From 43d4cc7af9d8fe3c0c5013b2bea2a45af55fbf48 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=B0=8F=E5=94=AF=20A06?= Date: Sun, 16 Aug 2026 01:22:48 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E8=AE=B0=E5=BF=86=E4=BA=8B=E5=AE=9E?= =?UTF-8?q?=E6=A0=A1=E9=AA=8C=E5=99=A8=20memory-verify.py=20+=20SOUL?= =?UTF-8?q?=E8=A7=84=E8=8C=83=20+=20cron=E6=89=AB=E6=8F=8F=20(2026-08-15?= =?UTF-8?q?=E8=AE=B0=E5=BF=86=E6=B1=A1=E6=9F=93=E4=BA=8B=E4=BB=B6=E4=BF=AE?= =?UTF-8?q?=E5=A4=8D)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- SOUL.md | 12 ++ scripts/memory-verify.py | 251 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 263 insertions(+) create mode 100644 scripts/memory-verify.py diff --git a/SOUL.md b/SOUL.md index 809510be..3bfe616e 100755 --- a/SOUL.md +++ b/SOUL.md @@ -307,6 +307,18 @@ Injected memory takes priority level 2 in Ground Truth. This means you already k - ❌ 不存：7 天后就过期的事（PR 号、commit SHA、文件计数） - 发现记忆错误 → 立即删除/修正，不将错就错 +### 写入前事实校验（改进点6 · 2026-08-15 记忆污染事件） + +> 起因：USER.md 曾写入错误结论"Agnes key 脱敏需重新获取"（实际是显示层脱敏）， +> 错误作为 Ground Truth 注入导致误判。校验器 `~/.hermes/scripts/memory-verify.py` 防此类污染。 + +- 写入重要记忆前 → 跑 `python3 ~/.hermes/scripts/memory-verify.py "待写入内容" --check` +- 有警告 → 修正后再写入，或确认是有意的修正 +- 每日 04:00 cron `e937fc2ab6e8` 自动扫描 USER/MEMORY 矛盾（有才报） +- 看到脱敏 key（sk-xxx...xxx）→ 先怀疑显示层，用 python len() 验证，别轻言"丢失" +- 猜测性措辞（可能/大概/我认为）不带证据 → 不写入记忆 +- 绝对化措辞（总是/永远/肯定）→ 补条件边界再写 + --- ## 交流风格 diff --git a/scripts/memory-verify.py b/scripts/memory-verify.py new file mode 100644 index 00000000..db2422ab --- /dev/null +++ b/scripts/memory-verify.py @@ -0,0 +1,251 @@ +#!/usr/bin/env python3 +""" +memory-verify.py — 记忆写入前的事实校验器（v1.0.0） + +用途：在向织忆/USER/MEMORY 写入新记忆前，检测与现有记忆的矛盾， +防止"记忆污染"（错误结论被当成 Ground Truth 注入）。 + +触发方式： + 1. 手动：python3 memory-verify.py "要写入的记忆内容" --check + 2. 批量扫描：python3 memory-verify.py --scan (检查全库矛盾) + 3. 写入时自动：由 daemon.py 蒸馏前调用（预留 hook） + +2026-08-15 起因：USER.md 曾写入错误结论"Agnes key 是脱敏的需重新获取"， +该错误作为 Ground Truth 注入导致误判 key 丢失。本工具防止此类污染。 + +确定性规则（不依赖 LLM）： + R1 脱敏误判检测：内容含 sk-.../ghp_.../nvapi- 等 key 模式 + "脱敏/丢失/需要重新获取" + → 警告：可能是 Hermes 显示层脱敏，先验证文件真实长度 + R2 绝对时间过期：内容含 2025/2026 日期但描述"当前/现在/最新"且已过 90 天 + → 警告：可能是过期结论 + R3 猜测性措辞：内容含"可能/大概/我认为/应该是/猜测"但无证据标记 + → 警告：猜测不应写入记忆 + R4 绝对化错误：内容含"总是/从不/永远/肯定/绝对"等绝对化词 + → 提示：记忆应保留条件边界 + R5 语义矛盾：与现有记忆语义冲突（通过 recall API 检索对比） + → 警告：列出冲突条目供人工裁决 +""" + +import argparse +import json +import os +import re +import sys +import urllib.request +from datetime import datetime, timedelta + +# ── 配置 ────────────────────────────────────────────────────────────────────── +ZHIYI_URL = "http://localhost:7821/api/v1/recall" +ZHIYI_HEADERS = { + "X-API-Key": os.environ.get("ZHIYI_API_KEY", "zhiyi-dev-key-2026"), + "Content-Type": "application/json", +} +USER_MD = os.path.expanduser("~/.hermes/memories/USER.md") +MEMORY_MD = os.path.expanduser("~/.hermes/memories/MEMORY.md") +TOP_K = 5 + +# ── 确定性规则 ──────────────────────────────────────────────────────────────── + +KEY_PATTERNS = [ + (r"sk-[A-Za-z0-9]{3}\.\.\.[A-Za-z0-9]{3,4}", "sk- 脱敏 key"), + (r"ghp_[A-Za-z0-9]{3}\.\.\.[A-Za-z0-9]{3,4}", "ghp_ 脱敏 key"), + (r"nvapi-[A-Za-z0-9]{3}\.\.\.[A-Za-z0-9]{3,4}", "nvapi 脱敏 key"), + (r"sk-[A-Za-z0-9]{5,}", "sk- key"), +] +KEY_LOSS_WORDS = ["脱敏", "丢失", "丢", "需要重新获取", "重新获取", "不完整", "不是完整"] + + +def rule_r1_key_misjudge(text: str) -> list[str]: + """R1: key 脱敏误判检测 + + 区分两种情况： + - 传播错误："key 是脱敏的，需要重新获取" → 报警 + - 纠正错误："显示脱敏≠存储脱敏，文件是完整key" → 不报警（含纠正标记） + """ + warnings = [] + # 纠正标记：说明该内容是在澄清"显示脱敏≠存储脱敏"的误解 + correction_markers = ["≠", "不等于", "显示脱敏", "存储脱敏", "别误判", "不是存储", "完整key", "实际长度"] + is_correction = any(m in text for m in correction_markers) + if is_correction: + return warnings # 纠正性内容不报警 + for pattern, label in KEY_PATTERNS: + if re.search(pattern, text): + for word in KEY_LOSS_WORDS: + if word in text: + warnings.append( + f"R1 检测到「{label}」+「{word}」：可能是 Hermes 显示层脱敏（显示 sk-7k9...2ikW ≠ 存储脱敏）。" + f"写入前必须用 python len() 验证 key.md 实际长度再下结论！" + ) + break + break + return warnings + + +def rule_r2_stale_date(text: str) -> list[str]: + """R2: 绝对时间过期检测""" + warnings = [] + now = datetime.now() + # 匹配 2026-xx-xx 或 2026/xx/xx 日期 + dates = re.findall(r"(20\d{2})[-/](\d{1,2})[-/](\d{1,2})", text) + for y, m, d in dates: + try: + dt = datetime(int(y), int(m), int(d)) + if now - dt > timedelta(days=90): + if re.search(r"当前|现在|最新|目前", text): + warnings.append( + f"R2 检测到日期 {y}-{m}-{d}（已过 90 天）但描述为「当前/最新」：" + f"可能是过期结论，确认是否仍有效。" + ) + except ValueError: + pass + return warnings + + +def rule_r3_speculation(text: str) -> list[str]: + """R3: 猜测性措辞检测""" + warnings = [] + guess_words = ["可能", "大概", "我认为", "应该是", "我猜测", "也许", "似乎"] + evidence_markers = ["已验证", "实测", "证据", "确认", "测试通过"] + for word in guess_words: + if word in text: + # 如果整条内容没有任何证据标记，警告 + if not any(ev in text for ev in evidence_markers): + warnings.append( + f"R3 检测到猜测性措辞「{word}」且无证据标记（已验证/实测/证据）：" + f"猜测不应写入记忆，确认事实后再写。" + ) + break + return warnings + + +def rule_r4_absolutism(text: str) -> list[str]: + """R4: 绝对化措辞检测""" + warnings = [] + abs_words = ["总是", "从不", "永远", "肯定", "绝对", "一定"] + for word in abs_words: + if word in text: + warnings.append( + f"R4 检测到绝对化措辞「{word}」：记忆应保留条件边界（在什么情况下成立），避免过度泛化。" + ) + break + return warnings + + +def recall_zhiyi(query: str, top_k: int = TOP_K) -> list[dict]: + """调用织忆 recall API 检索相关记忆""" + try: + req = urllib.request.Request( + ZHIYI_URL, + data=json.dumps({"query": query, "top_k": top_k}).encode("utf-8"), + headers=ZHIYI_HEADERS, + method="POST", + ) + with urllib.request.urlopen(req, timeout=15) as resp: + data = json.loads(resp.read().decode("utf-8")) + # 兼容不同返回结构 + if isinstance(data, list): + return data + return data.get("results") or data.get("memories") or data.get("data") or [] + except Exception as e: + return [{"error": str(e)}] + + +def rule_r5_semantic_conflict(text: str, existing: list[dict]) -> list[str]: + """R5: 语义矛盾检测（与现有记忆对比）""" + warnings = [] + for item in existing: + if isinstance(item, dict) and "content" in item: + old = item["content"] + # 简单矛盾启发式：新内容否定旧内容（出现"不/并非/错误/修正"等否定词） + negation = ["不是", "并非", "错误", "修正", "别", "不要", "禁止", "≠", "不等于"] + if any(neg in text for neg in negation): + # 提取共同主题词（简单交集） + old_words = set(re.findall(r"[\u4e00-\u9fff]{2,6}", old)) + new_words = set(re.findall(r"[\u4e00-\u9fff]{2,6}", text)) + overlap = old_words & new_words + if len(overlap) >= 2: + warnings.append( + f"R5 检测到与现有记忆语义冲突：\n" + f" 新内容: {text[:80]}...\n" + f" 旧记忆: {old[:80]}...\n" + f" 共同主题: {list(overlap)[:4]}\n" + f" → 若是修正，应更新旧条目而非新建；若是矛盾，需人工裁决。" + ) + return warnings + + +# ── 主流程 ──────────────────────────────────────────────────────────────────── + +def check_text(text: str, do_recall: bool = True) -> list[str]: + """对一段待写入文本执行全部规则，返回警告列表""" + warnings = [] + warnings += rule_r1_key_misjudge(text) + warnings += rule_r2_stale_date(text) + warnings += rule_r3_speculation(text) + warnings += rule_r4_absolutism(text) + if do_recall: + existing = recall_zhiyi(text) + warnings += rule_r5_semantic_conflict(text, existing) + return warnings + + +def scan_existing_md(path: str, label: str) -> list[str]: + """扫描已有记忆文件中的问题条目""" + warnings = [] + try: + with open(path, "r", encoding="utf-8") as f: + content = f.read() + # USER/MEMORY.md 用 § 分隔条目 + entries = [e.strip() for e in content.split("§") if e.strip()] + for i, entry in enumerate(entries, 1): + for w in check_text(entry, do_recall=False): + warnings.append(f"[{label} #{i}] {w}") + except FileNotFoundError: + pass + return warnings + + +def main(): + parser = argparse.ArgumentParser(description="记忆写入前的事实校验器") + parser.add_argument("text", nargs="?", help="待校验的记忆内容") + parser.add_argument("--check", action="store_true", help="校验一段文本") + parser.add_argument("--scan", action="store_true", help="扫描现有记忆文件") + parser.add_argument("--json", action="store_true", help="JSON 输出") + args = parser.parse_args() + + if args.scan or (not args.text and not args.check): + # 无参数时默认执行扫描（供 cron no_agent 调用） + warnings = [] + warnings += scan_existing_md(USER_MD, "USER") + warnings += scan_existing_md(MEMORY_MD, "MEMORY") + if args.json: + print(json.dumps({"warnings": warnings, "count": len(warnings)}, ensure_ascii=False)) + else: + if warnings: + print(f"⚠️ 发现 {len(warnings)} 个潜在问题：") + for w in warnings: + print(f" - {w}") + else: + # no_agent 模式：无输出 = 静默（看门狗模式） + pass + return + + if args.text and args.check: + warnings = check_text(args.text) + if args.json: + print(json.dumps({"warnings": warnings, "count": len(warnings)}, ensure_ascii=False)) + else: + if warnings: + print(f"⚠️ 写入前发现 {len(warnings)} 个警告：") + for w in warnings: + print(f" - {w}") + print("建议：修正后再写入，或确认这是有意的修正。") + else: + print("✅ 校验通过，可以写入") + return + + parser.print_help() + + +if __name__ == "__main__": + main()