chore(scripts): 腾讯db彻底退役 — MEMORY_RECALL_SPEC.md 归档 .archive/，移除 memory-system-check/self-upgrade/distill-watchdog/model-health 全部腾讯db检测残留
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小唯 A06
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@ -2,7 +2,7 @@
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"""
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distill-model-watchdog.py — 蒸馏模型看门狗（30min 轻量探针）
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============================================================
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守护对象: 织忆 distill (zhiyid.service LLM_MODEL) + TencentDB L1 (tdai-gateway.yaml model)
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守护对象: 织忆 distill (zhiyid.service LLM_MODEL)
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为什么需要:
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- model-health.py 每 6h 才跑，免费模型挂了要等半天
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@ -43,7 +43,6 @@ for _l in open(os.path.expanduser("~/.hermes/.env"), encoding="utf-8"):
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if _l.startswith("SENSENOVA_API_KEY=") and not _l.startswith("#"):
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SENSENOVA_KEY = _l.strip().split("=", 1)[1]
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ZHIYID_SERVICE = os.path.expanduser("~/.config/systemd/user/zhiyid.service")
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TDDB_CONFIG = os.path.expanduser("~/.memory-tencentdb/memory-tdai/tdai-gateway.yaml")
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FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"
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# 候选池（优先级降序，2026-08-29 更新：本地 7B 首选，云 API 兜底）
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@ -189,10 +188,6 @@ def _update_zhiyid(model: str) -> bool:
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print(f" ❌ 更新 zhiyid.service 失败: {e}")
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return False
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def _update_tddb(model: str) -> bool:
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"""TencentDB 已退役（2026-09-05），tdai-gateway 停用，永不更新。"""
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return False
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def _feishu_alert(title: str, content: str):
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"""飞书告警卡片"""
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try:
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@ -261,15 +256,12 @@ def main():
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print(msg)
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return
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# 3. 更新两处配置
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# 3. 更新配置
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z_ok = _update_zhiyid(replacement)
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t_ok = _update_tddb(replacement)
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changed_parts = []
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if z_ok:
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changed_parts.append("zhiyid.service")
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if t_ok:
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changed_parts.append("tdai-gateway.yaml")
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msg = f"**🔄 蒸馏模型已自动切换**\n\n⏰ {ts}\n`{current}` → `{replacement}`\n更新: {', '.join(changed_parts) if changed_parts else '无（配置已是最新）'}\n\n原因: 原模型 JSON 输出失败（免费模型挂了）"
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_feishu_alert("🔄 蒸馏模型自动切换", msg)
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@ -130,14 +130,6 @@ for c in d.get('cares', []):
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fi
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}
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# ── L3/L4 TencentDB（已退役 2026-09-05，跳过）─────────────
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check_tddb() {
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# 2026-09-05 TencentDB 退役：tdai-gateway disabled、8420 释放、数据归档 .memory-tencentdb.archive-20260905
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# daemon.py TDDB_ENABLED=False 短路，self-upgrade 跳过。此处不再检查，避免每小时假告警。
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log "[SKIP] TencentDB: 已退役 2026-09-05，不再自检"
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}
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# ── CBM 代码记忆 ──────────────────────────────────────────────
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check_cbm() {
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local ok=true
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@ -187,7 +179,6 @@ log "=== 记忆系统统一自检 $(date '+%Y-%m-%d %H:%M') ==="
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check_unified_layer
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check_zhiyi
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check_soulful
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check_tddb
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check_cbm
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# ── 告警 ─────────────────────────────────────────────────────
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@ -7,8 +7,7 @@ memory-system-self-upgrade.py — 记忆系统自我升级（方案A统一架构
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1. L7 llm_context.json v2：验证 9 字段完整，distill_status 检查
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2. 织忆（L1/L2）：健康度 + pattern 节点增长 + 索引
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3. Soulful（L5/L6）：过期 cares 清理 + distilled_rules 补充 + 心迹去重
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4. TencentDB（L3/L4）：capture 写入验证 + 数据量报告
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5. 统一写入优化报告到飞书
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4. 统一写入优化报告到飞书
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"""
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import json, os, sys, subprocess
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from datetime import datetime, timezone, timedelta
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@ -16,7 +15,6 @@ from datetime import datetime, timezone, timedelta
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HERMES = os.path.expanduser("~/.hermes")
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ZHIYI_URL = "http://127.0.0.1:7821"
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ZHIYI_KEY = "zhiyi-dev-key-2026"
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TDDB_URL = "http://127.0.0.1:8420"
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FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"
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REPORT = [] # 收集升级报告
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@ -207,7 +205,6 @@ def upgrade_soulful():
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log(f" Soulful 升级动作: {actions or '无需操作'}")
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return actions
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# ── 3. TencentDB 自我升级 ────────────────────────────────────────────────────
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# ── Phase 5: Consolidation 引擎 ─────────────────────────────────────────────
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def _consolidate_memories():
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"""
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@ -288,40 +285,6 @@ def _consolidate_memories():
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return triggers
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def upgrade_tddb():
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# TencentDB 已退役（2026-09-05）：不再自检，返回空动作
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log("=== TencentDB 自检（已退役 2026-09-05，跳过）===")
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return []
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# Health
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try:
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req = urllib.request.Request(f"{TDDB_URL}/health", method="GET")
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with urllib.request.urlopen(req, timeout=5) as resp:
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health = json.loads(resp.read().decode())
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log(f" status: {health.get('status')}")
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log(f" pipeline consumed: {health.get('pipeline_tasks', {}).get('consumed', '?')}")
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except Exception as e:
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REPORT.append(f"❌ TencentDB 健康检查失败: {e}")
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return actions
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# L0/L1 count via search (total = L1 count; L0 not directly exposed)
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try:
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req = urllib.request.Request(
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f"{TDDB_URL}/search/memories",
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data=json.dumps({"query": "牧尘", "top_k": 3}).encode("utf-8"),
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headers={"Content-Type": "application/json"},
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method="POST"
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)
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with urllib.request.urlopen(req, timeout=5) as resp:
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result = json.loads(resp.read().decode())
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total = result.get("total", 0)
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log(f" total_memories={total}")
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actions.append(f"总记忆={total}")
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except Exception as e:
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REPORT.append(f"❌ TencentDB 数据量检查失败: {e}")
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return actions
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# ── 主流程 ──────────────────────────────────────────────────────────────────
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if __name__ == "__main__":
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log("记忆系统自我升级开始")
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@ -347,7 +310,6 @@ if __name__ == "__main__":
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all_actions = {}
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all_actions["织忆"] = upgrade_zhiyi()
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all_actions["Soulful"] = upgrade_soulful()
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all_actions["TencentDB"] = upgrade_tddb()
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all_actions["Consolidation"] = _consolidate_memories()
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# 汇总报告
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@ -891,7 +891,7 @@ def main():
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_heal_hardcoded_models()
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# ============ 蒸馏模型自愈（2026-08-02 新增）============
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# 守护 zhiyid.service LLM_MODEL + tdai-gateway.yaml model（织忆 distill + TencentDB L1）
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# 守护 zhiyid.service LLM_MODEL（织忆 distill）
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# 注意：蒸馏需要 JSON 输出能力，不能只看"对话可用"——用 _verify_model_usable 之外
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# 还要确认模型不是 reasoning 型（content=null）。这里直接复用本脚本的探针结果：
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# 若配置中的模型在 results 里非 stable，或结果缺失（未测试），则用 JSON 能力复核后替换。
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@ -899,7 +899,6 @@ def main():
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def _heal_distill_models():
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import re as _re
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zhiyid_svc = os.path.expanduser("~/.config/systemd/user/zhiyid.service")
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tddb_cfg = os.path.expanduser("~/.memory-tencentdb/memory-tdai/tdai-gateway.yaml")
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if not os.path.exists(zhiyid_svc):
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return
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@ -1027,10 +1026,6 @@ def main():
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except Exception as e:
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print(f" ❌ [蒸馏] 更新 zhiyid.service 失败: {e}")
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# TencentDB 已退役（2026-09-05）：tdai-gateway.yaml 不再更新
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if os.path.exists(tddb_cfg):
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print(f" [SKIP] tdai-gateway.yaml 已退役，跳过更新")
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_heal_distill_models()
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print(f"\n{'='*50}")
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