fix: 资源包查询修复翻页死循环并加 Status 过滤

- debug_volc_sync.py 缺少 seen_tokens 防循环保护，火山 API 翻页到头后
  NextToken 循环回起始 token，导致无限翻页（实测 900s 拉 1893 页假象，
  真实数据仅 8 页 137 个包）
- 两个 fetch_all_packages 请求加 Status=Effective，服务端直接过滤
  UsedUp/Expired/Refunded 等余额为 0 的无用包（实测过滤后 0 余额包为 0）
- 主脚本循环检测日志从 DEBUG 提升为 WARNING，循环收尾不再静默

debug_volc_sync.py

@@ -116,12 +116,15 @@ def fetch_all_packages():
     version = "2022-01-01"
     all_packages = []
     current_token = ""
+    seen_tokens = set()
 
     while True:
         try:
             payload = {
                 "ResourceType": "Package",
                 "MaxResults": "20",
+                # 只拉生效中的数据包，跳过 UsedUp/Expired/Refunded 等余额为 0 的无用包
+                "Status": "Effective",
                 "NextToken": current_token,
             }
             headers, body = get_signed_headers(action, version, payload)
@@ -134,8 +137,19 @@ def fetch_all_packages():
             if items:
                 all_packages.extend(items)
             next_token = data.get("Result", {}).get("NextToken", "")
-            if not next_token or next_token == current_token:
+
+            # Infinite Loop Protection: VolcEngine API 翻页到头后 NextToken 会
+            # 循环回起始 token（实测：数据只有 ~8 页，第 9 页绕回第一个 token），
+            # 没有该保护会无限翻页。
+            if not next_token:
                 break
+            if next_token == current_token:
+                break
+            if next_token in seen_tokens:
+                print(f"WARNING: Detected pagination cycle with token {next_token}. Stopping.")
+                break
+
+            seen_tokens.add(next_token)
             current_token = next_token
             time.sleep(0.2)
         except Exception as e:

volc_limit_sync.py

@@ -41,6 +41,27 @@ except ImportError:
         pass
 
 
+# ==========================================
+# 🏷️ Unified Log Tag (统一日志标识，便于过滤)
+# ==========================================
+# 本脚本所有输出统一带 [VolcSync] 前缀，方便日志筛选：
+#   docker logs litellm 2>&1 | grep VolcSync
+# 实现方式：模块级重绑定 print（`print` 在模块命名空间中按调用时查找），
+# 一处覆盖 log()/dprint 与全部裸 print 调用；对模块外部无任何影响。
+LOG_TAG = "[VolcSync]"
+
+_original_print = print
+
+
+def _tagged_print(*args, **kwargs):
+    if args and isinstance(args[0], str):
+        args = (args[0].lstrip("\n"), *args[1:])
+    _original_print(LOG_TAG, *args, **kwargs)
+
+
+print = _tagged_print
+
+
 # ==========================================
 # 🛠️ Configuration & Constants
 # ==========================================
@@ -157,7 +178,7 @@ def log(msg, level="INFO"):
         icon = {"DEBUG": "🔍", "INFO": "ℹ️", "WARNING": "⚠️", "ERROR": "❌"}.get(
             level, "📝"
         )
-        print(f"{icon} [VolcSync] {msg}", flush=True)
+        print(f"{icon} {msg}", flush=True)
 
 
 def dprint(msg):
@@ -842,6 +863,10 @@ def fetch_all_packages():
             payload = {
                 "ResourceType": "Package",
                 "MaxResults": "20",
+                # 服务端只返回生效中的数据包，跳过 UsedUp/Expired/Refunded 等
+                # 余额为 0 的无用包，显著减少翻页次数与 QPS 占用。
+                # 周期型包（月度重置）状态仍为 Effective，不会被误过滤。
+                "Status": "Effective",
                 "NextToken": current_token,
             }
             headers, body = get_signed_headers(action, version, payload)
@@ -855,14 +880,17 @@ def fetch_all_packages():
             next_token = data.get("Result", {}).get("NextToken", "")
 
             # Infinite Loop Protection
+            # 火山 API 翻页到头后 NextToken 会循环回起始 token（实测数据只有
+            # ~8 页时第 9 页绕回第一个 token），必须用 seen_tokens 拦下载断。
             if not next_token:
                 break
             if next_token == current_token:
                 break
             if next_token in seen_tokens:
-                if DEBUG_MODE:
+                log(
-                    print(
+                    f"⚠️ VolcEngine pagination cycle detected (token {next_token} repeated). "
-                        f"DEBUG: Detected pagination cycle with token {next_token}. Stopping."
+                    f"Stopping after {len(all_packages)} packages.",
+                    level="WARNING",
                 )
                 break
 
@@ -1308,21 +1336,32 @@ def active_monitor_loop():
                         dynamic_key = f"limit:dynamic:volcengine:remaining:{target}"
 
                         # ==========================================
-                        # 🏔️ Smart Peak Tracking (Auto-Correction)
+                        # 🏔️ Daily Peak Lock (First-Sync + Balance-Gated Re-Lock)
                         # ==========================================
-                        # Strategy:
+                        # 背景：AvailableAmount 是各资源包实例的实时剩余，但火山统计有
-                        # 1. Capture Jumps (Recovery): If Balance jumps UP, trust it immediately. (Fixes latency)
+                        # 更新滞后（高用量时段会短暂冻结，实测 20 万 token 消耗内余额不动）。
-                        # 2. Capture Drops (Expiry): If Balance drops HUGE (>20%), trust it. (Fixes expiry)
+                        # 旧逻辑把每次用量增长误判为"余额恢复"（Jump）锁更高峰值，
-                        #    - Why trust drops? Because if it's a false drop (glitch), Step 1 will fix it
+                        # 导致 stable_limit 越算越多（当天 399,836 -> 599,511 一路抬升）。
-                        #      automatically on the next sync when it "Jumps" back up.
+                        # 修正策略（日内限额单调可控）：
+                        #   1. 首次同步锁定当日峰值（= usage + balance 的总配额估计）；
+                        #   2. 仅当 balance 自身净上涨（新资源包发放/对账回补，≥50k）
+                        #      时，按新增额度抬高峰值 —— 幅度 = 历史峰值 + 发放增量，
+                        #      绝不把滞后虚高的 usage 一起算进去；
+                        #   3. balance 回落（额度扣减追上用量）时 Drop 收紧；
+                        #   4. usage 增长驱动的 pool 上涨一律不得抬高限额。
+                        # 实测：协作奖励计划包每自然日发放、偶发一天 2 个，故必须有第 2 条；
+                        #       次日 00:00 (CST) 自动重建当日峰值。
 
                         total_pool = current_usage + balance
                         peak_key = f"volc:peak_pool:{today_str}:{target}"
 
-                        # Short-term memory (Last seen value)
+                        # Short-term memory (Last seen value) - 仅用于日志对比/增量计算
                         last_pool_key = f"volc:last_seen_pool:{target}"
                         last_pool_val = redis_client.get(last_pool_key)
                         last_pool = float(last_pool_val) if last_pool_val else 0.0
+                        last_balance_key = f"volc:last_balance:{target}"
+                        last_balance_val = redis_client.get(last_balance_key)
+                        last_balance = float(last_balance_val) if last_balance_val else 0.0
 
                         # Long-term memory (Day's High Water Mark)
                         old_peak_val = redis_client.get(peak_key)
@@ -1330,21 +1369,31 @@ def active_monitor_loop():
 
                         current_peak = historical_peak
 
-                        # 1. JUMP DETECTION (Recharge / Latency Resolved)
+                        # 1. INITIALIZATION (First sync of the day): lock once
-                        # If pool jumps significantly (>5%) from last seen, it's a fresh, true value.
+                        if historical_peak == 0:
-                        if total_pool > (last_pool * 1.05) and last_pool > 0:
+                            if DEBUG_MODE and last_pool > 0:
-                            if DEBUG_MODE:
                                 print(
-                                    f"DEBUG: 📈 Balance Jump ({int(last_pool):,} -> {int(total_pool):,}) - Locking New Peak.",
+                                    f"DEBUG: 📌 Locking Daily Peak ({int(last_pool):,} -> {int(total_pool):,}) - First Sync Today.",
                                     flush=True,
                                 )
                             current_peak = total_pool
                             redis_client.setex(peak_key, 172800, int(current_peak))
 
-                        # 2. DROP DETECTION (Resource Expiry)
+                        # 2. RECHARGE (Balance-driven upward re-lock)
-                        # If pool drops (even small amounts), we accept it.
+                        # 新资源包发放 / API 对账回补 → balance 自身净上涨 ≥50k。
-                        # Why? Because keeping a phantom high peak is dangerous.
+                        # 只把"发放增量"加进已锁定的峰值，不重算整个滞后 pool。
-                        # If it was a glitch, Rule #1 will fix it next time it bounces back.
+                        elif last_balance > 0 and (balance - last_balance) >= 50000:
+                            grant_delta = int(balance - last_balance)
+                            current_peak = historical_peak + grant_delta
+                            if DEBUG_MODE:
+                                print(
+                                    f"DEBUG: 🆕 New Quota Detected (balance {int(last_balance):,} -> {int(balance):,}, +{grant_delta:,}) - Re-locking Daily Peak to {int(current_peak):,}.",
+                                    flush=True,
+                                )
+                            redis_client.setex(peak_key, 172800, int(current_peak))
+
+                        # 3. DROP DETECTION (Resource Expiry / latency catch-up)
+                        # pool 回落时收紧限额；回落之后保持不变，绝不回升。
                         elif total_pool < historical_peak and historical_peak > 0:
                             drop_ratio = (
                                 historical_peak - total_pool
@@ -1357,13 +1406,12 @@ def active_monitor_loop():
                             current_peak = total_pool
                             redis_client.setex(peak_key, 172800, int(current_peak))
 
-                        # 3. INITIALIZATION / DRIFT
+                        # 4. NO USAGE-DRIVEN RE-LOCK: 用量增长（balance 不变）不得抬高限额。
-                        elif historical_peak == 0 or total_pool > historical_peak:
+                        #    （旧逻辑的 Bug 就在这里：把滞后虚高当余额恢复。）
-                            current_peak = total_pool
-                            redis_client.setex(peak_key, 172800, int(current_peak))
 
                         # Always update "Last Seen" for next comparison
                         redis_client.setex(last_pool_key, 86400, int(total_pool))
+                        redis_client.setex(last_balance_key, 86400, int(balance))
 
                         # Calculate Stable Limit
                         safety_margin = max(current_peak * 0.15, 250000)
@@ -1472,7 +1520,7 @@ def active_monitor_loop():
 
         except Exception as e:
             print(f"Error in monitor loop / 监控循环出错: {e}", flush=True)
-            traceback.print_exc()
+            print(traceback.format_exc(), end="")
             time.sleep(5)