Record streaming summaries for agent tool calls

app/agent/middleware/skills.py

@@ -3,7 +3,7 @@ import re
 import shutil
 from collections.abc import Awaitable, Callable
 from pathlib import Path
-from typing import Annotated, List, Optional
+from typing import Annotated, Any, List, Optional
 from typing import NotRequired, TypedDict
 
 import yaml  # noqa
@@ -15,6 +15,7 @@ from langchain.agents.middleware.types import (
     ModelRequest,
     ModelResponse,
     ResponseT,
+    ToolCallRequest,
 )
 from langchain.agents.middleware.types import PrivateStateAttr  # noqa
 from langchain_core.runnables import RunnableConfig
@@ -525,6 +526,7 @@ class SkillsMiddleware(AgentMiddleware[SkillsState, ContextT, ResponseT]):  # no
         *,
         sources: list[str],
         bundled_skills_dir: str | None = None,
+        stream_handler: Optional[Any] = None,
     ) -> None:
         """初始化 Skill 中间件。
 
@@ -535,9 +537,12 @@ class SkillsMiddleware(AgentMiddleware[SkillsState, ContextT, ResponseT]):  # no
         bundled_skills_dir : str | None
             项目内置技能目录路径。若提供，在首次加载前会将其中不存在于
             sources 首个目录的技能自动复制过去。
+        stream_handler : Optional[Any]
+            流式输出处理器，用于记录 skill 工具调用摘要。
         """
         self.sources = sources
         self.bundled_skills_dir = bundled_skills_dir
+        self.stream_handler = stream_handler
         self.system_prompt_template = SKILLS_SYSTEM_PROMPT
         self._skill_provider = _SkillToolProvider(sources=sources)
         self.tools = [
@@ -584,7 +589,8 @@ class SkillsMiddleware(AgentMiddleware[SkillsState, ContextT, ResponseT]):  # no
             skills_catalog=_format_skill_tool_catalog(skills)
         )
 
-    def _format_skills_list(self, skills: list[SkillMetadata]) -> str:
+    @staticmethod
+    def _format_skills_list(skills: list[SkillMetadata]) -> str:
         """格式化技能元数据列表用于系统提示词。"""
         if not skills:
             return "(No skills available yet.)"
@@ -657,5 +663,38 @@ class SkillsMiddleware(AgentMiddleware[SkillsState, ContextT, ResponseT]):  # no
         modified_request = self.modify_request(request)
         return await handler(modified_request)
 
+    async def awrap_tool_call(
+        self,
+        request: ToolCallRequest,
+        handler: Callable[[ToolCallRequest], Awaitable[Any]],
+    ) -> Any:
+        """在 skill 工具执行时记录聚合摘要。"""
+        tool = request.tool
+        tool_name = getattr(tool, "name", None)
+        if tool_name != SKILL_TOOL_NAME:
+            return await handler(request)
+
+        tool_call = request.tool_call or {}
+        tool_args = tool_call.get("args") or {}
+        if not isinstance(tool_args, dict):
+            tool_args = {}
+        logger.info(
+            f"开始执行 Skill 工具: name={tool_args.get('name') or '-'}, "
+            f"explanation={tool_args.get('explanation') or '-'}"
+        )
+        if self.stream_handler and getattr(self.stream_handler, "is_streaming", False):
+            self.stream_handler.record_tool_call(
+                tool_name=SKILL_TOOL_NAME,
+                tool_message="Skill loaded",
+                tool_kwargs=tool_args,
+            )
+        try:
+            result = await handler(request)
+        except Exception as err:
+            logger.error(f"Skill 工具执行失败: error={err}")
+            raise
+        logger.info("Skill 工具执行完成")
+        return result
+
 
 __all__ = ["SKILL_TOOL_NAME", "SkillMetadata", "SkillsMiddleware"]