makemd/dashboard/src/services/adOptimizationDataSource.ts

/**
 * [MOCK-AD-001] Ad Optimization数据源抽象层
 * AI注意: 这是数据源抽象层，业务组件通过此层获取数据
 * 仅在REACT_APP_USE_MOCK=true时启用Mock
 * 
 * @module services/adOptimizationDataSource
 * @created 2026-03-19
 */



// ============================================
// 类型定义
// ============================================

export interface OptimizationSuggestion {
  id: string;
  adId: string;
  adName: string;
  currentCPC: number;
  suggestedCPC: number;
  currentROI: number;
  expectedROI: number;
  currentSpend: number;
  suggestedSpend: number;
  confidence: number;
  status: 'pending' | 'applied' | 'rejected';
}

export interface AdPerformance {
  id: string;
  date: string;
  clicks: number;
  conversions: number;
  spend: number;
  roi: number;
}

export interface AdOptimizationQueryParams {
  adId?: string;
  startDate?: string;
  endDate?: string;
}

export interface AdOptimizationData {
  suggestions: OptimizationSuggestion[];
  performance: AdPerformance[];
}

// ============================================
// Ad Optimization专用接口
// ============================================

export interface IAdOptimizationDataSource {
  optimize(params?: AdOptimizationQueryParams): Promise<AdOptimizationData>;
  fetchSuggestions(): Promise<OptimizationSuggestion[]>;
  fetchPerformance(): Promise<AdPerformance[]>;
  applySuggestion(id: string): Promise<OptimizationSuggestion>;
  rejectSuggestion(id: string): Promise<OptimizationSuggestion>;
}

// ============================================
// API实现
// ============================================

class ApiAdOptimizationDataSource implements IAdOptimizationDataSource {
  async optimize(params?: AdOptimizationQueryParams): Promise<AdOptimizationData> {
    const [suggestions, performance] = await Promise.all([
      this.fetchSuggestions(),
      this.fetchPerformance(),
    ]);
    return { suggestions, performance };
  }

  async fetchSuggestions(): Promise<OptimizationSuggestion[]> {
    const response = await fetch('/api/v1/ad/optimization/suggestions');
    const result = await response.json();
    return result.data;
  }

  async fetchPerformance(): Promise<AdPerformance[]> {
    const response = await fetch('/api/v1/ad/optimization/performance');
    const result = await response.json();
    return result.data;
  }

  async applySuggestion(id: string): Promise<OptimizationSuggestion> {
    const response = await fetch(`/api/v1/ad/optimization/suggestions/${id}/apply`, {
      method: 'POST',
    });
    const result = await response.json();
    return result.data;
  }

  async rejectSuggestion(id: string): Promise<OptimizationSuggestion> {
    const response = await fetch(`/api/v1/ad/optimization/suggestions/${id}/reject`, {
      method: 'POST',
    });
    const result = await response.json();
    return result.data;
  }
}

// ============================================
// Mock实现
// ============================================

/**
 * [MOCK] Ad Optimization Mock数据源
 * AI注意: 这是Mock实现，不是真实业务逻辑
 * 仅在REACT_APP_USE_MOCK=true时启用
 */
class MockAdOptimizationDataSource implements IAdOptimizationDataSource {
  readonly __MOCK__ = true as const;
  readonly __MOCK_NAME__ = 'MockAdOptimizationDataSource';

  private mockSuggestions: OptimizationSuggestion[] = [
    {
      id: '1',
      adId: 'AD001',
      adName: '智能手表推广',
      currentCPC: 1.5,
      suggestedCPC: 1.2,
      currentROI: 3.2,
      expectedROI: 4.5,
      currentSpend: 1000,
      suggestedSpend: 1200,
      confidence: 0.85,
      status: 'pending',
    },
    {
      id: '2',
      adId: 'AD002',
      adName: '无线耳机促销',
      currentCPC: 0.8,
      suggestedCPC: 1.0,
      currentROI: 2.8,
      expectedROI: 3.5,
      currentSpend: 800,
      suggestedSpend: 900,
      confidence: 0.90,
      status: 'pending',
    },
    {
      id: '3',
      adId: 'AD003',
      adName: '智能音箱新品',
      currentCPC: 2.0,
      suggestedCPC: 1.8,
      currentROI: 2.5,
      expectedROI: 3.2,
      currentSpend: 1200,
      suggestedSpend: 1000,
      confidence: 0.80,
      status: 'pending',
    },
  ];

  private mockPerformance: AdPerformance[] = [
    { id: '1', date: '2026-03-12', clicks: 1200, conversions: 120, spend: 1800, roi: 3.2 },
    { id: '2', date: '2026-03-13', clicks: 1300, conversions: 135, spend: 1950, roi: 3.4 },
    { id: '3', date: '2026-03-14', clicks: 1100, conversions: 105, spend: 1650, roi: 3.1 },
    { id: '4', date: '2026-03-15', clicks: 1400, conversions: 150, spend: 2100, roi: 3.3 },
    { id: '5', date: '2026-03-16', clicks: 1500, conversions: 165, spend: 2250, roi: 3.5 },
    { id: '6', date: '2026-03-17', clicks: 1600, conversions: 180, spend: 2400, roi: 3.6 },
    { id: '7', date: '2026-03-18', clicks: 1700, conversions: 195, spend: 2550, roi: 3.8 },
  ];

  async optimize(params?: AdOptimizationQueryParams): Promise<AdOptimizationData> {
    await this.simulateDelay(1500);
    const [suggestions, performance] = await Promise.all([
      this.fetchSuggestions(),
      this.fetchPerformance(),
    ]);
    return { suggestions, performance };
  }

  async fetchSuggestions(): Promise<OptimizationSuggestion[]> {
    await this.simulateDelay(300);
    return [...this.mockSuggestions];
  }

  async fetchPerformance(): Promise<AdPerformance[]> {
    await this.simulateDelay(200);
    return [...this.mockPerformance];
  }

  async applySuggestion(id: string): Promise<OptimizationSuggestion> {
    await this.simulateDelay(200);
    const index = this.mockSuggestions.findIndex(s => s.id === id);
    if (index === -1) throw new Error('Suggestion not found');
    this.mockSuggestions[index] = { ...this.mockSuggestions[index], status: 'applied' };
    return this.mockSuggestions[index];
  }

  async rejectSuggestion(id: string): Promise<OptimizationSuggestion> {
    await this.simulateDelay(200);
    const index = this.mockSuggestions.findIndex(s => s.id === id);
    if (index === -1) throw new Error('Suggestion not found');
    this.mockSuggestions[index] = { ...this.mockSuggestions[index], status: 'rejected' };
    return this.mockSuggestions[index];
  }

  private simulateDelay(ms: number): Promise<void> {
    return new Promise(resolve => setTimeout(resolve, ms));
  }

  // Mock特定方法
  reset(): void {
    this.mockSuggestions = [
      {
        id: '1',
        adId: 'AD001',
        adName: '智能手表推广',
        currentCPC: 1.5,
        suggestedCPC: 1.2,
        currentROI: 3.2,
        expectedROI: 4.5,
        currentSpend: 1000,
        suggestedSpend: 1200,
        confidence: 0.85,
        status: 'pending',
      },
      {
        id: '2',
        adId: 'AD002',
        adName: '无线耳机促销',
        currentCPC: 0.8,
        suggestedCPC: 1.0,
        currentROI: 2.8,
        expectedROI: 3.5,
        currentSpend: 800,
        suggestedSpend: 900,
        confidence: 0.90,
        status: 'pending',
      },
      {
        id: '3',
        adId: 'AD003',
        adName: '智能音箱新品',
        currentCPC: 2.0,
        suggestedCPC: 1.8,
        currentROI: 2.5,
        expectedROI: 3.2,
        currentSpend: 1200,
        suggestedSpend: 1000,
        confidence: 0.80,
        status: 'pending',
      },
    ];
  }

  getMockData(): OptimizationSuggestion[] {
    return this.mockSuggestions;
  }
}

// ============================================
// 导出数据源实例
// ============================================

const useMock = process.env.REACT_APP_USE_MOCK === 'true';

export const adOptimizationDataSource: IAdOptimizationDataSource = useMock
  ? new MockAdOptimizationDataSource()
  : new ApiAdOptimizationDataSource();

export const __MOCK__ = useMock;
export const __DATA_SOURCE_TYPE__ = useMock ? 'mock' : 'api';