feat: integrate RouteLLM BERT router for intelligent query classification

- 添加 transformers 和 torch 依赖
- 创建 bert_router.py 封装 RouteLLM BERT 分类器
- 新增 select_model_by_bert() 函数替代 token 长度路由
- BERT 输出映射: strong->qwen-max, weak->qwen-flash
- 保留 token 长度路由作为 fallback

main.py

@@ -13,6 +13,7 @@ from litellm import acompletion
 import litellm
 
 from config import MODEL_CONFIG, ROUTING_THRESHOLDS, DEFAULT_ROUTING, DASHSCOPE_API_KEY
+from bert_router import get_bert_router, route_with_bert
 
 # 配置 LiteLLM 使用 DashScope (Qwen)
 if DASHSCOPE_API_KEY:
@@ -20,6 +21,16 @@ if DASHSCOPE_API_KEY:
     # Qwen 使用 OpenAI 兼容接口，但需要通过 api_base 指定
     litellm.api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
 
+# BERT Router 实例（延迟加载）
+_bert_router = None
+
+def get_router():
+    """获取 BERT Router 实例（延迟加载）"""
+    global _bert_router
+    if _bert_router is None:
+        _bert_router = get_bert_router()
+    return _bert_router
+
 
 # 调用历史记录
 call_history: List[Dict[str, Any]] = []
@@ -80,7 +91,7 @@ def estimate_tokens(messages: List[Message]) -> int:
 
 
 def select_model_by_length(messages: List[Message]) -> str:
-    """基于 token 长度选择模型"""
+    """基于 token 长度选择模型（备用策略）"""
     token_count = estimate_tokens(messages)
     
     if token_count < ROUTING_THRESHOLDS["simple"]:
@@ -91,6 +102,33 @@ def select_model_by_length(messages: List[Message]) -> str:
         return DEFAULT_ROUTING["complex"]
 
 
+def select_model_by_bert(messages: List[Message]) -> str:
+    """
+    基于 BERT 分类器选择模型
+    
+    BERT 输出: strong / weak
+    映射到 Qwen 模型:
+    - strong -> qwen-max (复杂任务)
+    - weak -> qwen-flash (简单任务)
+    """
+    # 取最后一条用户消息作为查询
+    query = messages[-1].content if messages else ""
+    
+    try:
+        router = get_router()
+        complexity = router.predict(query)
+        
+        # BERT 二分类映射到三模型
+        if complexity == "strong":
+            return "qwen-max"
+        else:
+            return "qwen-flash"
+    except Exception as e:
+        # BERT 失败时回退到 token 长度策略
+        print(f"BERT routing failed: {e}, falling back to token length")
+        return select_model_by_length(messages)
+
+
 def get_provider_model(model_key: str) -> str:
     """获取 LiteLLM 格式的模型名称"""
     config = MODEL_CONFIG.get(model_key)
@@ -142,7 +180,8 @@ async def chat_completions(request: ChatRequest):
     if request.model:
         model_key = request.model
     else:
-        model_key = select_model_by_length(request.messages)
+        # 使用 BERT 智能路由（替代原来的 token 长度路由）
+        model_key = select_model_by_bert(request.messages)
     
     # 获取 LiteLLM 模型名称
     provider_model = get_provider_model(model_key)