feat: 实现饮食记录确认流程
- 新增饮食记录确认流程，将自动记录模式升级为用户确认模式，提升用户交互体验。 - 实现两阶段饮食记录流程，支持AI识别食物并生成确认选项，用户选择后记录到数据库并提供营养分析。 - 扩展DTO层，新增相关数据结构以支持确认流程。 - 更新服务层，新增处理确认逻辑的方法，优化饮食记录的创建流程。 - 增强API文档，详细说明新流程及使用建议，确保开发者理解和使用新功能。
This commit is contained in:
richarjiang
@@ -25,6 +25,33 @@ export interface DietAnalysisResult {
|
||||
analysisText: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* 食物确认选项接口
|
||||
*/
|
||||
export interface FoodConfirmationOption {
|
||||
id: string;
|
||||
label: string;
|
||||
foodName: string;
|
||||
portion: string;
|
||||
calories: number;
|
||||
mealType: MealType;
|
||||
nutritionData: {
|
||||
proteinGrams?: number;
|
||||
carbohydrateGrams?: number;
|
||||
fatGrams?: number;
|
||||
fiberGrams?: number;
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 食物识别确认结果接口
|
||||
*/
|
||||
export interface FoodRecognitionResult {
|
||||
recognizedItems: FoodConfirmationOption[];
|
||||
analysisText: string;
|
||||
confidence: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* 饮食分析服务
|
||||
* 负责处理饮食相关的AI分析、营养评估和上下文构建
|
||||
@@ -50,6 +77,47 @@ export class DietAnalysisService {
|
||||
this.visionModel = this.configService.get<string>('DASHSCOPE_VISION_MODEL') || 'qwen-vl-max';
|
||||
}
|
||||
|
||||
/**
|
||||
* 食物识别用于用户确认 - 新的确认流程
|
||||
* @param imageUrls 图片URL数组
|
||||
* @returns 食物识别确认结果
|
||||
*/
|
||||
async recognizeFoodForConfirmation(imageUrls: string[]): Promise<FoodRecognitionResult> {
|
||||
try {
|
||||
const currentHour = new Date().getHours();
|
||||
const suggestedMealType = this.getSuggestedMealType(currentHour);
|
||||
|
||||
const prompt = this.buildFoodRecognitionPrompt(suggestedMealType);
|
||||
|
||||
const completion = await this.client.chat.completions.create({
|
||||
model: this.visionModel,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: [
|
||||
{ type: 'text', text: prompt },
|
||||
...imageUrls.map((imageUrl) => ({ type: 'image_url', image_url: { url: imageUrl } as any })),
|
||||
] as any,
|
||||
},
|
||||
],
|
||||
temperature: 0.3,
|
||||
response_format: { type: 'json_object' } as any,
|
||||
});
|
||||
|
||||
const rawResult = completion.choices?.[0]?.message?.content || '{}';
|
||||
this.logger.log(`Food recognition result: ${rawResult}`);
|
||||
|
||||
return this.parseRecognitionResult(rawResult, suggestedMealType);
|
||||
} catch (error) {
|
||||
this.logger.error(`食物识别失败: ${error instanceof Error ? error.message : String(error)}`);
|
||||
return {
|
||||
recognizedItems: [],
|
||||
analysisText: '食物识别失败，请稍后重试',
|
||||
confidence: 0
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 增强版饮食图片分析 - 返回结构化数据
|
||||
* @param imageUrls 图片URL数组
|
||||
@@ -91,6 +159,55 @@ export class DietAnalysisService {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 从用户确认的选项创建饮食记录
|
||||
* @param userId 用户ID
|
||||
* @param confirmedOption 用户确认的食物选项
|
||||
* @param imageUrl 图片URL
|
||||
* @returns 饮食记录响应
|
||||
*/
|
||||
async createDietRecordFromConfirmation(
|
||||
userId: string,
|
||||
confirmedOption: FoodConfirmationOption,
|
||||
imageUrl: string
|
||||
): Promise<CreateDietRecordDto | null> {
|
||||
try {
|
||||
const createDto: CreateDietRecordDto = {
|
||||
mealType: confirmedOption.mealType,
|
||||
foodName: confirmedOption.foodName,
|
||||
portionDescription: confirmedOption.portion,
|
||||
estimatedCalories: confirmedOption.calories,
|
||||
proteinGrams: confirmedOption.nutritionData.proteinGrams,
|
||||
carbohydrateGrams: confirmedOption.nutritionData.carbohydrateGrams,
|
||||
fatGrams: confirmedOption.nutritionData.fatGrams,
|
||||
fiberGrams: confirmedOption.nutritionData.fiberGrams,
|
||||
source: DietRecordSource.Vision,
|
||||
imageUrl: imageUrl,
|
||||
aiAnalysisResult: {
|
||||
shouldRecord: true,
|
||||
confidence: 95, // 用户确认后置信度很高
|
||||
extractedData: {
|
||||
foodName: confirmedOption.foodName,
|
||||
mealType: confirmedOption.mealType,
|
||||
portionDescription: confirmedOption.portion,
|
||||
estimatedCalories: confirmedOption.calories,
|
||||
proteinGrams: confirmedOption.nutritionData.proteinGrams,
|
||||
carbohydrateGrams: confirmedOption.nutritionData.carbohydrateGrams,
|
||||
fatGrams: confirmedOption.nutritionData.fatGrams,
|
||||
fiberGrams: confirmedOption.nutritionData.fiberGrams,
|
||||
},
|
||||
analysisText: `用户确认记录：${confirmedOption.label}`
|
||||
}
|
||||
};
|
||||
|
||||
await this.usersService.addDietRecord(userId, createDto);
|
||||
return createDto;
|
||||
} catch (error) {
|
||||
this.logger.error(`用户确认添加饮食记录失败: ${error instanceof Error ? error.message : String(error)}`);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 处理饮食记录并添加到数据库
|
||||
* @param userId 用户ID
|
||||
@@ -203,6 +320,46 @@ export class DietAnalysisService {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 构建食物识别提示（用于确认流程）
|
||||
* @param suggestedMealType 建议的餐次类型
|
||||
* @returns 提示文本
|
||||
*/
|
||||
private buildFoodRecognitionPrompt(suggestedMealType: MealType): string {
|
||||
return `作为专业营养分析师，请分析这张食物图片并生成用户确认选项。
|
||||
|
||||
当前时间建议餐次：${suggestedMealType}
|
||||
|
||||
请识别图片中的食物，并为每种食物生成确认选项。返回以下格式的JSON：
|
||||
{
|
||||
"confidence": number, // 整体识别置信度 0-100
|
||||
"analysisText": string, // 简短的识别说明文字
|
||||
"recognizedItems": [ // 识别的食物列表
|
||||
{
|
||||
"id": string, // 唯一标识符
|
||||
"foodName": string, // 食物名称
|
||||
"portion": string, // 份量描述（如"1碗"、"150g"等）
|
||||
"calories": number, // 估算热量
|
||||
"mealType": "${suggestedMealType}", // 餐次类型
|
||||
"label": string, // 显示给用户的完整选项文本（如"一条鱼 200卡"）
|
||||
"nutritionData": {
|
||||
"proteinGrams": number, // 蛋白质
|
||||
"carbohydrateGrams": number, // 碳水化合物
|
||||
"fatGrams": number, // 脂肪
|
||||
"fiberGrams": number // 膳食纤维
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
要求：
|
||||
1. 如果图片中有多种食物，为每种主要食物生成一个选项
|
||||
2. label字段要简洁易懂，格式如"一条鱼 200卡"、"一碗米饭 150卡"
|
||||
3. 营养数据要合理估算
|
||||
4. 如果图片模糊或无法识别，返回空的recognizedItems数组
|
||||
5. 最多生成5个选项，优先选择主要食物`;
|
||||
}
|
||||
|
||||
/**
|
||||
* 构建饮食分析提示
|
||||
* @param suggestedMealType 建议的餐次类型
|
||||
@@ -242,6 +399,55 @@ export class DietAnalysisService {
|
||||
4. analysisText要详细说明识别的食物和营养分析`;
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析食物识别结果
|
||||
* @param rawResult 原始结果字符串
|
||||
* @param suggestedMealType 建议的餐次类型
|
||||
* @returns 解析后的识别结果
|
||||
*/
|
||||
private parseRecognitionResult(rawResult: string, suggestedMealType: MealType): FoodRecognitionResult {
|
||||
let parsedResult: any;
|
||||
try {
|
||||
parsedResult = JSON.parse(rawResult);
|
||||
} catch (parseError) {
|
||||
this.logger.error(`食物识别JSON解析失败: ${parseError}`);
|
||||
return {
|
||||
recognizedItems: [],
|
||||
analysisText: '图片分析失败：无法解析识别结果',
|
||||
confidence: 0
|
||||
};
|
||||
}
|
||||
|
||||
const recognizedItems: FoodConfirmationOption[] = [];
|
||||
|
||||
if (parsedResult.recognizedItems && Array.isArray(parsedResult.recognizedItems)) {
|
||||
parsedResult.recognizedItems.forEach((item: any, index: number) => {
|
||||
if (item.foodName && item.calories) {
|
||||
recognizedItems.push({
|
||||
id: item.id || `food_${index}`,
|
||||
label: item.label || `${item.foodName} ${item.calories}卡`,
|
||||
foodName: item.foodName,
|
||||
portion: item.portion || '1份',
|
||||
calories: this.validateNumber(item.calories, 1, 2000) || 0,
|
||||
mealType: this.validateMealType(item.mealType) || suggestedMealType,
|
||||
nutritionData: {
|
||||
proteinGrams: this.validateNumber(item.nutritionData?.proteinGrams, 0, 200),
|
||||
carbohydrateGrams: this.validateNumber(item.nutritionData?.carbohydrateGrams, 0, 500),
|
||||
fatGrams: this.validateNumber(item.nutritionData?.fatGrams, 0, 200),
|
||||
fiberGrams: this.validateNumber(item.nutritionData?.fiberGrams, 0, 50),
|
||||
}
|
||||
});
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
return {
|
||||
recognizedItems,
|
||||
analysisText: parsedResult.analysisText || '已识别图片中的食物',
|
||||
confidence: Math.min(100, Math.max(0, parsedResult.confidence || 0))
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* 解析和验证分析结果
|
||||
* @param rawResult 原始结果字符串
|
||||
|
||||
Reference in New Issue
Block a user