fix(agent): stabilize tool selector logging

app/agent/middleware/tool_selection.py

@@ -1,6 +1,6 @@
 """MoviePilot 自定义工具筛选中间件。"""
 
-from dataclasses import replace
+from dataclasses import dataclass, replace
 import json
 from collections.abc import Awaitable, Callable
 from typing import Annotated, Any, NotRequired
@@ -68,6 +68,16 @@ class ToolSelectionStateUpdate(TypedDict):
     selected_tool_names: list[str] | None
 
 
+@dataclass(frozen=True)
+class _ToolSelectionAttempt:
+    """工具筛选尝试结果，用于统一记录最终日志。"""
+
+    request: ModelRequest
+    selected_tool_names: list[str]
+    status: str
+    detail: str = ""
+
+
 class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
     """
     使用 provider-neutral JSON 提示执行工具筛选。
@@ -321,8 +331,6 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
         处理工具筛选响应，并保留空结果回退所有工具的 MoviePilot 策略。
         """
         if response.get("tools") == []:
-            logger.info("工具筛选结果为空，将恢复使用所有工具。")
-
             always_included_tools: list[BaseTool] = [
                 tool
                 for tool in request.tools
@@ -349,8 +357,6 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
             valid_tool_names,
             request,
         )
-        selected_tool_names = self._extract_selected_tool_names(modified_request)
-        logger.info(f"工具筛选结果: {', '.join(selected_tool_names) or '无有效工具'}")
         return modified_request
 
     @staticmethod
@@ -483,6 +489,34 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
         """从已筛选后的请求中提取最终工具名，保留原有顺序。"""
         return [tool.name for tool in request.tools if not isinstance(tool, dict)]
 
+    @staticmethod
+    def _count_request_tools(request: ModelRequest) -> int:
+        """统计当前请求中的 LangChain 工具数量，不包含 provider 原生工具字典。"""
+        return len([tool for tool in request.tools if not isinstance(tool, dict)])
+
+    @classmethod
+    def _log_selection_attempt(cls, attempt: _ToolSelectionAttempt) -> None:
+        """按工具筛选最终状态记录稳定日志。"""
+        tool_count = cls._count_request_tools(attempt.request)
+        if attempt.status == "selected":
+            selected_text = ", ".join(attempt.selected_tool_names) or "无有效工具"
+            logger.info(f"工具筛选结果: {selected_text}")
+            return
+        if attempt.status == "empty_fallback":
+            logger.info(f"工具筛选结果为空，将恢复使用所有工具（共 {tool_count} 个）。")
+            return
+        if attempt.status == "failed_fallback":
+            logger.warning(
+                f"工具筛选失败，将恢复使用所有工具（共 {tool_count} 个）: {attempt.detail}"
+            )
+            return
+        if attempt.status == "skipped":
+            logger.info(f"工具筛选跳过: {attempt.detail}。")
+            return
+        if attempt.status == "reused":
+            selected_text = ", ".join(attempt.selected_tool_names) or "无有效工具"
+            logger.info(f"工具筛选复用已有结果: {selected_text}")
+
     @staticmethod
     def _apply_selected_tools(
             request: ModelRequest[ContextT],
@@ -517,21 +551,48 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
         这里单独抽成 helper，便于首次筛选后缓存结果，也便于测试覆盖
         “首轮筛选，后续复用”的行为。
         """
+        return (await self._aselect_request_once_with_status(request)).request
+
+    async def _aselect_request_once_with_status(
+            self, request: ModelRequest[ContextT]
+    ) -> _ToolSelectionAttempt:
+        """
+        执行一次真实工具筛选，并携带最终状态供调用方统一记录日志。
+        """
         selection_request = self._prepare_selection_request(request)
         if selection_request is None:
-            return request
+            return _ToolSelectionAttempt(
+                request=request,
+                selected_tool_names=self._extract_selected_tool_names(request),
+                status="skipped",
+                detail="没有需要筛选的工具",
+            )
 
         try:
             response = await self._aselect_tools_with_json_prompt(selection_request)
-            return self._process_selection_response(
+            modified_request = self._process_selection_response(
                 response,
                 selection_request.available_tools,
                 selection_request.valid_tool_names,
                 request,
             )
+            status = (
+                "empty_fallback"
+                if response.get("tools") == []
+                else "selected"
+            )
+            return _ToolSelectionAttempt(
+                request=modified_request,
+                selected_tool_names=self._extract_selected_tool_names(modified_request),
+                status=status,
+            )
         except Exception as err:
-            logger.warning(f"工具筛选失败，将恢复使用所有工具: {str(err)}")
-            return request
+            return _ToolSelectionAttempt(
+                request=request,
+                selected_tool_names=self._extract_selected_tool_names(request),
+                status="failed_fallback",
+                detail=str(err),
+            )
 
     async def abefore_agent(  # noqa
             self,
@@ -546,9 +607,37 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
         不会为每次模型回合重复追加一笔 selector LLM 开销。
         """
         if "selected_tool_names" in state:
+            self._log_selection_attempt(
+                _ToolSelectionAttempt(
+                    request=ModelRequest(
+                        model=self.model,
+                        tools=list(self.selection_tools),
+                        messages=state["messages"],
+                        state=state,
+                        runtime=runtime,
+                    ),
+                    selected_tool_names=state.get("selected_tool_names") or [],
+                    status="reused",
+                )
+            )
             return None
 
         if not self.selection_tools or self.model is None:
+            detail = "没有可筛选工具" if not self.selection_tools else "未配置筛选模型"
+            self._log_selection_attempt(
+                _ToolSelectionAttempt(
+                    request=ModelRequest(
+                        model=self.model,
+                        tools=list(self.selection_tools),
+                        messages=state["messages"],
+                        state=state,
+                        runtime=runtime,
+                    ),
+                    selected_tool_names=[],
+                    status="skipped",
+                    detail=detail,
+                )
+            )
             return ToolSelectionStateUpdate(selected_tool_names=None)
 
         selection_request = ModelRequest(
@@ -558,8 +647,9 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
             state=state,
             runtime=runtime,
         )
-        modified_request = await self._aselect_request_once(selection_request)
-        selected_tool_names = self._extract_selected_tool_names(modified_request)
+        attempt = await self._aselect_request_once_with_status(selection_request)
+        self._log_selection_attempt(attempt)
+        selected_tool_names = attempt.selected_tool_names
         return ToolSelectionStateUpdate(selected_tool_names=selected_tool_names or None)
 
     async def awrap_model_call(
@@ -581,8 +671,10 @@ class ToolSelectorMiddleware(LLMToolSelectorMiddleware):
                 and self.selection_tools
                 and self.model is not None
         ):
-            request = await self._aselect_request_once(request)
-            selected_tool_names = self._extract_selected_tool_names(request) or None
+            attempt = await self._aselect_request_once_with_status(request)
+            self._log_selection_attempt(attempt)
+            request = attempt.request
+            selected_tool_names = attempt.selected_tool_names or None
             request.state["selected_tool_names"] = selected_tool_names  # noqa
 
         if selected_tool_names: