feat: SmartRouter - intelligent model routing based on task complexity

agentmain.py

@@ -6,7 +6,7 @@
 elif hasattr(sys.stderr, 'reconfigure'): sys.stderr.reconfigure(errors='replace')
 sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
 
-from llmcore import reload_mykeys, LLMSession, ToolClient, ClaudeSession, MixinSession, NativeToolClient, NativeClaudeSession, NativeOAISession, resolve_client
+from llmcore import reload_mykeys, LLMSession, ToolClient, ClaudeSession, MixinSession, NativeToolClient, NativeClaudeSession, NativeOAISession, resolve_client, SmartRouter
 from agent_loop import agent_runner_loop
 from ga import GenericAgentHandler, smart_format, get_global_memory, format_error, consume_file
 
@@ -49,6 +49,8 @@ def __init__(self):
         self.is_running = False; self.stop_sig = False
         self.llm_no = 0;  self.inc_out = False; self.verbose = True
         self.peer_hint = True
+        self.router = SmartRouter()
+        self.auto_route = False
         self.log_path = os.path.join(script_dir, f'temp/model_responses/model_responses_{int(time.time()*1e6)%1000000:06d}.txt')
         self.load_llm_sessions()
 
@@ -120,6 +122,21 @@ def _handle_slash_cmd(self, raw_query, display_queue):
             return None
         if raw_query.strip() == '/resume':
             return r'帮我看看最近有哪些会话可以恢复。读model_responses/目录，按修改时间取最近10个文件，从每个文件里找最后一个<history>...</history>块，用一句话总结每个会话在聊什么，列表给我选。注意读文件后要把字面的\n替换成真换行才能正确匹配。'
+        if raw_query.strip() == '/llm auto':
+            self.auto_route = not self.auto_route
+            display_queue.put({'done': smart_format(f"✅ 智能路由 {'开启' if self.auto_route else '关闭'}"), 'source': 'system'})
+            return None
+        if raw_query.strip().startswith('/llm'):
+            parts = raw_query.strip().split()
+            if len(parts) == 2 and parts[1] in ('simple', 'complex'):
+                target_no = 1 if parts[1] == 'complex' else 0
+                if target_no < len(self.llmclients):
+                    self.llm_no = target_no
+                    self.next_llm(self.llm_no)
+                    display_queue.put({'done': smart_format(f"✅ 已切换到 {parts[1].upper()} 模型: {self.get_llm_name(b=True)}"), 'source': 'system'})
+                else:
+                    display_queue.put({'done': smart_format(f"❌ 没有 {parts[1].upper()} 模型可用"), 'source': 'system'})
+                return None
         return raw_query
 
     def run(self):
@@ -143,6 +160,19 @@ def run(self):
                 if ps > 0: handler.working['key_info'] += f'\n[SYSTEM] 此为 {ps} 个对话前设置的key_info，若已在新任务，先更新或清除工作记忆。\n'
             self.handler = handler  # although new handler, the **full** history is in llmclient, so it is full history!
             self.llmclient.log_path = self.log_path
+            # 自动路由逻辑
+            if self.auto_route:
+                decision = self.router.classify(raw_query)
+                target_no = 1 if decision == "complex" else 0
+                if target_no < len(self.llmclients) and target_no != self.llm_no:
+                    old_name = self.get_llm_name(model=True)
+                    self.llm_no = target_no
+                    self.next_llm(self.llm_no)
+                    new_sys_prompt = get_system_prompt() + getattr(self.llmclient.backend, "extra_sys_prompt", "")
+                    handler = GenericAgentHandler(self, self.history, os.path.join(script_dir, "temp"))
+                    self.handler = handler
+                    self.llmclient.log_path = self.log_path
+                    sys_prompt = new_sys_prompt
             gen = agent_runner_loop(self.llmclient, sys_prompt, raw_query, 
                                 handler, TOOLS_SCHEMA, max_turns=70, verbose=self.verbose)
             try:
@@ -268,3 +298,4 @@ def run(self):
             except KeyboardInterrupt:
                 agent.abort()
                 print('\n[Interrupted]')
+

llmcore.py

@@ -1021,3 +1021,56 @@ def fast_ask(prompt, cfg_name):
     sess = resolve_session(cfg_name)
     if not sess: raise ValueError(f"fast_ask: '{cfg_name}' unsupported")
     return "".join(sess.raw_ask([{"role": "user", "content": prompt}]))
+
+class SmartRouter:
+    """根据用户查询自动分类任务复杂度，推荐 simple(flash) 或 complex(pro) 模型组。"""
+
+    COMPLEX_KEYWORDS = [
+        '代码', '框架', '实现', '架构', '设计模式', '重构', '调试', '算法',
+        '数据库', 'SQL', 'API', '设计', '优化', '性能', '安全', '部署',
+        '测试', '单元测试', '集成', 'CI', 'CD', '并发', '线程', '异步',
+        '网络', '协议', '加密', '认证', '授权', '缓存', '索引', '事务',
+        'middleware', 'pipeline', 'workflow', 'orchestration', '微服务',
+        'docker', 'kubernetes', 'k8s', '容器', '编排',
+        'framework', 'architecture', 'refactor', '重构',
+        'code', 'programming', 'function', 'class', 'module',
+        'implement', 'implementation', 'design pattern',
+    ]
+    SIMPLE_KEYWORDS = [
+        '你好', 'hi', 'hello', '天气', '今天', '早上', '晚上', '下午',
+        '谢谢', '感谢', '再见', '拜拜', '嗯', '好', 'ok',
+        '名字', '你是谁', '你能做什么',
+    ]
+
+    def __init__(self):
+        self.enabled = False
+
+    def enable(self):
+        self.enabled = True
+
+    def disable(self):
+        self.enabled = False
+
+    def classify(self, query: str) -> str:
+        """返回 'simple' 或 'complex'"""
+        q = query.strip()
+        if not q:
+            return 'simple'
+
+        # 长查询倾向于复杂
+        if len(q) > 100:
+            return 'complex'
+
+        # 含代码块标记
+        if '```' in q or 'def ' in q or 'class ' in q or 'import ' in q:
+            return 'complex'
+
+        # 复杂关键词匹配
+        q_lower = q.lower()
+        complex_score = sum(1 for kw in self.COMPLEX_KEYWORDS if kw.lower() in q_lower)
+        simple_score = sum(1 for kw in self.SIMPLE_KEYWORDS if kw.lower() in q_lower)
+
+        if complex_score > simple_score:
+            return 'complex'
+        return 'simple'
+