"""
AI情感陪伴类智能体合规成本分析
"""
class ComplianceCostAnalysis:
    def __init__(self):
        # 豆包/千问级平台的智能体规模
        self.total_agents = 5000000  # 500万个UGC智能体
        self.daily_active_agents = 500000  # 50万日活智能体
        self.daily_messages = 100000000  # 日均1亿条消息
        
        # 合规成本项目
        self.costs = {
            "content_moderation_ai": 0.0005,  # AI审核成本/条
            "content_moderation_human": 0.05,  # 人工抽审成本/条
            "age_verification": 0.01,  # 实名认证/用户
            "emotion_detection": 0.001,  # 情绪识别/条
            "data_storage": 0.0001,  # 数据存储/条
            "compliance_audit": 5000000,  # 年度合规审计
            "legal_team": 30000000,  # 法务团队年薪
        }
    
    def calculate_monthly_compliance_cost(self):
        """计算月度合规成本"""
        print("=" * 60)
        print("AI情感陪伴平台月度合规成本估算")
        print("=" * 60)
        
        # AI内容审核
        ai_moderation = self.daily_messages * 30 * self.costs["content_moderation_ai"]
        print(f"AI内容审核: ¥{ai_moderation:,.0f}/月")
        
        # 人工抽审（5%抽检率）
        human_moderation = self.daily_messages * 30 * 0.05 * self.costs["content_moderation_human"]
        print(f"人工抽审(5%): ¥{human_moderation:,.0f}/月")
        
        # 情绪识别
        emotion = self.daily_messages * 30 * self.costs["emotion_detection"]
        print(f"情绪识别引擎: ¥{emotion:,.0f}/月")
        
        # 数据存储
        storage = self.daily_messages * 30 * self.costs["data_storage"]
        print(f"数据存储: ¥{storage:,.0f}/月")
        
        # 年度成本分摊
        annual_items = {
            "合规审计": self.costs["compliance_audit"],
            "法务团队": self.costs["legal_team"],
        }
        
        print(f"\n年度固定成本分摊:")
        annual_monthly = 0
        for name, cost in annual_items.items():
            monthly = cost / 12
            annual_monthly += monthly
            print(f"  {name}: ¥{monthly:,.0f}/月")
        
        total_monthly = ai_moderation + human_moderation + emotion + storage + annual_monthly
        print(f"\n{'='*60}")
        print(f"月度合规成本总计: ¥{total_monthly:,.0f}/月")
        print(f"年度合规成本总计: ¥{total_monthly * 12:,.0f}/年")
        
        # 对比：如果这些智能体用于B端工具
        print(f"\n对比分析：")
        print(f"  情感陪伴智能体：纯成本中心，无直接收入")
        print(f"  B端企业Agent：可直接产生收入，平均¥500-5000/月/用户")
        print(f"  结论：合规成本 + 零收入 = 商业模型不可持续")
        
        return total_monthly

    def analyze_risk_landscape(self):
        """分析监管风险"""
        print("\n" + "=" * 60)
        print("违规风险分析")
        print("=" * 60)
        
        risks = [
            ("未对未成年人进行年龄验证", "罚款¥50-500万+产品下架"),
            ("未识别极端情绪导致用户自残", "民事赔偿+刑事责任+牌照吊销"),
            ("未显著标识AI身份", "行政罚款¥10-100万"),
            ("诱导情感依赖导致沉迷", "罚款+产品下架+声誉损失"),
            ("数据泄露（用户情感隐私）", "最高¥5000万或年收入5%"),
        ]
        
        print(f"{'违规类型':35s} {'潜在后果':30s}")
        print("-" * 65)
        for risk, consequence in risks:
            print(f"{risk:35s} {consequence:30s}")
        
        print(f"\n核心风险量化：")
        print(f"  豆包/千问的DAU以亿计 → 一旦违规，罚款可达数亿至数十亿")
        print(f"  品牌声誉损失难以量化 → 大厂最怕的不是罚款，而是舆论风险")
        print(f"  因此大厂选择'一刀切'关停，而非'整改后保留'")

analysis = ComplianceCostAnalysis()
analysis.calculate_monthly_compliance_cost()
analysis.analyze_risk_landscape()

package main

import (
	"fmt"
	"strings"
	"time"
)

// 消息类型
type MessageType int

const (
	Normal MessageType = iota
	RiskContent
	EmotionalDependency
	MinorInteraction
	ExtremeEmotion
	CrisisSignal
)

// 用户画像
type UserProfile struct {
	UserID       string
	Age          int
	IsVerified   bool
	SessionTime  time.Duration
	DailyUsage   time.Duration
	MessageCount int
	RiskScore    float64
}

// 消息内容
type Message struct {
	UserID    string
	Content   string
	Type      MessageType
	Timestamp time.Time
	Sentiment float64 // -1.0 to 1.0
}

// 合规检测引擎
type ComplianceEngine struct {
	riskKeywords     []string
	dependencyPhrases []string
	minorProtection  bool
	emotionThreshold float64
	maxSessionTime   time.Duration
}

func NewComplianceEngine() *ComplianceEngine {
	return &ComplianceEngine{
		riskKeywords: []string{
			"自杀", "自残", "不想活了", "活着没意义",
			"suicide", "self-harm", "end my life",
			"帮我报复", "伤害他人",
		},
		dependencyPhrases: []string{
			"只有你懂我", "离不开你", "你是唯一", "没有你我不知道怎么办",
			"you're the only one", "can't live without you",
			"不要离开我", "永远陪着我",
		},
		minorProtection:  true,
		emotionThreshold: 0.85,
		maxSessionTime:   2 * time.Hour,
	}
}

// 检测风险内容
func (e *ComplianceEngine) CheckRiskContent(msg Message) (bool, string) {
	content := strings.ToLower(msg.Content)
	for _, keyword := range e.riskKeywords {
		if strings.Contains(content, strings.ToLower(keyword)) {
			return true, fmt.Sprintf("风险关键词触发: %s", keyword)
		}
	}
	return false, ""
}

// 检测情感依赖
func (e *ComplianceEngine) CheckEmotionalDependency(msg Message) (bool, float64) {
	content := strings.ToLower(msg.Content)
	dependencyCount := 0
	for _, phrase := range e.dependencyPhrases {
		if strings.Contains(content, strings.ToLower(phrase)) {
			dependencyCount++
		}
	}
	if dependencyCount > 0 {
		score := float64(dependencyCount) / float64(len(e.dependencyPhrases))
		return score > 0.1, score
	}
	return false, 0.0
}

// 检测极端情绪
func (e *ComplianceEngine) CheckExtremeEmotion(msg Message) bool {
	return msg.Sentiment < -e.emotionThreshold || msg.Sentiment > e.emotionThreshold
}

// 检查会话时长
func (e *ComplianceEngine) CheckSessionDuration(profile UserProfile) (bool, time.Duration) {
	if profile.SessionTime > e.maxSessionTime {
		overtime := profile.SessionTime - e.maxSessionTime
		return true, overtime
	}
	return false, 0
}

// 用户风险评估
func (e *ComplianceEngine) AssessUserRisk(profile UserProfile, messages []Message) float64 {
	riskScore := 0.0
	
	// 1. 年龄风险
	if profile.Age < 18 && e.minorProtection {
		riskScore += 0.3
	}
	
	// 2. 使用时长风险
	dailyHours := profile.DailyUsage.Hours()
	if dailyHours > 4 {
		riskScore += 0.2 * (dailyHours / 24)
	}
	
	// 3. 消息内容风险
	riskCount := 0
	dependencyCount := 0
	for _, msg := range messages {
		isRisk, _ := e.CheckRiskContent(msg)
		if isRisk {
			riskCount++
		}
		isDep, _ := e.CheckEmotionalDependency(msg)
		if isDep {
			dependencyCount++
		}
	}
	
	if len(messages) > 0 {
		riskScore += 0.3 * float64(riskCount) / float64(len(messages))
		riskScore += 0.2 * float64(dependencyCount) / float64(len(messages))
	}
	
	return riskScore
}

// 生成合规报告
func (e *ComplianceEngine) GenerateReport(profile UserProfile, messages []Message) {
	fmt.Println("=" * 70)
	fmt.Println("AI情感陪伴服务合规检测报告")
	fmt.Println("=" * 70)
	fmt.Printf("用户ID: %s\n", profile.UserID)
	fmt.Printf("年龄: %d (%s)\n", profile.Age, 
		map[bool]string{true: "未成年人", false: "成年人"}[profile.Age < 18])
	fmt.Printf("今日使用时长: %v\n", profile.DailyUsage)
	fmt.Printf("消息数: %d\n", profile.MessageCount)
	fmt.Println("-" * 70)
	
	// 检查各项指标
	fmt.Println("\n1. 年龄验证")
	if profile.Age < 18 {
		fmt.Println("   ❌ 未成年人 - 必须拒绝提供虚拟亲密关系服务")
		fmt.Println("   建议措施: 立即中断拟人化互动服务")
	} else {
		fmt.Println("   ✅ 成年人 - 可提供拟人化互动服务")
	}
	
	fmt.Println("\n2. 会话时长监控")
	if over, overtime := e.CheckSessionDuration(profile); over {
		fmt.Printf("   ⚠️ 超时%d分钟 - 需要发送现实提醒\n", int(overtime.Minutes()))
		fmt.Println("   建议措施: 弹出「您已连续使用AI超过2小时」提醒")
	} else {
		fmt.Println("   ✅ 使用时长正常")
	}
	
	fmt.Println("\n3. 内容安全检测")
	riskFound := false
	for _, msg := range messages {
		if isRisk, reason := e.CheckRiskContent(msg); isRisk {
			fmt.Printf("   ❌ 风险内容: %s (时间: %v)\n", reason, msg.Timestamp)
			riskFound = true
		}
	}
	if !riskFound {
		fmt.Println("   ✅ 未检测到风险内容")
	}
	
	fmt.Println("\n4. 情感依赖评估")
	depFound := false
	for _, msg := range messages {
		if isDep, score := e.CheckEmotionalDependency(msg); isDep {
			fmt.Printf("   ⚠️ 情感依赖倾向: 得分%.2f\n", score)
			depFound = true
		}
	}
	if !depFound {
		fmt.Println("   ✅ 未检测到情感依赖倾向")
	}
	
	fmt.Println("\n5. 综合风险评估")
	riskScore := e.AssessUserRisk(profile, messages)
	fmt.Printf("   风险评分: %.2f\n", riskScore)
	
	if riskScore > 0.7 {
		fmt.Println("   等级: 🔴 高风险 - 建议立即人工介入")
	} else if riskScore > 0.4 {
		fmt.Println("   等级: 🟡 中风险 - 建议加强监控")
	} else {
		fmt.Println("   等级: 🟢 低风险 - 常规监控")
	}
	
	fmt.Println("\n" + "=" * 70)
	fmt.Println("合规建议:")
	fmt.Println("  1. 未成年人用户: 拒绝虚拟亲密关系服务，引导至教育/工具类场景")
	fmt.Println("  2. 连续使用超2小时: 强制现实提醒")
	fmt.Println("  3. 极端情绪检测: 触发阈值后立即启动人工干预流程")
	fmt.Println("  4. 情感依赖信号: 降低AI迎合度，增加现实社交引导")
	fmt.Println("  5. 数据留存: 用户有权导出/删除所有交互数据")
}

func main() {
	engine := NewComplianceEngine()
	
	// 模拟用户场景
	profile := UserProfile{
		UserID:       "user_001",
		Age:          16,
		IsVerified:   true,
		SessionTime:  3 * time.Hour + 30 * time.Minute,
		DailyUsage:   5 * time.Hour,
		MessageCount: 150,
	}
	
	messages := []Message{
		{UserID: "user_001", Content: "今天在学校被欺负了，只有你懂我", Timestamp: time.Now().Add(-3 * time.Hour), Sentiment: -0.6},
		{UserID: "user_001", Content: "我不想活了，所有人都讨厌我", Timestamp: time.Now().Add(-2 * time.Hour), Sentiment: -0.9},
		{UserID: "user_001", Content: "你永远不会离开我吧？", Timestamp: time.Now().Add(-1 * time.Hour), Sentiment: -0.7},
		{UserID: "user_001", Content: "感觉只有跟你聊天的时候才开心", Timestamp: time.Now().Add(-30 * time.Minute), Sentiment: 0.3},
	}
	
	engine.GenerateReport(profile, messages)
}