/**
 * useConversation — Active conversation management
 *
 * The core business logic composable:
 * - Manages the currently active conversation
 * - Handles sending messages and receiving mock AI responses
 * - Auto-generates workspace items for substantial responses
 * - Coordinates between useConversations, useWorkflow, and useWorkspace
 */

import type { Message, WorkflowId, Conversation, WorkspaceItem } from '@/types/index'
import { STORAGE_KEYS, generateId, MOCK_AI_DELAY_MS } from '@/constants/index'
import { useStorage } from './useStorage'

// Mock AI response templates per workflow
const AI_RESPONSES: Record<WorkflowId, string[]> = {
  general: [
    '这是一个很好的问题！让我来为你详细解答。\n\n首先，我们需要理解核心概念。人工智能正在快速发展，已经渗透到我们生活的方方面面。\n\n**关键要点：**\n- 保持好奇心，不断学习新知识\n- 实践是检验真理的唯一标准\n- 多角度思考问题能带来更好的解决方案\n\n希望这些对你有所帮助！还有其他问题吗？',
    '感谢你的提问！关于这个问题，我有以下几点建议：\n\n1. **明确目标**：先确定你想要达到的具体结果\n2. **制定计划**：把大目标拆分成小步骤\n3. **持续迭代**：在执行过程中不断优化调整\n\n如果你能提供更多具体信息，我可以给出更具针对性的建议。',
    '让我从几个角度来分析这个问题：\n\n从技术层面看，这涉及到系统的整体架构设计。从用户体验角度来说，简洁直观的交互至关重要。\n\n综合考虑，我建议采用渐进式的方法，先验证核心功能，再逐步扩展。你觉得这个思路如何？',
  ],
  code: [
    '好的，让我来帮你解决这个编程问题。\n\n```\nfunction solve(arr: number[]): number {\n  const n = arr.length\n  let result = 0\n  for (let i = 0; i < n; i++) {\n    result += arr[i]\n  }\n  return result\n}\n```\n\n这段代码的时间复杂度是 O(n)，空间复杂度是 O(1)。\n\n**注意事项：**\n- 记得处理边界情况（空数组）\n- 可以考虑使用 reduce 方法简化代码\n- 如果需要处理大数，注意整数溢出问题\n\n还有什么需要我帮忙的吗？',
    '这是一个经典的设计模式问题。我推荐使用以下架构：\n\n```\nclass EventBus {\n  private handlers: Map<string, Function[]>\n  \n  on(event: string, handler: Function) {\n    // 注册事件处理器\n  }\n  \n  emit(event: string, data: any) {\n    // 触发事件\n  }\n}\n```\n\n这种发布-订阅模式可以有效解耦模块间的依赖，让代码更具可维护性。',
    '让我看看你的代码逻辑...\n\n问题在于异步操作的处理。你需要使用 `await` 来等待 Promise 完成：\n\n```\nasync function fetchData(url: string) {\n  try {\n    const response = await fetch(url)\n    const data = await response.json()\n    return data\n  } catch (error) {\n    console.error(\'Failed to fetch:\', error)\n    throw error\n  }\n}\n```\n\n另外建议添加错误处理和重试机制，提高代码的健壮性。',
  ],
  document: [
    '好的，我来帮你撰写这篇文档。\n\n---\n\n**引言**\n\n在当今快速发展的数字化时代，企业面临着前所未有的机遇与挑战。如何有效利用技术手段提升业务效率，已成为每个管理者必须思考的问题。\n\n**核心观点**\n\n- 数字化转型不仅仅是技术升级，更是思维方式的转变\n- 数据驱动决策能够显著提升业务精准度\n- 用户体验应始终放在产品设计的首位\n\n**总结**\n\n通过系统化的方法推进数字化转型，企业能够在竞争激烈的市场中保持领先地位。\n\n---\n\n以上是初稿，你觉得需要调整什么方向吗？',
    '帮你润色了一下这段文字：\n\n**原文**：这个产品很好用，功能很多，界面也好看。\n\n**润色后**：这款产品表现优秀，不仅功能丰富全面，界面设计也简洁美观，为用户带来了出色的使用体验。\n\n**修改要点：**\n- 用词更加正式专业\n- 句式更加丰富多变\n- 增强了文字的感染力\n\n需要继续优化其他内容吗？',
  ],
  data: [
    '根据你提供的数据，我进行了详细分析：\n\n📊 **数据概览**\n\n| 指标 | 当前值 | 环比变化 |\n|------|--------|----------|\n| 用户数 | 12,580 | +8.3% |\n| 活跃率 | 67.2% | +2.1% |\n| 转化率 | 3.8% | -0.5% |\n\n🔍 **关键洞察**\n\n1. 用户增长保持良好势头，增长率超过行业平均水平\n2. 活跃率稳步提升，说明产品粘性增强\n3. 转化率略有下降，需要关注转化漏斗的优化\n\n💡 **建议措施**\n\n- 针对转化率问题，优化注册流程\n- 分析高活跃用户的行为特征并复制推广\n- 关注用户留存曲线的变化趋势\n\n需要我深入分析某个具体指标吗？',
    '让我从数据角度来分析这个趋势：\n\n**相关性分析结果：**\n- 变量A与变量B的相关系数：0.87（强正相关）\n- 变量C与结果的相关系数：-0.42（中等负相关）\n\n这意味着当A增加时，B也倾向于增加。而C的增加反而会抑制结果的提升。\n\n**统计显著性**：p值 < 0.01，结果具有统计意义。\n\n建议重点关注A和B的关系，这可能是一个关键的驱动因素。',
  ],
  creative: [
    '好的，让我来一场头脑风暴！🎯\n\n**方案一：社交裂变**\n利用用户的社交网络，通过分享激励机制实现病毒式传播。核心是设计一个让用户"忍不住想分享"的体验。\n\n**方案二：内容IP化**\n打造独特的品牌IP形象，通过故事化内容与用户建立情感连接。IP可以出现在产品各个触点。\n\n**方案三：场景化营销**\n深入用户真实使用场景，在不同场景下提供定制化的解决方案。让产品"恰好"出现在用户需要的时候。\n\n💡 我个人最看好方案二的长期价值，但方案一能在短期内带来快速增长。你觉得哪个方向更符合你的目标？',
    '让我们跳出常规思维，重新构想这个问题的解决方案！\n\n想象一下，如果完全没有技术和资源的限制，理想的解决方案会是什么样？\n\n从这个"理想态"往回推导：\n1. 理想体验的核心要素是什么？\n2. 哪些要素可以通过现有技术实现？\n3. 哪些需要创新的替代方案？\n\n这种"反向思维"往往能激发出意想不到的创意。比如Airbnb就是通过"让陌生人住进家里"这个看似疯狂的创意颠覆了酒店行业。\n\n你有什么初步的想法吗？我们一起碰撞出更多灵感！',
  ],
}

/**
 * @param conversationsApi — functions from useConversations(): getConversation, saveConversation, createConversation
 * @param getActiveWorkflowId — getter function that returns the current active workflow ID from useWorkflow()
 * @param addWorkspaceItemFn — function from useWorkspace() to add workspace items.
 *   All are passed in as dependencies so the same state is shared with the page.
 */
export function useConversation(
  conversationsApi: {
    getConversation: (id: string) => Conversation | undefined
    saveConversation: (conv: Conversation) => void
    createConversation: (workflowId: WorkflowId, title?: string) => Conversation
  },
  getActiveWorkflowId: () => WorkflowId,
  addWorkspaceItemFn?: (item: WorkspaceItem) => void
) {
  const { loadValue, saveValue } = useStorage()
  const { getConversation, saveConversation, createConversation } = conversationsApi

  // Fallback no-op if not provided
  const addWorkspaceItem = addWorkspaceItemFn ?? (() => {})

  // Active conversation ID
  const activeConversationId = ref<string | null>(
    loadValue<string | null>(STORAGE_KEYS.ACTIVE_CONVERSATION_ID, null)
  )

  // Whether the AI is currently "typing"
  const isLoading = ref(false)

  /**
   * Messages of the currently active conversation (computed).
   */
  const messages = computed<Message[]>(() => {
    if (!activeConversationId.value) return []
    const conv = getConversation(activeConversationId.value)
    return conv ? conv.messages : []
  })

  /**
   * Set the active conversation ID and persist.
   */
  function setActiveConversationId(id: string | null): void {
    activeConversationId.value = id
    if (id) {
      saveValue(STORAGE_KEYS.ACTIVE_CONVERSATION_ID, id)
    } else {
      saveValue(STORAGE_KEYS.ACTIVE_CONVERSATION_ID, null)
    }
  }

  /**
   * Start a new conversation with the given workflow.
   */
  function startNewConversation(workflowId: WorkflowId): void {
    const conv = createConversation(workflowId)
    setActiveConversationId(conv.id)
    isLoading.value = false
  }

  /**
   * Load an existing conversation by ID.
   */
  function loadConversation(id: string): void {
    const conv = getConversation(id)
    if (conv) {
      setActiveConversationId(id)
      isLoading.value = false
    }
  }

  /**
   * Send a message from the user.
   * Adds the user message, then triggers a mock AI response after a delay.
   */
  function sendMessage(content: string): void {
    if (!content.trim() || isLoading.value) return

    // Ensure we have an active conversation
    if (!activeConversationId.value) {
      startNewConversation(getActiveWorkflowId())
    }

    const convId: string = activeConversationId.value ?? ''
    if (!convId) return

    const conv = getConversation(convId)
    if (!conv) {
      startNewConversation(getActiveWorkflowId())
      // Retry after creating
      sendMessage(content)
      return
    }

    // Add user message
    const userMessage: Message = {
      id: generateId(),
      role: 'user',
      content: content.trim(),
      timestamp: Date.now(),
      status: 'sent',
    }

    conv.messages.push(userMessage)
    conv.updatedAt = Date.now()

    // Auto-title: use first user message as conversation title
    if (conv.messages.filter((m) => m.role === 'user').length === 1) {
      let title = content.trim()
      if (title.length > 20) {
        title = title.substring(0, 20) + '...'
      }
      conv.title = title
    }

    saveConversation(conv)

    // Trigger mock AI response
    isLoading.value = true
    setTimeout(() => {
      simulateAiResponse(conv)
    }, MOCK_AI_DELAY_MS)
  }

  /**
   * Retry sending a message (for error recovery).
   */
  function retryMessage(messageId: string): void {
    const conv = getConversation(activeConversationId.value ?? '')
    if (!conv) return

    const msg = conv.messages.find((m) => m.id === messageId)
    if (msg) {
      msg.status = 'sent'
      saveConversation(conv)
    }
  }

  /**
   * Simulate an AI response.
   * In production, replace this with a real API call.
   */
  function simulateAiResponse(conv: Conversation): void {
    const responses = AI_RESPONSES[conv.workflowId] ?? AI_RESPONSES['general']
    const responseContent = responses[Math.floor(Math.random() * responses.length)]

    const aiMessage: Message = {
      id: generateId(),
      role: 'assistant',
      content: responseContent,
      timestamp: Date.now(),
      status: 'sent',
    }

    // Get fresh reference in case conversations array changed
    const freshConv = getConversation(conv.id)
    if (!freshConv) {
      isLoading.value = false
      return
    }

    freshConv.messages.push(aiMessage)
    freshConv.updatedAt = Date.now()
    saveConversation(freshConv)

    // Auto-generate workspace item for substantial responses
    if (conv.workflowId !== 'general') {
      generateWorkspaceItem(freshConv, aiMessage)
    }

    isLoading.value = false
  }

  /**
   * Generate a workspace item from an AI response.
   */
  function generateWorkspaceItem(conv: Conversation, message: Message): void {
    const typeMap: Record<string, string> = {
      code: 'code_snippet',
      document: 'document',
      data: 'analysis_report',
      creative: 'creative_output',
    }

    const titles: Record<string, string> = {
      code: '代码片段',
      document: '文档草稿',
      data: '分析报告',
      creative: '创意方案',
    }

    const itemType = (typeMap[conv.workflowId] ?? 'document') as import('@/types/index').WorkspaceItemType
    const autoTitle = titles[conv.workflowId] ?? '工作结果'

    // Only create if response is long enough to be "substantial"
    if (message.content.length < 50) return

    addWorkspaceItem({
      id: generateId(),
      conversationId: conv.id,
      workflowId: conv.workflowId,
      type: itemType,
      title: `${autoTitle} - ${conv.title}`,
      content: message.content,
      summary: message.content.substring(0, 120) + '...',
      createdAt: Date.now(),
    })
  }

  return {
    activeConversationId,
    messages,
    isLoading,
    sendMessage,
    retryMessage,
    loadConversation,
    startNewConversation,
    setActiveConversationId,
  }
}