wurenzhi
136c2fa579
- 新增文档模板和导航结构 - 实现服务器基础API路由和控制器 - 添加扩展插件配置和前端框架 - 引入多租户和权限管理模块 - 集成日志和数据库配置 - 添加核心业务模型和类型定义
55 lines
1.7 KiB
TypeScript
55 lines
1.7 KiB
TypeScript
import { AIService } from './AIService';
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import { logger } from '../utils/logger';
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export interface ReviewAnalysis {
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sentiment: 'POSITIVE' | 'NEGATIVE' | 'NEUTRAL';
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score: number; // 0-1
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keywords: string[];
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suggestedReply: string;
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}
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/**
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* [CORE_AI_22] 多模态 SKU 情感分析与评论生成 (Sentiment AI)
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* @description 利用 LLM 分析商品评论情感、提取关键词并自动生成高质量、个性化的回复建议
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*/
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export class SentimentAIService {
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/**
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* 分析单条评论
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*/
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static async analyzeReview(text: string, images?: string[]): Promise<ReviewAnalysis> {
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logger.info(`[SentimentAI] Analyzing review sentiment...`);
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// 实际应调用 AIService 集成 GPT-4o
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// 这里模拟 LLM 分析逻辑
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const mockAnalysis: ReviewAnalysis = {
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sentiment: text.includes('good') || text.includes('great') ? 'POSITIVE' : 'NEGATIVE',
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score: 0.85,
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keywords: ['quality', 'shipping', 'customer service'],
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suggestedReply: `Thank you for your feedback! We're glad you liked the quality of our product. We'll continue to improve our shipping speed.`
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};
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return mockAnalysis;
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}
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/**
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* 批量分析评论并生成月度报告
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*/
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static async aggregateSentiment(reviews: string[]): Promise<{
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overallSentiment: number;
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topKeywords: string[];
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actionItems: string[];
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}> {
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logger.info(`[SentimentAI] Aggregating sentiment for ${reviews.length} reviews`);
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// 模拟聚合逻辑
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return {
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overallSentiment: 0.78,
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topKeywords: ['value for money', 'fast delivery', 'size issue'],
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actionItems: [
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'Improve size chart accuracy for Apparel category',
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'Reward fast shipping logistics partners'
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]
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};
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}
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}
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