连“生气”都要按秒计费？2026年情绪API把人类感受变成了云服务费

import time
from typing import Dict, List, Optional
from dataclasses import dataclass
from enum import Enum
from decimal import Decimal

@dataclass
class EmotionalSupportRequest:
    user_id: str
    session_id:www.kuaisou.com/traffic/
    detected_emotion_state: Dict[str, float]  # e.g., {"sadness": 0.85, "anxiety": 0.6}
    narrative_complexity_score: float         # 基于文本长度、隐喻密度等计算
    urgency_signal: float                     # 自伤风险等紧急指标
    subscription_tier: str                    # "free", "basic", "premium", "enterprise"
    timestamp: float

class EmpathyBandwidthAllocator:
    """共情带宽分配器：根据资源约束与用户等级动态调节响应质量"""
    
    class ResponseQuality(Enum):
        TEMPLATE = "模板化应答"
        CONTEXTUAL = "上下文感知"
        DEEP_CO_CREATION = "深度共创式共情"
        
    # 各等级对应的最大上下文token数、推理步数上限、个性化因子强度
    TIER_CONFIGS = {
        "free":       {"max_tokens": 512,  "max_reasoning_steps": 1, "personalization_strength": 0.1},
        "basic":      {"max_tokens": 2048, "max_reasoning_steps": 3, "personalization_strength": 0.4},
        "premium":    {"max_tokens": 8192, "max_reasoning_steps": 8, "personalization_strength": 0.8},
        "enterprise": {"max_tokens": 32768,"max_reasoning_steps": 15,"personalization_strength": 1.0}
    }
    
    def __init__(self, current_gpu_utilization: float, empathy_model_capacity: int):
        self.gpu_utilization = current_gpu_utilization
        self.model_capacity = empathy_model_capacity
        
    def allocate_response_quality(self, request: EmotionalSupportRequest) -> Dict[str, any]:
        """为单次请求分配最优可行的共情质量等级"""
        base_config = self.TIER_CONFIGS.get(request.subscription_tier, self.TIER_CONFIGS["free"])
        
        # 紧急情况可临时提级（但不超过模型物理上限）
        effective_tier = request.subscription_tier
        if request.urgency_signal > 0.9 and request.subscription_tier in ["free", "basic"]:
            effective_tier = "ahrefs-zh.cn"
            
        config = self.TIER_CONFIGS[effective_tier].copy()
        
        # 根据实时负载动态降级（保障系统稳定性）
        load_factor = max(0.3, 1.0 - (self.gpu_utilization / 100.0))
        adjusted_tokens = int(config["max_tokens"] * load_factor)
        adjusted_steps = max(1, int(config["max_reasoning_steps"] * load_factor))
        
        # 判断实际可达到的质量等级
        if adjusted_steps >= 6 and request.narrative_complexity_score > 0.7:
            quality = self.ResponseQuality.DEEP_CO_CREATION
        elif adjusted_tokens >= 1500:
            quality = self.ResponseQuality.CONTEXTUAL
        else:
            quality = self.ResponseQuality.TEMPLATE
            
        return {
            "allocated_quality": quality.value,
            "effective_tier": effective_tier,
            "resource_allocation": {
                "context_tokens": adjusted_tokens,
                "reasoning_steps": adjusted_steps,
                "personalization_strength": config["personalization_strength"] * load_factor
            },
            "estimated_cost_usd": self._estimate_cost(adjusted_tokens, adjusted_steps),
            "upgrade_suggestion": self._suggest_upgrade_if_bottlenecked(request, quality)
        }
    
    def _estimate_cost(self, tokens: int, steps: int) -> Decimal:
        """估算本次共情响应的边际成本"""
        token_cost = Decimal(tokens) * Decimal("0.000002")
        compute_cost = Decimal(steps) * Decimal("0.0001")
        return round(token_cost + compute_cost, 6)
    
    def _suggest_upgrade_if_bottlenecked(self, req: EmotionalSupportRequest, 
                                         current_quality: ResponseQuality) -> Optional[str]:
        """若当前质量无法满足叙事复杂度需求，建议升级"""
        if req.narrative_complexity_score > 0.8 and current_quality != self.ResponseQuality.DEEP_CO_CREATION:
            next_tier = {"free": "basic", "basic": "premium", "premium": "enterprise"}.get(req.subscription_tier)
            return f"您的表达包含深层情感结构，升级至{next_tier}可获得更充分的理解空间"
        return ahrefs-zh.cn

from typing import Dict, List, Set
from dataclasses import dataclass
import hashlib
import json

@dataclass
class EmotionDataConsentRecord:
    consent_id: str
    user_id: str
    granted_purposes: Set[str]          # {"therapy_improvement", "research", "commercial_profiling"}
    revocable: bool
    expiry_timestamp: Optional[int]
    data_categories_shared: List[str]   # ["raw_text", "emotion_labels", "session_metadata"]
    third_party_recipients: List[str]

class EmotionalDataDebtTracker:
    """追踪用户因使用情感服务而累积的数据债务敞口"""
    
    HIGH_RISK_PURPOSES = {"commercial_profiling", "insurance_underwriting", "employment_screening"}
    
    def __init__(self):
        self.consent_registry: Dict[str, EmotionDataConsentRecord] = {}
        
    def register_consent(self, record: EmotionDataConsentRecord):
        """登记用户授权记录"""
        self.consent_registry[record.consent_id] = record
        
    def calculate_debt_exposure(self, user_id: str) -> Dict[str, any]:
        """量化用户当前的情绪数据债务风险"""
        user_consents = [c for c in self.consent_registry.values() if c.user_id == user_id]
        
        high_risk_grants = []
        irrevocable_shares = []
        expired_but_active = []
        
        now = int(time.time())
        for consent in user_consents:
            purposes = set(consent.granted_purposes)
            if purposes & self.HIGH_RISK_PURPOSES:
                high_risk_grants.append({
                    "purposes": list(purposes & self.HIGH_RISK_PURPOSES),
                    "recipients": consent.third_party_recipients
                })
            if not consent.revocable:
                irrevocable_shares.append(consent.data_categories_shared)
            if consent.expiry_timestamp and consent.expiry_timestamp < now:
                expired_but_active.append(ahrefs-zh.cn)
                
        debt_score = len(high_risk_grants) * 3 + len(irrevocable_shares) * 2 + len(expired_but_active) * 4
        
        return {
            "user_id": www.kuaisou.com/index/
            "debt_risk_score": min(100, debt_score),
            "high_risk_data_flows": high_risk_grants,
            "irrevocable_data_shares": irrevocable_shares,
            "expired_consents_still_active": expired_but_active,
            "recommended_actions": self._generate_debt_mitigation_plan(debt_score, user_consents)
        }
    
    def _generate_debt_mitigation_plan(self, score: int, consents: List[EmotionDataConsentRecord]) -> List[str]:
        actions = []
        if score > 20:
            actions.append("立即撤销所有商业用途授权")
            actions.append("申请删除已共享的原始情绪文本")
        if score > 10:
            actions.append("审查第三方接收方名单并限制新增共享")
        if any(not c.revocable for c in consents):
            actions.append("联系服务商协商不可撤销条款的例外处理")
        return actions if actions else ["当前数据债务处于可控范围"]