fix: default remaining to high quota for unknown models on startup and update AGENTS.md

AGENTS.md

@@ -4,11 +4,14 @@
 
 ## 1. 项目上下文
 此仓库包含用于 **LiteLLM** 的自定义回调脚本，核心功能是限制模型用量（特别是火山引擎/VolcEngine）。
-- **核心逻辑**：通过 `quota_interceptor` 拦截请求，并通过 `DailyLimitHandler` 记录用量到 Redis。
+- **核心逻辑**：通过 `quota_interceptor` 拦截请求，并通过 `DailyLimitHandler` 记录用量到 Redis。后台 `active_monitor_loop` 守护线程定期从火山引擎 API 同步配额到 Redis。
+- **架构**：所有逻辑统一在 `volc_limit_sync.py` 单文件中。LiteLLM 通过 `config.yaml` 中 `callbacks: ["volc_limit_sync.proxy_handler_instance"]` 加载回调，模块加载时自动启动后台同步线程。
 - **关键文件**：
-  - `volc_limit_sync.py`: 主同步逻辑，从火山引擎 API 拉取配额并更新 Redis。
-  - `daily_limit.py`: 轻量级回调，用于 LiteLLM 运行时检查。
-  - `config.yaml`: 包含模型定义的 LiteLLM 配置文件。
+  - `volc_limit_sync.py`: **唯一核心文件**，包含同步守护线程（`active_monitor_loop`）、LiteLLM 回调（`DailyLimitHandler` + `quota_interceptor`）、限额计算、模型屏蔽/恢复等全部逻辑。
+  - `config.yaml`: LiteLLM 配置文件，包含模型定义和回调配置。
+  - `docker-compose.yml`: 容器编排，仅挂载 `config.yaml` 和 `volc_limit_sync.py`。
+  - `debug_volc_sync.py` / `debug_volc_sync_manual.py`: 调试脚本，用于手动验证 API 和 Redis 状态。
+  - `daily_limit.py.deprecated`: 已废弃，功能已全部合并到 `volc_limit_sync.py`，仅保留作历史参考。
 
 ## 2. 环境与运行 (Build & Run)
 
@@ -40,7 +43,7 @@ pip install litellm redis requests
 ### 3.1 基础规范
 - **Python 版本**：兼容 Python 3.8+。
 - **命名规范**：
-  - 变量/函数：`snake_case` (e.g., `clean_model_name`, `get_daily_limit`)
+  - 变量/函数：`snake_case` (e.g., `clean_model_name`, `get_effective_limit`)
   - 常量：`UPPER_CASE` (e.g., `LOG_LEVEL`, `REDIS_HOST`)
   - 类名：`PascalCase` (e.g., `DailyLimitHandler`)
 - **类型提示 (Typing)**：

docker-compose.yml

@@ -8,9 +8,7 @@ services:
     volumes:
       - ./config.yaml:/app/config.yaml
       # 【关键】挂载自定义脚本到容器根目录
-      - ./daily_limit.py:/app/daily_limit.py
       - ./volc_limit_sync.py:/app/volc_limit_sync.py  
-      - ./debug_volc_sync_manual.py:/app/debug_volc_sync_manual.py
     command:
       - "--config=/app/config.yaml"
     ports:

volc_limit_sync.py

@@ -1025,14 +1025,36 @@ def active_monitor_loop():
             beijing_time_ts = now + (8 * 3600)
             today_str = time.strftime("%Y-%m-%d", time.gmtime(beijing_time_ts))
 
-            # Idle Check
-            usage_key_global = f"daily_usage:{today_str}:global_total"
-            current_usage_global = int(redis_client.get(usage_key_global) or 0)
-            last_usage_global = sum(last_usage_map.values()) if last_usage_map else 0
-            delta = current_usage_global - last_usage_global
+            # Idle Check - Only exit idle if a "low quota" model has usage
+            LOW_QUOTA_THRESHOLD = 800000  # 判定为“低额度”的阈值
+            model_usages = {}
+            any_low_quota_usage = False
+            
+            for m in MONITORED_MODELS:
+                m_usage = 0
+                target_hashes = [p[1] for p in MONITORED_MODEL_PAIRS if p[0] == m]
+                for h in target_hashes:
+                    val = redis_client.get(f"daily_usage:{today_str}:{m}:{h}")
+                    if val: m_usage += float(val)
+                val_no_hash = redis_client.get(f"daily_usage:{today_str}:{m}")
+                if val_no_hash: m_usage += float(val_no_hash)
+                model_usages[m] = m_usage
+
+                # Calculate delta for this specific model
+                m_delta = m_usage - last_usage_map.get(m, 0.0)
+                
+                # Check if this model is considered "low quota"
+                rem_key = f"limit:dynamic:volcengine:remaining:{m}"
+                rem_val = redis_client.get(rem_key)
+                # 未知额度视为充足，避免首次启动时所有模型被误判为"低额度"
+                remaining = float(rem_val) if rem_val is not None else float(LOW_QUOTA_THRESHOLD)
+
+                if m_delta > 0 and remaining < LOW_QUOTA_THRESHOLD:
+                    any_low_quota_usage = True
+
             time_diff = now - last_sync_time
 
-            if delta <= 0:
+            if not any_low_quota_usage:
                 if idle_start_time == 0:
                     idle_start_time = now
             else:
@@ -1085,10 +1107,8 @@ def active_monitor_loop():
             burst_reason = ""
 
             for model in MONITORED_MODELS:
-                # 1. Get Current Usage
-                curr_usage_key = f"limit:dynamic:volcengine:usage:{model}"
-                curr_usage_val = redis_client.get(curr_usage_key)
-                curr_usage = float(curr_usage_val) if curr_usage_val else 0.0
+                # 1. Get Current Usage (calculated above)
+                curr_usage = model_usages.get(model, 0.0)
 
                 # 2. Get Last Synced Usage (Snapshot)
                 last_usage = last_usage_map.get(model, 0.0)
@@ -1325,15 +1345,8 @@ def active_monitor_loop():
                     global_min_remaining = temp_min_remaining
 
                 # Update snapshots for next iteration delta calculation
-                current_usage_global_snapshot = 0
-                for m in MONITORED_MODELS:
-                    uk = f"limit:dynamic:volcengine:usage:{m}"
-                    uv = redis_client.get(uk)
-                    u_val = float(uv) if uv else 0.0
+                for m, u_val in model_usages.items():
                     last_usage_map[m] = u_val
-                    current_usage_global_snapshot += u_val
-
-                last_usage_map["global"] = current_usage_global_snapshot
                 last_sync_time = now
 
                 if global_min_remaining > 800000: