {
            skillCtx = { skillDef }
          } else {
            aiLogger.warn('IPC', `Skill not found: ${skillId}`)
          }
        } else if (enableAutoSkill) {
          const effectiveChatType = chatType ?? 'group'
          const allowedTools = assistantConfig?.allowedBuiltinTools
          const menu = skillManager.getSkillMenu(effectiveChatType, allowedTools)
          if (menu) {
            skillCtx = { skillMenu: menu }
          }
        }

        // 工具结果 token 预算注入：基于 context window 百分比计算
        const maxToolResultPercent = compressionConfig?.maxToolResultPercent ?? 50
        const modelDef = llm.findModelDefinition(activeAIConfig.provider, activeAIConfig.model || '')
        const resolvedContextWindow = modelDef?.contextWindow || 128000
        const maxToolResultTokens = Math.floor(resolvedContextWindow * (maxToolResultPercent / 100))
        const enrichedContext: ToolContext = { ...context, maxToolResultTokens }

        const agent = new Agent(
          enrichedContext,
          piModel,
          activeAIConfig.apiKey,
          { abortSignal: abortController.signal },
          chatType ?? 'group',
          locale ?? 'zh-CN',
          assistantConfig,
          skillCtx
        )

        // 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
              }
              if (chunk.type === 'tool_start') {
                aiLogger.info('IPC', `Tool call: ${chunk.toolName}`, chunk.toolParams)
              }
              win.webContents.send('agent:streamChunk', { requestId, chunk })
            })

            if (abortController.signal.aborted) {
              aiLogger.info('IPC', `Agent aborted: ${requestId}`)
              win.webContents.send('agent:complete', {
                requestId,
                result: {
                  content: result.content,
                  toolsUsed: result.toolsUsed,
                  toolRounds: result.toolRounds,
                  totalUsage: result.totalUsage,
                  aborted: true,
                },
              })
              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 execution completed: ${requestId}`, {
              toolsUsed: result.toolsUsed,
              toolRounds: result.toolRounds,
              contentLength: result.content.length,
              totalUsage: result.totalUsage,
            })
          } catch (error) {
            if (error instanceof Error && error.name === 'AbortError') {
              aiLogger.info('IPC', `Agent request aborted (error): ${requestId}`)
              win.webContents.send('agent:complete', {
                requestId,
                result: { content: '', toolsUsed: [], toolRounds: 0, aborted: true },
              })
              return
            }
            const serializedError = serializeError(error, activeAIConfig.provider)
            serializedError.friendlyMessage = formatAIError(error, activeAIConfig.provider)
            if (!serializedError.url && activeAIConfig.baseUrl) {
              serializedError.url = activeAIConfig.baseUrl
            }
            aiLogger.error('IPC', `Agent execution error: ${requestId}`, serializedError)
            // 发送错误 chunk
            win.webContents.send('agent:streamChunk', {
              requestId,
              chunk: { type: 'error', error: serializedError, 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: serializedError,
              },
            })
          } finally {
            // 清理请求追踪
            activeAgentRequests.delete(requestId)
          }
        })()

        return { success: true }
      } catch (error) {
        aiLogger.error('IPC', `Failed to create Agent request: ${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', `Abort request received: ${requestId}`)

    const abortController = activeAgentRequests.get(requestId)
    if (abortController) {
      abortController.abort()
      activeAgentRequests.delete(requestId)
      aiLogger.info('IPC', `Agent request aborted: ${requestId}`)
      return { success: true }
    } else {
      aiLogger.warn('IPC', `Agent request not found: ${requestId}`)
      return { success: false, error: 'Request not found' }
    }
  })

  // ==================== 上下文压缩 ====================

  ipcMain.handle(
    'ai:compressContext',
    async (_, conversationId: string, compressionConfig: CompressionConfig, systemPrompt: string) => {
      try {
        const activeAIConfig = getDefaultAssistantConfig()
        if (!activeAIConfig) {
          return { success: false, error: t('llm.notConfigured') }
        }

        const result = await manualCompress(conversationId, compressionConfig, systemPrompt, activeAIConfig)
        return { success: true, result }
      } catch (error) {
        aiLogger.error('IPC', 'Manual compression failed', { error: String(error) })
        return { success: false, error: String(error) }
      }
    }
  )

  ipcMain.handle('ai:estimateContextTokens', async (_, conversationId: string) => {
    try {
      const history = aiConversations.getHistoryForAgent(conversationId)
      const tokens = countMessagesTokens(history.map((m) => ({ role: m.role, content: m.content })))
      return { success: true, tokens, messageCount: history.length }
    } catch (error) {
      return { success: false, tokens: 0, error: String(error) }
    }
  })

  // ==================== 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', 'Failed to get Embedding configs', 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', 'Failed to get Embedding config', 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', 'Adding Embedding config', { name: config.name, model: config.model })
        const result = rag.addEmbeddingConfig(config)
        if (result.success) {
          await rag.resetEmbeddingService()
        }
        return result
      } catch (error) {
        aiLogger.error('IPC', 'Failed to add Embedding config', 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', 'Updating Embedding config', { id })
        const result = rag.updateEmbeddingConfig(id, updates)
        if (result.success) {
          await rag.resetEmbeddingService()
        }
        return result
      } catch (error) {
        aiLogger.error('IPC', 'Failed to update Embedding config', error)
        return { success: false, error: String(error) }
      }
    }
  )

  /**
   * 删除 Embedding 配置
   */
  ipcMain.handle('embedding:deleteConfig', async (_, id: string) => {
    try {
      aiLogger.info('IPC', 'Deleting Embedding config', { id })
      const result = rag.deleteEmbeddingConfig(id)
      if (result.success) {
        await rag.resetEmbeddingService()
      }
      return result
    } catch (error) {
      aiLogger.error('IPC', 'Failed to delete Embedding config', 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', 'Setting active Embedding config', { id })
      const result = rag.setActiveEmbeddingConfig(id)
      if (result.success) {
        await rag.resetEmbeddingService()
      }
      return result
    } catch (error) {
      aiLogger.error('IPC', 'Failed to set active Embedding config', 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 ====================

  /**
   * [Debug] 获取 AI 数据库 Schema
   */
  ipcMain.handle('ai:getAiSchema', async () => {
    try {
      return aiConversations.getAiSchema()
    } catch (error) {
      console.error('Failed to get AI schema:', error)
      return []
    }
  })

  /**
   * [Debug] 在 AI 数据库上执行原始 SQL
   */
  ipcMain.handle('ai:executeAiSQL', async (_, sql: string) => {
    try {
      return aiConversations.executeAiSQL(sql)
    } catch (error: any) {
      console.error('Failed to execute AI SQL:', error)
      throw error
    }
  })

  /**
   * 获取向量存储统计信息
   */
  ipcMain.handle('rag:getVectorStoreStats', async () => {
    try {
      return await rag.getVectorStoreStats()
    } catch (error) {
      console.error('Failed to get vector store stats:', 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: 'Vector store not enabled' }
    } catch (error) {
      console.error('Failed to clear vector store:', error)
      return { success: false, error: String(error) }
    }
  })
}