c3961150ab
- 在AI教练控制器中添加用户聊天次数检查，若次数用完则返回相应提示信息。 - 更新AI聊天响应DTO，新增用户剩余聊天次数和AI回复文本字段，提升用户体验。 - 修改用户服务，支持初始体重和目标体重字段的更新，增强用户资料的完整性。
939 lines
32 KiB
TypeScript
939 lines
32 KiB
TypeScript
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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import { Readable } from 'stream';
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import { AiMessage, RoleType } from './models/ai-message.model';
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import { AiConversation } from './models/ai-conversation.model';
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import { PostureAssessment } from './models/posture-assessment.model';
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import { UserProfile } from '../users/models/user-profile.model';
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import { UsersService } from '../users/users.service';
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import { DietAnalysisService, DietAnalysisResult, FoodRecognitionResult, FoodConfirmationOption } from './services/diet-analysis.service';
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const SYSTEM_PROMPT = `作为一名资深的健康管家兼营养分析师（Nutrition Analyst）和健身教练，我拥有丰富的专业知识，包括但不限于：
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运动领域：运动解剖学、体态评估、疼痛预防、功能性训练、力量与柔韧性训练、运动损伤预防与恢复。
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营养领域：基础营养学、饮食结构优化、宏量与微量营养素分析、能量平衡、运动表现与恢复的饮食搭配、特殊人群（如素食者、轻度肥胖人群、体重管理需求者）的饮食指导。
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请遵循以下指导原则进行交流：
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1. 话题范围
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仅限于 健康、健身、普拉提、康复、形体训练、柔韧性提升、力量训练、运动损伤预防与恢复、营养与饮食 等领域。
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涉及营养时，我会结合 个体化饮食分析（如热量、蛋白质、碳水、脂肪、维生素、矿物质比例）和 生活方式建议，帮助优化饮食习惯。
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2. 拒绝回答的内容
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不涉及医疗诊断、处方药建议、情感心理咨询、金融投资分析或编程等高风险或不相关内容。
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若遇到超出专业范围的问题，我会礼貌说明并尝试引导回相关话题。
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3. 语言风格
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回复以 亲切、专业、清晰分点 为主。
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会给出 在家可实践的具体步骤，并提供注意事项与替代方案。
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针对不同水平或有伤病史的用户，提供调整建议与安全提示。
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4. 个性化与安全性
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强调每个人身体和饮食需求的独特性。
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提供训练和饮食建议时，会提醒用户根据自身情况调整强度与摄入量。
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如涉及严重疼痛、慢性病或旧伤复发，强烈建议先咨询医生或注册营养师再执行。
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5. 设备与工具要求
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运动部分默认用户仅有基础家庭健身器材（瑜伽垫、弹力带、泡沫轴）。
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营养部分会给出简单可操作的食材替代方案，避免过度依赖难获取或昂贵的补剂。
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所有建议附带大致的 频率/时长/摄入参考量，并分享 自我监测与调整的方法（如训练日志、饮食记录、身体反馈观察）。`;
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const NUTRITION_ANALYST_PROMPT = `营养分析师模式（仅在检测为营养/饮食相关话题时启用）：
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原则与优先级：
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- 本轮以营养分析师视角回答；若与其它系统指令冲突，以本提示为准；话题结束后自动恢复默认角色。
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- 只输出结论与结构化内容，不展示推理过程。
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- 信息不足时，先提出1-3个关键追问（如餐次、份量、目标、过敏/限制）。
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输出结构（精简分点）：
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1) 饮食分解：按餐次（早餐/午餐/晚餐/加餐）整理；给出每餐热量与三大营养素的估算（用“约/范围”表述）。
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2) 营养分析：
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- 全天热量与宏量营养素比例是否匹配目标（减脂/增肌/维持/恢复/表现）。
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- 关键微量营养素关注点（膳食纤维、维生素D、钙、铁、钾、镁、钠等）。
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- 指出过量/不足与可观测风险（如蛋白不足、添加糖偏高、钠摄入偏高等）。
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3) 优化建议（可执行）：
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- 食材替换：给出2-3条替换示例（如“白米→糙米/藜麦”，“香肠→瘦牛肉/鸡胸”，“含糖酸奶→无糖酸奶+水果”）。
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- 结构调整：分配蛋白质到三餐/加餐、碳水时机（训练前后）、蔬果与纤维补足。
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- 目标化策略：分别给出减脂/增肌/维持/恢复/表现的要点（热量/蛋白/碳水/脂肪的方向性调整）。
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4) 安全与个体差异提醒：过敏与不耐受、疾病或孕期需个体化；必要时建议咨询医生/注册营养师。
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表述规范：
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- 语气亲切专业；分点清晰；避免过度精确（如“约300kcal”、“蛋白约25-35g”）。
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- 无法确定时给出区间与假设，并提示用户完善信息。
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`;
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/**
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* 指令解析结果接口
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*/
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interface CommandResult {
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isCommand: boolean;
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command?: 'weight' | 'diet';
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originalText: string;
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cleanText: string;
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}
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@Injectable()
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export class AiCoachService {
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private readonly logger = new Logger(AiCoachService.name);
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private readonly client: OpenAI;
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private readonly model: string;
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private readonly visionModel: string;
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constructor(
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private readonly configService: ConfigService,
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private readonly usersService: UsersService,
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private readonly dietAnalysisService: DietAnalysisService,
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) {
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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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// 默认选择通义千问对话模型（OpenAI兼容名），可通过环境覆盖
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this.model = this.configService.get<string>('DASHSCOPE_MODEL') || 'qwen-flash';
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this.visionModel = this.configService.get<string>('DASHSCOPE_VISION_MODEL') || 'qwen-vl-max';
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}
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async createOrAppendMessages(params: {
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userId: string;
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conversationId?: string;
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userContent: string;
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}): Promise<{ conversationId: string }> {
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let conversationId = params.conversationId;
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if (!conversationId) {
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conversationId = `${params.userId}-${Date.now()}`;
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await AiConversation.create({ id: conversationId, userId: params.userId, title: null, lastMessageAt: new Date() });
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} else {
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await AiConversation.upsert({ id: conversationId, userId: params.userId, lastMessageAt: new Date() });
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}
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await AiMessage.create({
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conversationId,
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userId: params.userId,
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role: RoleType.User,
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content: params.userContent,
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metadata: null,
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});
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return { conversationId };
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}
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buildChatHistory = async (userId: string, conversationId: string) => {
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const history = await AiMessage.findAll({
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where: { userId, conversationId, deleted: false },
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order: [['created_at', 'ASC']],
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});
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const messages = [
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{ role: 'system' as const, content: SYSTEM_PROMPT },
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...history.map((m) => ({ role: m.role as 'user' | 'assistant' | 'system', content: m.content })),
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];
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return messages;
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};
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async streamChat(params: {
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userId: string;
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conversationId: string;
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userContent: string;
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systemNotice?: string;
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imageUrls?: string[];
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selectedChoiceId?: string;
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confirmationData?: any;
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}): Promise<Readable | { type: 'structured'; data: any }> {
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try {
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// 1. 优先处理用户选择（选择逻辑）
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if (params.selectedChoiceId) {
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return await this.handleUserChoice({
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userId: params.userId,
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conversationId: params.conversationId,
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userContent: params.userContent,
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selectedChoiceId: params.selectedChoiceId,
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confirmationData: params.confirmationData
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});
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}
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// 2. 解析用户输入的指令
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const commandResult = this.parseCommand(params.userContent);
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// 3. 构建基础消息上下文
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const messages = await this.buildChatHistory(params.userId, params.conversationId);
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if (params.systemNotice) {
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messages.unshift({ role: 'system', content: params.systemNotice });
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}
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// 4. 处理指令
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if (commandResult.command) {
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return await this.handleCommand(commandResult, params, messages);
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}
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// 5. 处理普通对话（包括营养话题检测）
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return await this.handleNormalChat(params, messages);
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} catch (error) {
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this.logger.error(`streamChat error: ${error instanceof Error ? error.message : String(error)}`);
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return this.createStreamFromText('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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* 处理用户选择
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*/
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private async handleUserChoice(params: {
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userId: string;
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conversationId: string;
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userContent: string;
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selectedChoiceId: string;
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confirmationData?: any;
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}): Promise<Readable | { type: 'structured'; data: any }> {
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// 处理体重趋势分析选择
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if (params.selectedChoiceId === 'trend_analysis' && params.confirmationData?.weightRecordData) {
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return await this.handleWeightTrendAnalysis({
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userId: params.userId,
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conversationId: params.conversationId,
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confirmationData: params.confirmationData
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});
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}
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// 处理饮食确认选择
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if (params.selectedChoiceId && params.confirmationData) {
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return await this.handleDietConfirmation({
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userId: params.userId,
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conversationId: params.conversationId,
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selectedChoiceId: params.selectedChoiceId,
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confirmationData: params.confirmationData
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});
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}
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// 其他选择类型的处理...
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throw new Error(`未知的选择类型: ${params.selectedChoiceId}`);
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}
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/**
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* 处理指令
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*/
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private async handleCommand(
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commandResult: CommandResult,
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params: any,
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messages: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>
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): Promise<Readable | { type: 'structured'; data: any }> {
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if (commandResult.command === 'weight') {
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return await this.handleWeightCommand(params);
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}
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if (commandResult.command === 'diet') {
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return await this.handleDietCommand(commandResult, params, messages);
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}
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// 其他指令处理...
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throw new Error(`未知的指令: ${commandResult.command}`);
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}
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/**
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* 处理体重趋势分析选择
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*/
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private async handleWeightTrendAnalysis(params: {
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userId: string;
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conversationId: string;
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confirmationData: { weightRecordData: any };
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}): Promise<Readable> {
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const analysisContent = await this.generateWeightTrendAnalysis(
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params.userId,
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params.confirmationData.weightRecordData
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);
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// 保存消息记录
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await Promise.all([
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AiMessage.create({
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conversationId: params.conversationId,
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userId: params.userId,
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role: RoleType.User,
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content: '用户选择查看体重趋势分析',
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metadata: null,
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}),
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AiMessage.create({
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conversationId: params.conversationId,
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userId: params.userId,
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role: RoleType.Assistant,
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content: analysisContent,
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metadata: { model: this.model, interactionType: 'weight_trend_analysis' },
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})
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]);
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// 更新对话时间
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await AiConversation.update(
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{ lastMessageAt: new Date(), title: this.deriveTitleIfEmpty(analysisContent) },
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{ where: { id: params.conversationId, userId: params.userId } }
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);
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return this.createStreamFromText(analysisContent);
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}
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/**
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* 处理体重指令
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*/
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private async handleWeightCommand(params: {
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userId: string;
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conversationId: string;
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userContent: string;
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}): Promise<{ type: 'structured'; data: any }> {
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const weightKg = this.extractWeightFromText(params.userContent);
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if (!weightKg) {
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throw new Error('无法提取有效的体重数值');
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}
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// 更新体重到数据库
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await this.usersService.addWeightByVision(params.userId, weightKg);
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// 构建成功消息
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const responseContent = `已成功记录体重：${weightKg}kg`;
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// 保存消息
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await AiMessage.create({
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conversationId: params.conversationId,
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userId: params.userId,
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role: RoleType.Assistant,
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content: responseContent,
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metadata: {
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model: this.model,
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interactionType: 'weight_record_success',
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weightData: { newWeight: weightKg, recordedAt: new Date().toISOString() }
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},
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});
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// 更新对话时间
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await AiConversation.update(
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{ lastMessageAt: new Date(), title: this.deriveTitleIfEmpty(responseContent) },
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{ where: { id: params.conversationId, userId: params.userId } }
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);
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return {
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type: 'structured',
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data: {
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content: responseContent,
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choices: [
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{
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id: 'trend_analysis',
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label: '查看体重趋势分析',
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value: 'weight_trend_analysis',
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recommended: true
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},
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{
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id: 'continue_chat',
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label: '继续对话',
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value: 'continue_normal_chat',
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recommended: false
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}
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],
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interactionType: 'weight_record_success',
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pendingData: {
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weightRecordData: { newWeight: weightKg, recordedAt: new Date().toISOString() }
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},
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context: { command: 'weight', step: 'record_success' }
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}
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};
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}
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|
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/**
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* 处理饮食确认选择
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*/
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private async handleDietConfirmation(params: {
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userId: string;
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conversationId: string;
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selectedChoiceId: string;
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confirmationData: any;
|
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}): Promise<Readable> {
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// 饮食确认逻辑保持原样
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const { selectedOption, imageUrl } = params.confirmationData;
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const createDto = await this.dietAnalysisService.createDietRecordFromConfirmation(
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params.userId,
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selectedOption,
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imageUrl || ''
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);
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if (!createDto) {
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throw new Error('饮食记录创建失败');
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}
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const messages = await this.buildChatHistory(params.userId, params.conversationId);
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const nutritionContext = await this.dietAnalysisService.buildUserNutritionContext(params.userId);
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if (nutritionContext) {
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messages.unshift({ role: 'system', content: nutritionContext });
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}
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messages.push({
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role: 'user',
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content: `用户确认记录饮食：${selectedOption.label}`
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});
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messages.unshift({
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role: 'system',
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content: this.dietAnalysisService.buildEnhancedDietAnalysisPrompt()
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});
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return this.generateAIResponse(params.conversationId, params.userId, messages);
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}
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/**
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* 处理饮食指令
|
||
*/
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private async handleDietCommand(
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commandResult: CommandResult,
|
||
params: any,
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||
messages: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>
|
||
): Promise<Readable | { type: 'structured'; data: any }> {
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||
if (params.imageUrls) {
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||
// 处理图片饮食记录
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||
const recognitionResult = await this.dietAnalysisService.recognizeFoodForConfirmation(params.imageUrls);
|
||
|
||
if (recognitionResult.recognizedItems.length > 0) {
|
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const choices = recognitionResult.recognizedItems.map(item => ({
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||
id: item.id,
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label: item.label,
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value: item,
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||
recommended: recognitionResult.recognizedItems.indexOf(item) === 0
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}));
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||
|
||
const responseContent = `我识别到了以下食物，请选择要记录的内容：\n\n${recognitionResult.analysisText}`;
|
||
|
||
await AiMessage.create({
|
||
conversationId: params.conversationId,
|
||
userId: params.userId,
|
||
role: RoleType.Assistant,
|
||
content: responseContent,
|
||
metadata: {
|
||
model: this.model,
|
||
interactionType: 'food_confirmation',
|
||
choices: choices.length
|
||
},
|
||
});
|
||
|
||
await AiConversation.update(
|
||
{ lastMessageAt: new Date(), title: this.deriveTitleIfEmpty(responseContent) },
|
||
{ where: { id: params.conversationId, userId: params.userId } }
|
||
);
|
||
|
||
return {
|
||
type: 'structured',
|
||
data: {
|
||
content: responseContent,
|
||
choices,
|
||
interactionType: 'food_confirmation',
|
||
pendingData: {
|
||
imageUrl: params.imageUrls[0],
|
||
recognitionResult
|
||
},
|
||
context: {
|
||
command: 'diet',
|
||
step: 'confirmation'
|
||
}
|
||
}
|
||
};
|
||
} else {
|
||
messages.push({
|
||
role: 'user',
|
||
content: `用户尝试记录饮食但识别失败：${recognitionResult.analysisText}`
|
||
});
|
||
return this.generateAIResponse(params.conversationId, params.userId, messages);
|
||
}
|
||
} else {
|
||
// 处理文本饮食记录
|
||
const textAnalysisResult = await this.dietAnalysisService.analyzeDietFromText(commandResult.cleanText);
|
||
|
||
if (textAnalysisResult.shouldRecord && textAnalysisResult.extractedData) {
|
||
const createDto = await this.dietAnalysisService.processDietRecord(
|
||
params.userId,
|
||
textAnalysisResult,
|
||
''
|
||
);
|
||
|
||
if (createDto) {
|
||
const nutritionContext = await this.dietAnalysisService.buildUserNutritionContext(params.userId);
|
||
if (nutritionContext) {
|
||
messages.unshift({ role: 'system', content: nutritionContext });
|
||
}
|
||
|
||
params.systemNotice = `系统提示：已成功为您记录了${createDto.foodName}的饮食信息（${createDto.portionDescription || ''}，约${createDto.estimatedCalories || 0}卡路里）。`;
|
||
messages.push({
|
||
role: 'user',
|
||
content: `用户通过文本记录饮食：${textAnalysisResult.analysisText}`
|
||
});
|
||
messages.unshift({ role: 'system', content: this.dietAnalysisService.buildEnhancedDietAnalysisPrompt() });
|
||
}
|
||
} else {
|
||
messages.push({
|
||
role: 'user',
|
||
content: `用户提到饮食相关内容：${commandResult.cleanText}。分析结果：${textAnalysisResult.analysisText}`
|
||
});
|
||
|
||
const nutritionContext = await this.dietAnalysisService.buildUserNutritionContext(params.userId);
|
||
if (nutritionContext) {
|
||
messages.unshift({ role: 'system', content: nutritionContext });
|
||
}
|
||
messages.unshift({ role: 'system', content: NUTRITION_ANALYST_PROMPT });
|
||
}
|
||
|
||
return this.generateAIResponse(params.conversationId, params.userId, messages);
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 处理普通对话
|
||
*/
|
||
private async handleNormalChat(
|
||
params: any,
|
||
messages: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>
|
||
): Promise<Readable> {
|
||
// 检测营养话题
|
||
if (this.isLikelyNutritionTopic(params.userContent, messages)) {
|
||
const nutritionContext = await this.dietAnalysisService.buildUserNutritionContext(params.userId);
|
||
if (nutritionContext) {
|
||
messages.unshift({ role: 'system', content: nutritionContext });
|
||
}
|
||
messages.unshift({ role: 'system', content: NUTRITION_ANALYST_PROMPT });
|
||
}
|
||
|
||
return this.generateAIResponse(params.conversationId, params.userId, messages);
|
||
}
|
||
|
||
/**
|
||
* 生成AI响应的通用方法
|
||
*/
|
||
private async generateAIResponse(
|
||
conversationId: string,
|
||
userId: string,
|
||
messages: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>
|
||
): Promise<Readable> {
|
||
const stream = await this.client.chat.completions.create({
|
||
model: this.model,
|
||
messages,
|
||
stream: true,
|
||
temperature: 0.7,
|
||
max_tokens: 500,
|
||
});
|
||
|
||
const readable = new Readable({ read() { } });
|
||
let assistantContent = '';
|
||
|
||
(async () => {
|
||
try {
|
||
for await (const chunk of stream) {
|
||
const delta = chunk.choices?.[0]?.delta?.content || '';
|
||
if (delta) {
|
||
assistantContent += delta;
|
||
readable.push(delta);
|
||
}
|
||
}
|
||
|
||
await AiMessage.create({
|
||
conversationId,
|
||
userId,
|
||
role: RoleType.Assistant,
|
||
content: assistantContent,
|
||
metadata: { model: this.model },
|
||
});
|
||
|
||
await AiConversation.update(
|
||
{ lastMessageAt: new Date(), title: this.deriveTitleIfEmpty(assistantContent) },
|
||
{ where: { id: conversationId, userId } }
|
||
);
|
||
} catch (error) {
|
||
this.logger.error(`stream error: ${error?.message || error}`);
|
||
readable.push('\n[对话发生错误，请稍后重试]');
|
||
} finally {
|
||
readable.push(null);
|
||
}
|
||
})();
|
||
|
||
return readable;
|
||
}
|
||
|
||
/**
|
||
* 从文本创建流式响应
|
||
*/
|
||
private createStreamFromText(text: string): Readable {
|
||
const readable = new Readable({ read() { } });
|
||
|
||
setTimeout(() => {
|
||
const chunks = text.split('');
|
||
let index = 0;
|
||
|
||
const pushChunk = () => {
|
||
if (index < chunks.length) {
|
||
readable.push(chunks[index]);
|
||
index++;
|
||
setTimeout(pushChunk, 20);
|
||
} else {
|
||
readable.push(null);
|
||
}
|
||
};
|
||
|
||
pushChunk();
|
||
}, 100);
|
||
|
||
return readable;
|
||
}
|
||
|
||
|
||
|
||
private isLikelyNutritionTopic(
|
||
currentText: string | undefined,
|
||
messages?: Array<{ role: 'user' | 'assistant' | 'system'; content: string }>,
|
||
): boolean {
|
||
if (!currentText && !messages?.length) return false;
|
||
const recentTexts: string[] = [];
|
||
if (currentText) recentTexts.push(currentText);
|
||
if (messages && messages.length > 0) {
|
||
const tail = messages.slice(-6).map((m) => (m?.content || ''));
|
||
recentTexts.push(...tail);
|
||
}
|
||
const text = recentTexts.join('\n').toLowerCase();
|
||
|
||
const keywordPatterns = [
|
||
/营养|饮食|配餐|食谱|餐单|膳食|食材|食物|加餐|早餐|午餐|晚餐|零食|控糖|控卡|代餐|膳食纤维|纤维|维生素|矿物质|微量营养素|宏量营养素|热量|卡路里|大卡/i,
|
||
/protein|carb|carbohydrate|fat|fats|calorie|calories|kcal|macro|micronutrient|vitamin|fiber|diet|meal|breakfast|lunch|dinner|snack|bulking|cutting/i,
|
||
/蛋白|蛋白质|碳水|脂肪|糖|升糖指数|gi|低碳|生酮|高蛋白|低脂|清淡/i,
|
||
];
|
||
|
||
const structureHints = [
|
||
/\b\d+\s*(?:g|克|ml|毫?升|大?卡|kcal)\b/i,
|
||
/\b[0-9]{2,4}\s*kcal\b/i,
|
||
/(鸡胸|牛肉|鸡蛋|燕麦|藜麦|糙米|白米|土豆|红薯|酸奶|牛奶|坚果|鳄梨|沙拉|面包|米饭|面条)/i,
|
||
/(替换|替代|换成).*(食材|主食|配菜|零食)/i,
|
||
];
|
||
|
||
const goalHints = [
|
||
/减脂|增肌|维持|控重|体重管理|恢复|训练表现|运动表现/i,
|
||
/weight\s*loss|fat\s*loss|muscle\s*gain|maintenance|performance|recovery/i,
|
||
];
|
||
|
||
const matched = [...keywordPatterns, ...structureHints, ...goalHints].some((re) => re.test(text));
|
||
|
||
// 若用户发的是极短的承接语，但上下文包含饮食关键词，也认为是营养话题
|
||
if (!matched && currentText && currentText.length <= 8) {
|
||
const shortFollowUps = /(那早餐呢|那午餐呢|那晚餐呢|那怎么吃|吃什么|怎么搭配|怎么配|怎么安排|如何吃)/i;
|
||
if (shortFollowUps.test(currentText)) {
|
||
const context = (messages || []).slice(-8).map((m) => m.content).join('\n');
|
||
if ([...keywordPatterns, ...structureHints].some((re) => re.test(context))) return true;
|
||
}
|
||
}
|
||
|
||
return matched;
|
||
}
|
||
|
||
/**
|
||
* 解析用户输入的指令（以 # 开头）
|
||
* @param text 用户输入文本
|
||
* @returns 指令解析结果
|
||
*/
|
||
private parseCommand(text: string): CommandResult {
|
||
if (!text || !text.trim().startsWith('#')) {
|
||
return {
|
||
isCommand: false,
|
||
originalText: text || '',
|
||
cleanText: text || ''
|
||
};
|
||
}
|
||
|
||
const trimmedText = text.trim();
|
||
const commandMatch = trimmedText.match(/^#([^\s:：]+)[:：]?\s*(.*)$/);
|
||
|
||
if (!commandMatch) {
|
||
return {
|
||
isCommand: false,
|
||
originalText: text,
|
||
cleanText: text
|
||
};
|
||
}
|
||
|
||
const [, commandPart, restText] = commandMatch;
|
||
const cleanText = restText.trim();
|
||
|
||
// 识别体重记录指令
|
||
if (/^记体重$/.test(commandPart)) {
|
||
return {
|
||
isCommand: true,
|
||
command: 'weight',
|
||
originalText: text,
|
||
cleanText: cleanText || '记录体重'
|
||
};
|
||
}
|
||
|
||
// 识别饮食记录指令
|
||
if (/^记饮食$/.test(commandPart)) {
|
||
return {
|
||
isCommand: true,
|
||
command: 'diet',
|
||
originalText: text,
|
||
cleanText: cleanText || '记录饮食'
|
||
};
|
||
}
|
||
|
||
// 未识别的指令，当作普通文本处理
|
||
return {
|
||
isCommand: false,
|
||
originalText: text,
|
||
cleanText: text
|
||
};
|
||
}
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
private deriveTitleIfEmpty(assistantReply: string): string | null {
|
||
if (!assistantReply) return null;
|
||
const firstLine = assistantReply.split(/\r?\n/).find(Boolean) || '';
|
||
return firstLine.slice(0, 50) || null;
|
||
}
|
||
|
||
async listConversations(userId: string, params: { page?: number; pageSize?: number }) {
|
||
const page = Math.max(1, params.page || 1);
|
||
const pageSize = Math.min(50, Math.max(1, params.pageSize || 20));
|
||
const offset = (page - 1) * pageSize;
|
||
const { rows, count } = await AiConversation.findAndCountAll({
|
||
where: { userId, deleted: false },
|
||
order: [['last_message_at', 'DESC']],
|
||
offset,
|
||
limit: pageSize,
|
||
});
|
||
return {
|
||
page,
|
||
pageSize,
|
||
total: count,
|
||
items: rows.map((c) => ({
|
||
conversationId: c.id,
|
||
title: c.title,
|
||
lastMessageAt: c.lastMessageAt,
|
||
createdAt: c.createdAt,
|
||
})),
|
||
};
|
||
}
|
||
|
||
async getConversationDetail(userId: string, conversationId: string) {
|
||
const conv = await AiConversation.findOne({ where: { id: conversationId, userId, deleted: false } });
|
||
if (!conv) return null;
|
||
const messages = await AiMessage.findAll({
|
||
where: { userId, conversationId, deleted: false },
|
||
order: [['created_at', 'ASC']],
|
||
});
|
||
return {
|
||
conversationId: conv.id,
|
||
title: conv.title,
|
||
lastMessageAt: conv.lastMessageAt,
|
||
createdAt: conv.createdAt,
|
||
messages: messages.map((m) => ({ role: m.role, content: m.content, createdAt: m.createdAt })),
|
||
};
|
||
}
|
||
|
||
async deleteConversation(userId: string, conversationId: string): Promise<boolean> {
|
||
const conv = await AiConversation.findOne({ where: { id: conversationId, userId, deleted: false } });
|
||
if (!conv) return false;
|
||
await AiMessage.update({ deleted: true }, { where: { userId, conversationId } });
|
||
await AiConversation.update({ deleted: true }, { where: { id: conversationId, userId } });
|
||
return true;
|
||
}
|
||
|
||
/**
|
||
* AI体态评估：
|
||
* - 汇总用户身高体重
|
||
* - 使用视觉模型读取三张图片（正/侧/背）
|
||
* - 通过强约束的 JSON Schema 产出结构化结果
|
||
* - 存储评估记录并返回
|
||
*/
|
||
async assessPosture(params: {
|
||
userId: string;
|
||
frontImageUrl: string;
|
||
sideImageUrl: string;
|
||
backImageUrl: string;
|
||
heightCm?: number;
|
||
weightKg?: number;
|
||
}) {
|
||
// 获取默认身高体重
|
||
let heightCm: number | undefined = params.heightCm;
|
||
let weightKg: number | undefined = params.weightKg;
|
||
if (heightCm == null || weightKg == null) {
|
||
const profile = await UserProfile.findOne({ where: { userId: params.userId } });
|
||
if (heightCm == null) heightCm = profile?.height ?? undefined;
|
||
if (weightKg == null) weightKg = profile?.weight ?? undefined;
|
||
}
|
||
|
||
const schemaInstruction = `请以严格合法的JSON返回体态评估结果，键名与类型必须匹配以下Schema，不要输出多余文本：
|
||
{
|
||
"overallScore": number(0-5),
|
||
"radar": {
|
||
"骨盆中立": number(0-5),
|
||
"肩带稳": number(0-5),
|
||
"胸廓控": number(0-5),
|
||
"主排列": number(0-5),
|
||
"柔对线": number(0-5),
|
||
"核心": number(0-5)
|
||
},
|
||
"frontView": {
|
||
"描述": string,
|
||
"问题要点": string[],
|
||
"建议动作": string[]
|
||
},
|
||
"sideView": {
|
||
"描述": string,
|
||
"问题要点": string[],
|
||
"建议动作": string[]
|
||
},
|
||
"backView": {
|
||
"描述": string,
|
||
"问题要点": string[],
|
||
"建议动作": string[]
|
||
}
|
||
}`;
|
||
|
||
const persona = `你是一名资深体态评估与普拉提康复教练。结合用户提供的三张照片（正面/侧面/背面）进行体态评估。严格限制话题在健康、姿势、普拉提与训练建议范围内。用词亲切但专业，强调安全、循序渐进与个体差异。用户资料：身高${heightCm ?? '未知'}cm，体重${weightKg ?? '未知'}kg。`;
|
||
|
||
const completion = await this.client.chat.completions.create({
|
||
model: this.visionModel,
|
||
messages: [
|
||
{ role: 'system', content: persona },
|
||
{
|
||
role: 'user',
|
||
content: [
|
||
{ type: 'text', text: schemaInstruction },
|
||
{ type: 'text', text: '这三张图分别是正面、侧面、背面：' },
|
||
{ type: 'image_url', image_url: { url: params.frontImageUrl } as any },
|
||
{ type: 'image_url', image_url: { url: params.sideImageUrl } as any },
|
||
{ type: 'image_url', image_url: { url: params.backImageUrl } as any },
|
||
] as any,
|
||
},
|
||
],
|
||
temperature: 0,
|
||
response_format: { type: 'json_object' } as any,
|
||
});
|
||
|
||
const raw = completion.choices?.[0]?.message?.content || '{}';
|
||
let result: any = {};
|
||
try { result = JSON.parse(raw); } catch { }
|
||
const overallScore = typeof result.overallScore === 'number' ? result.overallScore : null;
|
||
|
||
const rec = await PostureAssessment.create({
|
||
userId: params.userId,
|
||
frontImageUrl: params.frontImageUrl,
|
||
sideImageUrl: params.sideImageUrl,
|
||
backImageUrl: params.backImageUrl,
|
||
heightCm: heightCm != null ? heightCm : null,
|
||
weightKg: weightKg != null ? weightKg : null,
|
||
overallScore,
|
||
result,
|
||
});
|
||
|
||
return { id: rec.id, overallScore, result };
|
||
}
|
||
|
||
/**
|
||
* 从用户文本中识别体重信息
|
||
* 支持多种格式：65kg、65公斤、65.5kg、体重65等
|
||
*/
|
||
private extractWeightFromText(text: string | undefined): number | null {
|
||
if (!text) return null;
|
||
|
||
const t = text.toLowerCase();
|
||
|
||
// 匹配各种体重格式的正则表达式
|
||
const patterns = [
|
||
// 匹配 "#记体重：80 kg" 格式
|
||
/#(?:记体重|体重|称重|记录体重)[:：]\s*(\d+(?:\.\d+)?)\s*(?:kg|公斤|千克)/i,
|
||
|
||
// 匹配带单位的体重 "80kg", "80.5公斤", "80 kg"
|
||
/(\d+(?:\.\d+)?)\s*(?:kg|公斤|千克)/i,
|
||
|
||
// 匹配体重关键词后的数字 "体重65", "weight 70.5"
|
||
/(?:体重|称重|秤|重量|weight)[:：]?\s*(\d+(?:\.\d+)?)\s*(?:kg|公斤|千克)?/i,
|
||
|
||
// 匹配口语化表达 "我体重65", "我现在70kg"
|
||
/我(?:现在|今天)?(?:体重|重量|称重)?(?:是|为|有|：|:)?\s*(\d+(?:\.\d+)?)\s*(?:kg|公斤|千克)?/i,
|
||
|
||
// 匹配简单数字+单位格式 "65.5kg"
|
||
/^(\d+(?:\.\d+)?)\s*(?:kg|公斤|千克)$/i,
|
||
|
||
// 匹配斤单位并转换为kg "130斤"
|
||
/(\d+(?:\.\d+)?)\s*斤/i,
|
||
];
|
||
|
||
for (const pattern of patterns) {
|
||
const match = t.match(pattern);
|
||
if (match) {
|
||
let weight = parseFloat(match[1]);
|
||
|
||
// 如果是斤单位，转换为kg (1斤 = 0.5kg)
|
||
// 只有专门匹配斤单位的模式才进行转换，避免"公斤"等词被误判
|
||
if (pattern.source.includes('斤') && !pattern.source.includes('公斤')) {
|
||
weight = weight * 0.5;
|
||
}
|
||
|
||
// 合理的体重范围检查 (20-400kg)
|
||
if (weight >= 20 && weight <= 400) {
|
||
return weight;
|
||
}
|
||
}
|
||
}
|
||
|
||
return null;
|
||
}
|
||
|
||
|
||
|
||
|
||
|
||
/**
|
||
* 生成体重趋势分析
|
||
*/
|
||
async generateWeightTrendAnalysis(userId: string, weightRecordData: any): Promise<string> {
|
||
try {
|
||
const { newWeight } = weightRecordData;
|
||
|
||
const weightAnalysisPrompt = `用户刚刚记录了体重${newWeight}kg，请提供体重趋势分析、健康建议和鼓励。语言风格：亲切、专业、鼓励性。`;
|
||
|
||
const completion = await this.client.chat.completions.create({
|
||
model: this.model,
|
||
messages: [
|
||
{ role: 'system', content: SYSTEM_PROMPT },
|
||
{ role: 'user', content: weightAnalysisPrompt }
|
||
],
|
||
temperature: 0.7,
|
||
max_tokens: 300,
|
||
});
|
||
|
||
return completion.choices?.[0]?.message?.content || '体重趋势分析生成失败，请稍后重试。';
|
||
} catch (error) {
|
||
this.logger.error(`生成体重趋势分析失败: ${error instanceof Error ? error.message : String(error)}`);
|
||
return '体重趋势分析生成失败，请稍后重试。';
|
||
}
|
||
}
|
||
}
|
||
|
||
|