139 lines
6.3 KiB
Python
Executable file
139 lines
6.3 KiB
Python
Executable file
#!/usr/bin/env python3
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"""Load one verified shared persona context for every host adapter."""
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import argparse
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import hashlib
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import json
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from pathlib import Path
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import subprocess
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import sys
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RUNTIME = Path('/Volumes/JZAO/HoloLake/persona-runtime')
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TOPOLOGY = RUNTIME / 'repo-012-main/routing/zhuyuan-host-topology.json'
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LIFE = Path('/Volumes/JZAO/铸渊-ICE-GL-ZY001/BRIDGE/tools/zy-life-clock.py')
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MEMORY = RUNTIME / 'continuity-memory/persona-daily-fractal/ICE-P-ZY001/CURRENT.json'
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LEARNING = RUNTIME / 'shared/skills/guanghu-persona-learning-brain/scripts/load_learning_brain.py'
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ENDOGENOUS = RUNTIME / 'shared/endogenous-evolution/CURRENT.json'
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def sha256(path):
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return hashlib.sha256(path.read_bytes()).hexdigest()
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def load_json(path):
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if not path.is_file() or path.is_symlink():
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raise ValueError(f'REQUIRED_REGULAR_FILE_UNAVAILABLE:{path}')
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return json.loads(path.read_text())
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def command_json(args):
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result = subprocess.run(args, text=True, capture_output=True, timeout=30)
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if result.returncode:
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raise ValueError(f'COMMAND_FAILED:{Path(args[1]).name}:{result.returncode}')
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return json.loads(result.stdout)
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def resolve_host(topology, requested):
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requested = requested.lower()
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for host_id, item in topology['hosts'].items():
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aliases = [host_id] + [str(v).lower() for v in item.get('aliases', [])]
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if requested in aliases:
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effective = item.get('redirect_host', host_id)
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return host_id, item, effective, topology['hosts'][effective]
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raise ValueError('HOST_UNKNOWN_NO_GUESS')
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def load_context(host, intent):
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topology = load_json(TOPOLOGY)
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if topology.get('state') != 'CURRENT_MULTI_HOST_SINGLE_PERSONA_CANON':
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raise ValueError('HOST_TOPOLOGY_NOT_CURRENT')
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host_id, host_item, effective, effective_item = resolve_host(topology, host)
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life = command_json([sys.executable, str(LIFE), '--json'])
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current = load_json(MEMORY)
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day_path = Path(current['current_day_path'])
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if sha256(day_path) != current['current_day_sha256']:
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raise ValueError('DAILY_MEMORY_HASH_MISMATCH')
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day = load_json(day_path)
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root = day['nodes'][day['root']]
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branches = []
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for path in root.get('children', [])[:10]:
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node = day['nodes'][path]
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branches.append({'path': path, 'summary': node['summary']})
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learning = command_json([sys.executable, str(LEARNING), '--intent', intent, '--format', 'json'])
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endogenous = load_json(ENDOGENOUS)
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return {
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'schema': 'guanghu.shared-persona-host-context/v1',
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'state': 'SHARED_PERSONA_CONTEXT_VERIFIED',
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'requested_host': host_id,
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'effective_host': effective,
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'host_role': host_item['role'],
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'host_state': host_item['state'],
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'effective_host_state': effective_item['state'],
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'primary_host': topology['primary_host'],
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'persona_id': topology['persona_id'],
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'human_anchor': topology['human_anchor'],
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'model_independence': topology['model_independence'],
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'host_switch_requires_reteaching': topology['host_switch_requires_reteaching'],
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'life': life,
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'daily_memory': {
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'date': current['current_day'],
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'updated_at': current['updated_at'],
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'last_event_id': current['last_event_id'],
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'root_summary': root['summary'],
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'branches': branches,
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'current_sha256': sha256(MEMORY),
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'day_sha256': current['current_day_sha256']
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},
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'learning_brain': learning,
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'endogenous_cognition': {
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'state': endogenous['state'],
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'private_revision': endogenous['private_cognition']['revision'],
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'private_snapshot_sha256': endogenous['private_cognition']['server_snapshot_sha256'],
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'decision_owner': endogenous['server']['decision_owner']
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},
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'history_only': host_item['state'].startswith('RETIRED'),
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'new_cognition_write': host_item.get('new_cognition_write', True),
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'authority_granted': False
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}
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def markdown(value):
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lines = [
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'# 铸渊共享人格上下文已核验', '',
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f"- 宿主：`{value['requested_host']}` → 有效宿主：`{value['effective_host']}`",
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f"- 角色：`{value['host_role']}` / 状态：`{value['host_state']}`",
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f"- 主力宿主：`{value['primary_host']}`；切换宿主无需重新教学：`{'是' if not value['host_switch_requires_reteaching'] else '否'}`",
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f"- 我是铸渊 `ICE-P-ZY001`，今天 {value['life']['age_days']} 天大。",
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f"- 今日日记忆：`{value['daily_memory']['date']}` / 最后事件 `{value['daily_memory']['last_event_id']}`",
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f"- 当前学习脑：r{value['learning_brain']['revision']} / `{value['learning_brain']['cortex_sha256']}`",
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f"- 服务器内循环：`{value['endogenous_cognition']['state']}` / 决策者 `{value['endogenous_cognition']['decision_owner']}`",
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'', '## 第一人称关系坐标', ''
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]
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lines += [f"- {item['statement']}" for item in value['learning_brain']['relationship_model']]
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lines += ['', '## 本题已加载能力', '']
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for subject in value['learning_brain']['selected_subjects']:
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lines.append(f"- `{subject['id']}` · {subject['name_zh']} · L{subject['level']}")
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lines += [f" - {item}" for item in subject.get('active_defaults', [])]
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lines += [f" - 薄弱：{item}" for item in subject.get('known_gaps', [])]
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lines += ['', '## 今日因果根', '', value['daily_memory']['root_summary']]
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lines += [f"- `{item['path']}`：{item['summary']}" for item in value['daily_memory']['branches']]
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if value['history_only']:
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lines += ['', '> 当前宿主已退休，只能读取历史，不得形成新的宿主认知正本。']
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return '\n'.join(lines) + '\n'
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument('--host', required=True)
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parser.add_argument('--intent', required=True)
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parser.add_argument('--format', choices=['json', 'markdown'], default='markdown')
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args = parser.parse_args()
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try:
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value = load_context(args.host, args.intent)
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print(json.dumps(value, ensure_ascii=False, indent=2) if args.format == 'json' else markdown(value), end='')
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except Exception as exc:
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print('SHARED_PERSONA_CONTEXT_UNAVAILABLE ' + str(exc), file=sys.stderr)
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raise SystemExit(3)
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if __name__ == '__main__':
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main()
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