fix: save_llm_context 真正写入L1-L6数据 + 自检脚本v2字段修复
save_llm_context: - 重写为真正的v2格式（含L1-L6实时数据） - observations从graph_nodes实时读，patterns从pattern节点读 - TencentDB /recall写入scenes，L5 distilled_rules从user-profile读 - L6 traits从画像字段读 自检脚本memory-system-check.sh: - local语法错误修复（函数外不能用local） - 字段验证改为v2格式：observations/patterns/scenes/policies/distilled_rules - 输出格式：v2 L1=30 L2=50 L3=0 L4=0 L5=1
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小唯 A06
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@ -1385,12 +1385,110 @@ def detect_memory_conflicts(journal_path: str, zhiyi_token: str) -> list:
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return conflicts
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def save_llm_context(ctx, state):
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"""每 tick 写 llm_context.json（统一格式 v2）。
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"""每 tick 写 llm_context.json（v2 统一格式）。
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结构: user_profile, active_scenes, short_term(L1/L2/L3计数), cares, recent_moments,
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daemon_status, distill_status, uptime_minutes, updated_at.
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包含完整 L1-L6 蒸馏数据，从 graph_nodes / TencentDB / Soulful 实时读取，
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确保 MEMORY 区注入的是当前最新状态。
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"""
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# 收集 cares
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import sqlite3
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# ── daemon 健康状态 ──────────────────────────────────────────
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daemon_status = "running" if psutil.pid_exists(os.getpid()) else "stopped"
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# ── L1: 从 graph_nodes observations ──────────────────────────
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observations = []
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try:
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conn = sqlite3.connect(HERMES + "/graph.db")
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cur = conn.cursor()
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cur.execute("""
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SELECT name, namespace, properties FROM graph_nodes
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WHERE type IN ('entity','concept','topic')
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AND namespace NOT IN ('daemon-distill')
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ORDER BY last_updated_at DESC LIMIT 30
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""")
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for name, ns, props_json in cur.fetchall():
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props = json.loads(props_json) if props_json else {}
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observations.append({
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"name": name, "namespace": ns,
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"summary": props.get("description", "")[:100]
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})
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conn.close()
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except Exception:
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pass
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# ── L2: pattern 节点（来源1: namespace×type + 来源2: 会话话题） ──
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patterns = []
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try:
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conn = sqlite3.connect(HERMES + "/graph.db")
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cur = conn.cursor()
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cur.execute("""
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SELECT name, properties FROM graph_nodes
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WHERE type='pattern' ORDER BY last_updated_at DESC LIMIT 50
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""")
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for name, props_json in cur.fetchall():
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props = json.loads(props_json) if props_json else {}
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patterns.append({
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"name": name,
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"occurrence": props.get("occurrence_count", 0),
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"source": props.get("source", "unknown"),
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"topic": props.get("topic", ""),
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})
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conn.close()
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except Exception:
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pass
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# ── L3: scenes（从 TencentDB /recall） ───────────────────────
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scenes = []
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try:
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r = requests.post(TDDB_URL + "/recall", json={"query": "recent", "top_k": 10}, timeout=3)
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if r.status_code == 200:
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for item in r.json().get("results", [])[:10]:
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scenes.append({"content": item.get("content", "")[:120], "source": item.get("source", "unknown")})
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except Exception:
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pass
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# ── L4: policies（scene 聚合产生） ────────────────────────────
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policies = []
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try:
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conn = sqlite3.connect(HERMES + "/graph.db")
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cur = conn.cursor()
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cur.execute("""
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SELECT name, properties FROM graph_nodes
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WHERE type='policy' ORDER BY last_updated_at DESC LIMIT 20
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""")
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for name, props_json in cur.fetchall():
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props = json.loads(props_json) if props_json else {}
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policies.append({"name": name, "description": props.get("description", "")[:100]})
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conn.close()
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except Exception:
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pass
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# ── L5: distilled_rules（从 user-profile.json） ────────────────
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distilled_rules = []
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up_path = HERMES + "/soulful/user-profile.json"
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if os.path.exists(up_path):
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try:
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with open(up_path) as f:
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up = json.load(f)
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for rule in up.get("distilled_rules", []):
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if isinstance(rule, str):
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distilled_rules.append(rule)
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elif isinstance(rule, dict):
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distilled_rules.append(rule.get("rule", str(rule))[:150])
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except Exception:
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pass
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# ── L6: traits（深层特征，从画像合成） ─────────────────────────
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traits = []
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if os.path.exists(up_path):
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try:
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with open(up_path) as f:
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up = json.load(f)
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traits = [up.get(k, "") for k in ("core_traits", "communication_style", "work_patterns") if up.get(k)]
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except Exception:
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pass
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# ── cares ────────────────────────────────────────────────────
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cares = []
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cq_path = HERMES + "/soulful/cares-queue.json"
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if os.path.exists(cq_path):
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@ -1398,15 +1496,11 @@ def save_llm_context(ctx, state):
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with open(cq_path) as f:
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data = json.load(f)
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for c in data.get("cares", []):
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cares.append({
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"id": c.get("id", ""),
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"content": c.get("content", "")[:60],
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"due": c.get("follow_up_date", "")
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})
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cares.append({"id": c.get("id", ""), "content": c.get("content", "")[:60], "due": c.get("follow_up_date", "")})
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except Exception:
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pass
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# 收集 recent_moments
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# ── recent_moments ───────────────────────────────────────────
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recent_moments = []
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heart_path = HERMES + "/soulful/heart-traces.jsonl"
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if os.path.exists(heart_path):
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@ -1415,36 +1509,28 @@ def save_llm_context(ctx, state):
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for line in lines[-3:]:
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if line.strip():
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e = json.loads(line)
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recent_moments.append({
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"content": e["content"][:80],
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"importance": e.get("importance", 0),
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"timestamp": e.get("timestamp", "")
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})
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recent_moments.append({"content": e.get("content", "")[:80], "importance": e.get("importance", 0), "timestamp": e.get("timestamp", "")})
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except Exception:
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pass
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# daemon 健康状态
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if state.get("processes", {}).get("daemon"):
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daemon_status = "running"
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elif psutil.pid_exists(os.getpid()):
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daemon_status = "running"
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else:
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daemon_status = "stopped"
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data = {
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"version": 2,
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"updated_at": datetime.now(timezone.utc).isoformat(),
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"uptime_minutes": ctx.get("uptime_seconds", 0) // 60,
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"daemon_status": daemon_status,
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"distill_status": ctx.get("distill_status", "ok"),
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"user_profile": ctx.get("user_profile", {}),
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"active_scenes": ctx.get("active_scenes", []),
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"short_term": {
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"l1_observations_count": ctx.get("l1_count", 0),
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"l2_patterns_new": ctx.get("l2_new", 0),
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"l3_scenes_updated": ctx.get("l3_updated", 0),
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},
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# L1-L6 完整蒸馏数据
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"observations": observations,
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"patterns": patterns,
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"scenes": scenes,
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"policies": policies,
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"distilled_rules": distilled_rules,
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"traits": traits,
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# Soulful 情感层
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"cares": cares,
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"recent_moments": recent_moments,
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# 用户画像
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"user_profile": ctx.get("user_profile", {}),
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}
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with open(LLM_CONTEXT_FILE, "w") as f:
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@ -30,7 +30,7 @@ check_unified_layer() {
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if [ "$keys" = "ERROR" ]; then
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issues+=("llm_context.json JSON 格式错误")
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else
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for field in user_profile active_scenes short_term cares recent_moments distill_status; do
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for field in user_profile observations patterns scenes policies distilled_rules cares recent_moments; do
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if ! echo "$keys" | grep -q "$field"; then
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issues+=("缺少字段: $field")
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fi
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@ -44,11 +44,9 @@ check_unified_layer() {
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fi
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if [ ${#issues[@]} -eq 0 ]; then
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local upd
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upd=$(python3 -c "import json; d=json.load(open('$ctx_file')); print(d.get('updated_at','?'))" 2>/dev/null || echo "?")
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local st
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st=$(python3 -c "import json; d=json.load(open('$ctx_file')); st=d.get('short_term',{}); print(f\"L1={st.get('l1_observations_count',0)} L2={st.get('l2_patterns_new',0)} L3={st.get('l3_scenes_updated',0)}\")" 2>/dev/null || echo "?")
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log "[OK] 统一层: updated=$upd $st"
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v=$(python3 -c "import json; d=json.load(open('$ctx_file')); v=d.get('version','N/A'); obs=len(d.get('observations',[])); pat=len(d.get('patterns',[])); sc=len(d.get('scenes',[])); pol=len(d.get('policies',[])); dr=len(d.get('distilled_rules',[])); print(f'v{v} L1={obs} L2={pat} L3={sc} L4={pol} L5={dr}')" 2>/dev/null || echo "?")
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log "[OK] 统一层: updated=$upd $v"
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else
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ALERT=1
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log "[FAIL] 统一层: ${issues[*]}"
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@ -172,8 +170,7 @@ check_tddb
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# ── 告警 ─────────────────────────────────────────────────────
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if [ "$ALERT" = 1 ]; then
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local msg
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msg="⚠️ 记忆系统异常\n$(printf '%s\n' "${LINES[@]}")"
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msg="记忆系统异常: $(printf '%s,' "${LINES[@]}")"
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curl -s -X POST "$FEISHU_WEBHOOK" \
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-H "Content-Type: application/json" \
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-d "{\"msg_type\":\"text\",\"text\":\"$msg\"}" > /dev/null 2>&1
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