feat(diet-records): 新增营养成分表图片分析功能
- 添加营养成分表图片识别API接口，支持通过AI模型分析食物营养成分 - 新增NutritionAnalysisService服务，集成GLM-4.5V和Qwen VL视觉模型 - 实现营养成分提取和健康建议生成功能 - 添加完整的API文档和TypeScript类型定义 - 支持多种营养素类型识别，包括热量、蛋白质、脂肪等20+种营养素
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richarjiang
282
src/diet-records/services/nutrition-analysis.service.ts
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282
src/diet-records/services/nutrition-analysis.service.ts
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import { Injectable, Logger } from '@nestjs/common';
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import { ConfigService } from '@nestjs/config';
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import { OpenAI } from 'openai';
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/**
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* 营养成分分析结果接口
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*/
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export interface NutritionAnalysisResult {
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key: string; // 营养素的唯一标识，如 energy_kcal
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name: string; // 营养素的中文名称，如"热量"
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value: string; // 从图片中识别的原始值和单位，如"840千焦"
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analysis: string; // 针对该营养素的详细健康建议
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}
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/**
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* 营养成分分析响应接口
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*/
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export interface NutritionAnalysisResponse {
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success: boolean;
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data: NutritionAnalysisResult[];
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message?: string;
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}
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/**
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* 营养成分分析服务
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* 负责处理食物营养成分表的AI分析
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*
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* 支持多种AI模型：
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* - GLM-4.5V (智谱AI) - 设置 AI_VISION_PROVIDER=glm
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* - Qwen VL (阿里云DashScope) - 设置 AI_VISION_PROVIDER=dashscope (默认)
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*/
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@Injectable()
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export class NutritionAnalysisService {
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private readonly logger = new Logger(NutritionAnalysisService.name);
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private readonly client: OpenAI;
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private readonly visionModel: string;
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private readonly apiProvider: string;
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constructor(private readonly configService: ConfigService) {
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// Support both GLM-4.5V and DashScope (Qwen) models
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this.apiProvider = this.configService.get<string>('AI_VISION_PROVIDER') || 'dashscope';
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if (this.apiProvider === 'glm') {
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// GLM-4.5V Configuration
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const glmApiKey = this.configService.get<string>('GLM_API_KEY');
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const glmBaseURL = this.configService.get<string>('GLM_BASE_URL') || 'https://open.bigmodel.cn/api/paas/v4';
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this.client = new OpenAI({
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apiKey: glmApiKey,
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baseURL: glmBaseURL,
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});
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this.visionModel = this.configService.get<string>('GLM_VISION_MODEL') || 'glm-4v-plus';
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} else {
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// DashScope Configuration (default)
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const dashScopeApiKey = this.configService.get<string>('DASHSCOPE_API_KEY') || 'sk-e3ff4494c2f1463a8910d5b3d05d3143';
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const baseURL = this.configService.get<string>('DASHSCOPE_BASE_URL') || 'https://dashscope.aliyuncs.com/compatible-mode/v1';
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this.client = new OpenAI({
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apiKey: dashScopeApiKey,
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baseURL,
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});
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this.visionModel = this.configService.get<string>('DASHSCOPE_VISION_MODEL') || 'qwen-vl-max';
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}
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}
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/**
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* 分析食物营养成分表图片
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* @param imageUrl 图片URL
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* @returns 营养成分分析结果
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*/
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async analyzeNutritionImage(imageUrl: string): Promise<NutritionAnalysisResponse> {
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try {
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this.logger.log(`开始分析营养成分表图片: ${imageUrl}`);
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const prompt = this.buildNutritionAnalysisPrompt();
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const completion = await this.makeVisionApiCall(prompt, [imageUrl]);
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const rawResult = completion.choices?.[0]?.message?.content || '[]';
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this.logger.log(`营养成分分析原始结果: ${rawResult}`);
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return this.parseNutritionAnalysisResult(rawResult);
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} catch (error) {
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this.logger.error(`营养成分表分析失败: ${error instanceof Error ? error.message : String(error)}`);
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return {
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success: false,
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data: [],
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message: '营养成分表分析失败，请稍后重试'
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};
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}
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}
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/**
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* 制作视觉模型API调用 - 兼容GLM-4.5V和DashScope
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* @param prompt 提示文本
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* @param imageUrls 图片URL数组
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* @returns API响应
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*/
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private async makeVisionApiCall(prompt: string, imageUrls: string[]) {
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const baseParams = {
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model: this.visionModel,
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temperature: 0.3,
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response_format: { type: 'json_object' } as any,
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};
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// 处理图片URL
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const processedImages = imageUrls.map((imageUrl) => ({
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type: 'image_url',
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image_url: { url: imageUrl } as any,
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}));
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if (this.apiProvider === 'glm') {
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// GLM-4.5V format
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return await this.client.chat.completions.create({
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...baseParams,
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messages: [
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{
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role: 'user',
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content: [
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{ type: 'text', text: prompt },
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...processedImages,
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] as any,
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},
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],
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} as any);
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} else {
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// DashScope format (default)
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return await this.client.chat.completions.create({
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...baseParams,
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messages: [
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{
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role: 'user',
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content: [
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{ type: 'text', text: prompt },
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...processedImages,
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] as any,
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},
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],
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});
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}
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}
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/**
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* 构建营养成分分析提示
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* @returns 提示文本
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*/
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private buildNutritionAnalysisPrompt(): string {
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return `作为专业的营养分析师，请仔细分析这张图片中的营养成分表。
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**任务要求：**
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1. 识别图片中的营养成分表，提取所有可见的营养素信息
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2. 为每个营养素提供详细的健康建议和分析
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3. 返回严格的JSON数组格式，不包含任何额外的解释或对话文本
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**输出格式要求：**
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请严格按照以下JSON数组格式返回，每个对象包含四个字段：
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[
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{
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"key": "energy_kcal",
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"name": "热量",
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"value": "840千焦",
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"analysis": "840千焦约等于201卡路里，占成人每日推荐摄入总热量的10%，属于中等热量水平。"
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},
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{
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"key": "protein",
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"name": "蛋白质",
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"value": "12.5g",
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"analysis": "12.5克蛋白质占成人每日推荐摄入量的21%，是良好的蛋白质来源，有助于肌肉修复和生长。"
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}
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]
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**营养素标识符对照表：**
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- 热量/能量: energy_kcal
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- 蛋白质: protein
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- 脂肪: fat
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- 碳水化合物: carbohydrate
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- 膳食纤维: fiber
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- 钠: sodium
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- 钙: calcium
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- 铁: iron
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- 锌: zinc
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- 维生素C: vitamin_c
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- 维生素A: vitamin_a
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- 维生素D: vitamin_d
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- 维生素E: vitamin_e
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- 维生素B1: vitamin_b1
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- 维生素B2: vitamin_b2
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- 维生素B6: vitamin_b6
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- 维生素B12: vitamin_b12
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- 叶酸: folic_acid
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- 胆固醇: cholesterol
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- 饱和脂肪: saturated_fat
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- 反式脂肪: trans_fat
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- 糖: sugar
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- 其他营养素: other_nutrient
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**分析要求：**
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1. 如果图片中没有营养成分表，返回空数组 []
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2. 为每个识别到的营养素提供具体的健康建议
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3. 建议应包含营养素的作用、摄入量参考和健康影响
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4. 数值分析要准确，建议要专业且实用
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5. 只返回JSON数组，不要包含任何其他文本
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**重要提醒：**
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- 严格按照JSON数组格式返回
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- 不要添加任何解释性文字或对话内容
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- 确保JSON格式正确，可以被直接解析`;
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}
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/**
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* 解析营养成分分析结果
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* @param rawResult 原始结果字符串
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* @returns 解析后的分析结果
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*/
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private parseNutritionAnalysisResult(rawResult: string): NutritionAnalysisResponse {
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try {
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// 尝试解析JSON
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let parsedResult: any;
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try {
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parsedResult = JSON.parse(rawResult);
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} catch (parseError) {
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this.logger.error(`营养成分分析JSON解析失败: ${parseError}`);
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this.logger.error(`原始结果: ${rawResult}`);
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return {
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success: false,
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data: [],
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message: '营养成分表解析失败，无法识别有效的营养信息'
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};
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}
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// 确保结果是数组
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if (!Array.isArray(parsedResult)) {
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this.logger.error(`营养成分分析结果不是数组格式: ${typeof parsedResult}`);
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return {
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success: false,
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data: [],
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message: '营养成分表格式错误，无法识别有效的营养信息'
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};
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}
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// 验证和标准化每个营养素项
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const nutritionData: NutritionAnalysisResult[] = [];
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for (const item of parsedResult) {
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if (item && typeof item === 'object' && item.key && item.name && item.value && item.analysis) {
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nutritionData.push({
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key: String(item.key).trim(),
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name: String(item.name).trim(),
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value: String(item.value).trim(),
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analysis: String(item.analysis).trim()
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});
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} else {
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this.logger.warn(`跳过无效的营养素项: ${JSON.stringify(item)}`);
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}
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}
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if (nutritionData.length === 0) {
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return {
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success: false,
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data: [],
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message: '图片中未检测到有效的营养成分表信息'
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};
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}
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this.logger.log(`成功解析 ${nutritionData.length} 项营养素信息`);
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return {
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success: true,
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data: nutritionData
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};
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} catch (error) {
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this.logger.error(`营养成分分析结果处理失败: ${error instanceof Error ? error.message : String(error)}`);
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return {
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success: false,
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data: [],
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message: '营养成分表处理失败，请稍后重试'
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};
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}
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}
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}
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