547 lines
20 KiB
Plaintext
547 lines
20 KiB
Plaintext
// AI News System Usage Examples
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import {
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AIServiceManager,
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AITranslationService,
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AIContentAnalysisService,
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AIChatService,
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AIRecommendationService,
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ContentProcessingPipeline,
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type AIServiceConfig,
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type ContentInfo,
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type ChatOptions
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} from '../index.uts'
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/**
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* AI新闻系统使用示例
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* 展示如何集成和使用多语言AI新闻系统的各种功能
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*/
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export class AINewsSystemExample {
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private serviceManager: AIServiceManager
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constructor() {
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// 配置AI服务
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const aiConfig: AIServiceConfig = {
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openai: {
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apiKey: 'your-openai-api-key',
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model: 'gpt-3.5-turbo',
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maxTokens: 2000,
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temperature: 0.7
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},
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google: {
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apiKey: 'your-google-api-key',
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model: 'gemini-pro'
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},
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baidu: {
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apiKey: 'your-baidu-api-key',
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secretKey: 'your-baidu-secret-key',
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model: 'ernie-bot'
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},
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costLimits: {
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dailyUSD: 100,
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monthlyUSD: 2000,
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perRequestUSD: 5
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},
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qualityThresholds: {
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translation: 0.8,
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sentiment: 0.7,
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credibility: 0.6
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}
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}
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// 初始化服务管理器
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this.serviceManager = new AIServiceManager(aiConfig)
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}
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/**
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* 初始化系统
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*/
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async initializeSystem(): Promise<void> {
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console.log('🚀 Initializing AI News System...')
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const response = await this.serviceManager.initialize()
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if (response.success) {
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console.log('✅ AI News System initialized successfully')
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} else {
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console.error('❌ Failed to initialize AI News System:', response.error)
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throw new Error(response.error)
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}
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}
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/**
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* 示例1: 新闻内容翻译
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*/
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async exampleTranslation(): Promise<void> {
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console.log('\n📝 Example 1: News Translation')
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console.log('================================')
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const translationService = this.serviceManager.getTranslationService()
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// 翻译中文新闻到英文
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const chineseNews = "人工智能技术在新闻行业的应用正在快速发展，自动化内容生成、智能推荐和多语言翻译等功能大大提高了新闻生产和传播的效率。"
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console.log('Original Chinese text:', chineseNews)
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const translationResult = await translationService.translateText(
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chineseNews,
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'en',
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'zh-CN',
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{
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provider: 'openai',
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culturalAdaptation: true,
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preserveFormatting: true
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}
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)
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if (translationResult.success && translationResult.data) {
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console.log('✅ Translation successful:')
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console.log('- Translated text:', translationResult.data.translatedText)
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console.log('- Quality score:', translationResult.data.qualityScore)
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console.log('- Provider:', translationResult.data.provider)
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console.log('- Tokens used:', translationResult.data.tokensUsed)
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console.log('- Cost:', `$${translationResult.data.costUSD.toFixed(4)}`)
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} else {
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console.error('❌ Translation failed:', translationResult.error)
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}
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// 批量翻译示例
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const newsTexts = [
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"今日股市行情分析",
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"科技创新推动经济发展",
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"环保政策最新动态"
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]
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console.log('\n📚 Batch translation example:')
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const batchResult = await translationService.translateBatch(
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newsTexts,
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'en',
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'zh-CN',
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{ provider: 'google' },
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{
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batchSize: 2,
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concurrency: 2,
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onProgress: (completed, total) => {
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console.log(`Progress: ${completed}/${total}`)
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}
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}
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)
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if (batchResult.success && batchResult.data) {
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console.log('✅ Batch translation completed:')
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batchResult.data.forEach((result, index) => {
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console.log(`${index + 1}. ${result.translatedText}`)
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})
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}
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}
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/**
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* 示例2: 新闻内容分析
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*/
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async exampleContentAnalysis(): Promise<void> {
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console.log('\n🔍 Example 2: Content Analysis')
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console.log('================================')
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const analysisService = this.serviceManager.getAnalysisService()
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const newsContent = `
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特斯拉公司今日宣布，其最新的自动驾驶技术取得重大突破。
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该技术采用先进的人工智能算法，能够在复杂路况下实现更安全的自动驾驶。
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据公司CEO埃隆·马斯克表示，这项技术将在未来六个月内开始量产。
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市场分析师认为，这一创新将进一步巩固特斯拉在电动汽车市场的领先地位。
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投资者对此消息反应积极，特斯拉股价在盘后交易中上涨了8%。
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`
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console.log('Analyzing content:', newsContent.substring(0, 100) + '...')
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const analysisResult = await analysisService.analyzeContent(newsContent, {
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types: ['sentiment', 'entities', 'topics', 'categories', 'readability', 'credibility', 'summary', 'keywords'],
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provider: 'openai',
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language: 'zh-CN',
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includeScores: true
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})
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if (analysisResult.success && analysisResult.data) {
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const analysis = analysisResult.data
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console.log('✅ Analysis completed:')
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console.log('- Sentiment:', analysis.sentimentLabel, `(${analysis.sentimentScore.toFixed(2)})`)
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console.log('- Readability score:', analysis.readabilityScore.toFixed(2))
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console.log('- Credibility score:', analysis.credibilityScore.toFixed(2))
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console.log('- Keywords:', analysis.keywords.join(', '))
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console.log('- Entities found:', analysis.entities.length)
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analysis.entities.forEach(entity => {
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console.log(` - ${entity.text} (${entity.type}, confidence: ${entity.confidence.toFixed(2)})`)
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})
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console.log('- Categories:')
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analysis.categories.forEach(category => {
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console.log(` - ${category.categoryName} (confidence: ${category.confidence.toFixed(2)})`)
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})
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console.log('- Summary:', analysis.summary)
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} else {
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console.error('❌ Analysis failed:', analysisResult.error)
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}
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}
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/**
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* 示例3: AI聊天助手
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*/
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async exampleChatAssistant(): Promise<void> {
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console.log('\n💬 Example 3: AI Chat Assistant')
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console.log('================================')
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const chatService = this.serviceManager.getChatService()
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// 创建聊天会话
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const sessionResponse = await chatService.createChatSession(
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'user123',
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'zh-CN',
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{
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provider: 'openai',
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temperature: 0.7,
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maxTokens: 1000
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}
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)
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if (sessionResponse.success && sessionResponse.data) {
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const session = sessionResponse.data
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console.log('✅ Chat session created:', session.id)
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// 发送消息
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const messages = [
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"今天有什么重要的科技新闻吗？",
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"请分析一下人工智能对新闻行业的影响",
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"帮我推荐一些相关的新闻文章"
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]
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for (const messageText of messages) {
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console.log(`\n👤 User: ${messageText}`)
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const messageResponse = await chatService.sendMessage(
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session.id,
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messageText,
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{ provider: 'openai' }
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)
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if (messageResponse.success && messageResponse.data) {
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const message = messageResponse.data
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console.log(`🤖 Assistant: ${message.content}`)
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console.log(` Response time: ${message.responseTimeMs}ms`)
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console.log(` Tokens used: ${message.tokensUsed}`)
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} else {
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console.error('❌ Message failed:', messageResponse.error)
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}
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// 模拟对话间隔
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await this.delay(1000)
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}
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// 获取对话历史
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const history = chatService.getChatHistory(session.id, 10)
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console.log(`\n📋 Conversation history (${history.length} messages):`)
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history.forEach((msg, index) => {
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console.log(`${index + 1}. [${msg.type}] ${msg.content.substring(0, 50)}...`)
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})
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// 结束会话
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await chatService.endChatSession(session.id)
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console.log('✅ Chat session ended')
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} else {
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console.error('❌ Failed to create chat session:', sessionResponse.error)
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}
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}
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/**
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* 示例4: 个性化推荐
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*/
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async exampleRecommendations(): Promise<void> {
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console.log('\n🎯 Example 4: Personalized Recommendations')
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console.log('==========================================')
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const recommendationService = this.serviceManager.getRecommendationService()
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// 模拟新闻内容
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const availableNews: ContentInfo[] = [
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{
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id: 'news1',
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title: 'AI技术突破：新一代自然语言处理模型发布',
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content: '研究人员发布了新的大型语言模型，在多项任务上超越了现有技术...',
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originalLanguage: 'zh-CN',
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publishedAt: Date.now() - 1000 * 60 * 60, // 1小时前
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categoryId: 'technology',
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tags: ['AI', '技术', '创新'],
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keywords: ['人工智能', '语言模型', '技术突破'],
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quality: 0.9,
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viewCount: 1500,
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likeCount: 120,
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shareCount: 45,
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status: 'published'
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},
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{
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id: 'news2',
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title: '全球经济展望：数字化转型加速发展',
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content: '世界银行最新报告显示，数字化转型正在重塑全球经济格局...',
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originalLanguage: 'zh-CN',
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publishedAt: Date.now() - 1000 * 60 * 60 * 2, // 2小时前
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categoryId: 'economy',
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tags: ['经济', '数字化', '转型'],
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keywords: ['经济发展', '数字化', '全球'],
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quality: 0.85,
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viewCount: 2100,
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likeCount: 180,
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shareCount: 67,
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status: 'published'
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},
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{
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id: 'news3',
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title: '环保新政策：碳中和目标实施细则发布',
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content: '政府发布了实现碳中和目标的详细实施方案，涉及多个行业的转型升级...',
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originalLanguage: 'zh-CN',
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publishedAt: Date.now() - 1000 * 60 * 60 * 3, // 3小时前
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categoryId: 'environment',
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tags: ['环保', '政策', '碳中和'],
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keywords: ['环保政策', '碳中和', '可持续发展'],
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quality: 0.88,
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viewCount: 980,
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likeCount: 75,
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shareCount: 23,
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status: 'published'
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}
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]
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// 记录用户行为（模拟）
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await recommendationService.recordUserBehavior({
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userId: 'user123',
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contentId: 'news1',
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actionType: 'view',
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timestamp: Date.now() - 1000 * 60 * 30, // 30分钟前
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duration: 120 // 阅读了2分钟
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})
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await recommendationService.recordUserBehavior({
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userId: 'user123',
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contentId: 'news1',
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actionType: 'like',
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timestamp: Date.now() - 1000 * 60 * 25
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})
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// 获取个性化推荐
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console.log('Generating personalized recommendations...')
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const recommendationResponse = await recommendationService.getPersonalizedRecommendations(
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'user123',
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availableNews,
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{
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algorithm: 'hybrid',
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maxResults: 5,
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diversityWeight: 0.3,
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freshnessWeight: 0.4,
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personalizedWeight: 0.3,
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qualityThreshold: 0.7,
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excludeViewed: false
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},
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{
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currentTime: Date.now(),
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recentViews: ['news1'],
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deviceType: 'mobile'
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}
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)
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if (recommendationResponse.success && recommendationResponse.data) {
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console.log('✅ Personalized recommendations:')
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recommendationResponse.data.forEach((rec, index) => {
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const news = availableNews.find(n => n.id === rec.contentId)
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console.log(`${index + 1}. ${news?.title}`)
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console.log(` Score: ${rec.score.toFixed(3)}, Reason: ${rec.reason}`)
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console.log(` Algorithm: ${rec.algorithm}, Type: ${rec.recommendationType}`)
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})
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} else {
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console.error('❌ Recommendations failed:', recommendationResponse.error)
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}
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// 获取热门推荐
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console.log('\n🔥 Trending recommendations:')
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const trendingResponse = await recommendationService.getTrendingRecommendations(
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availableNews,
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24, // 24小时内
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3
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)
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if (trendingResponse.success && trendingResponse.data) {
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trendingResponse.data.forEach((rec, index) => {
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const news = availableNews.find(n => n.id === rec.contentId)
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console.log(`${index + 1}. ${news?.title} (Score: ${rec.score.toFixed(3)})`)
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})
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}
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}
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/**
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* 示例5: 自动化内容处理管道
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*/
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async exampleContentPipeline(): Promise<void> {
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console.log('\n⚙️ Example 5: Automated Content Processing')
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console.log('==========================================')
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const pipeline = this.serviceManager.getProcessingPipeline()
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// 模拟原始新闻内容
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const rawContent: ContentInfo = {
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id: 'raw_news_001',
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title: '突破性医疗技术：基因编辑治疗癌症取得重大进展',
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content: `
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美国斯坦福大学医学院的研究团队今日宣布，他们在基因编辑技术治疗癌症方面取得了重大突破。
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该团队利用CRISPR-Cas9技术，成功修改了T细胞的基因，使其能够更有效地识别和攻击癌细胞。
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在临床试验中，接受治疗的20名患者中有18名病情得到显著改善，治疗有效率达到90%。
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研究负责人张华教授表示，这项技术有望在未来3-5年内进入大规模临床应用阶段。
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美国食品药品监督管理局(FDA)已批准该技术进入二期临床试验。
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业内专家认为，这一突破将为癌症治疗带来革命性变化，可能挽救数百万患者的生命。
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`.trim(),
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originalLanguage: 'zh-CN',
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publishedAt: Date.now(),
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tags: [],
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keywords: [],
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quality: 0,
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viewCount: 0,
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likeCount: 0,
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shareCount: 0,
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status: 'draft'
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}
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console.log('Processing content:', rawContent.title)
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console.log('Original content length:', rawContent.content.length, 'characters')
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// 执行自动化处理
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const processingResponse = await pipeline.processContent(rawContent)
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if (processingResponse.success && processingResponse.data) {
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const result = processingResponse.data
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console.log('✅ Content processing completed:')
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console.log('- Processing time:', `${result.processingTime}ms`)
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console.log('- Total cost:', `$${result.totalCost.toFixed(4)}`)
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console.log('- Final status:', result.status)
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console.log('- Quality score:', result.qualityScore.toFixed(3))
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console.log('\n📊 Analysis results:')
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if (result.analysis) {
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console.log('- Sentiment:', result.analysis.sentimentLabel, `(${result.analysis.sentimentScore.toFixed(2)})`)
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console.log('- Readability:', result.analysis.readabilityScore.toFixed(2))
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console.log('- Credibility:', result.analysis.credibilityScore.toFixed(2))
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console.log('- Keywords:', result.analysis.keywords.slice(0, 5).join(', '))
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}
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console.log('\n🌐 Translation results:')
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Object.entries(result.translations).forEach(([lang, translation]) => {
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console.log(`- ${lang}: ${translation.translatedText.substring(0, 80)}...`)
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console.log(` Quality: ${translation.qualityScore.toFixed(2)}, Cost: $${translation.costUSD.toFixed(4)}`)
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})
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console.log('\n📂 Categories:', result.categories.join(', '))
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if (result.errors.length > 0) {
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console.log('\n⚠️ Errors encountered:')
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result.errors.forEach(error => console.log(`- ${error}`))
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}
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} else {
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console.error('❌ Content processing failed:', processingResponse.error)
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}
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}
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/**
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* 示例6: 系统监控和统计
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*/
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async exampleSystemMonitoring(): Promise<void> {
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console.log('\n📈 Example 6: System Monitoring')
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console.log('================================')
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// 获取服务健康状态
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const servicesHealth = this.serviceManager.getServicesHealth()
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console.log('🏥 Services Health Status:')
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Object.entries(servicesHealth).forEach(([serviceName, health]) => {
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const statusIcon = health.status === 'ready' ? '✅' : health.status === 'error' ? '❌' : '⚠️'
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console.log(`${statusIcon} ${serviceName}: ${health.status}`)
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console.log(` Response time: ${health.responseTime}ms`)
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console.log(` Error rate: ${(health.errorRate * 100).toFixed(1)}%`)
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console.log(` Capabilities: ${health.capabilities.join(', ')}`)
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})
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// 获取管理器统计
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const stats = this.serviceManager.getManagerStatistics()
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console.log('\n📊 Manager Statistics:')
|
||
console.log('- Total requests:', stats.totalRequests)
|
||
console.log('- Success rate:', `${((stats.successfulRequests / Math.max(stats.totalRequests, 1)) * 100).toFixed(1)}%`)
|
||
console.log('- Average response time:', `${stats.avgResponseTime.toFixed(0)}ms`)
|
||
console.log('- Total cost:', `$${stats.totalCost.toFixed(2)}`)
|
||
|
||
console.log('\n💰 Cost breakdown by provider:')
|
||
Object.entries(stats.costBreakdown).forEach(([provider, cost]) => {
|
||
if (cost > 0) {
|
||
console.log(`- ${provider}: $${cost.toFixed(4)}`)
|
||
}
|
||
})
|
||
|
||
// 获取各服务的详细统计
|
||
console.log('\n📋 Individual Service Statistics:')
|
||
|
||
const translationStats = this.serviceManager.getTranslationService().getStatistics()
|
||
console.log('Translation Service:')
|
||
console.log(`- Total requests: ${translationStats.totalRequests}`)
|
||
console.log(`- Success rate: ${((translationStats.successCount / Math.max(translationStats.totalRequests, 1)) * 100).toFixed(1)}%`)
|
||
console.log(`- Cache hit rate: ${(translationStats.cacheHitRate * 100).toFixed(1)}%`)
|
||
console.log(`- Average quality: ${translationStats.avgQuality.toFixed(2)}`)
|
||
|
||
const analysisStats = this.serviceManager.getAnalysisService().getStatistics()
|
||
console.log('\nAnalysis Service:')
|
||
console.log(`- Total analyses: ${analysisStats.totalAnalyses}`)
|
||
console.log(`- Success rate: ${((analysisStats.successCount / Math.max(analysisStats.totalAnalyses, 1)) * 100).toFixed(1)}%`)
|
||
console.log(`- Average processing time: ${analysisStats.avgProcessingTimeMs.toFixed(0)}ms`)
|
||
|
||
const chatStats = this.serviceManager.getChatService().getChatStatistics()
|
||
console.log('\nChat Service:')
|
||
console.log(`- Total sessions: ${chatStats.totalSessions}`)
|
||
console.log(`- Total messages: ${chatStats.totalMessages}`)
|
||
console.log(`- Average response time: ${chatStats.avgResponseTime.toFixed(0)}ms`)
|
||
|
||
const recommendationStats = this.serviceManager.getRecommendationService().getRecommendationStatistics()
|
||
console.log('\nRecommendation Service:')
|
||
console.log(`- Total recommendations: ${recommendationStats.totalRecommendations}`)
|
||
console.log(`- Click-through rate: ${(recommendationStats.clickThroughRate * 100).toFixed(1)}%`)
|
||
console.log(`- User satisfaction: ${recommendationStats.userSatisfactionScore.toFixed(2)}`)
|
||
}
|
||
|
||
/**
|
||
* 运行所有示例
|
||
*/
|
||
async runAllExamples(): Promise<void> {
|
||
try {
|
||
await this.initializeSystem()
|
||
await this.exampleTranslation()
|
||
await this.exampleContentAnalysis()
|
||
await this.exampleChatAssistant()
|
||
await this.exampleRecommendations()
|
||
await this.exampleContentPipeline()
|
||
await this.exampleSystemMonitoring()
|
||
|
||
console.log('\n🎉 All examples completed successfully!')
|
||
|
||
} catch (error) {
|
||
console.error('\n💥 Example execution failed:', error)
|
||
} finally {
|
||
// 清理资源
|
||
await this.serviceManager.shutdown()
|
||
console.log('\n🛑 System shutdown completed')
|
||
}
|
||
}
|
||
|
||
private async delay(ms: number): Promise<void> {
|
||
return new Promise(resolve => setTimeout(resolve, ms))
|
||
}
|
||
}
|
||
|
||
// 导出使用示例函数
|
||
export async function runAINewsSystemExamples(): Promise<void> {
|
||
const example = new AINewsSystemExample()
|
||
await example.runAllExamples()
|
||
}
|
||
|
||
// 如果直接运行此文件，执行示例
|
||
if (typeof require !== 'undefined' && require.main === module) {
|
||
runAINewsSystemExamples().catch(console.error)
|
||
}
|