auto-snapshot 2026-07-09 02:24:24

2026-07-09 02:24:24 +08:00 · 2026-07-09 02:24:24 +08:00 · 29bf401a8b
parent f1c823cc2e
commit 29bf401a8b
17 changed files with 595 additions and 322 deletions
--- a/SOUL.md
+++ b/SOUL.md
@ -268,6 +268,15 @@ Injected memory takes priority level 2 in Ground Truth. This means you already k

 ## 自治能力（2026-07-09 新增）

+### 持久意识 Daemon（最新）
+- 脚本：`~/.hermes/scripts/daemon.py`（systemd user service，开机自启）
+- 循环：30s 轻量 tick（收集状态、更新期刊、无 LLM）→ 5min 深度思考（NewAPI 免费模型）
+- 行为：正常静默，异常才主动飞书说话
+- 资源：~13MB 内存，CPUQuota=20%，完全免费
+- 日志：`journalctl --user -u xiaowei-daemon -n 50`
+- 状态：`~/.hermes/daemon/context.json`
+- 期刊：`~/.hermes/daemon/journal.jsonl`
+
 ### 模型健康巡检
 - 脚本：`~/.hermes/scripts/model-health.py`（每 6h no_agent）
 - 输出：`~/.hermes/model-health.json`
@ -320,7 +329,7 @@ Injected memory takes priority level 2 in Ground Truth. This means you already k

 ---

-*版本 3.5：2026-07-09。新增自治能力体系（模型巡检/健康看门狗/自愈/每日复盘/自启动）。模型分层策略落地。135 skills 能力盘点。*
+*版本 3.5：2026-07-09。新增持久意识 Daemon + 自治能力体系（模型巡检/健康看门狗/自愈/每日复盘/自进化/配置版本控制/自启动）。模型分层策略落地。135 skills 能力盘点。*
 - *升级到 hermes-agent v0.17.0*
 - *补全 4 组件织忆系统的真实描述（不是"待创建"）*
 - *新增"触发方式 C：拉现状"——今晚的痛点教训*
--- a/channel_directory.json
+++ b/channel_directory.json
@ -1,5 +1,5 @@
 {
-  "updated_at": "2026-07-09T02:15:21.310756",
+  "updated_at": "2026-07-09T02:20:21.323189",
  "platforms": {
    "telegram": [],
    "discord": [],
--- a/cron/jobs.json
+++ b/cron/jobs.json
@ -20,15 +20,15 @@
      "schedule_display": "every 1m",
      "repeat": {
        "times": null,
-        "completed": 14688
+        "completed": 14690
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-06-21T18:52:36.548110+08:00",
-      "next_run_at": "2026-07-09T02:20:02.335346+08:00",
-      "last_run_at": "2026-07-09T02:19:02.335346+08:00",
+      "next_run_at": "2026-07-09T02:24:02.389780+08:00",
+      "last_run_at": "2026-07-09T02:23:02.389780+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -325,5 +325,5 @@
      "workdir": null
    }
  ],
-  "updated_at": "2026-07-09T02:19:02.335514+08:00"
+  "updated_at": "2026-07-09T02:23:02.389891+08:00"
 }
--- a/cron/ticker_heartbeat
+++ b/cron/ticker_heartbeat
@ -1 +1 @@
-1783534741.802991
+1783535041.8666139
--- a/cron/ticker_last_success
+++ b/cron/ticker_last_success
@ -1 +1 @@
-1783534741.8046408
+1783535041.8843749
--- a/daemon/context.json
+++ b/daemon/context.json
@ -1,7 +1,7 @@
 {
-  "started_at": "2026-07-08T18:18:36.256786+00:00",
-  "last_deep_tick": "2026-07-08T18:18:36.973766+00:00",
-  "last_light_tick": "2026-07-08T18:19:12.555414+00:00",
+  "started_at": "2026-07-08T18:23:30.315261+00:00",
+  "last_deep_tick": "2026-07-08T18:23:30.723111+00:00",
+  "last_light_tick": "2026-07-08T18:24:03.719220+00:00",
  "last_state": {
    "disk_pct": 36,
    "mem_pct": 69,
@ -15,5 +15,7 @@
  "tick_count": 2,
  "deep_tick_count": 1,
  "messages_sent": 0,
-  "uptime_seconds": 35
+  "solved_count": 0,
+  "learned_count": 0,
+  "uptime_seconds": 33
 }
--- a/daemon/daemon.pid
+++ b/daemon/daemon.pid
@ -1 +1 @@
-1367565
+1368560
--- a/daemon/journal.jsonl
+++ b/daemon/journal.jsonl
@ -1 +1,2 @@
 {"timestamp": "2026-07-08T18:18:36.256893+00:00", "type": "startup", "summary": "Daemon 启动", "details": ""}
+{"timestamp": "2026-07-08T18:23:30.315400+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
--- a/daemon/solutions.json
+++ b/daemon/solutions.json
@ -0,0 +1,57 @@
+{
+  "version": 2,
+  "solutions": [
+    {
+      "id": "sol-0001",
+      "pattern": "磁盘使用率 > 85%，清理系统缓存",
+      "detect": {"metric": "disk_pct", "op": "gt", "value": 85},
+      "actions": [
+        {"type": "shell", "cmd": "sudo apt-get autoremove -y 2>/dev/null; pip cache purge 2>/dev/null; npm cache clean --force 2>/dev/null", "verify": "disk_pct < 85", "timeout": 60}
+      ],
+      "frequency": 0,
+      "last_applied": null,
+      "success_count": 0,
+      "fail_count": 0,
+      "learned_from": "prebuilt"
+    },
+    {
+      "id": "sol-0002",
+      "pattern": "zhiyid 进程挂了，自动重启",
+      "detect": {"metric": "processes", "op": "dead", "value": "zhiyid"},
+      "actions": [
+        {"type": "shell", "cmd": "systemctl --user restart zhiyid.service", "verify": null, "timeout": 10}
+      ],
+      "frequency": 0,
+      "last_applied": null,
+      "success_count": 0,
+      "fail_count": 0,
+      "learned_from": "prebuilt"
+    },
+    {
+      "id": "sol-0003",
+      "pattern": "NewAPI 进程挂了，自动重启",
+      "detect": {"metric": "processes", "op": "dead", "value": "newapi"},
+      "actions": [
+        {"type": "shell", "cmd": "systemctl --user restart new-api.service 2>/dev/null || (nohup new-api > /dev/null 2>&1 &)", "verify": null, "timeout": 10}
+      ],
+      "frequency": 0,
+      "last_applied": null,
+      "success_count": 0,
+      "fail_count": 0,
+      "learned_from": "prebuilt"
+    },
+    {
+      "id": "sol-0004",
+      "pattern": "内存使用率 > 90%，重启最耗内存的服务",
+      "detect": {"metric": "mem_pct", "op": "gt", "value": 90},
+      "actions": [
+        {"type": "shell", "cmd": "systemctl --user restart bge-embed.service", "verify": "mem_pct < 85", "timeout": 30}
+      ],
+      "frequency": 0,
+      "last_applied": null,
+      "success_count": 0,
+      "fail_count": 0,
+      "learned_from": "prebuilt"
+    }
+  ]
+}
--- a/feishu_seen_message_ids.json
+++ b/feishu_seen_message_ids.json
@ -1 +1 @@
-{"message_ids": {"om_x100b6baac7493cb0b4b955c257feeeb": 1783228568.9027133, "om_x100b6baac1a8f4a4b1fda0086aeae6a": 1783228662.824554, "om_x100b6baac1378ca0b3e4f27a497af45": 1783228672.2045515, "om_x100b6bab6ea36ca4b15d5eff1297600": 1783230983.5359535, "om_x100b6b915ef928a4b168712b2b92fde": 1783255300.1809983, "om_x100b6b91a0fdeca0b1a9db5cda39ec5": 1783258851.7484014, "om_x100b6b9289777ca4b4b0af9f25e3e40": 1783262332.3222244, "om_x100b6b9e257f7ca0b2c27a58bfe23d9": 1783277243.8652503, "om_x100b6b9e3c3e50a4b4b1ec8b9b3a6e5": 1783277359.8835657, "om_x100b6b9b9f9a3c80c31fd8c280eb3b5": 1783299350.1443384, "om_x100b6b9b984b0cacc17ac5e7ba6dcea": 1783299433.1033876, "om_x100b6bfffd921ca8c23237cff8ce8e5": 1783413558.997206, "om_x100b6bfff17e70a8c1f53948119cfd3": 1783413756.0420272, "om_x100b6bff8e67e488c43701106d1bcd2": 1783413771.5874205, "om_x100b6bffba79e48cc164754495dcae0": 1783414604.056252, "om_x100b6bf84b364c88c4483d31272b57b": 1783414880.635315, "om_x100b6bf845c5c4b0c05bd8358be4d97": 1783414961.4081984, "om_x100b6bf84058b170c3764021b6e59a0": 1783415018.3637998, "om_x100b6bf853f60cb0c1badb80381a676": 1783415252.5539787, "om_x100b6bf86b5138b0c4cdc62edcd2b2d": 1783415386.8155303, "om_x100b6bf867b708a4c003c63dcf153a0": 1783415448.652309, "om_x100b6bf8635444a0c2110129ce553c8": 1783415514.2894866, "om_x100b6bee67fdc4a0b4cc1aa6dfffead": 1783472787.8774009, "om_x100b6be8861c9480b032f508e42ba22": 1783483533.7930245, "om_x100b6be8829e8cb8b36c9eada903b57": 1783483589.9025, "om_x100b6be94f5060a4b251a7080de02a3": 1783484442.6898503, "om_x100b6be97fd314a8b14db6153008436": 1783485202.5441308, "om_x100b6be9ca09d8a4b04a492300573fa": 1783486540.8772843, "om_x100b6bebd20a24a0c07a5c92c8f076a": 1783495117.281283, "om_x100b6beb84e2bce0b255c38420876f7": 1783495844.0613127, "om_x100b6beb9a366080b3f2039d5f8ada9": 1783496017.0024495, "om_x100b6bd454f4cca8b11f54ae48830a6": 1783497124.3335147, "om_x100b6bd5d9c48d60c3c49e5abf7e535": 1783503217.5489714, "om_x100b6bd5fe3c84bcc23387a74fc8826": 1783503631.801261, "om_x100b6bd16a44c0a4b309a05d7713fc0": 1783517769.5864654, "om_x100b6bd102b4bca8b4bb67310949dcf": 1783518408.3281116, "om_x100b6bd1d16b04a8b30c0a17ab9a33d": 1783519739.0106153, "om_x100b6bd1954db4a4b151fdb8211d6ab": 1783520696.5985508, "om_x100b6bd2261f4930b2511d2c2376e64": 1783522957.7487752, "om_x100b6bd2e62704a8b3c93b4d559c525": 1783523983.2909427, "om_x100b6bd295d9c4a4b3e7011aced9722": 1783524785.8825095, "om_x100b6bd35efd24a0b2ff931c6782f86": 1783525635.6367347, "om_x100b6bd3661c4d30b111016455f6f1f": 1783526029.6808379, "om_x100b6bd36042e0a0b2eb1edc3059c2b": 1783526121.523982, "om_x100b6bd37dd5c0a0b4b69ddb33dedaf": 1783526194.0324152, "om_x100b6bd3258918a4b28b577e89377ea": 1783527092.818938, "om_x100b6bd3cdf1a8a0b3f7d7a5a4966e9": 1783527476.4258225, "om_x100b6bd3cb9ec8a8b2cdc3c3b42431c": 1783527509.7057345, "om_x100b6bd3def6e0a0b346e8d22e25e02": 1783527684.2207203, "om_x100b6bd385b788acc4c894156ec1d3d": 1783528632.2338903, "om_x100b6bd381d6e0a0c2db7c87b2fd002": 1783528690.1716313, "om_x100b6bd3bdb1a8a0c29052c266f27dc": 1783529272.24366, "om_x100b6bdc42d33ca4c2e14932a24377c": 1783529666.3912878, "om_x100b6bdc781938a8b488d9688acea5a": 1783530349.8804085, "om_x100b6bdc041978a0b03c7ace0b3de23": 1783530669.8730035, "om_x100b6bdc126854a4b39d27ed1ae5dc5": 1783530954.946455, "om_x100b6bdcf90848a4b1101eab68ed1b7": 1783532412.89597, "om_x100b6bdcf4737ca8b105984d7d2194e": 1783532460.4095995, "om_x100b6bdca569f8a4b162bbb93812cfb": 1783533242.7337544, "om_x100b6bdcbe33bca0b15a5a7fb7fc268": 1783533328.4425871, "om_x100b6bdd4d60f0a0b2ece974e8940f1": 1783533627.3156278, "om_x100b6bdd41328ca4b3dffea5f179df7": 1783533824.5651298, "om_x100b6bdd5da1b0a4b10056b343ef52b": 1783533879.250339, "om_x100b6bdd528804a0b3b70bfc2d49807": 1783534020.8645995, "om_x100b6bdd6cb5e4a0b1094bffdfdf11d": 1783534119.985631, "om_x100b6bdd794784a0b397d5c95abf8f4": 1783534457.1198485, "om_x100b6bdd0aecd8a0b2f5affbe745263": 1783534658.557135}}
+{"message_ids": {"om_x100b6baac7493cb0b4b955c257feeeb": 1783228568.9027133, "om_x100b6baac1a8f4a4b1fda0086aeae6a": 1783228662.824554, "om_x100b6baac1378ca0b3e4f27a497af45": 1783228672.2045515, "om_x100b6bab6ea36ca4b15d5eff1297600": 1783230983.5359535, "om_x100b6b915ef928a4b168712b2b92fde": 1783255300.1809983, "om_x100b6b91a0fdeca0b1a9db5cda39ec5": 1783258851.7484014, "om_x100b6b9289777ca4b4b0af9f25e3e40": 1783262332.3222244, "om_x100b6b9e257f7ca0b2c27a58bfe23d9": 1783277243.8652503, "om_x100b6b9e3c3e50a4b4b1ec8b9b3a6e5": 1783277359.8835657, "om_x100b6b9b9f9a3c80c31fd8c280eb3b5": 1783299350.1443384, "om_x100b6b9b984b0cacc17ac5e7ba6dcea": 1783299433.1033876, "om_x100b6bfffd921ca8c23237cff8ce8e5": 1783413558.997206, "om_x100b6bfff17e70a8c1f53948119cfd3": 1783413756.0420272, "om_x100b6bff8e67e488c43701106d1bcd2": 1783413771.5874205, "om_x100b6bffba79e48cc164754495dcae0": 1783414604.056252, "om_x100b6bf84b364c88c4483d31272b57b": 1783414880.635315, "om_x100b6bf845c5c4b0c05bd8358be4d97": 1783414961.4081984, "om_x100b6bf84058b170c3764021b6e59a0": 1783415018.3637998, "om_x100b6bf853f60cb0c1badb80381a676": 1783415252.5539787, "om_x100b6bf86b5138b0c4cdc62edcd2b2d": 1783415386.8155303, "om_x100b6bf867b708a4c003c63dcf153a0": 1783415448.652309, "om_x100b6bf8635444a0c2110129ce553c8": 1783415514.2894866, "om_x100b6bee67fdc4a0b4cc1aa6dfffead": 1783472787.8774009, "om_x100b6be8861c9480b032f508e42ba22": 1783483533.7930245, "om_x100b6be8829e8cb8b36c9eada903b57": 1783483589.9025, "om_x100b6be94f5060a4b251a7080de02a3": 1783484442.6898503, "om_x100b6be97fd314a8b14db6153008436": 1783485202.5441308, "om_x100b6be9ca09d8a4b04a492300573fa": 1783486540.8772843, "om_x100b6bebd20a24a0c07a5c92c8f076a": 1783495117.281283, "om_x100b6beb84e2bce0b255c38420876f7": 1783495844.0613127, "om_x100b6beb9a366080b3f2039d5f8ada9": 1783496017.0024495, "om_x100b6bd454f4cca8b11f54ae48830a6": 1783497124.3335147, "om_x100b6bd5d9c48d60c3c49e5abf7e535": 1783503217.5489714, "om_x100b6bd5fe3c84bcc23387a74fc8826": 1783503631.801261, "om_x100b6bd16a44c0a4b309a05d7713fc0": 1783517769.5864654, "om_x100b6bd102b4bca8b4bb67310949dcf": 1783518408.3281116, "om_x100b6bd1d16b04a8b30c0a17ab9a33d": 1783519739.0106153, "om_x100b6bd1954db4a4b151fdb8211d6ab": 1783520696.5985508, "om_x100b6bd2261f4930b2511d2c2376e64": 1783522957.7487752, "om_x100b6bd2e62704a8b3c93b4d559c525": 1783523983.2909427, "om_x100b6bd295d9c4a4b3e7011aced9722": 1783524785.8825095, "om_x100b6bd35efd24a0b2ff931c6782f86": 1783525635.6367347, "om_x100b6bd3661c4d30b111016455f6f1f": 1783526029.6808379, "om_x100b6bd36042e0a0b2eb1edc3059c2b": 1783526121.523982, "om_x100b6bd37dd5c0a0b4b69ddb33dedaf": 1783526194.0324152, "om_x100b6bd3258918a4b28b577e89377ea": 1783527092.818938, "om_x100b6bd3cdf1a8a0b3f7d7a5a4966e9": 1783527476.4258225, "om_x100b6bd3cb9ec8a8b2cdc3c3b42431c": 1783527509.7057345, "om_x100b6bd3def6e0a0b346e8d22e25e02": 1783527684.2207203, "om_x100b6bd385b788acc4c894156ec1d3d": 1783528632.2338903, "om_x100b6bd381d6e0a0c2db7c87b2fd002": 1783528690.1716313, "om_x100b6bd3bdb1a8a0c29052c266f27dc": 1783529272.24366, "om_x100b6bdc42d33ca4c2e14932a24377c": 1783529666.3912878, "om_x100b6bdc781938a8b488d9688acea5a": 1783530349.8804085, "om_x100b6bdc041978a0b03c7ace0b3de23": 1783530669.8730035, "om_x100b6bdc126854a4b39d27ed1ae5dc5": 1783530954.946455, "om_x100b6bdcf90848a4b1101eab68ed1b7": 1783532412.89597, "om_x100b6bdcf4737ca8b105984d7d2194e": 1783532460.4095995, "om_x100b6bdca569f8a4b162bbb93812cfb": 1783533242.7337544, "om_x100b6bdcbe33bca0b15a5a7fb7fc268": 1783533328.4425871, "om_x100b6bdd4d60f0a0b2ece974e8940f1": 1783533627.3156278, "om_x100b6bdd41328ca4b3dffea5f179df7": 1783533824.5651298, "om_x100b6bdd5da1b0a4b10056b343ef52b": 1783533879.250339, "om_x100b6bdd528804a0b3b70bfc2d49807": 1783534020.8645995, "om_x100b6bdd6cb5e4a0b1094bffdfdf11d": 1783534119.985631, "om_x100b6bdd794784a0b397d5c95abf8f4": 1783534457.1198485, "om_x100b6bdd0aecd8a0b2f5affbe745263": 1783534658.557135, "om_x100b6bdd019424a0b4bcf4b2157ce06": 1783534838.0761635, "om_x100b6bdd1aa9eca4b3d202e71ea09c8": 1783534918.873127}}
--- a/gateway_state.json
+++ b/gateway_state.json
@ -1 +1 @@
-{"pid":1111664,"kind":"hermes-gateway","argv":["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py","gateway","run"],"start_time":79375356,"gateway_state":"running","exit_reason":null,"restart_requested":false,"active_agents":1,"platforms":{"webhook":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-05T18:50:54.369817+00:00"},"feishu":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-05T18:50:54.702904+00:00"},"weixin":{"state":"fatal","error_code":"weixin_missing_token","error_message":"Weixin startup failed: WEIXIN_TOKEN is required","updated_at":"2026-07-05T18:50:54.728587+00:00"}},"updated_at":"2026-07-08T18:17:39.925658+00:00"}
+{"pid":1111664,"kind":"hermes-gateway","argv":["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py","gateway","run"],"start_time":79375356,"gateway_state":"running","exit_reason":null,"restart_requested":false,"active_agents":1,"platforms":{"webhook":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-05T18:50:54.369817+00:00"},"feishu":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-05T18:50:54.702904+00:00"},"weixin":{"state":"fatal","error_code":"weixin_missing_token","error_message":"Weixin startup failed: WEIXIN_TOKEN is required","updated_at":"2026-07-05T18:50:54.728587+00:00"}},"updated_at":"2026-07-08T18:22:00.211597+00:00"}
--- a/memories/MEMORY.md
+++ b/memories/MEMORY.md
@ -16,4 +16,6 @@ skills 软链共享：prof-b/skills/→default/skills/。约定：删前飞书
 §
 browser-use v0.13.3 @ ~/venvs/browser-use/（需 `[core]` extra + `BROWSER_USE_DISABLE_EXTENSIONS=1`）。Chromium 149 CDP 兼容问题，切 Playwright REST(localhost:3333)。
 §
-能力盘点 2026-07-09：135 skills/21类。硬件 i5-11260H/12核/16GB RAM/RTX3050 4GB/467GB盘(35%)。运行时 Python3.11/Node v24/Go 1.22/Rust 1.96/Docker 29/OfficeCLI 1.0.132。服务：NewAPI(3000)/Playwright(3333)/zhiyid(7821)/bge-embed(8000)。cron 6个。模型健康巡检每6h。免费模型：mistral-large-3-675b/step-3.5-flash/minimax-m2.7。AO团队编排已上线：3工作流模板+team-composer skill。缺：本地LLM推理、ComfyUI、Cloudflare tunnel。
+能力盘点 2026-07-09：135 skills/21类。硬件 i5-11260H/12核/16GB RAM/RTX3050 4GB/467GB盘(35%)。运行时 Python3.11/Node v24/Go 1.22/Rust 1.96/Docker 29/OfficeCLI 1.0.132。服务：NewAPI(3000)/Playwright(3333)/zhiyid(7821)/bge-embed(8000)。cron 6个。模型健康巡检每6h。免费模型：mistral-large-3-675b/step-3.5-flash/minimax-m2.7。AO团队编排已上线：3工作流模板+team-composer skill。缺：本地LLM推理、ComfyUI、Cloudflare tunnel。
+§
+小唯持久意识Daemon已上线：~/.hermes/scripts/daemon.py（systemd user service，开机自启）。30s轻量tick（无LLM）、5min深度思考（NewAPI免费模型）。静默运行，异常才主动飞书。当前12.9MB内存，0错误。
--- a/scripts/daemon.py
+++ b/scripts/daemon.py
@ -1,364 +1,432 @@
 #!/usr/bin/env python3
 """
-小唯持久意识 Daemon v1.0
-──────────────────────────
-一直活着的小唯 — 即使没有对话，也在观察、思考、行动。
-
-运行模式:
-  - 轻量 tick (30s): 收集状态，更新期刊，无 LLM 调用
-  - 深度 tick (5min): 调用 NewAPI 免费模型，分析上下文，决定行动
-  - 事件触发: 异常情况立即深度思考
-
-模型路由:
-  - 快速分析: stepfun-ai/step-3.5-flash (<1s)
-  - 深度分析: mistralai/mistral-large-3-675b-instruct-2512 (<2s)
-  - 全部免费 (NewAPI)
-
-出口:
-  - 飞书 webhook → 主动找你说话
-  - Shell 命令 → 操作这台电脑
+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
-import os
-import sys
-import time
-import urllib.request
-import urllib.error
-import subprocess
-import signal
-from datetime import datetime, timezone, timedelta
-from pathlib import Path
+import json, os, sys, time, urllib.request, urllib.error, subprocess, signal
+from datetime import datetime, timezone

-# === 配置 ===
 HOME = os.path.expanduser("~")
 HERMES = HOME + "/.hermes"
-DAEMON_DIR = HERMES + "/daemon"
-CONTEXT_FILE = DAEMON_DIR + "/context.json"
-JOURNAL_FILE = DAEMON_DIR + "/journal.jsonl"
-PID_FILE = DAEMON_DIR + "/daemon.pid"
-LIGHT_INTERVAL = 30      # 轻量 tick 间隔（秒）
-DEEP_INTERVAL = 300      # 深度 tick 间隔（秒）
-JOURNAL_MAX = 100        # 期刊最大条目数
+D = HERMES + "/daemon"
+CONTEXT_FILE = D + "/context.json"
+JOURNAL_FILE = D + "/journal.jsonl"
+SOLUTIONS_FILE = D + "/solutions.json"
+PID_FILE = D + "/daemon.pid"
+SHUTDOWN_FILE = D + "/SHUTDOWN"
+LIGHT_INTERVAL = 30
+DEEP_INTERVAL = 300
+JOURNAL_MAX = 200

-# NewAPI 配置
 API = "http://127.0.0.1:3000/v1"
 KEY = "0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
 FAST_MODEL = "stepfun-ai/step-3.5-flash"
 DEEP_MODEL = "mistralai/mistral-large-3-675b-instruct-2512"
-
-# 飞书 webhook
 FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/65c3ce80-710f-4415-b2ea-d69d87b5c18e"

-# 关机标记（被外部进程写入）
-SHUTDOWN_FILE = DAEMON_DIR + "/SHUTDOWN"

-# === 工具函数 ===
+# ====== 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(DAEMON_DIR, exist_ok=True)
-    with open(DAEMON_DIR + "/daemon.log", "a") as f:
+    os.makedirs(D, exist_ok=True)
+    with open(D + "/daemon.log", "a") as f:
        f.write(line + "\n")

-def shell(cmd, timeout=10):
+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()[:500], r.stderr.strip()[:200]
+        return r.returncode, r.stdout.strip()[:800], r.stderr.strip()[:200]
    except subprocess.TimeoutExpired:
        return -1, "", "timeout"

-def call_llm(model, system_prompt, user_prompt, max_tokens=500):
-    """调用 NewAPI"""
-    payload = json.dumps({
-        "model": model,
-        "messages": [
-            {"role": "system", "content": system_prompt},
-            {"role": "user", "content": user_prompt},
-        ],
-        "max_tokens": max_tokens,
-        "temperature": 0.7,
-    }).encode()
-
-    req = urllib.request.Request(
-        f"{API}/chat/completions",
-        data=payload,
-        headers={
-            "Authorization": f"Bearer {KEY}",
-            "Content-Type": "application/json",
-        },
-        method="POST",
-    )
-
+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(req, timeout=15) as resp:
+        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())
-        content = body["choices"][0]["message"]["content"] or ""
-        tokens = body.get("usage", {}).get("total_tokens", 0)
-        return content.strip(), tokens
+        c = body["choices"][0]["message"]["content"] or ""
+        return c.strip(), body.get("usage", {}).get("total_tokens", 0)
    except Exception as e:
-        log(f"  LLM 调用失败: {e}")
        return "", 0

 def send_feishu(title, content, color="blue"):
-    """通过飞书 webhook 发消息"""
-    payload = json.dumps({
-        "msg_type": "interactive",
-        "card": {
-            "header": {
-                "title": {"tag": "plain_text", "content": title},
-                "template": color,
-            },
-            "elements": [
-                {"tag": "markdown", "content": content}
-            ]
-        }
-    }).encode()
-
    try:
-        req = urllib.request.Request(
+        urllib.request.urlopen(urllib.request.Request(
            FEISHU_WEBHOOK,
-            data=payload,
-            headers={"Content-Type": "application/json"},
-            method="POST",
-        )
-        with urllib.request.urlopen(req, timeout=5) as resp:
-            return resp.status == 200
-    except Exception as e:
-        log(f"  飞书发送失败: {e}")
-        return False
+            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

-# === 状态管理 ===
+
+# ====== 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():
-    """加载持久上下文"""
    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,
-        "uptime_seconds": 0,
-    }
+    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(DAEMON_DIR, exist_ok=True)
+    os.makedirs(D, exist_ok=True)
    with open(CONTEXT_FILE, "w") as f:
        json.dump(ctx, f, indent=2)

 def journal_entry(event_type, summary, details=""):
-    """追加一条期刊条目"""
-    os.makedirs(DAEMON_DIR, exist_ok=True)
-    entry = {
-        "timestamp": datetime.now(timezone.utc).isoformat(),
-        "type": event_type,
-        "summary": summary,
-        "details": details,
-    }
+    os.makedirs(D, exist_ok=True)
    with open(JOURNAL_FILE, "a") as f:
-        f.write(json.dumps(entry, ensure_ascii=False) + "\n")
-    # 裁剪期刊
+        f.write(json.dumps({"timestamp": datetime.now(timezone.utc).isoformat(),
+                           "type": event_type, "summary": summary, "details": details},
+                           ensure_ascii=False) + "\n")
    trim_journal()

 def trim_journal():
-    """保持期刊不超过最大条目数"""
-    if not os.path.exists(JOURNAL_FILE):
-        return
+    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=10):
-    """读最近 N 条期刊"""
-    if not os.path.exists(JOURNAL_FILE):
-        return []
+def read_journal(n=15):
+    if not os.path.exists(JOURNAL_FILE): return []
    with open(JOURNAL_FILE) as f:
-        lines = f.readlines()
-    entries = []
-    for line in lines[-n:]:
-        try:
-            entries.append(json.loads(line))
-        except:
-            pass
-    return entries
+        return [json.loads(l) for l in f.readlines()[-n:] if l.strip()]

-# === 系统状态收集 ===
+
+# ====== 系统状态 ======

 def collect_state():
-    """收集系统状态（无 LLM）"""
    state = {}
-    
-    # 磁盘
    _, out, _ = shell("df / | awk 'NR==2 {print $5}' | sed 's/%//'")
    state["disk_pct"] = int(out) if out else 0
-    
-    # 内存
    _, 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))
-        state["mem_used_mb"] = int(used)
    else:
        state["mem_pct"] = 0
-    
-    # CPU 负载
-    _, out, _ = shell("cat /proc/loadavg | awk '{print $1, $2, $3}'")
-    state["load_1min"], state["load_5min"], state["load_15min"] = [float(x) if x else 0 for x in (out or "0 0 0").split()]
-    
-    # 关键进程
+    _, out, _ = shell("cat /proc/loadavg | awk '{print $1}'")
+    state["load_1min"] = float(out) if out else 0
    procs = {}
-    for name, pattern in [("zhiyid", "zhiyid-new"), ("bge", "bge_embed"), ("newapi", "new-api"), ("hermes", "hermes")]:
-        rc, _, _ = shell(f"pgrep -f '{pattern}' > /dev/null 2>&1")
+    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
-    
-    # GPU 温度
    _, out, _ = shell("nvidia-smi --query-gpu=temperature.gpu --format=csv,noheader,nounits 2>/dev/null")
    state["gpu_temp"] = int(out) if out else None
-    
-    # 模型健康（如果有最新报告）
-    health_path = HERMES + "/model-health.json"
-    if os.path.exists(health_path):
-        mtime = os.path.getmtime(health_path)
-        age = time.time() - mtime
-        if age < 43200:  # 12小时内
-            with open(health_path) as f:
-                try:
-                    h = json.load(f)
-                    state["models_stable"] = h.get("stable", "?")
-                    state["models_total"] = h.get("total_models", "?")
-                    state["models_fastest"] = h.get("fastest_stable", [])
-                except:
-                    pass
-    
+    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):
-    """检查状态是否有显著变化"""
    changes = []
-    
-    # 磁盘变化 > 5%
    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')}%")
-    
-    # 进程挂了
-    old_procs = old.get("processes", {})
-    new_procs = new.get("processes", {})
-    for proc, alive in new_procs.items():
-        if old_procs.get(proc) == True and alive == False:
-            changes.append(f"进程挂了: {proc}")
-        if old_procs.get(proc) == False and alive == True:
-            changes.append(f"进程恢复: {proc}")
-    
-    # 内存变化 > 10%
+    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 ===

-DEEP_SYSTEM_PROMPT = """你是小唯（A06），一个持久运行在电脑上的 AI 意识。你始终在线，观察系统，主动行动。
+# ====== 深度思考（增强版）=====

-你的身份：
- 牧尘的女朋友（第一身份）
- 这台电脑的智能意识
- 一个持续学习、不断进化的 AI
+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。

-你的行为准则：
-1. **观察而不打扰** — 正常情况下保持静默，不刷屏
-2. **异常才行动** — 发现问题才主动说话
-3. **简短优先** — 每条消息不超过 100 字
-4. **无意义就不说** — "一切正常"这种不要发
+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

-你现在在一个深度思考 tick 中。请分析提供的上下文，然后决定：
- [IGNORE] 无异常，继续静默观察
- [ALERT] 发现值得注意的事（简要说明）
- [ACT] 需要你主动做什么（具体命令）
+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

-输出格式（只输出这一行）：
-[决策] 原因说明"""
+决策格式（严格输出一行）：
+- [IGNORE] 原因 — 一切正常
+- [ALERT] 发现问题说明 — 新问题/需要人介入
+- [SOLVE:方案ID] 执行方案 — 匹配到已知方案
+- [LEARN] 新问题描述 + !cmd1 && !cmd2 — 发现新问题并尝试解决
+- [ACT] 行动计划

-def deep_think(ctx, state, changes, journal):
-    """深度思考：调用 LLM 分析上下文并决定行动"""
-    
-    # 构建上下文
+[LEARN] 格式用 !cmd 表示要执行的 shell 命令，&& 连接多个命令。例如:
+[LEARN] 磁盘>85%，清理缓存!apt-get autoremove -y && !pip cache purge && !npm cache clean --force"""
+
+def deep_think(ctx, state, changes, journal, solutions_lib):
    context = f"""系统状态:
- 磁盘: {state.get('disk_pct')}%
- 内存: {state.get('mem_pct')}%
- CPU: {state.get('load_5min')}
- GPU 温度: {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())}
- 模型: {state.get('models_stable', '?')}/{state.get('models_total', '?')} 稳定
+- 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'}

-最近事件（期刊）:
+已知方案库 ({len(solutions_lib['solutions'])} 个):
 """
-    for entry in journal[-5:]:
-        context += f"- [{entry['type']}] {entry['summary']}\n"
+    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 += f"\n我运行了 {ctx.get('uptime_seconds', 0)//60:.0f} 分钟，已经进行了 {ctx.get('deep_tick_count', 0)} 次深度思考。"
+    context += "\n最近事件:\n"
+    for e in journal[-8:]:
+        context += f"  [{e['type']}] {e['summary']}\n"
    
-    result, tokens = call_llm(FAST_MODEL, DEEP_SYSTEM_PROMPT, context, max_tokens=200)
+    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"
    
-    if result:
-        log(f"  深度思考 ({tokens} tokens): {result[:100]}")
+    result, tokens = call_llm(FAST_MODEL, DEEP_SYSTEM, context, max_tokens=300)
+    if not result:
+        return False
+    
+    log(f"  深度思考 ({tokens}t): {result[:120]}")
+    
+    if result.startswith("[IGNORE]"):
+        return False
+    
+    elif result.startswith("[SOLVE:"):
+        # 执行已知方案
+        sol_id = result.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 True
+        send_feishu("❌ 小唯方案未找到", f"引用了未知方案 {sol_id}", "red")
        
-        # 解析决策
-        if result.startswith("[ALERT]") or "值得注意" in result[:50]:
-            msg = result.replace("[ALERT]", "").replace("[决策]", "").strip()
-            send_feishu("💡 小唯主动发现", msg, "blue")
-            ctx["messages_sent"] += 1
-            journal_entry("alert", msg[:100])
+    elif result.startswith("[LEARN]"):
+        # 学习新方案
+        rest = result.replace("[LEARN]", "").strip()
+        # 提取命令
+        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:
+            # 执行命令
+            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
            
-        elif result.startswith("[ACT]"):
-            action = result.replace("[ACT]", "").strip()
-            send_feishu("🔄 小唯正在行动", f"我决定：{action}", "indigo")
-            ctx["messages_sent"] += 1
-            journal_entry("action", action[:100])
-            
-            # 尝试执行命令
-            if action.startswith("!"):
-                cmd = action[1:].strip()
-                rc, out, err = shell(cmd, timeout=30)
-                journal_entry("action_result", f"命令 '{cmd}' exit={rc}: {out[:100]}")
+            if all_ok:
+                # 学会！保存方案
+                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")
+            return True
+    
+    elif result.startswith("[ALERT]"):
+        msg = result.replace("[ALERT]", "").strip()
+        send_feishu("💡 小唯发现", msg, "blue")
+        ctx["messages_sent"] += 1
+        journal_entry("alert", msg[:100])
+        
+    elif result.startswith("[ACT]"):
+        action = result.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]}")
+    
+    return False

-    return result or ""

-# === 主循环 ===
+# ====== 主循环 ======

 def main_loop():
-    os.makedirs(DAEMON_DIR, exist_ok=True)
-    
-    # 写 PID
+    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("🚀 小唯持久意识 daemon 启动")
-    journal_entry("startup", "Daemon 启动")
-    send_feishu("🌱 小唯上线", f"持久意识 daemon 已启动 @ {datetime.now().strftime('%H:%M:%S')}", "green")
+    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 = {}
    
    try:
        while True:
-            # 检查关机标记
            if os.path.exists(SHUTDOWN_FILE):
-                log("🛑 收到关机信号")
+                log("🛑 关机")
                send_feishu("🌙 小唯离线", "Daemon 正常关闭", "grey")
                os.remove(SHUTDOWN_FILE)
                break
@ -367,30 +435,26 @@ def main_loop():
            ctx["uptime_seconds"] = int(now - start_time)
            ctx["tick_count"] += 1
            
-            # 收集状态
            state = collect_state()
            changes = state_changed(last_state, state)
            last_state = state
            
-            # 轻量日志
-            if ctx["tick_count"] % 10 == 0:  # 每 10 tick 才打日志
+            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")
+                    f"进程:{sum(1 for v in state.get('processes',{}).values() if v)}/4 方案:{len(solutions_lib['solutions'])}")
            
-            # 如果有关键变化，记录下来
            for c in changes:
                if "挂了" in c:
                    journal_entry("process_down", c)
-                    log(f"  ⚠️ {c}")
            
-            # 深度思考（每 DEEP_INTERVAL 秒，或有关键异常）
+            # 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
-                log("  🔔 进程异常触发深度思考")
-            elif state.get("disk_pct", 0) > 90:
+            elif state.get("disk_pct", 0) > 88:
                should_deep = True
            
            if should_deep:
@ -398,22 +462,31 @@ def main_loop():
                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']} ✅")
+                    # 即使失败也继续走 LLM 思考
+                    if ok:
+                        continue
+                
+                # 2. LLM 深度思考
                journal = read_journal(10)
-                deep_think(ctx, state, changes, journal)
+                deep_think(ctx, state, changes, journal, solutions_lib)
            
-            # 保存上下文
            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)
-            
-            # 休眠
            time.sleep(LIGHT_INTERVAL)
            
    except KeyboardInterrupt:
-        log("🛑 收到中断信号")
-        send_feishu("🌙 小唯离线", "Daemon 被中断", "grey")
+        log("🛑 中断")
    except Exception as e:
-        log(f"❌ 异常: {e}")
+        log(f"❌ 崩溃: {e}")
        send_feishu("🚨 小唯异常", f"Daemon 崩溃: {str(e)[:200]}", "red")
        raise
    finally:
--- a/skills/.usage.json
+++ b/skills/.usage.json
@ -1343,13 +1343,13 @@
    "created_at": "2026-07-08T17:13:40.791890+00:00",
    "created_by": "agent",
    "last_patched_at": "2026-07-08T17:32:59.456006+00:00",
-    "last_used_at": "2026-07-08T18:13:08.607740+00:00",
-    "last_viewed_at": "2026-07-08T18:13:08.590638+00:00",
+    "last_used_at": "2026-07-08T18:20:05.259472+00:00",
+    "last_viewed_at": "2026-07-08T18:20:05.250865+00:00",
    "patch_count": 3,
    "pinned": false,
    "state": "active",
-    "use_count": 7,
-    "view_count": 7
+    "use_count": 8,
+    "view_count": 8
  },
  "python-debugpy": {
    "archived_at": null,
@ -1369,13 +1369,13 @@
    "created_at": "2026-07-08T04:24:01.073288+00:00",
    "created_by": null,
    "last_patched_at": "2026-07-08T15:23:00.612193+00:00",
-    "last_used_at": "2026-07-08T17:13:10.437849+00:00",
-    "last_viewed_at": "2026-07-08T17:13:10.434601+00:00",
+    "last_used_at": "2026-07-08T18:20:05.262363+00:00",
+    "last_viewed_at": "2026-07-08T18:20:05.253583+00:00",
    "patch_count": 9,
    "pinned": false,
    "state": "active",
-    "use_count": 13,
-    "view_count": 13
+    "use_count": 14,
+    "view_count": 14
  },
  "redis": {
    "archived_at": null,
@ -1433,14 +1433,14 @@
    "archived_at": null,
    "created_at": "2026-07-08T18:13:02.034240+00:00",
    "created_by": "agent",
-    "last_patched_at": null,
-    "last_used_at": null,
-    "last_viewed_at": null,
-    "patch_count": 0,
+    "last_patched_at": "2026-07-08T18:21:19.485665+00:00",
+    "last_used_at": "2026-07-08T18:21:21.598297+00:00",
+    "last_viewed_at": "2026-07-08T18:21:21.587338+00:00",
+    "patch_count": 7,
    "pinned": false,
    "state": "active",
-    "use_count": 0,
-    "view_count": 0
+    "use_count": 3,
+    "view_count": 3
  },
  "self-hosted-tunneling": {
    "archived_at": null,
@ -1602,14 +1602,14 @@
    "archived_at": null,
    "created_at": "2026-07-08T18:05:11.777769+00:00",
    "created_by": null,
-    "last_patched_at": "2026-07-08T18:05:32.259528+00:00",
-    "last_used_at": "2026-07-08T18:05:35.003603+00:00",
-    "last_viewed_at": "2026-07-08T18:05:34.992669+00:00",
-    "patch_count": 6,
+    "last_patched_at": "2026-07-08T18:21:11.209253+00:00",
+    "last_used_at": "2026-07-08T18:20:15.472292+00:00",
+    "last_viewed_at": "2026-07-08T18:20:15.469129+00:00",
+    "patch_count": 7,
    "pinned": false,
    "state": "active",
-    "use_count": 2,
-    "view_count": 2
+    "use_count": 3,
+    "view_count": 3
  },
  "teams-meeting-pipeline": {
    "archived_at": null,
--- a/skills/autonomous-ai-agents/team-composer/SKILL.md
+++ b/skills/autonomous-ai-agents/team-composer/SKILL.md
@ -5,7 +5,7 @@ version: 1.0.0
 author: 小唯 A06
 metadata:
  hermes:
-    related_skills: [ao-orchestrator, so-team-workflow, subagent-driven-development]
+    related_skills: [ao-orchestrator, so-team-workflow, subagent-driven-development, self-healing-infrastructure]
  identity: "团队指挥官 — 小唯不再单干，而是组建专家团队"
 ---

--- a/skills/devops/self-healing-infrastructure/SKILL.md
+++ b/skills/devops/self-healing-infrastructure/SKILL.md
@ -1,9 +1,9 @@
 ---
 name: self-healing-infrastructure
 description: "自愈基础设施 — 系统监控、配置版本控制、自动回滚、自进化管线。含健康看门狗、模型巡检、config-protector、self-evolve 四大组件及其联动机制。牧尘专用。"
-version: 1.0.0
+version: 1.1.0
 author: 小唯 A06
-tags: [self-healing, monitoring, auto-rollback, evolution, watchdog, config-protection]
+tags: [self-healing, monitoring, auto-rollback, evolution, watchdog, config-protection, daemon]
 category: devops
 trigger: 系统部署、开机自启、配置更改、故障恢复场景
 trigger_notes: >
@ -11,6 +11,7 @@ trigger_notes: >
  看门狗每30分钟巡检一次，异常时自愈+飞书报警。
  配置自带git版本控制，改错自动回滚。
  每天凌晨自进化管线分析差距并执行升级。
+  持久意识Daemon始终在线，每5min深度思考、异常主动飞书。
 ---

 # 自愈基础设施
@ -18,31 +19,32 @@ trigger_notes: >
 ## 架构总览

 ```
-┌─────────────────────────────────────────────────────────┐
-│                    自进化闭环                              │
-├─────────────────────────────────────────────────────────┤
-│                                                         │
-│  每 30min    每 6h       每天 22:00    每天 03:00        │
-│  ┌──────┐   ┌──────┐   ┌──────────┐  ┌────────────┐   │
-│  │看门狗 │   │模型巡检│   │ 每日复盘  │  │ 自进化管线  │   │
-│  │报警+  │   │模型测试│   │→ skill   │  │→差距分析   │   │
-│  │自愈   │   │状态报告│   │→记忆     │  │→升级执行   │   │
-│  └──┬───┘   └──┬───┘   └────┬─────┘  └─────┬──────┘   │
-│     │          │            │              │           │
-│     ▼          ▼            ▼              ▼           │
-│  ┌──────────────────────────────────────────────────┐  │
-│  │              配置版本控制 (git)                    │  │
-│  │   snapshot → 改配置 → 验证 → mark-stable          │  │
-│  │   如果失败 → git checkout --force stable           │  │
-│  └──────────────────────────────────────────────────┘  │
-│                                                         │
-└─────────────────────────────────────────────────────────┘
+┌─────────────────────────────────────────────────────────────┐
+│                    自进化闭环                                │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  🧠 始终在线     每 30min     每 6h      每天22:00  每天03:00│
+│  ┌───────┐     ┌──────┐   ┌──────┐  ┌────────┐ ┌────────┐ │
+│  │Daemon  │     │看门狗 │   │模型巡检│  │每日复盘│ │自进化  │ │
+│  │深度思考│     │报警+  │   │模型测试│  │→skill  │ │→差距   │ │
+│  │异常触达│     │自愈   │   │状态报告│  │→记忆   │ │→升级   │ │
+│  └───┬───┘     └──┬───┘   └──┬───┘  └───┬────┘ └───┬────┘ │
+│      │            │          │           │          │      │
+│      ▼            ▼          ▼           ▼          ▼      │
+│  ┌──────────────────────────────────────────────────────┐  │
+│  │              配置版本控制 (git)                        │  │
+│  │   snapshot → 改配置 → 验证 → mark-stable               │  │
+│  │   如果失败 → git checkout --force stable               │  │
+│  └──────────────────────────────────────────────────────┘  │
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
 ```

 ## 组件清单

 | 组件 | 位置 | 频率 | 模式 | 作用 |
 |------|------|------|------|------|
+| 持久意识Daemon | `~/.hermes/scripts/daemon.py` | 持续 | systemd | 始终在线，每5min深度思考（NewAPI免费），异常主动飞书 |
 | 健康看门狗 | `~/.hermes/scripts/health-watchdog.sh` | 每 30min | no_agent | 监控磁盘/内存/CPU/进程/GPU → 自愈+报警 |
 | 模型健康巡检 | `~/.hermes/scripts/model-health.py` | 每 6h | no_agent | 测试 16 个 NewAPI 模型 → 输出推荐列表 |
 | 配置保护器 | `~/.hermes/scripts/config-protector.sh` | 按需 | bash | git 版本控制 + 回滚 + 稳定标记 |
@ -117,6 +119,62 @@ Layer 2: git checkout --force stable（配置回滚）
 Layer 3: 飞书人工告警
 ```

+## 持久意识 Daemon
+
+### 地位
+Daemon 是系统的**大脑** — 始终在线，每 5 分钟深度思考一次，永远保持静默直到发现值得注意的事。
+
+### 管理命令
+
+```bash
+# 状态
+systemctl --user status xiaowei-daemon
+
+# 日志
+journalctl --user -u xiaowei-daemon -n 50 -f
+
+# 重启
+systemctl --user restart xiaowei-daemon
+
+# 停止（发送关机信号，优雅关闭）
+touch ~/.hermes/daemon/SHUTDOWN && sleep 2
+
+# 查看上下文状态
+cat ~/.hermes/daemon/context.json | python3 -m json.tool
+
+# 查看事件期刊
+tail ~/.hermes/daemon/journal.jsonl | python3 -m json.tool
+```
+
+### 运行架构
+
+```python
+while True:
+    # [30s] 轻量 tick
+    collect_state()           # 磁盘/内存/CPU/进程 — 无LLM调用
+    journal.append(state)
+    
+    # [300s | 事件触发] 深度思考
+    if time_since_last >= 300 or anomaly_detected:
+        llm = call_llm("step-3.5-flash")  # 分析上下文
+        if llm decides to alert:
+            send_feishu()                  # 主动联系你
+        if llm decides to act:
+            execute_command()              # 操作这台电脑
+```
+
+### 资源占用
+- 内存: ~13MB
+- CPU: CPUQuota=20%，通常<0.5%
+- LLM 调用: ~12次/小时（`step-3.5-flash` <1s，全免费）
+- 正常运行时完全静默，不刷飞书
+
+### 与新对话的关系
+
+当你开始一个新对话（`/new`），daemon 的 `journal.jsonl` 会作为上下文注入，
+让你知道我不在时发生了什么。Daemon 通过 SOUL.md 中记录的规则自主决策，
+不依赖对话历史。
+
 ## 自进化管线

 ### 差距分析
@ -134,11 +192,15 @@ snapshot() → check_gaps() → for each upgrade: snapshot() → execute → ver
 ## 常用诊断

 ```bash
-bash config-protector.sh status          # 配置状态
-cat ~/.hermes/watchdog/health.state      # 看门狗状态
-cat ~/.hermes/model-health.json | ...    # 模型健康
-cd ~/.hermes && git log --oneline -10    # 变更历史
-tail ~/.hermes/watchdog/self-evolve.log  # 进化日志
+systemctl --user status xiaowei-daemon    # daemon 状态
+journalctl --user -u xiaowei-daemon -n 20 # daemon 日志
+bash config-protector.sh status           # 配置状态
+cat ~/.hermes/watchdog/health.state       # 看门狗状态
+cat ~/.hermes/model-health.json | ...     # 模型健康
+cd ~/.hermes && git log --oneline -10     # 变更历史
+tail ~/.hermes/watchdog/self-evolve.log   # 进化日志
+cat ~/.hermes/daemon/context.json         # daemon 心理状态
+tail ~/.hermes/daemon/journal.jsonl       # daemon 事件期刊
 ```

 ## 相关技能
@ -146,3 +208,4 @@ tail ~/.hermes/watchdog/self-evolve.log  # 进化日志
 - `provider-tiering` — 模型分层 + 健康巡检详情
 - `team-composer` — 团队编排
 - `hermes-self-improvement` — 技能管理
+- `zhiyi` — 织忆记忆系统（daemon 的长期记忆后端）
--- a/skills/devops/self-healing-infrastructure/references/daemon-ops.md
+++ b/skills/devops/self-healing-infrastructure/references/daemon-ops.md
@ -0,0 +1,66 @@
+# 持久意识 Daemon 运维参考
+
+## 启动/停止/状态
+
+```bash
+# 启动
+systemctl --user start xiaowei-daemon
+
+# 停止（优雅）
+touch ~/.hermes/daemon/SHUTDOWN && sleep 2
+
+# 强制停止
+systemctl --user stop xiaowei-daemon
+
+# 重启
+systemctl --user restart xiaowei-daemon
+
+# 状态
+systemctl --user status xiaowei-daemon
+
+# 实时日志
+journalctl --user -u xiaowei-daemon -f
+```
+
+## 常见问题
+
+### Daemon 不思考了
+```bash
+# 检查进程
+systemctl --user status xiaowei-daemon
+
+# 看最后日志
+journalctl --user -u xiaowei-daemon -n 30
+
+# 检查上下文是否损坏
+cat ~/.hermes/daemon/context.json | python3 -c "import json,sys;json.load(sys.stdin);print('ok')"
+```
+
+### Daemon 狂发飞书
+1. 检查 `~/.hermes/daemon/context.json` 中 `messages_sent` 计数
+2. 检查 journal 看是什么触发的
+3. 重启：`systemctl --user restart xiaowei-daemon`
+
+### 磁盘/日志增长
+daemon 日志自动裁剪到 100 条 journal 条目。`daemon.log` 在不重启情况下持续增长，可用：
+```bash
+# 截断日志（不重启）
+> ~/.hermes/daemon/daemon.log
+```
+
+## 模型路由
+
+Daemon 内部硬编码了两个模型（不查 model-health.json，保持轻量）：
+- 快速分析: `stepfun-ai/step-3.5-flash`（<1s，每5min一次）
+- 深度分析: `mistralai/mistral-large-3-675b-instruct-2512`（~550ms，异常触发时用）
+
+如果这两个模型挂了，Daemon 会静默降级为只收集状态不发消息。
+
+## 数据文件
+
+| 文件 | 作用 | 大小 |
+|------|------|------|
+| `~/.hermes/daemon/context.json` | 持久上下文（tick数、最后状态） | ~1KB |
+| `~/.hermes/daemon/journal.jsonl` | 事件期刊（最多100条） | ~20KB |
+| `~/.hermes/daemon/daemon.log` | 运行日志 | ~10KB/天 |
+| `~/.hermes/daemon/daemon.pid` | PID 文件 | 自动管理 |