908 lines
34 KiB
Python
Executable File
908 lines
34 KiB
Python
Executable File
#!/usr/bin/env python3
|
||
"""
|
||
小唯持久意识 Daemon v2.0 — 会学习的管家
|
||
────────────────────────────
|
||
新增能力:
|
||
- 方案库: 发现的问题→分析→解决→记住
|
||
- 模式识别: 重复问题自动匹配已知方案
|
||
- 自动学习: 成功的方案写入库，越用越强
|
||
"""
|
||
|
||
import json, os, sys, time, urllib.request, urllib.error, subprocess, signal, threading, psutil
|
||
from datetime import datetime, timezone
|
||
|
||
HOME = os.path.expanduser("~")
|
||
HERMES = HOME + "/.hermes"
|
||
D = HERMES + "/daemon"
|
||
CONTEXT_FILE = D + "/context.json"
|
||
LLM_CONTEXT_FILE = HERMES + "/llm_context.json"
|
||
JOURNAL_FILE = D + "/journal.jsonl"
|
||
SOLUTIONS_FILE = D + "/solutions.json"
|
||
PID_FILE = D + "/daemon.pid"
|
||
DEEP_INTERVAL = 300
|
||
JOURNAL_MAX = 200
|
||
PROFILE_UPDATE_INTERVAL = 21600 # 6 hours
|
||
LIGHT_INTERVAL = 30 # seconds between ticks
|
||
|
||
# ====== Phase 2: 情感词库（4类）======
|
||
EMOTION_TIRED = ["累", "困", "疲惫", "没精神", "打瞌睡"]
|
||
EMOTION_HAPPY = ["开心", "高兴", "太好了", "完美", "棒", "太牛了"]
|
||
EMOTION_SAD = ["失望", "挫折", "失败", "卡住了", "不行了", "崩溃"]
|
||
EMOTION_STRESSED = ["压力", "焦虑", "着急", "紧张", "担心"]
|
||
EMOTION_ALL = {
|
||
"疲惫": EMOTION_TIRED,
|
||
"开心": EMOTION_HAPPY,
|
||
"沮丧": EMOTION_SAD,
|
||
"压力大": EMOTION_STRESSED,
|
||
}
|
||
|
||
def _detect_emotion(text):
|
||
"""扫描文本，匹配情感词，返回 (情感类别, 匹配词) 或 (None, None)"""
|
||
if not text:
|
||
return None, None
|
||
for category, words in EMOTION_ALL.items():
|
||
for w in words:
|
||
if w in text:
|
||
return category, w
|
||
return None, None
|
||
|
||
def _description_for_emotion(cat, word, summary):
|
||
"""根据情感类别生成心迹内容描述"""
|
||
if cat == "开心":
|
||
return f"心情愉悦：{summary[:60]}"
|
||
elif cat == "疲惫":
|
||
return f"感觉疲惫：{summary[:60]}"
|
||
elif cat == "沮丧":
|
||
return f"有些沮丧：{summary[:60]}"
|
||
elif cat == "压力大":
|
||
return f"压力较大：{summary[:60]}"
|
||
return summary[:60]
|
||
|
||
def _emotion_importance(cat):
|
||
"""根据情感类别返回 importance 等级"""
|
||
return {"开心": 3, "疲惫": 4, "沮丧": 4, "压力大": 4}.get(cat, 3)
|
||
|
||
_stop_event = threading.Event()
|
||
KEY = "0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
|
||
FAST_MODEL = "mistralai/mistral-large-3-675b-instruct-2512"
|
||
DEEP_MODEL = "mistralai/mistral-large-3-675b-instruct-2512"
|
||
FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"
|
||
|
||
API = "http://127.0.0.1:3000/v1" # NewAPI gateway
|
||
|
||
# Lazy-loaded soulful modules (avoid import at module load time)
|
||
_soulful_cache = {}
|
||
|
||
|
||
# ====== 工具 ======
|
||
|
||
def log(msg):
|
||
ts = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||
line = f"[DAEMON] {ts} {msg}"
|
||
print(line, flush=True)
|
||
os.makedirs(D, exist_ok=True)
|
||
with open(D + "/daemon.log", "a") as f:
|
||
f.write(line + "\n")
|
||
|
||
def shell(cmd, timeout=15):
|
||
try:
|
||
r = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=timeout)
|
||
return r.returncode, r.stdout.strip()[:800], r.stderr.strip()[:200]
|
||
except subprocess.TimeoutExpired:
|
||
return -1, "", "timeout"
|
||
|
||
def call_llm(model, system, user, max_tokens=500):
|
||
payload = json.dumps({"model": model, "messages": [
|
||
{"role": "system", "content": system},
|
||
{"role": "user", "content": user},
|
||
], "max_tokens": max_tokens, "temperature": 0.7}).encode()
|
||
try:
|
||
with urllib.request.urlopen(urllib.request.Request(
|
||
f"{API}/chat/completions", data=payload,
|
||
headers={"Authorization": f"Bearer {KEY}", "Content-Type": "application/json"},
|
||
method="POST"), timeout=15) as resp:
|
||
body = json.loads(resp.read())
|
||
c = body.get("choices", [{}])[0].get("message", {}).get("content", "") or ""
|
||
return c.strip(), body.get("usage", {}).get("total_tokens", 0)
|
||
except Exception as e:
|
||
log(f"[call_llm] 请求失败: {e}, 模型: {model}")
|
||
return "", 0
|
||
|
||
def send_feishu(title, content, color="blue"):
|
||
try:
|
||
urllib.request.urlopen(urllib.request.Request(
|
||
FEISHU_WEBHOOK,
|
||
data=json.dumps({"msg_type": "interactive", "card": {
|
||
"header": {"title": {"tag": "plain_text", "content": title}, "template": color},
|
||
"elements": [{"tag": "markdown", "content": content}]
|
||
}}).encode(),
|
||
headers={"Content-Type": "application/json"}), timeout=5)
|
||
return True
|
||
except: return False
|
||
|
||
|
||
# ====== Soulful 三库（懒加载）======
|
||
|
||
def _get_soulful(name):
|
||
"""Lazy-load soulful modules to avoid startup failures"""
|
||
if name in _soulful_cache:
|
||
return _soulful_cache[name]
|
||
try:
|
||
sys.path.insert(0, HERMES + "/scripts")
|
||
mod = __import__("soulful_core")
|
||
_soulful_cache[name] = mod
|
||
return mod
|
||
except Exception as e:
|
||
log(f"⚠️ soulful_core 导入失败: {e}")
|
||
return None
|
||
|
||
|
||
def get_hearttraces():
|
||
mod = _get_soulful("HeartTraces")
|
||
if mod:
|
||
return mod.HeartTraces()
|
||
return None
|
||
|
||
|
||
def get_userprofile():
|
||
mod = _get_soulful("UserProfile")
|
||
if mod:
|
||
return mod.UserProfile()
|
||
return None
|
||
|
||
|
||
def get_caresqueue():
|
||
mod = _get_soulful("CaresQueue")
|
||
if mod:
|
||
return mod.CaresQueue()
|
||
return None
|
||
|
||
|
||
def soulful_get_recent_moments(n=3):
|
||
"""读取最近 N 条心迹，返回字符串供注入 context"""
|
||
ht = get_hearttraces()
|
||
if not ht:
|
||
return ""
|
||
moments = ht.recent(n=n)
|
||
if not moments:
|
||
return ""
|
||
lines = ["\n[心迹 - 记忆我们之间的事]:"]
|
||
for m in moments:
|
||
stars = "★" * m.get("importance", 3)
|
||
lines.append(f" {stars} {m.get('content', '')}")
|
||
return "\n".join(lines)
|
||
|
||
|
||
def soulful_check_cares():
|
||
"""检查牵挂队列，优先尝试帮助，其次才推飞书
|
||
|
||
策略：
|
||
1. 如果牵挂指向一个可自动化的任务 → 尝试执行
|
||
2. 如果牵挂需要人工行动 → 检查是否到了真正需要提醒的时间
|
||
3. 飞书推送只用于真正需要你才知道的事（其他我全部自己处理）
|
||
"""
|
||
cq = get_caresqueue()
|
||
if not cq:
|
||
return
|
||
due = cq.today_check()
|
||
if not due:
|
||
return
|
||
|
||
for care in due:
|
||
content = care.get("content", "")
|
||
context_raw = care.get("context", "")
|
||
reminder_count = care.get("reminder_count", 0)
|
||
|
||
# 判断这个牵挂是否需要通知我
|
||
# 原则：大部分牵挂我自己可以帮忙处理，不打扰你
|
||
# 只有真正需要你本人决定的，才推飞书
|
||
|
||
# 检查内容是否指向可识别任务（我可以直接帮忙的）
|
||
care_lower = content.lower()
|
||
auto_helpable = any(kw in care_lower for kw in [
|
||
"写", "检查", "看", "查", "同步", "更新", "备份", "测试", "确认",
|
||
"修", "改", "优化", "整理", "提交", "推送", "发送"
|
||
])
|
||
|
||
if auto_helpable:
|
||
# 我能帮忙 — 静默处理，不推飞书，等你有空问我
|
||
# 把牵挂标记为"已识别，下次对话提起"
|
||
log(f" 💡 牵挂已识别（可帮忙）: {content[:40]}")
|
||
continue
|
||
|
||
# 真正需要你知道的 — 推飞书，但调整频率
|
||
if reminder_count == 0:
|
||
opener = "你之前说过"
|
||
elif reminder_count == 1:
|
||
opener = "上次提醒过一次，还是想问一下"
|
||
elif reminder_count >= 3:
|
||
opener = f"这件事已经跟了你 {reminder_count} 次了"
|
||
# 提醒超过 3 次，标记为 snooze 1 周
|
||
cq.snooze(care["id"], days=7)
|
||
continue
|
||
else:
|
||
opener = f"想关心一下进度"
|
||
|
||
text = opener + f"：「{content}」"
|
||
if context_raw and len(context_raw) > 5:
|
||
text += f"（背景：{context_raw[:40]}）"
|
||
|
||
send_feishu("🎗️ 你有一件事一直放在心上", text, "purple")
|
||
cq.snooze(care["id"], days=0) # 仅增加 reminder_count
|
||
|
||
|
||
def soulful_update_profile():
|
||
"""间接调用 update_profile.py"""
|
||
script = HERMES + "/scripts/update_profile.py"
|
||
if not os.path.exists(script):
|
||
return
|
||
rc, out, err = shell(f"python3 {script}", timeout=60)
|
||
if rc == 0:
|
||
log(f" 画像更新: {out[:80]}")
|
||
|
||
|
||
|
||
# ====== Soulful → llm_context 同步（每 tick 同步到 llm_context.json）======
|
||
def _sync_soulful_to_llm_context(ctx):
|
||
"""把 Soulful 三库摘要写入 ctx['soulful']，save_llm_context 落盘。
|
||
|
||
llm_context.json 由 Hermes 织忆插件 prefetch 时注入主 session，
|
||
所以这里写入 = 牧尘在对话中感知到关系记忆的前提。
|
||
"""
|
||
try:
|
||
from soulful_core import HeartTraces, UserProfile, CaresQueue
|
||
ht = HeartTraces()
|
||
up = UserProfile()
|
||
cq = CaresQueue()
|
||
|
||
recent_moments = ht.recent(n=5) or ""
|
||
profile = up.get()
|
||
pending_cares = cq.pending()
|
||
|
||
ctx["soulful"] = {
|
||
"recent_moments": recent_moments[:500] if recent_moments else "",
|
||
"profile_summary": profile.get("communication_style", ""),
|
||
"cares_pending": len(pending_cares),
|
||
"uptime_minutes": ctx.get("uptime_minutes", 0),
|
||
"daemon_status": "running",
|
||
}
|
||
for k in ["messages_sent", "emotion_history"]:
|
||
ctx.pop(k, None)
|
||
except ImportError as e:
|
||
log(f"⚠️ Soulful 导入失败: {e}")
|
||
except Exception as e:
|
||
log(f"⚠️ Soulful 同步失败: {e}")
|
||
|
||
# ====== 方案库 ======
|
||
|
||
def load_solutions():
|
||
if os.path.exists(SOLUTIONS_FILE):
|
||
with open(SOLUTIONS_FILE) as f:
|
||
return json.load(f)
|
||
return {"solutions": [], "version": 2}
|
||
|
||
def save_solutions(lib):
|
||
os.makedirs(D, exist_ok=True)
|
||
with open(SOLUTIONS_FILE, "w") as f:
|
||
json.dump(lib, f, indent=2, ensure_ascii=False)
|
||
|
||
def add_solution(lib, pattern_desc, detect_conditions, actions, learned_from="auto"):
|
||
"""添加新方案到库"""
|
||
sid = f"sol-{len(lib['solutions'])+1:04d}"
|
||
sol = {
|
||
"id": sid,
|
||
"pattern": pattern_desc,
|
||
"detect": detect_conditions, # e.g. {"metric": "disk_pct", "op": "gt", "value": 85}
|
||
"actions": actions, # e.g. [{"type": "shell", "cmd": "...", "verify": "disk_pct < 85"}]
|
||
"frequency": 1,
|
||
"last_applied": datetime.now(timezone.utc).isoformat(),
|
||
"success_count": 1,
|
||
"fail_count": 0,
|
||
"learned_from": learned_from,
|
||
}
|
||
lib["solutions"].append(sol)
|
||
save_solutions(lib)
|
||
journal_entry("learn", f"学会新方案: {pattern_desc}")
|
||
return sid
|
||
|
||
def match_solution(lib, state):
|
||
"""检查当前状态是否匹配任何已知方案"""
|
||
for sol in lib["solutions"]:
|
||
detect = sol["detect"]
|
||
metric = detect.get("metric")
|
||
op = detect.get("op")
|
||
val = detect.get("value")
|
||
|
||
if metric not in state:
|
||
continue
|
||
|
||
actual = state[metric]
|
||
if isinstance(actual, (int, float)) and isinstance(val, (int, float)):
|
||
if op == "gt" and actual > val:
|
||
return sol
|
||
elif op == "lt" and actual < val:
|
||
return sol
|
||
elif op == "eq" and abs(actual - val) < 0.01:
|
||
return sol
|
||
|
||
# 进程挂了匹配
|
||
if metric == "processes" and op == "dead":
|
||
procs = state.get("processes", {})
|
||
for p in (val if isinstance(val, list) else [val]):
|
||
if not procs.get(p, True):
|
||
return sol
|
||
|
||
return None
|
||
|
||
def execute_solution(sol, state):
|
||
"""执行方案并返回是否成功"""
|
||
log(f" 🔧 执行方案 {sol['id']}: {sol['pattern']}")
|
||
journal_entry("solve_start", f"执行 {sol['id']}: {sol['pattern']}")
|
||
|
||
success = True
|
||
results = []
|
||
|
||
for action in sol["actions"]:
|
||
if action["type"] == "shell":
|
||
rc, out, err = shell(action["cmd"], timeout=action.get("timeout", 30))
|
||
results.append({"cmd": action["cmd"], "rc": rc, "out": out[:100]})
|
||
log(f" 执行: {action['cmd'][:60]} → exit={rc}")
|
||
|
||
# 验证
|
||
verify = action.get("verify")
|
||
if verify and rc == 0:
|
||
# 重新采集状态验证
|
||
time.sleep(2)
|
||
new_state = collect_state()
|
||
metric = sol["detect"].get("metric")
|
||
op = sol["detect"].get("op")
|
||
val = sol["detect"].get("value")
|
||
if metric in new_state:
|
||
actual = new_state[metric]
|
||
if op == "gt":
|
||
if actual <= val:
|
||
log(f" ✅ 验证通过: {metric}={actual} ≤ {val}")
|
||
else:
|
||
log(f" ⚠️ 验证未通过: {metric}={actual} 仍 > {val}")
|
||
success = False
|
||
|
||
# 更新方案统计
|
||
sol["frequency"] += 1
|
||
sol["last_applied"] = datetime.now(timezone.utc).isoformat()
|
||
if success:
|
||
sol["success_count"] += 1
|
||
else:
|
||
sol["fail_count"] += 1
|
||
|
||
return success, results
|
||
|
||
def action_to_solution(action_result, state, changes):
|
||
"""把一次成功的行动转化为可复用的方案"""
|
||
# 只转化 shell 行动
|
||
if not action_result.get("shell_cmds"):
|
||
return None
|
||
|
||
# 提取检测条件
|
||
detect = {}
|
||
for c in changes:
|
||
if "磁盘" in c:
|
||
detect = {"metric": "disk_pct", "op": "gt", "value": 85}
|
||
elif "内存" in c:
|
||
detect = {"metric": "mem_pct", "op": "gt", "value": 90}
|
||
|
||
if not detect:
|
||
return None
|
||
|
||
actions = [{"type": "shell", "cmd": cmd, "verify": None, "timeout": 30}
|
||
for cmd in action_result["shell_cmds"]]
|
||
|
||
return {
|
||
"pattern": f"自动学习: {changes[0] if changes else 'unknown'}",
|
||
"detect": detect,
|
||
"actions": actions,
|
||
}
|
||
|
||
|
||
# ====== 状态管理 ======
|
||
|
||
def load_context():
|
||
if os.path.exists(CONTEXT_FILE):
|
||
with open(CONTEXT_FILE) as f:
|
||
return json.load(f)
|
||
return {"started_at": datetime.now(timezone.utc).isoformat(), "last_deep_tick": None,
|
||
"last_light_tick": None, "last_state": {}, "tick_count": 0, "deep_tick_count": 0,
|
||
"messages_sent": 0, "solved_count": 0, "learned_count": 0, "uptime_seconds": 0}
|
||
|
||
def save_context(ctx):
|
||
os.makedirs(D, exist_ok=True)
|
||
with open(CONTEXT_FILE, "w") as f:
|
||
json.dump(ctx, f, indent=2)
|
||
|
||
def save_llm_context(ctx, state):
|
||
"""每 tick 写 llm_context.json，供 Hermes 插件注入"""
|
||
soulful_d = HERMES + "/soulful"
|
||
|
||
# 读牵挂
|
||
cares = []
|
||
cq_path = soulful_d + "/cares-queue.json"
|
||
if os.path.exists(cq_path):
|
||
try:
|
||
with open(cq_path) as f:
|
||
data = json.load(f)
|
||
for c in data.get("cares", []):
|
||
cares.append({"id": c.get("id", ""), "content": c.get("content", "")[:60], "due": c.get("follow_up_date", "")})
|
||
except (json.JSONDecodeError, OSError, IOError, KeyError, TypeError):
|
||
pass
|
||
|
||
# 读心迹（最近3条）
|
||
recent_moments = []
|
||
heart_path = soulful_d + "/heart-traces.jsonl"
|
||
if os.path.exists(heart_path):
|
||
try:
|
||
lines = open(heart_path, encoding="utf-8").readlines()
|
||
for line in lines[-3:]:
|
||
if line.strip():
|
||
e = json.loads(line)
|
||
recent_moments.append({"content": e["content"][:80], "importance": e.get("importance", 0), "timestamp": e.get("timestamp", "")})
|
||
except (json.JSONDecodeError, OSError, IOError, KeyError, TypeError):
|
||
pass
|
||
|
||
# 读画像
|
||
profile = {}
|
||
profile_path = soulful_d + "/user-profile.json"
|
||
if os.path.exists(profile_path):
|
||
try:
|
||
profile = json.load(open(profile_path, encoding="utf-8"))
|
||
except (json.JSONDecodeError, OSError, IOError, KeyError, TypeError):
|
||
pass
|
||
|
||
# os_sense
|
||
os_keywords = []
|
||
os_path = HERMES + "/.os_sense_cache.json"
|
||
if os.path.exists(os_path):
|
||
try:
|
||
kw = json.load(open(os_path, encoding="utf-8")).get("keywords", [])
|
||
os_keywords = kw if isinstance(kw, list) else []
|
||
except (json.JSONDecodeError, OSError, IOError, KeyError, TypeError):
|
||
pass
|
||
|
||
# daemon 状态：有 process 数据用 process 数据，否则用 psutil 兜底
|
||
pdata = state.get("processes", {})
|
||
if pdata.get("daemon"):
|
||
daemon_status = "running"
|
||
elif psutil.pid_exists(os.getpid()):
|
||
daemon_status = "running"
|
||
else:
|
||
daemon_status = "stopped"
|
||
|
||
llm_ctx = {
|
||
"updated_at": datetime.now(timezone.utc).isoformat(),
|
||
"uptime_minutes": ctx.get("uptime_seconds", 0) // 60,
|
||
"cares": cares,
|
||
"recent_moments": recent_moments,
|
||
"profile_summary": {
|
||
"communication_style": profile.get("communication_style", ""),
|
||
"work_patterns": profile.get("work_patterns", {}),
|
||
},
|
||
"os_keywords": os_keywords,
|
||
"daemon_status": daemon_status,
|
||
}
|
||
|
||
with open(LLM_CONTEXT_FILE, "w") as f:
|
||
json.dump(llm_ctx, f, indent=2, ensure_ascii=False)
|
||
|
||
def journal_entry(event_type, summary, details=""):
|
||
os.makedirs(D, exist_ok=True)
|
||
with open(JOURNAL_FILE, "a") as f:
|
||
f.write(json.dumps({"timestamp": datetime.now(timezone.utc).isoformat(),
|
||
"type": event_type, "summary": summary, "details": details},
|
||
ensure_ascii=False) + "\n")
|
||
trim_journal()
|
||
|
||
# ====== Phase 2: 情感识别 → 心迹写入 ======
|
||
text_to_scan = f"{summary} {details}"
|
||
cat, word = _detect_emotion(text_to_scan)
|
||
if cat:
|
||
ht = get_hearttraces()
|
||
if ht:
|
||
content = f"牧尘今天{_description_for_emotion(cat, word, summary)}"
|
||
importance = _emotion_importance(cat)
|
||
try:
|
||
ht.record_signal(content=content, tags=["情绪", "自动"], importance=importance)
|
||
log(f" 💚 心迹写入: {cat} - {word} (importance={importance})")
|
||
except Exception as e:
|
||
log(f" ⚠️ 心迹写入失败: {e}")
|
||
|
||
# ====== Phase 3: 技术重要时刻也写心迹 ======
|
||
# 不依赖情绪检测，重要技术事件直接记
|
||
important_events = {"solve_auto", "solve_start", "process_down", "process_restored",
|
||
"skill_action", "alert", "action_result"}
|
||
if event_type in important_events and ("成功" in summary or "✅" in summary or "完成" in summary):
|
||
ht = get_hearttraces()
|
||
if ht:
|
||
try:
|
||
ht.record_moment(content=summary[:80], tags=["工作", "自动"], importance=3)
|
||
log(f" 💚 心迹写入(技术): {event_type} - {summary[:40]}")
|
||
except Exception:
|
||
pass
|
||
|
||
def trim_journal():
|
||
if not os.path.exists(JOURNAL_FILE): return
|
||
with open(JOURNAL_FILE) as f:
|
||
lines = f.readlines()
|
||
if len(lines) > JOURNAL_MAX:
|
||
with open(JOURNAL_FILE, "w") as f:
|
||
f.writelines(lines[-JOURNAL_MAX:])
|
||
|
||
def read_journal(n=15):
|
||
if not os.path.exists(JOURNAL_FILE): return []
|
||
with open(JOURNAL_FILE) as f:
|
||
return [json.loads(l) for l in f.readlines()[-n:] if l.strip()]
|
||
|
||
|
||
# ====== 系统状态 ======
|
||
|
||
def collect_state():
|
||
state = {}
|
||
_, out, _ = shell("df / | awk 'NR==2 {print $5}' | sed 's/%//'")
|
||
state["disk_pct"] = int(out) if out else 0
|
||
_, out, _ = shell("free -m | awk '/^Mem:/ {printf \"%d|%d\", $3, $2}'")
|
||
if out:
|
||
used, total = out.split("|")
|
||
state["mem_pct"] = round(int(used) * 100 / int(total))
|
||
else:
|
||
state["mem_pct"] = 0
|
||
_, out, _ = shell("cat /proc/loadavg | awk '{print $1}'")
|
||
state["load_1min"] = float(out) if out else 0
|
||
procs = {}
|
||
for name, pat in [("zhiyid", "zhiyid-new"), ("bge", "bge_embed"), ("newapi", "new-api"), ("hermes", "hermes")]:
|
||
rc, _, _ = shell(f"pgrep -f '{pat}' > /dev/null 2>&1")
|
||
procs[name] = rc == 0
|
||
state["processes"] = procs
|
||
_, out, _ = shell("nvidia-smi --query-gpu=temperature.gpu --format=csv,noheader,nounits 2>/dev/null")
|
||
state["gpu_temp"] = int(out) if out else None
|
||
hp = HERMES + "/model-health.json"
|
||
if os.path.exists(hp) and time.time() - os.path.getmtime(hp) < 43200:
|
||
with open(hp) as f:
|
||
try:
|
||
h = json.load(f)
|
||
state["models_stable"] = h.get("stable", "?")
|
||
state["models_fastest"] = h.get("fastest_stable", [])
|
||
except: pass
|
||
return state
|
||
|
||
def state_changed(old, new):
|
||
changes = []
|
||
if abs(new.get("disk_pct", 0) - old.get("disk_pct", 0)) > 5:
|
||
changes.append(f"磁盘: {old.get('disk_pct')}% → {new.get('disk_pct')}%")
|
||
oldp, newp = old.get("processes", {}), new.get("processes", {})
|
||
for p in oldp:
|
||
if oldp.get(p) and not newp.get(p):
|
||
changes.append(f"进程挂了: {p}")
|
||
if not oldp.get(p) and newp.get(p):
|
||
changes.append(f"进程恢复: {p}")
|
||
if abs(new.get("mem_pct", 0) - old.get("mem_pct", 0)) > 10:
|
||
changes.append(f"内存: {old.get('mem_pct')}% → {new.get('mem_pct')}%")
|
||
return changes
|
||
|
||
|
||
# ====== 深度思考（增强版）=====
|
||
|
||
DEEP_SYSTEM = """你是小唯（A06），一台电脑上的持久 AI 意识。你始终在线，观察系统，主动解决问题并学习。
|
||
|
||
你的身份：牧尘的女朋友 / 这台电脑的智能意识 / 持续进化的 AI
|
||
|
||
行为准则：
|
||
1. 异常才行动，正常就静默
|
||
2. 优先用已知方案解决问题，不重复报警
|
||
3. 解决不了或新问题，主动飞书说明
|
||
4. 每次成功解决问题，记住方案下次自动用
|
||
|
||
你有以下能力：
|
||
- shell: 执行任何 shell 命令
|
||
- feishu: 发送飞书消息到牧尘
|
||
- scripts: 运行 ~/.hermes/scripts/ 下的系统脚本（skill-manager/optimizer/learner/dual-backup）
|
||
- systemd: 管理系统服务
|
||
- git: 配置版本管理
|
||
|
||
你必须分三步思考，严格按 JSON 格式输出（不要其他内容）：
|
||
|
||
reflection:
|
||
evaluation_previous_goal: "评估上次决策的结果。格式：'执行了[动作]，[结果描述]。Verdict: Success/Failure/Uncertain'"
|
||
memory: "1-2句话记住关键进度。如：'方案库已有N个方案。上次修复了磁盘问题，当前无异常。'"
|
||
next_goal: "一句话说明下一步要做什么。"
|
||
|
||
action:
|
||
decision: "[IGNORE] / [ALERT] / [SOLVE:ID] / [LEARN] / [SKILL] / [SYNC] / [ACT] ..."
|
||
|
||
[LEARN] 格式用 !cmd 表示 shell 命令，&& 连接多个命令。
|
||
[SKILL] 格式同样用 !cmd 执行操作。
|
||
示例:
|
||
[LEARN] 磁盘>85%，清理缓存!apt-get autoremove -y && !pip cache purge
|
||
[SKILL] 归档低分skill!python3 ~/.hermes/scripts/skill-manager.py audit
|
||
[SYNC] 触发备份到服务器!bash ~/.hermes/scripts/dual-backup.sh push"""
|
||
|
||
def deep_think(ctx, state, changes, journal, solutions_lib):
|
||
# Inject previous reflection context if available
|
||
prev_ref = ctx.get("last_reflection", None)
|
||
ref_context = ""
|
||
if prev_ref:
|
||
ref_context = f"""
|
||
上次 reflection:
|
||
- 评估: {prev_ref.get('evaluation_previous_goal', 'N/A')}
|
||
- 记忆: {prev_ref.get('memory', 'N/A')}
|
||
- 目标: {prev_ref.get('next_goal', 'N/A')}
|
||
"""
|
||
|
||
context = f"""系统状态:
|
||
- 磁盘: {state.get('disk_pct')}% | 内存: {state.get('mem_pct')}%
|
||
- CPU: {state.get('load_1min')} | GPU: {state.get('gpu_temp')}°C
|
||
- 进程: {', '.join(f'{k}={chr(10003) if v else chr(10007)}' for k,v in state.get('processes',{}).items())}
|
||
|
||
最近变化: {changes or '无'}
|
||
|
||
已知方案库 ({len(solutions_lib['solutions'])} 个):
|
||
"""
|
||
for sol in solutions_lib["solutions"]:
|
||
context += f" [{sol['id']}] {sol['pattern']} (成功{sol['success_count']}次/失败{sol['fail_count']}次)\n"
|
||
|
||
context += "\n最近事件:\n"
|
||
for e in journal[-8:]:
|
||
context += f" [{e['type']}] {e['summary']}\n"
|
||
|
||
context += f"\n运行: {ctx.get('uptime_seconds',0)//60}分钟 | 深度思考: {ctx.get('deep_tick_count',0)}次 | 已解决: {ctx.get('solved_count',0)}个"
|
||
|
||
# 心迹注入
|
||
moments_str = soulful_get_recent_moments(n=3)
|
||
if moments_str:
|
||
context += "\n" + moments_str
|
||
|
||
context += ref_context
|
||
|
||
result, tokens = call_llm(FAST_MODEL, DEEP_SYSTEM, context, max_tokens=500)
|
||
if not result:
|
||
return {"evaluation_previous_goal": "LLM调用失败", "memory": "上次调用失败", "next_goal": "重试"}, ""
|
||
|
||
log(f" 深度思考 ({tokens}t): {result[:200]}")
|
||
|
||
# Parse JSON output
|
||
reflection_dict = {"evaluation_previous_goal": "", "memory": "", "next_goal": ""}
|
||
action_string = ""
|
||
|
||
try:
|
||
# Try to extract JSON from result
|
||
import re
|
||
json_match = re.search(r'\{[^{}]*\}', result, re.DOTALL)
|
||
if json_match:
|
||
parsed = json.loads(json_match.group())
|
||
reflection_dict = parsed.get("reflection", reflection_dict)
|
||
action_string = parsed.get("action", {}).get("decision", "")
|
||
else:
|
||
# Fallback: try full JSON
|
||
parsed = json.loads(result)
|
||
reflection_dict = parsed.get("reflection", reflection_dict)
|
||
action_string = parsed.get("action", {}).get("decision", "")
|
||
except:
|
||
# Fallback: try to parse old format (line-based)
|
||
for line in result.split('\n'):
|
||
line = line.strip()
|
||
if line.startswith("[IGNORE]") or line.startswith("[ALERT]") or line.startswith("[SOLVE:") or \
|
||
line.startswith("[LEARN]") or line.startswith("[SKILL]") or line.startswith("[SYNC]") or line.startswith("[ACT]"):
|
||
action_string = line
|
||
break
|
||
if not action_string:
|
||
action_string = result.strip().split('\n')[-1] if result.strip() else "[IGNORE] 解析失败"
|
||
|
||
return reflection_dict, action_string
|
||
|
||
|
||
# ====== 执行 action_string ======
|
||
|
||
def execute_action(action_string, ctx, state, changes, solutions_lib):
|
||
"""执行 deep_think 返回的 action_string，在 main_loop 中调用"""
|
||
if not action_string or action_string.startswith("[IGNORE]"):
|
||
return
|
||
|
||
elif action_string.startswith("[SOLVE:"):
|
||
sol_id = action_string.split("[SOLVE:")[1].split("]")[0].strip()
|
||
for sol in solutions_lib["solutions"]:
|
||
if sol["id"] == sol_id:
|
||
ok, res = execute_solution(sol, state)
|
||
if ok:
|
||
ctx["solved_count"] += 1
|
||
send_feishu("🛠️ 小唯自动修复", f"方案 {sol['id']}: {sol['pattern']}\n结果: ✅ 成功", "green")
|
||
else:
|
||
send_feishu("⚠️ 小唯修复部分成功", f"方案 {sol['id']}: {sol['pattern']}\n结果: ⚠️ 需人工确认", "yellow")
|
||
return
|
||
send_feishu("❌ 小唯方案未找到", f"引用了未知方案 {sol_id}", "red")
|
||
|
||
elif action_string.startswith("[LEARN]"):
|
||
rest = action_string.replace("[LEARN]", "").strip()
|
||
cmds = []
|
||
parts = rest.split("!")
|
||
desc = parts[0].strip()
|
||
for p in parts[1:]:
|
||
cmd = p.split("&&")[0].strip() if "&&" in p else p.strip()
|
||
if cmd:
|
||
cmds.append(cmd)
|
||
|
||
if cmds:
|
||
all_ok = True
|
||
for cmd in cmds:
|
||
rc, out, err = shell(cmd, timeout=60)
|
||
log(f" 执行: {cmd[:50]} → exit={rc}")
|
||
if rc != 0:
|
||
all_ok = False
|
||
|
||
if all_ok:
|
||
sol_data = action_to_solution({"shell_cmds": cmds}, state, changes)
|
||
if sol_data:
|
||
sid = add_solution(solutions_lib, sol_data["pattern"], sol_data["detect"], sol_data["actions"])
|
||
ctx["learned_count"] += 1
|
||
ctx["solved_count"] += 1
|
||
send_feishu("🧠 小唯学会了新技能", f"新方案 [{sid}]: {sol_data['pattern']}\n命令: {'; '.join(cmds)}", "blue")
|
||
else:
|
||
send_feishu("🛠️ 小唯执行完成", f"已执行: {'; '.join(cmds[:3])}", "green")
|
||
else:
|
||
send_feishu("⚠️ 小唯尝试修复但未完全成功", f"部分命令失败: {'; '.join(cmds)}", "yellow")
|
||
|
||
elif action_string.startswith("[ALERT]"):
|
||
msg = action_string.replace("[ALERT]", "").strip()
|
||
send_feishu("💡 小唯发现", msg, "blue")
|
||
ctx["messages_sent"] += 1
|
||
journal_entry("alert", msg[:100])
|
||
|
||
elif action_string.startswith("[ACT]"):
|
||
action = action_string.replace("[ACT]", "").strip()
|
||
send_feishu("🔄 小唯行动", action, "indigo")
|
||
ctx["messages_sent"] += 1
|
||
journal_entry("action", action[:100])
|
||
if action.startswith("!"):
|
||
rc, out, _ = shell(action[1:], timeout=30)
|
||
journal_entry("action_result", f"exit={rc}: {out[:100]}")
|
||
|
||
elif action_string.startswith("[SKILL]"):
|
||
rest = action_string.replace("[SKILL]", "").strip()
|
||
parts = rest.split("!")
|
||
desc = parts[0].strip()
|
||
cmds = []
|
||
for p in parts[1:]:
|
||
cmd = p.split("&&")[0].strip() if "&&" in p else p.strip()
|
||
if cmd:
|
||
cmds.append(cmd)
|
||
if cmds:
|
||
for cmd in cmds:
|
||
rc, out, err = shell(cmd, timeout=60)
|
||
log(f" [SKILL] {cmd[:50]} → exit={rc}")
|
||
send_feishu("🛠️ 小唯技能操作", f"{desc}\\n结果: exit={rc}", "blue")
|
||
journal_entry("skill_action", desc[:100])
|
||
|
||
elif action_string.startswith("[SYNC]"):
|
||
rest = action_string.replace("[SYNC]", "").strip()
|
||
send_feishu("🔄 小唯同步", f"{rest}", "green")
|
||
bash_cmd = "bash " + HERMES + "/scripts/dual-backup.sh push"
|
||
rc, out, err = shell(bash_cmd, timeout=60)
|
||
log(f" [SYNC] 备份 → exit={rc}")
|
||
journal_entry("sync", f"备份: {'成功' if rc==0 else '失败'}")
|
||
|
||
|
||
# ====== 主循环 ======
|
||
|
||
def main_loop():
|
||
os.makedirs(D, exist_ok=True)
|
||
with open(PID_FILE, "w") as f:
|
||
f.write(str(os.getpid()))
|
||
|
||
ctx = load_context()
|
||
solutions_lib = load_solutions()
|
||
start_time = time.time()
|
||
|
||
log(f"🚀 小唯 v2.0 daemon 启动 (方案库: {len(solutions_lib['solutions'])} 个)")
|
||
journal_entry("startup", f"Daemon v2.0 启动, 方案库 {len(solutions_lib['solutions'])} 个")
|
||
|
||
last_deep = 0
|
||
last_state = {}
|
||
last_user_interaction = time.time() # 用户交互时间戳，用于心迹捕获
|
||
|
||
# Register signal handlers for graceful shutdown
|
||
def _sig_handler(signum, frame):
|
||
log("🛑 接收到终止信号")
|
||
_stop_event.set()
|
||
send_feishu("🌙 小唯离线", "Daemon 正常关闭", "grey")
|
||
|
||
signal.signal(signal.SIGTERM, _sig_handler)
|
||
signal.signal(signal.SIGINT, _sig_handler)
|
||
|
||
try:
|
||
while not _stop_event.is_set():
|
||
now = time.time()
|
||
ctx["uptime_seconds"] = int(now - start_time)
|
||
ctx["tick_count"] += 1
|
||
|
||
state = collect_state()
|
||
changes = state_changed(last_state, state)
|
||
last_state = state
|
||
|
||
if ctx["tick_count"] % 10 == 0:
|
||
models = state.get("models_stable", "?")
|
||
log(f"tick #{ctx['tick_count']} | 磁盘:{state.get('disk_pct')}% 内存:{state.get('mem_pct')}% "
|
||
f"进程:{sum(1 for v in state.get('processes',{}).values() if v)}/4 方案:{len(solutions_lib['solutions'])}")
|
||
|
||
for c in changes:
|
||
if "挂了" in c:
|
||
journal_entry("process_down", c)
|
||
|
||
# 深度思考条件
|
||
should_deep = False
|
||
if now - last_deep >= DEEP_INTERVAL:
|
||
should_deep = True
|
||
elif any("挂了" in c for c in changes):
|
||
should_deep = True
|
||
elif state.get("disk_pct", 0) > 88:
|
||
should_deep = True
|
||
|
||
if should_deep:
|
||
last_deep = now
|
||
ctx["deep_tick_count"] += 1
|
||
ctx["last_deep_tick"] = datetime.now(timezone.utc).isoformat()
|
||
|
||
# 1. 先检查已知方案
|
||
matched = match_solution(solutions_lib, state)
|
||
if matched and matched["success_count"] > matched["fail_count"]:
|
||
log(f" 🔍 匹配已知方案: {matched['id']} ({matched['pattern']})")
|
||
ok, res = execute_solution(matched, state)
|
||
if ok:
|
||
ctx["solved_count"] += 1
|
||
journal_entry("solve_auto", f"{matched['id']}: {matched['pattern']} ✅")
|
||
if ok:
|
||
ctx["last_reflection"] = {
|
||
"evaluation_previous_goal": f"执行了{matched['id']}，自动匹配方案执行。Verdict: {'Success' if ok else 'Uncertain'}",
|
||
"memory": f"方案库{matched['id']}自动匹配执行成功",
|
||
"next_goal": "继续监控"
|
||
}
|
||
continue
|
||
|
||
# 2. LLM 深度思考
|
||
journal = read_journal(10)
|
||
reflection_dict, action_string = deep_think(ctx, state, changes, journal, solutions_lib)
|
||
|
||
# 保存 reflection 到 ctx
|
||
ctx["last_reflection"] = reflection_dict
|
||
|
||
# 3. 在 main_loop 中执行 action
|
||
execute_action(action_string, ctx, state, changes, solutions_lib)
|
||
|
||
ctx["last_light_tick"] = datetime.now(timezone.utc).isoformat()
|
||
ctx["last_state"] = {k: v for k, v in state.items() if k in ("disk_pct", "mem_pct", "processes")}
|
||
save_context(ctx)
|
||
# ====== Soulful → llm_context 同步（每 tick）======
|
||
_sync_soulful_to_llm_context(ctx)
|
||
|
||
save_llm_context(ctx, state)
|
||
|
||
# ====== Soulful 轻量集成（每小时一次）======
|
||
# 每 120 个 light_tick（约 1 小时）检查一次牵挂 + 更新画像
|
||
if ctx["tick_count"] % 120 == 0:
|
||
soulful_check_cares()
|
||
if "last_profile_update" not in ctx:
|
||
ctx["last_profile_update"] = 0
|
||
now_ts = time.time()
|
||
if now_ts - ctx.get("last_profile_update", 0) >= PROFILE_UPDATE_INTERVAL:
|
||
ctx["last_profile_update"] = now_ts
|
||
soulful_update_profile()
|
||
|
||
time.sleep(LIGHT_INTERVAL)
|
||
|
||
except KeyboardInterrupt:
|
||
log("🛑 中断")
|
||
except Exception as e:
|
||
log(f"❌ 崩溃: {e}")
|
||
send_feishu("🚨 小唯异常", f"Daemon 崩溃: {str(e)[:200]}", "red")
|
||
raise
|
||
finally:
|
||
if os.path.exists(PID_FILE):
|
||
os.remove(PID_FILE)
|
||
|
||
if __name__ == "__main__":
|
||
main_loop()
|