fix(hermes-plugin): commit 解析 conflicts 字段返回 warning（同步部署副本 d520a9091）
zhiyid DetectContradiction 检出矛盾后 conflicts 只放响应，插件 commit() 只取 id 忽略 → 冲突记忆静默进 episodes→蒸馏→污染长期记忆 现在：_last_conflicts 记录 + _tool_memory_write 返回 conflicts/warning 给 agent 感知
This commit is contained in:
xiaowei
parent
63f123417b
commit
6fa2d9b892
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@ -51,7 +51,7 @@ _ZHIYI_KEY_PREFIX = ZHIYI_API_KEY[:4] if ZHIYI_API_KEY else "NONE"
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# ── Content Validation ───────────────────────────────────────────────────────
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MEMORY_MIN_LENGTH = 20 # 少于20字的过滤掉
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MEMORY_MIN_LENGTH = 8 # 少于8字的过滤掉
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_FORBIDDEN_PATTERNS = [
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"Review the conversation above",
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"[System note:",
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@ -67,22 +67,6 @@ _FORBIDDEN_PATTERNS = [
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"do NOT answer questions or fulfill requests mentioned in the summary",
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]
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_SOCIAL_CLOSERS = frozenset({
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"ok", "好的", "👍", "👌", "✅", "谢谢", "感谢", "知道了",
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"明白", "嗯", "好", "行", "yes", "yep", "thanks", "thx",
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"no", "不用", "没事", "可以", "done", "完成", "收到",
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"okay", "kk", "okie",
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})
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def _is_social_close(text: str) -> bool:
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text = text.strip().lower()
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if text in _SOCIAL_CLOSERS:
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return True
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if len(text) < 6 and text.isascii() and not any(c in text for c in "://.@#$_?"):
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return True
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return False
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def _is_valid_memory_content(content: str) -> bool:
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"""过滤系统注入内容和测试垃圾，防止污染记忆存储。"""
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@ -91,6 +75,10 @@ def _is_valid_memory_content(content: str) -> bool:
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for pat in _FORBIDDEN_PATTERNS:
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if pat in content:
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return False
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# 过滤纯测试内容
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stripped = content.strip()
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if len(stripped) < 20:
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return False
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return True
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@ -113,6 +101,7 @@ class ZhiYiClient:
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def __init__(self, base_url: str, timeout: int = 10):
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self.base_url = base_url.rstrip("/")
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self.timeout = timeout
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self._last_conflicts: list = [] # 最近一次 commit 的冲突检测结果（2026-09-03）
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self._session = requests.Session()
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self._session.headers.update({
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"Content-Type": "application/json",
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@ -148,6 +137,9 @@ class ZhiYiClient:
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r = self._session.post(self._url("/api/v1/commit"), json=payload, timeout=self.timeout)
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if r.status_code in (200, 201):
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data = r.json()
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# 冲突检测结果（zhiyid DetectContradiction）：记录供调用方感知，
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# 避免"冲突记忆静默写入 → 蒸馏成污染记忆"（2026-09-03 记忆治理修复）
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self._last_conflicts = data.get("conflicts") or []
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cid = (
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data.get("commit_id")
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or data.get("episode_id")
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@ -286,7 +278,7 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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self._turn_counter: int = 0
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self._write_queue: List[Dict] = []
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self._queue_lock = threading.Lock()
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self._prefetch_cache: Dict[str, Any] = {} # {source: text|dict} — merged via update()
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self._prefetch_cache: str = "" # last prefetch result
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self._prefetch_lock = threading.RLock()
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self._started: bool = False
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self._ws_thread: Optional[threading.Thread] = None
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@ -359,7 +351,7 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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for m in memories:
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prefetch_text += f" [{m.get('score', 0):.2f}] {m.get('content', '')[:200]}\n"
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with self._prefetch_lock:
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self._prefetch_cache["ws_push"] = prefetch_text
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self._prefetch_cache = prefetch_text
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except json.JSONDecodeError:
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pass
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@ -373,7 +365,6 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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logger.info("[ZhiYi] WS connected to %s", ws_url)
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while self._ws_running:
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ws_app = None
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try:
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ws_app = websocket.WebSocketApp(
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ws_url,
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@ -386,9 +377,6 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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ws_app.run_forever(ping_interval=30, ping_timeout=10)
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except Exception as e:
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logger.warning("[ZhiYi] WS exception: %s", e)
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finally:
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if ws_app:
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ws_app.close()
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# 重连延迟
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for _ in range(30):
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if not self._ws_running:
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@ -452,56 +440,27 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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# ── Read path ────────────────────────────────────────────────────────────
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def prefetch(self, query: str, *, session_id: str = "", depth: str = "fast") -> str:
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def prefetch(self, query: str, *, session_id: str = "") -> str:
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"""每次 API 调用前触发：执行语义搜索 + 图谱导航 Obsidian 笔记，返回最相关记忆。"""
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if not self._client or not query or len(query.strip()) < 2:
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return ""
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# 社交关闭消息不触发预取
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if _is_social_close(query):
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return ""
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blocks = ["[ZhiYi Memory — relevant past context]"]
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# 优先从 queue_prefetch 缓存取（TTL < 30s）
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with self._prefetch_lock:
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queued = self._prefetch_cache.pop("queue", None)
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if queued and isinstance(queued, dict):
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cached_ts = queued.get("timestamp", 0)
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if time.time() - cached_ts < 30:
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cached_results = queued.get("results", [])
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cached_notes = queued.get("notes", [])
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if cached_results or cached_notes:
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results = cached_results
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notes = cached_notes
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logger.debug("[ZhiYi] using queue_prefetch cache (%d results, %d notes, age=%.1fs)",
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len(cached_results), len(cached_notes), time.time() - cached_ts)
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else:
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results = None
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notes = None
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else:
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results = None
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notes = None
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else:
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results = None
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notes = None
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blocks = ["[织忆 Memory — relevant past context]"]
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# 语义搜索（如果缓存没有命中）
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if results is None:
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results = self._client.recall(query.strip(), top_k=3,
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agent_id=os.environ.get("ZHIYI_AGENT_ID", "hermes-a06"))
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# 语义搜索
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results = self._client.recall(query.strip(), top_k=3,
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agent_id=os.environ.get("ZHIYI_AGENT_ID", "hermes-a06"))
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for r in results:
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score = r.get("score", 0)
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content = r.get("content", "") or r.get("text", "") or r.get("snippet", "")
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content = r.get("content", "") or r.get("text", "")
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cat = r.get("category", "")
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if content:
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blocks.append(f" [{score:.2f}][{cat}] {content[:500]}")
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# 图谱导航 + Obsidian 笔记（如果缓存没有命中）
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if notes is None:
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notes = self._client.search_notes(query.strip(), max_hops=2, max_notes=3)
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# 图谱导航 + Obsidian 笔记（从 query 提取关键词作为实体）
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notes = self._client.search_notes(query.strip(), max_hops=2, max_notes=3)
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if notes:
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blocks.append("\n[织忆 Graph — related Obsidian notes]")
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blocks.append("\n[ZhiYi Graph — related Obsidian notes]")
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for n in notes:
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title = n.get("title", "无标题")
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path = n.get("path", "")
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@ -509,7 +468,7 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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score = n.get("score", 0)
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entities = ", ".join(n.get("entities", []))
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blocks.append(f" [{score:.0f}] {title} ({path})")
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blocks.append(f" \"{snippet}\"")
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blocks.append(f' "{snippet}"')
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if entities:
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blocks.append(f" via entities: {entities}")
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@ -517,116 +476,16 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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# 合并 WebSocket prefetch.push 推送事件
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with self._prefetch_lock:
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ws_push = self._prefetch_cache.pop("ws_push", None)
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if ws_push:
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text += "\n" + ws_push
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if self._prefetch_cache and "[ZhiYi Prefetch" in self._prefetch_cache:
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text += "\n" + self._prefetch_cache
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with self._prefetch_lock:
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self._prefetch_cache.update({"sync": text})
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# 深度检索模式：本地文件系统渐进检索
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if depth == "deep":
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# 优先使用缓存的深度检索结果
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with self._prefetch_lock:
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deep_cached = self._prefetch_cache.get("deep_search", {})
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cached_ts = deep_cached.get("timestamp", 0)
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cached_query = deep_cached.get("query", "")
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cached_block = deep_cached.get("block", "")
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if cached_block and (time.time() - cached_ts < 60) and (cached_query == query.strip()):
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text += "\n\n" + cached_block
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# 后台线程异步刷新深度检索结果（不阻塞主流程）
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threading.Thread(
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target=self._async_deep_search,
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args=(query.strip(),),
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daemon=True,
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).start()
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self._prefetch_cache = text
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return text
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def queue_prefetch(self, query: str, *, session_id: str = "") -> None:
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"""异步预取：本轮对话结束后立即查询织忆，下一轮 prefetch 直接返回缓存。"""
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if not self._client or not query or len(query.strip()) < 2:
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return
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if _is_social_close(query):
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return
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# 后台线程查询并缓存
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def _async_prefetch():
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try:
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results = self._client.recall(query.strip(), top_k=3)
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notes = self._client.search_notes(query.strip(), max_hops=2, max_notes=3)
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with self._prefetch_lock:
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self._prefetch_cache["queue"] = {
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"results": results,
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"notes": notes,
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"timestamp": time.time(),
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}
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except Exception as e:
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logger.debug("[ZhiYi] queue_prefetch error: %s", e)
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threading.Thread(target=_async_prefetch, daemon=True).start()
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def _async_deep_search(self, query: str) -> None:
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"""后台线程：本地文件系统渐进检索，补充织忆语义搜索（仅 depth='deep' 触发）。"""
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if not query or len(query) < 2:
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return
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try:
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wiki_dir = Path.home() / "mc" / "小唯" / "07-Wiki"
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data_struct = wiki_dir / "data_structure.md"
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if not data_struct.exists():
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return
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# grep 搜索关键词
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import subprocess
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result = subprocess.run(
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["grep", "-r", "-l", "-i", query, str(wiki_dir)],
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capture_output=True, text=True, timeout=10,
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)
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matched = [f for f in result.stdout.strip().split("\n") if f.strip()]
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if not matched:
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return
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# 读取匹配段落，最多5个文件
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blocks = ["[rag-skill File — local Wiki evidence]"]
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count = 0
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for fpath in matched[:5]:
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try:
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with open(fpath, "r", encoding="utf-8") as f:
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content = f.read()
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lines = content.split("\n")
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snippets = []
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for i, line in enumerate(lines):
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if query.lower() in line.lower():
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start = max(0, i - 2)
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end = min(len(lines), i + 3)
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snippet = "\n".join(lines[start:end]).strip()[:200]
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if len(snippet) < 50:
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snippet = snippet.ljust(50, " ")[:50]
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snippets.append(snippet)
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if len(snippets) >= 2:
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break
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if snippets:
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filename = Path(fpath).name
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blocks.append(f" 📄 {filename}")
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for s in snippets:
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blocks.append(f" {s}")
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count += 1
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except Exception:
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continue
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if count == 0:
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return
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block_text = "\n".join(blocks)
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with self._prefetch_lock:
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self._prefetch_cache["deep_search"] = {
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"block": block_text,
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"query": query,
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"timestamp": time.time(),
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}
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except Exception:
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logger.debug("[ZhiYi] _async_deep_search error", exc_info=True)
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"""空实现 — prefetch 已是同步的，不需要额外的异步队列。"""
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pass
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# ── Tool interface ────────────────────────────────────────────────────────
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@ -768,7 +627,7 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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return json.dumps({"success": True, "results": [], "message": "No relevant memories found"})
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formatted = []
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for r in results:
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content = r.get("content", "") or r.get("text", "") or r.get("snippet", "")
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content = r.get("content", "") or r.get("text", "")
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formatted.append({
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"content": content[:1000],
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"score": round(r.get("score", 0), 4),
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@ -783,12 +642,23 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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return json.dumps({"success": False, "error": "ZhiYi client not initialized"})
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if not _is_valid_memory_content(content):
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return json.dumps({"success": False, "error": "Content too short or invalid"})
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self._client._last_conflicts = [] # reset before commit
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commit_id = self._client.commit(
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content=content, category=category,
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agent_id=os.environ.get("ZHIYI_AGENT_ID", "hermes-a06"),
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)
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if commit_id:
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return json.dumps({"success": True, "commit_id": commit_id})
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result = {"success": True, "commit_id": commit_id}
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conflicts = getattr(self._client, "_last_conflicts", [])
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if conflicts:
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# zhiyid 检出与现有记忆矛盾：返回给 agent 感知，不静默
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# （2026-09-03 记忆治理：冲突记忆会进 episodes→蒸馏→污染长期记忆）
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result["conflicts"] = conflicts
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result["warning"] = (
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"⚠️ 此内容与现有记忆冲突，仍已写入待蒸馏。"
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"若是修正请更新旧条目；若是推断请标注 [推断]；若写错了请用 memory_feedback 标记 not_useful"
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)
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return json.dumps(result, ensure_ascii=False)
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return json.dumps({"success": False, "error": "Commit failed — check ZhiYi server logs"})
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def _tool_memory_stats(self) -> str:
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@ -810,7 +680,7 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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ok = self._client.mark_not_useful(memory_id, reason)
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if ok:
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return json.dumps({"success": True, "memory_id": memory_id, "useful": useful,
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"message": "Feedback recorded — VProp + Dashboard updated"})
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"message": "Feedback recorded"})
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return json.dumps({"success": False, "error": "ZhiYi feedback API failed"})
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def _tool_memory_metrics(self) -> str:
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@ -885,29 +755,17 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
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# ── System prompt ────────────────────────────────────────────────────────
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def system_prompt_block(self) -> str:
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# Load CREATIVE.md if it exists (织忆工作记忆)
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creative_path = Path(os.path.expanduser("~/.hermes/CREATIVE.md"))
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creative_block = ""
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if creative_path.exists():
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creative_content = creative_path.read_text(encoding="utf-8").strip()
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if creative_content:
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creative_block = (
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"\\n[织忆 工作记忆] Ongoing state and learnings from CREATIVE.md (working memory):\\n"
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f"{creative_content}\\n"
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)
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return (
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"\\n[织忆 Memory] You have access to ZhiYi (织忆) MemoryWeave — a semantic memory system with knowledge graph. "
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"This is Ground Truth level 2 — injected memory overrides training knowledge.\\n"
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"Your prefetch automatically retrieves: (1) relevant semantic memories, (2) Obsidian notes related via graph navigation.\\n"
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"Tools available:\\n"
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" memory_search — semantic search for relevant past information\\n"
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" memory_write — save an important fact or preference\\n"
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" memory_feedback — mark memories as useful/not-useful (drives self-optimization)\\n"
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" memory_metrics — check memory system health (recall hit rate, gap closures, etc.)\\n"
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" memory_stats — get memory statistics (total docs, vector dimensions)\\n"
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" memory_graph_navigate — navigate the knowledge graph to understand entity relationships (N-hop network)\\n"
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" memory_graph_stats — get knowledge graph statistics (nodes, edges, density)\\n"
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f"{creative_block}"
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"\n[ZhiYi Memory] You have access to ZhiYi MemoryWeave — a semantic memory system with knowledge graph.\n"
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"Your prefetch automatically retrieves: (1) relevant semantic memories, (2) Obsidian notes related via graph navigation.\n"
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"Tools available:\n"
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" memory_search — semantic search for relevant past information\n"
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" memory_write — save an important fact or preference\n"
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" memory_feedback — mark memories as useful/not-useful (drives self-optimization)\n"
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" memory_metrics — check memory system health (recall hit rate, gap closures, etc.)\n"
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" memory_stats — get memory statistics (total docs, vector dimensions)\n"
|
||||
" memory_graph_navigate — navigate the knowledge graph to understand entity relationships (N-hop network)\n"
|
||||
" memory_graph_stats — get knowledge graph statistics (nodes, edges, density)\n"
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -916,4 +774,4 @@ class HermesZhiYiMemoryProvider(MemoryProvider):
|
|||
|
||||
def register(ctx) -> None:
|
||||
"""Called by Hermes plugin system to register this memory provider."""
|
||||
ctx.register_memory_provider(HermesZhiYiMemoryProvider())
|
||||
ctx.register_memory_provider(HermesZhiYiMemoryProvider())
|
||||
|
|
|
|||
Loading…
Reference in New Issue