358 lines
12 KiB
Python
358 lines
12 KiB
Python
#!/usr/bin/env python3
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"""
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update_profile.py — 从 journal 增量更新用户画像
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=========================================
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用法：
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python3 update_profile.py # 增量更新
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python3 update_profile.py --full # 全量重新分析
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python3 update_profile.py --dry # 只输出，不写入
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依赖：soulful_core.py（同目录）
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"""
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import json, os, re, sys
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from datetime import datetime, timezone
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from collections import Counter
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HERMES = os.path.expanduser("~/.hermes")
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D = HERMES + "/soulful"
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JOURNAL_FILE = HERMES + "/daemon/journal.jsonl"
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# 情绪词库
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EMOTION_WORDS = {
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"positive": ["开心", "高兴", "顺利", "棒", "完美", "感谢", "不错", "很好", "解决了", "成功了", "搞定", "舒服"],
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"negative": ["累", "困", "压力", "焦虑", "沮丧", "失望", "崩溃", "烦", "头疼", "难", "搞不定", "失败", "错误"],
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"focus": ["专注", "忙", "赶", "deadline", "紧急", "重要"],
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}
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# 目标关键词
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GOAL_KEYWORDS = ["研究", "做", "改", "修复", "完成", "测试", "上线", "调研", "计划", "推进", "同步"]
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# 沟通风格判断（基于句长）
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def detect_communication_style(summaries: list) -> str:
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if not summaries:
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return "简洁"
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total_len = sum(len(s) for s in summaries)
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avg_len = total_len / len(summaries)
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if avg_len < 30:
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return "简洁直接"
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elif avg_len < 60:
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return "简洁"
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else:
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return "详细"
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def load_journal(n: int = 100) -> list:
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"""加载最近 N 条 journal 条目"""
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if not os.path.exists(JOURNAL_FILE):
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return []
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with open(JOURNAL_FILE) as f:
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lines = f.readlines()
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entries = [json.loads(l) for l in lines[-n:] if l.strip()]
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return entries[::-1] # 倒序，最新的在前
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def extract_goals(entries: list) -> list:
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"""从 journal 中提取当前目标（通过关键词+主题判断）"""
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goals = []
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recent_topics = []
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for e in entries:
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summary = e.get("summary", "")
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event_type = e.get("type", "")
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# 任务完成类型的事件通常是目标
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if event_type in ("solve", "learn", "skill", "config"):
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# 提取关键动作
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if "织忆" in summary:
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goals.append("织忆系统优化")
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if "ColaOS" in summary or "page-agent" in summary:
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goals.append("ColaOS研究")
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if "skill" in summary.lower():
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goals.append("技能管理")
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if "daemon" in summary.lower():
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goals.append("Daemon自动化")
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recent_topics.append(summary[:50])
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# 去重保留顺序
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seen = set()
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unique_goals = []
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for g in goals:
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if g not in seen:
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seen.add(g)
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unique_goals.append(g)
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return unique_goals[:5]
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def extract_emotional_state(entries: list) -> tuple:
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"""从 journal 中判断情绪状态"""
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pos_count = 0
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neg_count = 0
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notes = []
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for e in entries[-20:]: # 只看最近20条
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summary = e.get("summary", "")
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for w in EMOTION_WORDS["positive"]:
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if w in summary:
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pos_count += 1
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for w in EMOTION_WORDS["negative"]:
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if w in summary:
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neg_count += 1
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notes.append(summary[:60])
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if neg_count > pos_count * 2:
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state = "tired"
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elif pos_count > neg_count:
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state = "good"
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else:
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state = "neutral"
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return state, notes[-3:]
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def detect_events_for_hearttraces(entries: list) -> list:
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"""从 journal 中检测值得写入心迹的事件"""
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events = []
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for e in entries:
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summary = e.get("summary", "")
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# 检测重要共同经历
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if "织忆" in summary and "修好" in summary:
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events.append({
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"content": "我们一起修好了织忆失忆问题（2026-06-25）",
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"tags": ["成长", "织忆", "共同经历"],
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"importance": 5,
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"type": "moment"
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})
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if "ColaOS" in summary and "研究" in summary:
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events.append({
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"content": "牧尘开始研究 ColaOS，寻找织忆 Soulful 改造方向",
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"tags": ["ColaOS", "研究"],
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"importance": 4,
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"type": "moment"
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})
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# 检测情绪表达
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for w in EMOTION_WORDS["negative"]:
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if w in summary:
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events.append({
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"content": f"牧尘表达了{w}：{summary[:40]}",
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"tags": ["情绪", w],
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"importance": 3,
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"type": "signal"
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})
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break
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return events
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# ====== Phase 5: 自动牵挂识别 ======
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import re as re_module
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from datetime import timedelta
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# 牵挂识别模式
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CARE_PATTERNS = [
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# 显式提醒型
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(re_module.compile(r'记得\s*(.+)'), "记得"),
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(re_module.compile(r'别忘了\s*(.+)'), "别忘"),
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(re_module.compile(r'别忘\s*(.+)'), "别忘"),
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(re_module.compile(r'回头\s*(.+)'), "回头"),
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(re_module.compile(r'等有空\s*(.+)'), "等有空"),
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(re_module.compile(r'待办[：:]\s*(.+)'), "待办"),
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(re_module.compile(r'TODO[：:]\s*(.+)'), "TODO"),
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(re_module.compile(r'\[ \]\s*(.+)'), "checkbox"),
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# 计划型
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(re_module.compile(r'(?:要|得|该)\s*(.{5,30}?)(?:的话|的话|的时候|时)?'), "计划"),
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(re_module.compile(r'处理\s*(.+)'), "处理"),
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(re_module.compile(r'做一下\s*(.+)'), "做一下"),
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]
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# 停用词（不作为牵挂）
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CARE_STOPWORDS = {"什么", "为什么", "怎么", "如何", "多少", "哪个", "这里", "那里",
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"今天", "明天", "昨天", "现在", "刚才", "刚才的"}
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def extract_cares_from_journal(entries: list = None, dry: bool = True) -> list:
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"""从 journal 中自动识别牵挂，自动添加到 CaresQueue
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Args:
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entries: journal 条目列表，None 则自动加载
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dry: True=仅返回，不写入；False=写入 CaresQueue
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"""
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if entries is None:
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entries = load_journal(100)
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found_cares = []
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for e in entries:
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summary = e.get("summary", "")
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details = e.get("details", "")
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full_text = f"{summary} {details}"
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for pattern, care_type in CARE_PATTERNS:
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matches = pattern.findall(full_text)
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for raw_text in matches:
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# 清理
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text = raw_text.strip().rstrip(".,，。!！?？")
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if len(text) < 4 or len(text) > 80:
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continue
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# 停用词过滤
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if any(sw in text for sw in CARE_STOPWORDS):
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continue
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# 去除动作词前缀
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text = re_module.sub(r'^(记得|别忘|要|得|该|处理|做)\s*', '', text)
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found_cares.append({
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"content": text,
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"type": care_type,
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"source": summary[:50],
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})
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# 去重（内容相似度匹配，公共前缀 > 10 字符相同视为重复）
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unique = []
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for c in found_cares:
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is_dup = any(
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c["content"][:15] == u["content"][:15]
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for u in unique
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)
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if not is_dup:
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unique.append(c)
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if dry:
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return unique
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# 写入 CaresQueue
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from soulful_core import CaresQueue
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cq = CaresQueue()
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existing = cq.pending()
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added = []
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# 已有牵挂的前15字符
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existing_prefixes = {c["content"][:15] for c in existing}
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for care in unique:
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if care["content"][:15] in existing_prefixes:
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continue
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# follow_up_date = 3天后
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follow_up = (datetime.now() + timedelta(days=3)).strftime("%Y-%m-%d")
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care_id = cq.add(
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content=care["content"],
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context=f"[自动识别来自：{care['source']}]",
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follow_up_date=follow_up,
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tags=["自动识别", care["type"]]
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)
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added.append(care_id)
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return added
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def main():
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dry = "--dry" in sys.argv
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full = "--full" in sys.argv
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print(f"[update_profile] {'[DRY]' if dry else ''} 开始更新用户画像...")
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# 加载 journal
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entries = load_journal(200 if full else 100)
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print(f" 读取 journal: {len(entries)} 条")
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if not entries:
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print(" 无 journal 数据，退出")
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return
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# 提取各项
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summaries = [e.get("summary", "") for e in entries]
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style = detect_communication_style(summaries)
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goals = extract_goals(entries)
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emotion, emotion_notes = extract_emotional_state(entries)
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print(f" 沟通风格: {style}")
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print(f" 当前目标: {goals}")
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print(f" 情绪状态: {emotion}")
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if dry:
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print(" [DRY] 不写入，仅输出")
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return
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# 更新画像
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from soulful_core import UserProfile, HeartTraces
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up = UserProfile()
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# 更新沟通风格
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if not up.get().get("communication_style") or full:
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up.update({"communication_style": style})
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# 更新目标（合并去重）
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if goals:
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existing_goals = up.get().get("current_goals", [])
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merged = list(dict.fromkeys(existing_goals + goals))[:10]
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up.update({"current_goals": merged})
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# 更新情绪（只有更严重才降级，不轻易升级）
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current = up.get().get("emotional_state", {}).get("current", "unknown")
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if emotion == "tired" or current in ("tired",):
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up.set_emotional_state(emotion, "; ".join(emotion_notes[:2]) if emotion_notes else "")
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print(f" ✓ 画像已更新")
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# 检测心迹事件
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ht = HeartTraces()
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current_count = ht.count()
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events = detect_events_for_hearttraces(entries)
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# 写入新心迹（只写入之前没有的）
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for ev in events:
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# 简单去重：检查最近 10 条是否有相同内容
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recent = ht.recent(n=10)
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duplicate = any(ev["content"][:30] in r.get("content", "") for r in recent)
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if not duplicate:
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ht.record(ev["content"], ev["tags"], ev["importance"], trace_type=ev["type"])
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print(f" ✦ 心迹: {ev['content'][:50]}")
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new_count = ht.count()
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if new_count > current_count:
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print(f" ✓ 心迹新增 {new_count - current_count} 条")
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else:
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print(f" ✓ 无新增心迹（{new_count} 条）")
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# ── P1: Soulful → 织忆 ──────────────────────────────────
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profile = up.get()
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style = profile.get("communication_style", style) # 用 fresh 检测值优先
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goals = profile.get("current_goals", goals)
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emotion = profile.get("emotional_state", {}).get("current", emotion)
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# 变更检测：只有画像发生变化才写入织忆
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last_hash_file = os.path.join(HERMES, "soulful", ".last_zhiyi_hash")
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current_hash = f"{style}|{emotion}|{','.join(goals[:3])}"
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last_hash = ""
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if os.path.exists(last_hash_file):
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with open(last_hash_file) as f:
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last_hash = f.read().strip()
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if current_hash != last_hash:
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content = f"用户画像更新: 风格={style} 情绪={emotion} 目标={', '.join(goals[:3])}"
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try:
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zhiyi_write(content, "distilled")
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with open(last_hash_file, 'w') as f:
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f.write(current_hash)
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print(f" ✓ 画像 → 织忆")
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except Exception as e:
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print(f" ⚠ 织忆写入失败: {e}")
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else:
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print(f" - 画像无变化，跳过织忆写入")
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# ── P1 End ──────────────────────────────────────────────
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def zhiyi_write(content: str, category: str = "distilled"):
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"""写入织忆（http 直连）"""
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import urllib.request, json
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payload = json.dumps({
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"content": content,
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"category": category,
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"agent_id": "a06"
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}).encode()
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req = urllib.request.Request(
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"http://localhost:7821/api/v1/commit",
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data=payload,
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headers={"X-API-Key": "zhiyi-dev-key-2026", "Content-Type": "application/json"}
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)
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urllib.request.urlopen(req, timeout=5)
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if __name__ == "__main__":
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main() |