修复空内容重试

agent/deep_assistant.py

@@ -45,10 +45,11 @@ from langchain_core.language_models import BaseChatModel
 from langgraph.pregel import Pregel
 # 新版本导入：MemoryMiddleware 和 SkillsMiddleware 已迁移到 deepagents.middleware
 from deepagents.middleware import MemoryMiddleware, SkillsMiddleware
-from langchain.agents.middleware import AgentMiddleware
+from langchain.agents.middleware import AgentMiddleware, ModelRequest, ModelResponse
+from langchain.agents.middleware import HumanInTheLoopMiddleware, InterruptOnConfig, TodoListMiddleware
+from langchain_core.messages import AIMessage, HumanMessage
 from langgraph.types import Checkpointer
 from deepagents_cli.config import settings, get_default_coding_instructions
-from langchain.agents.middleware import HumanInTheLoopMiddleware, InterruptOnConfig, TodoListMiddleware
 from deepagents.middleware.filesystem import FilesystemMiddleware
 from deepagents.middleware.patch_tool_calls import PatchToolCallsMiddleware
 from langchain_anthropic.middleware import AnthropicPromptCachingMiddleware
@@ -63,6 +64,51 @@ from .custom_filesystem_middleware import CustomFilesystemMiddleware
 # _global_checkpointer = MemorySaver()
 
 logger = logging.getLogger('app')
+
+
+class EmptyResponseRetryMiddleware(AgentMiddleware):
+    """当模型返回空内容（无文字、无工具调用）时自动重试"""
+
+    MAX_RETRIES = 5
+
+    def _is_empty_response(self, result: ModelResponse) -> bool:
+        """判断是否为空响应"""
+        if not result.result:
+            return True
+        msg = result.result[0]
+        if not isinstance(msg, AIMessage):
+            return False
+        content = msg.content or ""
+        has_text = bool(content.strip()) if isinstance(content, str) else bool(content)
+        return not has_text and len(msg.tool_calls) == 0
+
+    def wrap_model_call(self, request, handler):
+        result = handler(request)
+        retries = 0
+        while self._is_empty_response(result) and retries < self.MAX_RETRIES:
+            retries += 1
+            logger.warning(f"Empty response detected, retrying ({retries}/{self.MAX_RETRIES})")
+            retry_messages = list(request.messages) + [
+                HumanMessage(content="Please continue your response.")
+            ]
+            request = request.override(messages=retry_messages)
+            result = handler(request)
+        return result
+
+    async def awrap_model_call(self, request, handler):
+        result = await handler(request)
+        retries = 0
+        while self._is_empty_response(result) and retries < self.MAX_RETRIES:
+            retries += 1
+            logger.warning(f"Empty response detected, retrying ({retries}/{self.MAX_RETRIES})")
+            retry_messages = list(request.messages) + [
+                HumanMessage(content="Please continue your response.")
+            ]
+            request = request.override(messages=retry_messages)
+            result = await handler(request)
+        return result
+
+
 # Utility functions
 def read_system_prompt():
     """读取通用的无状态系统prompt"""
@@ -220,6 +266,8 @@ async def init_agent(config: AgentConfig):
 
     # 构建中间件列表
     middleware = []
+    # 添加空响应重试中间件（最先执行，最外层包裹）
+    middleware.append(EmptyResponseRetryMiddleware())
     # 首先添加 ToolUseCleanupMiddleware 来清理孤立的 tool_use
     middleware.append(ToolUseCleanupMiddleware())
     # 添加工具输出长度控制中间件

agent/logging_handler.py

@@ -41,16 +41,20 @@ class LoggingCallbackHandler(BaseCallbackHandler):
         if hasattr(response, 'generations') and response.generations:
             for gen_idx, generation_list in enumerate(response.generations):
                 for msg_idx, generation in enumerate(generation_list):
-                    if hasattr(generation, 'text'):
-                        output_list = generation.text.split("\n")
-                        for i, output in enumerate(output_list):
-                            if output.strip():
-                                self.logger.info(f"{output}")
-                    elif hasattr(generation, 'message'):
-                        output_list = generation.message.split("\n")
-                        for i, output in enumerate(output_list):
-                            if output.strip():
-                                self.logger.info(f"{output}")
+                    # ChatGeneration: 使用 text 属性获取内容
+                    if hasattr(generation, 'text') and generation.text:
+                        for line in generation.text.split("\n"):
+                            if line.strip():
+                                self.logger.info(f"  {line}")
+                    # 如果有 message 属性，输出额外信息（tool_calls 等）
+                    if hasattr(generation, 'message') and generation.message:
+                        msg = generation.message
+                        content = msg.content if hasattr(msg, 'content') else ''
+                        if not content or (isinstance(content, str) and not content.strip()):
+                            self.logger.info(f"  [EMPTY content]")
+                        tool_calls = msg.tool_calls if hasattr(msg, 'tool_calls') else []
+                        if tool_calls:
+                            self.logger.info(f"  [tool_calls: {[tc.get('name', '') for tc in tool_calls]}")
 
     def on_llm_error(
         self, error: Exception, **kwargs: Any