plates-server/src/ai-coach/services/diet-analysis.service.spec.ts

import { Test, TestingModule } from '@nestjs/testing';
import { ConfigService } from '@nestjs/config';
import { DietAnalysisService } from './diet-analysis.service';
import { DietRecordsService } from '../../diet-records/diet-records.service';

describe('DietAnalysisService - Text Analysis', () => {
  let service: DietAnalysisService;
  let mockDietRecordsService: Partial<DietRecordsService>;
  let mockConfigService: Partial<ConfigService>;

  beforeEach(async () => {
    // Mock services
    mockDietRecordsService = {
      addDietRecord: jest.fn().mockResolvedValue({}),
      getDietHistory: jest.fn().mockResolvedValue({ total: 0, records: [] }),
      getRecentNutritionSummary: jest.fn().mockResolvedValue({
        recordCount: 0,
        totalCalories: 0,
        totalProtein: 0,
        totalCarbohydrates: 0,
        totalFat: 0,
        totalFiber: 0
      })
    };

    mockConfigService = {
      get: jest.fn().mockImplementation((key: string) => {
        switch (key) {
          case 'DASHSCOPE_API_KEY':
            return 'test-api-key';
          case 'DASHSCOPE_BASE_URL':
            return 'https://test-api.com';
          case 'DASHSCOPE_VISION_MODEL':
            return 'test-model';
          default:
            return undefined;
        }
      })
    };

    const module: TestingModule = await Test.createTestingModule({
      providers: [
        DietAnalysisService,
        { provide: DietRecordsService, useValue: mockDietRecordsService },
        { provide: ConfigService, useValue: mockConfigService },
      ],
    }).compile();

    service = module.get<DietAnalysisService>(DietAnalysisService);
  });

  it('should be defined', () => {
    expect(service).toBeDefined();
  });

  describe('buildTextDietAnalysisPrompt', () => {
    it('should build a proper prompt for text analysis', () => {
      // 通过反射访问私有方法进行测试
      const prompt = (service as any).buildTextDietAnalysisPrompt('breakfast');

      expect(prompt).toContain('作为专业营养分析师');
      expect(prompt).toContain('breakfast');
      expect(prompt).toContain('shouldRecord');
      expect(prompt).toContain('confidence');
      expect(prompt).toContain('extractedData');
      expect(prompt).toContain('analysisText');
    });
  });

  describe('Text diet analysis scenarios', () => {
    const testCases = [
      {
        description: '应该识别简单的早餐描述',
        input: '今天早餐吃了一碗燕麦粥',
        expectedFood: '燕麦粥',
        shouldRecord: true
      },
      {
        description: '应该识别午餐描述',
        input: '午餐点了一份鸡胸肉沙拉',
        expectedFood: '鸡胸肉沙拉',
        shouldRecord: true
      },
      {
        description: '应该识别零食描述',
        input: '刚吃了两个苹果当零食',
        expectedFood: '苹果',
        shouldRecord: true
      },
      {
        description: '不应该记录模糊的描述',
        input: '今天吃得不错',
        shouldRecord: false
      }
    ];

    testCases.forEach(testCase => {
      it(testCase.description, () => {
        // 这里我们主要测试prompt构建逻辑
        // 实际的AI调用需要真实的API密钥，在单元测试中我们跳过
        const prompt = (service as any).buildTextDietAnalysisPrompt('breakfast');
        expect(prompt).toBeDefined();
        expect(typeof prompt).toBe('string');
        expect(prompt.length).toBeGreaterThan(100);
      });
    });
  });

  describe('processDietRecord', () => {
    it('should handle text-based diet records without image URL', async () => {
      const mockAnalysisResult = {
        shouldRecord: true,
        confidence: 85,
        extractedData: {
          foodName: '燕麦粥',
          mealType: 'breakfast' as any,
          portionDescription: '1碗',
          estimatedCalories: 200,
          proteinGrams: 8,
          carbohydrateGrams: 35,
          fatGrams: 3,
          fiberGrams: 4,
          nutritionDetails: {
            mainIngredients: ['燕麦'],
            cookingMethod: '煮制',
            foodCategories: ['主食']
          }
        },
        analysisText: '识别到燕麦粥'
      };

      const result = await service.processDietRecord('test-user-id', mockAnalysisResult);

      expect(result).toBeDefined();
      expect(result?.foodName).toBe('燕麦粥');
      expect(result?.source).toBe('manual'); // 文本记录应该是manual源
      expect(result?.imageUrl).toBeUndefined();
      expect(mockDietRecordsService.addDietRecord).toHaveBeenCalledWith('test-user-id', expect.objectContaining({
        foodName: '燕麦粥',
        source: 'manual'
      }));
    });

    it('should handle image-based diet records with image URL', async () => {
      const mockAnalysisResult = {
        shouldRecord: true,
        confidence: 90,
        extractedData: {
          foodName: '鸡胸肉沙拉',
          mealType: 'lunch' as any,
          portionDescription: '1份',
          estimatedCalories: 300,
          proteinGrams: 25,
          carbohydrateGrams: 10,
          fatGrams: 15,
          fiberGrams: 5,
          nutritionDetails: {
            mainIngredients: ['鸡胸肉', '生菜'],
            cookingMethod: '生食',
            foodCategories: ['蛋白质', '蔬菜']
          }
        },
        analysisText: '识别到鸡胸肉沙拉'
      };

      const result = await service.processDietRecord('test-user-id', mockAnalysisResult, 'https://example.com/image.jpg');

      expect(result).toBeDefined();
      expect(result?.foodName).toBe('鸡胸肉沙拉');
      expect(result?.source).toBe('vision'); // 有图片URL应该是vision源
      expect(result?.imageUrl).toBe('https://example.com/image.jpg');
    });
  });
});