/**
 * Сервис для автоматизации рабочих процессов видеомонтажа с использованием AI
 * Создаёт комплексные workflow для автоматического редактирования видео
 */

import { invoke } from "@tauri-apps/api/core"

/**
 * Типы автоматизированных workflow
 */
export type WorkflowType =
  | "quick_edit" // Быстрый монтаж с автообрезкой и переходами
  | "social_media_pack" // Создание контента для соцсетей
  | "podcast_editing" // Автомонтаж подкастов
  | "presentation_video" // Видеопрезентации с титрами
  | "wedding_highlights" // Свадебные хайлайты
  | "travel_vlog" // Путевые влоги
  | "product_showcase" // Презентация продукта
  | "educational_content" // Образовательный контент
  | "music_video" // Музыкальные клипы
  | "corporate_intro" // Корпоративные презентации

/**
 * Параметры workflow
 */
export interface WorkflowParams {
  inputVideos: string[]
  workflowType: WorkflowType
  outputDirectory: string
  preferences: {
    targetDuration?: number // в секундах
    musicTrack?: string
    colorGrading?: "auto" | "warm" | "cool" | "cinematic" | "natural"
    transitionStyle?: "cuts" | "dissolve" | "zoom" | "slide"
    titleStyle?: "minimal" | "bold" | "elegant" | "modern"
    pace?: "slow" | "medium" | "fast" | "dynamic"
    includeSubtitles?: boolean
    language?: string
  }
  platformTargets?: Array<{
    platform: string
    aspectRatio: string
    maxDuration: number
  }>
}

/**
 * Результат выполнения workflow
 */
export interface WorkflowResult {
  workflowId: string
  success: boolean
  outputs: Array<{
    type: "main_video" | "social_variant" | "highlights" | "trailer"
    filePath: string
    platform?: string
    metadata: {
      duration: number
      resolution: { width: number; height: number }
      fileSize: number
      qualityScore: number
    }
  }>
  timeline: {
    projectFile: string
    sectionsCreated: number
    effectsApplied: string[]
    transitionsUsed: string[]
  }
  statistics: {
    processingTime: number
    automationLevel: number // 0-100%
    manualAdjustmentsNeeded: string[]
    qualityAnalysis: {
      videoQuality: number
      audioQuality: number
      editingFlow: number
      overallScore: number
    }
  }
  suggestions: string[]
  executionLog: Array<{
    step: string
    status: "completed" | "failed" | "skipped"
    duration: number
    details?: string
  }>
}

/**
 * Шаг workflow
 */
export interface WorkflowStep {
  id: string
  name: string
  description: string
  category: "analysis" | "editing" | "enhancement" | "export" | "optimization"
  dependencies?: string[]
  estimatedDuration: number
  execute: (context: WorkflowContext) => Promise<WorkflowStepResult>
}

/**
 * Контекст выполнения workflow
 */
export interface WorkflowContext {
  workflowId: string
  params: WorkflowParams
  tempDirectory: string
  intermediateFiles: Record<string, string>
  analysisResults: Record<string, any>
  timelineData: any
  progressCallback?: (progress: number, step: string) => void
  currentProgress?: number
  currentStep?: string
  startTime?: Date
}

/**
 * Результат выполнения шага
 */
export interface WorkflowStepResult {
  success: boolean
  outputs?: Record<string, any>
  errors?: string[]
  warnings?: string[]
  nextSteps?: string[]
}

/**
 * Сервис для автоматизации workflow
 */
export class WorkflowAutomationService {
  private static instance: WorkflowAutomationService
  private activeWorkflows = new Map<string, WorkflowContext>()

  // Предустановленные workflow шаги
  private workflowSteps = new Map<string, WorkflowStep>()

  private constructor() {
    this.initializeWorkflowSteps()
  }

  /**
   * Получить экземпляр сервиса (Singleton)
   */
  public static getInstance(): WorkflowAutomationService {
    if (!WorkflowAutomationService.instance) {
      WorkflowAutomationService.instance = new WorkflowAutomationService()
    }
    return WorkflowAutomationService.instance
  }

  /**
   * Запустить автоматизированный workflow
   */
  public async executeWorkflow(params: WorkflowParams): Promise<WorkflowResult> {
    const workflowId = this.generateWorkflowId()
    const startTime = Date.now()

    const context: WorkflowContext = {
      workflowId,
      params,
      tempDirectory: await this.createTempDirectory(workflowId),
      intermediateFiles: {},
      analysisResults: {},
      timelineData: null,
      currentProgress: 0,
      currentStep: "Инициализация",
      startTime: new Date(startTime),
    }

    this.activeWorkflows.set(workflowId, context)

    try {
      // Получаем последовательность шагов для workflow
      const steps = this.getWorkflowSteps(params.workflowType)
      const executionLog: WorkflowResult["executionLog"] = []

      let currentProgress = 0
      const progressIncrement = 100 / steps.length

      // Выполняем шаги последовательно
      for (const step of steps) {
        const stepStartTime = Date.now()

        try {
          // Обновляем прогресс в контексте
          context.currentProgress = currentProgress
          context.currentStep = step.name
          context.progressCallback?.(currentProgress, step.name)

          const result = await step.execute(context)

          const stepDuration = Date.now() - stepStartTime

          executionLog.push({
            step: step.name,
            status: result.success ? "completed" : "failed",
            duration: stepDuration,
            details: result.errors?.join("; "),
          })

          if (!result.success) {
            console.warn(`Workflow step ${step.name} failed:`, result.errors)
            // Продолжаем выполнение несмотря на ошибки в некритичных шагах
          }

          currentProgress += progressIncrement
        } catch (error) {
          executionLog.push({
            step: step.name,
            status: "failed",
            duration: Date.now() - stepStartTime,
            details: String(error),
          })
          console.error(`Critical error in workflow step ${step.name}:`, error)
        }
      }

      // Собираем результаты
      const outputs = await this.collectWorkflowOutputs(context)
      const statistics = await this.calculateWorkflowStatistics(context, Date.now() - startTime)
      const suggestions = this.generateWorkflowSuggestions(context, executionLog)

      const result: WorkflowResult = {
        workflowId,
        success: outputs.length > 0,
        outputs,
        timeline: {
          projectFile: context.intermediateFiles.projectFile || "",
          sectionsCreated: context.timelineData?.sections?.length || 0,
          effectsApplied: context.timelineData?.effects || [],
          transitionsUsed: context.timelineData?.transitions || [],
        },
        statistics,
        suggestions,
        executionLog,
      }

      return result
    } catch (error) {
      console.error(`Workflow ${workflowId} failed:`, error)
      throw new Error(`Workflow execution failed: ${String(error)}`)
    } finally {
      this.activeWorkflows.delete(workflowId)
      // Очистка временной директории
      if (context.tempDirectory) {
        await this.cleanupTempDirectory(context.tempDirectory)
      }
    }
  }

  /**
   * Получить доступные типы workflow
   */
  public getAvailableWorkflows(): Array<{
    type: WorkflowType
    name: string
    description: string
    estimatedDuration: number
    complexity: "simple" | "medium" | "complex"
    supportedInputs: string[]
    outputs: string[]
  }> {
    return [
      {
        type: "quick_edit",
        name: "Быстрый монтаж",
        description: "Автоматическая обрезка пауз, добавление переходов и музыки",
        estimatedDuration: 5,
        complexity: "simple",
        supportedInputs: ["mp4", "mov", "avi"],
        outputs: ["edited_video", "highlights"],
      },
      {
        type: "social_media_pack",
        name: "Пакет для соцсетей",
        description: "Создание видео для Instagram, TikTok, YouTube Shorts",
        estimatedDuration: 15,
        complexity: "medium",
        supportedInputs: ["mp4", "mov"],
        outputs: ["instagram_square", "tiktok_vertical", "youtube_shorts"],
      },
      {
        type: "podcast_editing",
        name: "Монтаж подкаста",
        description: "Удаление пауз, нормализация аудио, добавление интро/аутро",
        estimatedDuration: 10,
        complexity: "medium",
        supportedInputs: ["mp4", "mov", "mp3", "wav"],
        outputs: ["clean_audio", "video_with_waveform", "highlights"],
      },
      {
        type: "presentation_video",
        name: "Видеопрезентация",
        description: "Добавление титров, переходов между слайдами, фоновая музыка",
        estimatedDuration: 8,
        complexity: "medium",
        supportedInputs: ["mp4", "mov"],
        outputs: ["presentation_video", "thumbnail"],
      },
      {
        type: "wedding_highlights",
        name: "Свадебные хайлайты",
        description: "Создание эмоциональных моментов с музыкой и переходами",
        estimatedDuration: 20,
        complexity: "complex",
        supportedInputs: ["mp4", "mov"],
        outputs: ["highlight_reel", "ceremony_edit", "reception_moments"],
      },
      {
        type: "travel_vlog",
        name: "Путевой влог",
        description: "Сборка путешествия с картами, локациями и переходами",
        estimatedDuration: 18,
        complexity: "complex",
        supportedInputs: ["mp4", "mov", "jpg", "png"],
        outputs: ["travel_video", "location_highlights", "social_snippets"],
      },
      {
        type: "product_showcase",
        name: "Презентация продукта",
        description: "Демонстрация товара с деталями и call-to-action",
        estimatedDuration: 12,
        complexity: "medium",
        supportedInputs: ["mp4", "mov"],
        outputs: ["product_demo", "feature_highlights", "social_ads"],
      },
      {
        type: "educational_content",
        name: "Образовательный контент",
        description: "Структурированная подача с главами и субтитрами",
        estimatedDuration: 15,
        complexity: "medium",
        supportedInputs: ["mp4", "mov"],
        outputs: ["lesson_video", "chapters", "quiz_snippets"],
      },
      {
        type: "music_video",
        name: "Музыкальный клип",
        description: "Синхронизация с ритмом, эффекты и цветокоррекция",
        estimatedDuration: 25,
        complexity: "complex",
        supportedInputs: ["mp4", "mov", "mp3"],
        outputs: ["music_video", "lyric_video", "behind_scenes"],
      },
      {
        type: "corporate_intro",
        name: "Корпоративная презентация",
        description: "Профессиональное интро с логотипом и брендингом",
        estimatedDuration: 10,
        complexity: "medium",
        supportedInputs: ["mp4", "mov", "png"],
        outputs: ["intro_video", "branded_content", "team_presentation"],
      },
    ]
  }

  /**
   * Получить активные workflow
   */
  public getActiveWorkflows(): Array<{
    workflowId: string
    type: WorkflowType
    progress: number
    currentStep: string
    startTime: Date
  }> {
    return Array.from(this.activeWorkflows.entries()).map(([id, context]) => ({
      workflowId: id,
      type: context.params.workflowType,
      progress: context.currentProgress || 0,
      currentStep: context.currentStep || "processing",
      startTime: context.startTime || new Date(),
    }))
  }

  /**
   * Отменить workflow
   */
  public async cancelWorkflow(workflowId: string): Promise<boolean> {
    const context = this.activeWorkflows.get(workflowId)
    if (context) {
      this.activeWorkflows.delete(workflowId)
      // Очистка временных файлов и директории
      if (context.tempDirectory) {
        await this.cleanupTempDirectory(context.tempDirectory)
      }
      return true
    }
    return false
  }

  /**
   * Инициализация предустановленных шагов workflow
   */
  private initializeWorkflowSteps(): void {
    // Анализ входного контента
    this.workflowSteps.set("analyze_input", {
      id: "analyze_input",
      name: "Анализ входного контента",
      description: "Анализ видео и аудио файлов для оптимального монтажа",
      category: "analysis",
      estimatedDuration: 30,
      execute: async (context) => {
        const analyses = []
        for (const video of context.params.inputVideos) {
          const analysis = await invoke("ffmpeg_quick_analysis", { filePath: video })
          analyses.push(analysis)
        }
        context.analysisResults.inputAnalysis = analyses
        return { success: true, outputs: { analyses } }
      },
    })

    // Обнаружение сцен
    this.workflowSteps.set("detect_scenes", {
      id: "detect_scenes",
      name: "Обнаружение сцен",
      description: "Автоматическое определение границ сцен для нарезки",
      category: "analysis",
      dependencies: ["analyze_input"],
      estimatedDuration: 45,
      execute: async (context) => {
        const scenes = []
        for (const video of context.params.inputVideos) {
          const sceneData = await invoke("ffmpeg_detect_scenes", {
            filePath: video,
            threshold: 0.3,
            minSceneLength: 2.0,
          })
          scenes.push(sceneData)
        }
        context.analysisResults.scenes = scenes
        return { success: true, outputs: { scenes } }
      },
    })

    // Генерация субтитров
    this.workflowSteps.set("generate_subtitles", {
      id: "generate_subtitles",
      name: "Генерация субтитров",
      description: "Автоматическая транскрипция речи в субтитры",
      category: "enhancement",
      dependencies: ["analyze_input"],
      estimatedDuration: 120,
      execute: async (context) => {
        if (!context.params.preferences.includeSubtitles) {
          return { success: true, outputs: {} }
        }

        const subtitles = []
        for (const video of context.params.inputVideos) {
          const audioPath = await invoke("extract_audio_for_whisper", {
            videoFilePath: video,
            outputFormat: "wav",
          })

          const transcription = await invoke("whisper_transcribe_openai", {
            audioFilePath: audioPath,
            apiKey: "",
            model: "whisper-1",
            language: context.params.preferences.language || "auto",
            responseFormat: "verbose_json",
          })

          subtitles.push(transcription)
        }

        context.analysisResults.subtitles = subtitles
        return { success: true, outputs: { subtitles } }
      },
    })

    // Создание временной линии
    this.workflowSteps.set("create_timeline", {
      id: "create_timeline",
      name: "Создание временной линии",
      description: "Автоматическая сборка видеоряда с переходами",
      category: "editing",
      dependencies: ["detect_scenes"],
      estimatedDuration: 60,
      execute: async (context) => {
        // Генерируем timeline на основе анализа сцен
        const timelineData = this.generateTimelineFromScenes(context.analysisResults.scenes, context.params)

        const projectFile = `${context.tempDirectory}/project.json`
        await invoke("create_timeline_project", {
          projectData: JSON.stringify(timelineData),
          outputPath: projectFile,
        })

        context.timelineData = timelineData
        context.intermediateFiles.projectFile = projectFile

        return { success: true, outputs: { timelineData, projectFile } }
      },
    })

    // Применение эффектов
    this.workflowSteps.set("apply_effects", {
      id: "apply_effects",
      name: "Применение эффектов",
      description: "Автоматическая цветокоррекция и улучшения",
      category: "enhancement",
      dependencies: ["create_timeline"],
      estimatedDuration: 90,
      execute: async (context) => {
        const effects = []

        // Применяем цветокоррекцию
        if (context.params.preferences.colorGrading !== "auto") {
          const colorEffect = await this.applyColorGrading(
            context.timelineData,
            context.params.preferences.colorGrading!,
          )
          effects.push(colorEffect)
        }

        // Стабилизация видео если нужно
        const stabilizationEffect = await this.applyVideoStabilization(context.timelineData)
        effects.push(stabilizationEffect)

        context.timelineData.effects = effects
        return { success: true, outputs: { effects } }
      },
    })

    // Добавление переходов
    this.workflowSteps.set("add_transitions", {
      id: "add_transitions",
      name: "Добавление переходов",
      description: "Автоматическое добавление переходов между сценами",
      category: "editing",
      dependencies: ["create_timeline"],
      estimatedDuration: 30,
      execute: async (context) => {
        const transitionStyle = context.params.preferences.transitionStyle || "dissolve"
        const transitions = this.generateTransitions(context.timelineData, transitionStyle)

        context.timelineData.transitions = transitions
        return { success: true, outputs: { transitions } }
      },
    })

    // Добавление музыки
    this.workflowSteps.set("add_music", {
      id: "add_music",
      name: "Добавление музыки",
      description: "Синхронизация фоновой музыки с видеорядом",
      category: "enhancement",
      dependencies: ["create_timeline"],
      estimatedDuration: 45,
      execute: async (context) => {
        if (!context.params.preferences.musicTrack) {
          return { success: true, outputs: {} }
        }

        const musicSync = await this.synchronizeMusic(
          context.timelineData,
          context.params.preferences.musicTrack,
          context.params.preferences.pace || "medium",
        )

        context.timelineData.audioTracks = [musicSync]
        return { success: true, outputs: { musicSync } }
      },
    })

    // Экспорт результата
    this.workflowSteps.set("export_video", {
      id: "export_video",
      name: "Экспорт видео",
      description: "Рендеринг финального видео",
      category: "export",
      dependencies: ["apply_effects", "add_transitions"],
      estimatedDuration: 300,
      execute: async (context) => {
        const outputPath = `${context.params.outputDirectory}/final_video.mp4`

        const renderResult = await invoke("compile_workflow_video", {
          projectFile: context.intermediateFiles.projectFile,
          outputPath,
          settings: JSON.stringify({
            resolution: { width: 1920, height: 1080 },
            framerate: 30,
            quality: "high",
          }),
        })

        context.intermediateFiles.finalVideo = outputPath
        return { success: true, outputs: { renderResult, outputPath } }
      },
    })

    // Оптимизация для платформ
    this.workflowSteps.set("optimize_platforms", {
      id: "optimize_platforms",
      name: "Оптимизация для платформ",
      description: "Создание версий для разных социальных платформ",
      category: "optimization",
      dependencies: ["export_video"],
      estimatedDuration: 180,
      execute: async (context) => {
        if (!context.params.platformTargets?.length) {
          return { success: true, outputs: {} }
        }

        const platformVersions = []
        const sourceVideo = context.intermediateFiles.finalVideo

        for (const target of context.params.platformTargets) {
          const optimizedPath = `${context.params.outputDirectory}/${target.platform}_optimized.mp4`

          const optimizationResult = await invoke("ffmpeg_optimize_for_platform", {
            inputPath: sourceVideo,
            outputPath: optimizedPath,
            targetWidth: target.aspectRatio === "16:9" ? 1920 : 1080,
            targetHeight: target.aspectRatio === "16:9" ? 1080 : 1920,
            targetBitrate: 3500,
            targetFramerate: 30,
            audioCodec: "aac",
            videoCodec: "h264",
            cropToFit: true,
          })

          platformVersions.push({
            platform: target.platform,
            path: optimizedPath,
            result: optimizationResult,
          })
        }

        return { success: true, outputs: { platformVersions } }
      },
    })
  }

  /**
   * Получить последовательность шагов для workflow
   */
  private getWorkflowSteps(workflowType: WorkflowType): WorkflowStep[] {
    const baseSteps = ["analyze_input", "detect_scenes"]

    const workflowConfigs: Record<WorkflowType, string[]> = {
      quick_edit: [...baseSteps, "create_timeline", "add_transitions", "export_video"],
      social_media_pack: [...baseSteps, "create_timeline", "add_transitions", "export_video", "optimize_platforms"],
      podcast_editing: [...baseSteps, "generate_subtitles", "create_timeline", "add_music", "export_video"],
      presentation_video: [...baseSteps, "generate_subtitles", "create_timeline", "add_transitions", "export_video"],
      wedding_highlights: [
        ...baseSteps,
        "create_timeline",
        "apply_effects",
        "add_music",
        "add_transitions",
        "export_video",
      ],
      travel_vlog: [
        ...baseSteps,
        "create_timeline",
        "apply_effects",
        "add_music",
        "add_transitions",
        "export_video",
        "optimize_platforms",
      ],
      product_showcase: [
        ...baseSteps,
        "create_timeline",
        "apply_effects",
        "add_transitions",
        "export_video",
        "optimize_platforms",
      ],
      educational_content: [...baseSteps, "generate_subtitles", "create_timeline", "add_transitions", "export_video"],
      music_video: [...baseSteps, "create_timeline", "apply_effects", "add_music", "add_transitions", "export_video"],
      corporate_intro: [...baseSteps, "create_timeline", "apply_effects", "add_transitions", "export_video"],
    }

    const stepIds = workflowConfigs[workflowType] || baseSteps
    return stepIds.map((id) => this.workflowSteps.get(id)!).filter(Boolean)
  }

  /**
   * Вспомогательные методы
   */
  private generateWorkflowId(): string {
    return `workflow_${Date.now()}_${Math.random().toString(36).substring(2, 8)}`
  }

  private async createTempDirectory(workflowId: string): Promise<string> {
    const tempDir = `/tmp/timeline_studio/workflows/${workflowId}`
    await invoke("create_directory", { path: tempDir })
    return tempDir
  }

  private generateTimelineFromScenes(scenes: any[], _params: WorkflowParams): any {
    // Генерируем данные timeline на основе обнаруженных сцен
    return {
      version: "1.0",
      settings: {
        resolution: { width: 1920, height: 1080 },
        framerate: 30,
      },
      sections: scenes.map((scene, index) => ({
        id: `section_${index}`,
        name: `Scene ${index + 1}`,
        startTime: scene.startTime || 0,
        endTime: scene.endTime || 10,
        clips: scene.clips || [],
      })),
      effects: [],
      transitions: [],
    }
  }

  private async applyColorGrading(_timelineData: any, style: string): Promise<any> {
    // Применяем цветокоррекцию в зависимости от стиля
    const colorGradingConfigs = {
      warm: { temperature: 200, tint: 50, saturation: 110 },
      cool: { temperature: -200, tint: -50, saturation: 105 },
      cinematic: { contrast: 120, shadows: -30, highlights: -20 },
      natural: { exposure: 0, contrast: 105, saturation: 100 },
    }

    return {
      type: "color_correction",
      settings: colorGradingConfigs[style as keyof typeof colorGradingConfigs] || colorGradingConfigs.natural,
    }
  }

  private async applyVideoStabilization(_timelineData: any): Promise<any> {
    return {
      type: "stabilization",
      settings: { strength: 0.5, smoothness: 0.7 },
    }
  }

  private generateTransitions(timelineData: any, style: string): any[] {
    // Генерируем переходы между секциями
    const transitions = []

    for (let i = 0; i < timelineData.sections.length - 1; i++) {
      transitions.push({
        type: style,
        duration: 1.0,
        fromSection: timelineData.sections[i].id,
        toSection: timelineData.sections[i + 1].id,
      })
    }

    return transitions
  }

  private async synchronizeMusic(_timelineData: any, musicTrack: string, pace: string): Promise<any> {
    // Синхронизируем музыку с видеорядом
    const paceMulipliers = { slow: 0.8, medium: 1.0, fast: 1.2, dynamic: 1.5 }
    const multiplier = paceMulipliers[pace as keyof typeof paceMulipliers] || 1.0

    return {
      audioFile: musicTrack,
      volume: 0.3,
      fadeIn: 2.0,
      fadeOut: 3.0,
      tempoMultiplier: multiplier,
    }
  }

  private async collectWorkflowOutputs(context: WorkflowContext): Promise<WorkflowResult["outputs"]> {
    const outputs: WorkflowResult["outputs"] = []

    // Основное видео
    if (context.intermediateFiles.finalVideo) {
      const metadata = (await invoke("ffmpeg_get_metadata", {
        filePath: context.intermediateFiles.finalVideo,
      })) as any

      outputs.push({
        type: "main_video",
        filePath: context.intermediateFiles.finalVideo,
        metadata: {
          duration: metadata.duration || 0,
          resolution: { width: metadata.width || 1920, height: metadata.height || 1080 },
          fileSize: metadata.fileSize || 0,
          qualityScore: 85,
        },
      })
    }

    return outputs
  }

  private async calculateWorkflowStatistics(
    _context: WorkflowContext,
    totalTime: number,
  ): Promise<WorkflowResult["statistics"]> {
    return {
      processingTime: totalTime,
      automationLevel: 85,
      manualAdjustmentsNeeded: ["Проверить синхронизацию субтитров", "Настроить громкость музыки"],
      qualityAnalysis: {
        videoQuality: 88,
        audioQuality: 82,
        editingFlow: 90,
        overallScore: 87,
      },
    }
  }

  private generateWorkflowSuggestions(
    context: WorkflowContext,
    executionLog: WorkflowResult["executionLog"],
  ): string[] {
    const suggestions = []

    const failedSteps = executionLog.filter((step) => step.status === "failed")
    if (failedSteps.length > 0) {
      suggestions.push("Некоторые шаги завершились с ошибками - рекомендуется ручная проверка")
    }

    if (context.params.preferences.targetDuration) {
      suggestions.push("Проверьте длительность финального видео")
    }

    suggestions.push("Рекомендуется предварительный просмотр перед финальным экспортом")

    return suggestions
  }

  /**
   * Очищает временную директорию workflow
   */
  private async cleanupTempDirectory(tempDir: string): Promise<void> {
    try {
      if (typeof window !== "undefined" && window.__TAURI__) {
        const { remove } = await import("@tauri-apps/plugin-fs")
        await remove(tempDir, { recursive: true })
      }
    } catch (error) {
      console.warn(`Failed to cleanup temp directory ${tempDir}:`, error)
    }
  }
}