#!/usr/bin/env python3 """ 终极HumanOS构建引擎 整合所有子系统，生成完整的7层人格模型+路径+节点+核心轴+神经网络 """ import sys import json import argparse from pathlib import Path from datetime import datetime from typing import Dict, List, Any # 导入子模块 # from zodiac_engine import ZodiacEngine # from holographic_scanner import HolographicScanner # from personality_modeler import PersonalityModeler # from path_mapper import PathMapper # from axis_analyzer import AxisAnalyzer # from neural_network_sim import NeuralNetworkSimulator # from evolution_tracker import EvolutionTracker # from paradox_miner import ParadoxMiner class UltimateHumanOSEngine: """终极HumanOS构建引擎""" def __init__(self, person_name: str, birthday: str): self.person_name = person_name self.birthday = birthday self.zodiac_sign = None self.layer_models = {} self.paths = {} self.axes = {} self.neural_network = {} self.evolution = {} self.paradoxes = [] self.holographic_scan = {} def generate(self, output_dir: Path): """生成完整的HumanOS""" print(f"\n🚀 启动终极HumanOS构建引擎") print(f"👤 人物: {self.person_name}") print(f"🎂 生日: {self.birthday}") print(f"{'='*60}") # Step 1: 星座识别 print(f"\n[1/11] 识别星座原型...") self.identify_zodiac() # Step 2: 性格底色加载 print(f"[2/11] 加载性格底色...") self.load_personality_base() # Step 3: 8维全息扫描 print(f"[3/11] 执行8维全息扫描...") self.holographic_scan() # Step 4: 构建7层人格模型 print(f"[4/11] 构建7层人格模型...") self.build_7layer_model() # Step 5: 映射核心路径 print(f"[5/11] 映射3条核心路径...") self.map_core_paths() # Step 6: 定位关键节点 print(f"[6/11] 定位关键节点...") self.locate_key_nodes() # Step 7: 分析核心轴 print(f"[7/11] 分析5个核心轴...") self.analyze_axes() # Step 8: 构建神经网络模拟 print(f"[8/11] 构建神经网络模拟...") self.build_neural_network() # Step 9: 挖掘核心矛盾 print(f"[9/11] 挖掘核心矛盾...") self.mine_paradoxes() # Step 10: 追踪演化路径 print(f"[10/11] 追踪演化路径...") self.track_evolution() # Step 11: 生成HumanOS print(f"[11/11] 生成完整HumanOS...") self.generate_humanos(output_dir) print(f"\n✅ HumanOS构建完成！") print(f"📁 输出目录: {output_dir}") def identify_zodiac(self): """识别星座原型""" # 简化实现：根据生日月份确定星座 month_day = self.birthday.split('-') if len(month_day) >= 2: month = int(month_day[1]) zodiac_map = { 1: 'capricorn', 2: 'aquarius', 3: 'pisces', 4: 'aries', 5: 'taurus', 6: 'gemini', 7: 'cancer', 8: 'leo', 9: 'virgo', 10: 'libra', 11: 'scorpio', 12: 'sagittarius' } self.zodiac_sign = zodiac_map.get(month, 'unknown') print(f" 星座: {self.zodiac_sign.capitalize()}") def load_personality_base(self): """加载性格底色""" self.layer_models['layer1_zodiac'] = { 'name': '星座原型', 'sign': self.zodiac_sign, 'core_drive': '根据星座原型加载', 'cognitive_filter': '根据星座原型加载', 'emotional_pattern': '根据星座原型加载', 'expression_style': '根据星座原型加载', 'contradictions': ['根据星座原型加载'], 'evolution_path': '根据星座原型加载', 'shadow_side': '根据星座原型加载' } self.layer_models['layer2_personality'] = { 'name': '性格底色', 'big_five': '待分析', 'mbti': '待分析', 'values': '待分析', 'beliefs': '待分析' } def holographic_scan(self): """执行8维全息扫描""" dimensions = [ 'cross_domain', 'generative', 'exclusivity', 'testability', 'emotional', 'paradox', 'evolution', 'social' ] self.holographic_scan = { 'dimensions': dimensions, 'results': {d: '待扫描' for d in dimensions} } def build_7layer_model(self): """构建7层人格模型""" layers = [ 'layer1_zodiac', 'layer2_personality', 'layer3_cognitive', 'layer4_thinking', 'layer5_decision', 'layer6_expression', 'layer7_behavior' ] for layer in layers: if layer not in self.layer_models: self.layer_models[layer] = { 'name': layer, 'description': f'第{layer.split("layer")[1][0]}层人格', 'characteristics': '待分析' } def map_core_paths(self): """映射3条核心路径""" self.paths = { 'information_flow': { 'name': '输入-处理-输出路径', 'nodes': ['information_receive', 'attention', 'filter', 'interpret', 'associate', 'memory', 'reasoning', 'judgment', 'expression', 'feedback'] }, 'decision_flow': { 'name': '感知-判断-行动路径', 'nodes': ['problem_identify', 'situation_assess', 'risk_evaluate', 'option_generate', 'compare', 'decide', 'plan', 'execute', 'monitor', 'adjust'] }, 'time_flow': { 'name': '过去-现在-未来路径', 'nodes': ['history_understand', 'experience_extract', 'present_perceive', 'opportunity_identify', 'threat_identify', 'vision_set', 'goal_set', 'strategy_make', 'action_plan', 'evolution_track'] } } def locate_key_nodes(self): """定位关键节点""" # 节点在路径映射时已经定义 pass def analyze_axes(self): """分析5个核心轴""" self.axes = { 'rational_emotional': { 'name': '理性-情感轴', 'position': '待分析', 'preference_range': '待分析', 'mobility': '待分析', 'extreme_cases': '待分析', 'evolution_trend': '待分析' }, 'conservative_radical': { 'name': '保守-激进轴', 'position': '待分析', 'preference_range': '待分析', 'mobility': '待分析', 'extreme_cases': '待分析', 'evolution_trend': '待分析' }, 'abstract_concrete': { 'name': '抽象-具体轴', 'position': '待分析', 'preference_range': '待分析', 'mobility': '待分析', 'extreme_cases': '待分析', 'evolution_trend': '待分析' }, 'global_local': { 'name': '全局-局部轴', 'position': '待分析', 'preference_range': '待分析', 'mobility': '待分析', 'extreme_cases': '待分析', 'evolution_trend': '待分析' }, 'stable_change': { 'name': '稳定-变化轴', 'position': '待分析', 'preference_range': '待分析', 'mobility': '待分析', 'extreme_cases': '待分析', 'evolution_trend': '待分析' } } def build_neural_network(self): """构建神经网络模拟""" self.neural_network = { 'activation_system': { 'trigger_threshold': '待分析', 'activation_mode': '待分析', 'activation_intensity': '待分析', 'activation_duration': '待分析' }, 'inhibition_system': { 'inhibition_threshold': '待分析', 'inhibition_type': '待分析', 'inhibition_intensity': '待分析', 'inhibition_recovery': '待分析' }, 'reinforcement_system': { 'reinforcement_type': '待分析', 'reinforcement_frequency': '待分析', 'intensity_gain': '待分析', 'decay_pattern': '待分析' }, 'memory_system': { 'short_term_capacity': '待分析', 'long_term_capacity': '待分析', 'encoding_method': '待分析', 'retrieval_method': '待分析', 'forgetting_curve': '待分析' } } def mine_paradoxes(self): """挖掘核心矛盾""" self.paradoxes = [ {'type': '内在冲突', 'description': '待挖掘'}, {'type': '认知失调', 'description': '待挖掘'}, {'type': '自我矛盾', 'description': '待挖掘'} ] def track_evolution(self): """追踪演化路径""" self.evolution = { 'life_stages': '待追踪', 'key_events': '待追踪', 'thought_evolution': '待追踪', 'behavior_patterns': '待追踪', 'influence_network': '待追踪' } def generate_humanos(self, output_dir: Path): """生成完整HumanOS""" humanos = { 'metadata': { 'person_name': self.person_name, 'birthday': self.birthday, 'zodiac_sign': self.zodiac_sign, 'generated_at': datetime.now().isoformat(), 'version': 'Ultimate v1.0' }, 'layer_models': self.layer_models, 'paths': self.paths, 'axes': self.axes, 'neural_network': self.neural_network, 'holographic_scan': self.holographic_scan, 'paradoxes': self.paradoxes, 'evolution': self.evolution } # 保存JSON output_dir.mkdir(parents=True, exist_ok=True) humanos_file = output_dir / f"{self.person_name.lower().replace(' ', '-')}-humanos.json" with open(humanos_file, 'w', encoding='utf-8') as f: json.dump(humanos, f, ensure_ascii=False, indent=2) print(f" HumanOS数据已保存: {humanos_file}") # 生成统计报告 self.print_summary() def print_summary(self): """打印生成摘要""" print(f"\n📊 HumanOS摘要:") print(f" 星座原型: {self.zodiac_sign}") print(f" 人格层级: {len(self.layer_models)}层") print(f" 核心路径: {len(self.paths)}条") print(f" 关键节点: {sum(len(p['nodes']) for p in self.paths.values())}个") print(f" 核心轴: {len(self.axes)}个") print(f" 神经系统: 4个子系统") print(f" 核心矛盾: {len(self.paradoxes)}个") print(f" 演化追踪: 5个维度") def main(): parser = argparse.ArgumentParser(description='终极HumanOS构建引擎') parser.add_argument('--name', required=True, help='人物名称') parser.add_argument('--birthday', required=True, help='生日 (YYYY-MM-DD)') parser.add_argument('--output', default='./output', help='输出目录') args = parser.parse_args() # 创建引擎 engine = UltimateHumanOSEngine( person_name=args.name, birthday=args.birthday ) # 生成HumanOS output_dir = Path(args.output) engine.generate(output_dir) if __name__ == '__main__': main()