Improve non-verbose agent tool summaries

app/agent/__init__.py

@@ -349,6 +349,14 @@ class MoviePilotAgent:
         except Exception as e:
             logger.debug(f"智能体输出回调失败: {e}")
 
+    def _handle_stream_text(self, text: str):
+        """
+        统一处理一段可见流式文本，确保工具统计注入后的内容会同时进入
+        消息缓冲区和外部流式回调。
+        """
+        emitted_text = self.stream_handler.emit(text)
+        self._emit_output(emitted_text)
+
     def _initialize_tools(self) -> List:
         """
         初始化工具列表
@@ -572,12 +580,13 @@ class MoviePilotAgent:
                     agent=agent,
                     messages={"messages": messages},
                     config=agent_config,
-                    on_token=lambda token: (
-                        self.stream_handler.emit(token),
-                        self._emit_output(token),
-                    ),
+                    on_token=self._handle_stream_text,
                 )
 
+                trailing_tool_summary = self.stream_handler.flush_pending_tool_summary()
+                if trailing_tool_summary:
+                    self._emit_output(trailing_tool_summary)
+
                 # 停止流式输出，返回是否已通过流式编辑发送了所有内容及最终文本
                 (
                     all_sent_via_stream,
@@ -588,8 +597,14 @@ class MoviePilotAgent:
                     # 流式输出未能发送全部内容（发送失败等）
                     # 通过常规方式发送剩余内容
                     remaining_text = await self.stream_handler.take()
-                    if remaining_text and not self._streamed_output:
-                        self._emit_output(remaining_text)
+                    if remaining_text:
+                        unsent_text = remaining_text
+                        if self._streamed_output and remaining_text.startswith(
+                            self._streamed_output
+                        ):
+                            unsent_text = remaining_text[len(self._streamed_output) :]
+                        if unsent_text:
+                            self._emit_output(unsent_text)
                     if (
                         remaining_text
                         and not self.suppress_user_reply

app/agent/callback/__init__.py

@@ -1,6 +1,6 @@
 import asyncio
 import threading
-from typing import Optional, Tuple
+from typing import Any, Optional, Tuple
 
 from fastapi.concurrency import run_in_threadpool
 
@@ -62,16 +62,30 @@ class StreamingHandler:
         self._user_id: Optional[str] = None
         self._username: Optional[str] = None
         self._title: str = ""
+        # 非啰嗦模式下的待输出工具统计，等下一段文本到来时再统一补一句摘要
+        self._pending_tool_stats: dict[str, dict[str, Any]] = {}
 
-    def emit(self, token: str):
+    def emit(self, token: str) -> str:
         """
         接收 LLM 流式 token，积累到缓冲区。
+        如果存在待输出的工具统计，则会先补上一句摘要再追加 token。
         """
         with self._lock:
+            emitted = token or ""
+
+            if self._pending_tool_stats:
+                summary = self._consume_pending_tool_summary_locked()
+                if summary:
+                    if emitted:
+                        emitted = f"{summary}{emitted.lstrip(chr(10))}"
+                    else:
+                        emitted = summary
+
             # 如果存量消息结束是两个换行，则去掉新消息前面的换行，避免过多空行
-            if self._buffer.endswith("\n\n") and token.startswith("\n"):
-                token = token.lstrip("\n")
-            self._buffer += token
+            if self._buffer.endswith("\n\n") and emitted.startswith("\n"):
+                emitted = emitted.lstrip("\n")
+            self._buffer += emitted
+            return emitted
 
     async def take(self) -> str:
         """
@@ -82,6 +96,8 @@ class StreamingHandler:
 
         注意：流式渠道不调用此方法，工具消息直接 emit 到 buffer 中。
         """
+        self.flush_pending_tool_summary()
+
         with self._lock:
             if not self._buffer:
                 return ""
@@ -99,6 +115,7 @@ class StreamingHandler:
             self._sent_text = ""
             self._message_response = None
             self._msg_start_offset = 0
+            self._pending_tool_stats = {}
 
     def reset(self):
         """
@@ -112,6 +129,7 @@ class StreamingHandler:
             self._buffer = ""
             self._sent_text = ""
             self._msg_start_offset = 0
+            self._pending_tool_stats = {}
 
     async def start_streaming(
         self,
@@ -141,6 +159,7 @@ class StreamingHandler:
         self._sent_text = ""
         self._message_response = None
         self._msg_start_offset = 0
+        self._pending_tool_stats = {}
 
         # 检查渠道是否支持消息编辑，不支持则仅收集 token 到 buffer，不实时推送
         if not self._can_stream():
@@ -176,6 +195,9 @@ class StreamingHandler:
         # 取消定时任务
         await self._cancel_flush_task()
 
+        # 将未落地的工具统计补入缓冲区，避免流式结束时丢失这段执行信息
+        self.flush_pending_tool_summary()
+
         # 执行最后一次刷新
         await self._flush()
 
@@ -194,11 +216,172 @@ class StreamingHandler:
             self._sent_text = ""
             self._message_response = None
             self._msg_start_offset = 0
+            self._pending_tool_stats = {}
             if all_sent:
                 # 所有内容已通过流式发送，清空缓冲区
                 self._buffer = ""
             return all_sent, final_text
 
+    def record_tool_call(
+        self,
+        tool_name: str,
+        tool_message: Optional[str] = None,
+        tool_kwargs: Optional[dict[str, Any]] = None,
+    ):
+        """
+        记录一次工具调用，供非啰嗦模式下延迟汇总输出。
+        """
+        category, target = self._classify_tool_call(
+            tool_name=tool_name,
+            tool_message=tool_message,
+            tool_kwargs=tool_kwargs or {},
+        )
+        with self._lock:
+            bucket = self._pending_tool_stats.setdefault(
+                category,
+                {
+                    "count": 0,
+                    "targets": set(),
+                },
+            )
+            bucket["count"] += 1
+            if target:
+                bucket["targets"].add(str(target))
+
+    def flush_pending_tool_summary(self) -> str:
+        """
+        将待输出的工具统计摘要补入缓冲区，并返回本次新增的摘要文本。
+        """
+        with self._lock:
+            summary = self._consume_pending_tool_summary_locked()
+            if summary:
+                self._buffer += summary
+            return summary
+
+    @staticmethod
+    def _classify_tool_call(
+        tool_name: str,
+        tool_message: Optional[str],
+        tool_kwargs: dict[str, Any],
+    ) -> tuple[str, Optional[str]]:
+        tool_name = (tool_name or "").strip().lower()
+        tool_message = (tool_message or "").strip()
+        tool_message_lower = tool_message.lower()
+
+        if tool_name == "read_file":
+            return "file_read", tool_kwargs.get("file_path")
+        if tool_name in {"write_file", "edit_file"}:
+            return "file_write", tool_kwargs.get("file_path")
+        if tool_name in {"list_directory", "query_directory_settings"}:
+            return "directory", tool_kwargs.get("path")
+        if tool_name == "browse_webpage":
+            return (
+                "web_browse",
+                tool_kwargs.get("url")
+                or tool_kwargs.get("target_url")
+                or tool_kwargs.get("path"),
+            )
+        if tool_name == "execute_command":
+            return "command", tool_kwargs.get("command")
+        if tool_name == "ask_user_choice":
+            return "interaction", tool_kwargs.get("message")
+        if tool_name.startswith("search_") or tool_name in {"get_search_results"}:
+            return (
+                "search",
+                tool_kwargs.get("query")
+                or tool_kwargs.get("title")
+                or tool_kwargs.get("keyword"),
+            )
+        if tool_name.startswith("query_") or tool_name.startswith("list_") or tool_name.startswith("get_"):
+            return "data_query", None
+        if tool_name.startswith(("add_", "update_", "delete_", "modify_", "run_")):
+            return "action", None
+        if tool_name in {
+            "recognize_media",
+            "scrape_metadata",
+            "transfer_file",
+            "test_site",
+            "send_message",
+            "send_local_file",
+            "send_voice_message",
+        }:
+            return "action", None
+
+        if "读取文件" in tool_message or "read file" in tool_message_lower:
+            return "file_read", tool_kwargs.get("file_path")
+        if (
+            "写入文件" in tool_message
+            or "编辑文件" in tool_message
+            or "write file" in tool_message_lower
+            or "edit file" in tool_message_lower
+        ):
+            return "file_write", tool_kwargs.get("file_path")
+        if "目录" in tool_message or "directory" in tool_message_lower:
+            return "directory", tool_kwargs.get("path")
+        if "搜索" in tool_message or "search" in tool_message_lower:
+            return (
+                "search",
+                tool_kwargs.get("query")
+                or tool_kwargs.get("title")
+                or tool_kwargs.get("keyword"),
+            )
+        if "网页" in tool_message or "browser" in tool_message_lower or "webpage" in tool_message_lower:
+            return "web_browse", tool_kwargs.get("url")
+        if "命令" in tool_message or "command" in tool_message_lower:
+            return "command", tool_kwargs.get("command")
+
+        return "tool", None
+
+    def _consume_pending_tool_summary_locked(self) -> str:
+        if not self._pending_tool_stats:
+            return ""
+
+        parts = []
+        for category, bucket in self._pending_tool_stats.items():
+            value = bucket["count"]
+            if category in {"file_read", "file_write", "directory", "web_browse"} and bucket["targets"]:
+                value = len(bucket["targets"])
+            part = self._format_tool_stat(category, value)
+            if part:
+                parts.append(part)
+
+        self._pending_tool_stats = {}
+        if not parts:
+            return ""
+
+        summary = f"（{'，'.join(parts)}）"
+        visible_buffer = self._buffer.rstrip(" \t")
+        last_char = visible_buffer[-1:] if visible_buffer.strip() else ""
+        prefix = ""
+        if self._buffer and last_char != "\n":
+            prefix = "\n"
+        return f"{prefix}{summary}\n"
+
+    @staticmethod
+    def _format_tool_stat(category: str, count: int) -> str:
+        if count <= 0:
+            return ""
+
+        if category == "search":
+            return f"执行了 {count} 次搜索"
+        if category == "file_read":
+            return f"读取了 {count} 个文件"
+        if category == "file_write":
+            return f"修改了 {count} 个文件"
+        if category == "directory":
+            return f"查看了 {count} 个目录"
+        if category == "web_browse":
+            return f"浏览了 {count} 个网页"
+        if category == "command":
+            return f"执行了 {count} 条命令"
+        if category == "data_query":
+            return f"查询了 {count} 次数据"
+        if category == "action":
+            return f"执行了 {count} 次操作"
+        if category == "interaction":
+            return f"发起了 {count} 次交互"
+        return f"调用了 {count} 次工具"
+
     def _can_stream(self) -> bool:
         """
         检查当前渠道是否支持流式输出（消息编辑）

app/agent/tools/base.py

@@ -124,9 +124,12 @@ class MoviePilotTool(BaseTool, metaclass=ABCMeta):
                         merged_message = "\n\n".join(messages)
                         await self.send_tool_message(merged_message)
             else:
-                # 非VERBOSE：工具边界至少补一个换行，避免工具前后的文本直接连在一起
-                if self._stream_handler.last_buffer_char not in ("", "\n"):
-                    self._stream_handler.emit("\n")
+                # 非VERBOSE：不逐条回显工具调用，转为在下一段文本前补一句聚合摘要
+                self._stream_handler.record_tool_call(
+                    tool_name=self.name,
+                    tool_message=tool_message,
+                    tool_kwargs=kwargs,
+                )
         else:
             # 未启用流式传输，不发送任何工具消息内容
             pass

app/api/endpoints/openai.py

@@ -69,9 +69,15 @@ class _OpenAIStreamingHandler(StreamingHandler):
         self._event_queue = queue
 
     def emit(self, token: str):
-        super().emit(token)
-        if token and self._event_queue is not None:
-            self._event_queue.put_nowait(token)
+        emitted = super().emit(token)
+        if emitted and self._event_queue is not None:
+            self._event_queue.put_nowait(emitted)
+
+    def flush_pending_tool_summary(self) -> str:
+        emitted = super().flush_pending_tool_summary()
+        if emitted and self._event_queue is not None:
+            self._event_queue.put_nowait(emitted)
+        return emitted
 
     async def start_streaming(
         self,

tests/test_agent_tool_streaming.py

@@ -9,6 +9,7 @@ if not hasattr(langchain_agents, "create_agent"):
 
 from app.agent.callback import StreamingHandler
 from app.agent.tools.base import MoviePilotTool
+from app.api.endpoints.openai import _OpenAIStreamingHandler
 from app.core.config import settings
 from app.schemas.message import MessageResponse
 from app.schemas.types import MessageChannel
@@ -37,23 +38,101 @@ class TestAgentToolStreaming(unittest.TestCase):
         buffered_message = await handler.take()
         return result, buffered_message
 
-    def test_non_verbose_tool_call_appends_newline_separator(self):
+    def test_non_verbose_tool_call_flushes_summary_on_take(self):
         result, buffered_message = asyncio.run(self._run_tool("prefix"))
 
         self.assertEqual(result, "ok")
-        self.assertEqual(buffered_message, "prefix\n")
+        self.assertEqual(buffered_message, "prefix\n（调用了 1 次工具）\n")
 
-    def test_non_verbose_tool_call_does_not_duplicate_newline(self):
+    def test_non_verbose_tool_call_reuses_existing_newline_before_summary(self):
         result, buffered_message = asyncio.run(self._run_tool("prefix\n"))
 
         self.assertEqual(result, "ok")
-        self.assertEqual(buffered_message, "prefix\n")
+        self.assertEqual(buffered_message, "prefix\n（调用了 1 次工具）\n")
 
-    def test_non_verbose_tool_call_keeps_empty_buffer_unchanged(self):
+    def test_non_verbose_tool_call_emits_summary_even_when_buffer_was_empty(self):
         result, buffered_message = asyncio.run(self._run_tool(""))
 
         self.assertEqual(result, "ok")
-        self.assertEqual(buffered_message, "")
+        self.assertEqual(buffered_message, "（调用了 1 次工具）\n")
+
+    def test_non_verbose_tool_summary_is_inserted_before_next_text(self):
+        async def _run():
+            tool = DummyTool(session_id="session-1", user_id="10001")
+            handler = StreamingHandler()
+            await handler.start_streaming()
+            handler.emit("让我来检查一下：")
+            tool.set_stream_handler(handler)
+
+            with patch.object(settings, "AI_AGENT_VERBOSE", False):
+                await tool._arun(explanation="run test tool")
+
+            handler.emit("已经拿到结果")
+            return await handler.take()
+
+        buffered_message = asyncio.run(_run())
+
+        self.assertEqual(
+            buffered_message,
+            "让我来检查一下：\n（调用了 1 次工具）\n已经拿到结果",
+        )
+
+    def test_non_verbose_tool_summary_aggregates_multiple_categories(self):
+        async def _run():
+            handler = StreamingHandler()
+            await handler.start_streaming()
+            handler.emit("处理中：")
+            handler.record_tool_call(
+                tool_name="search_web",
+                tool_message="搜索网络内容: MoviePilot",
+                tool_kwargs={"query": "MoviePilot"},
+            )
+            handler.record_tool_call(
+                tool_name="search_web",
+                tool_message="搜索网络内容: agent streaming",
+                tool_kwargs={"query": "agent streaming"},
+            )
+            handler.record_tool_call(
+                tool_name="read_file",
+                tool_message="读取文件: a.py",
+                tool_kwargs={"file_path": "/tmp/a.py"},
+            )
+            handler.record_tool_call(
+                tool_name="read_file",
+                tool_message="读取文件: b.py",
+                tool_kwargs={"file_path": "/tmp/b.py"},
+            )
+            handler.emit("继续分析")
+            return await handler.take()
+
+        buffered_message = asyncio.run(_run())
+
+        self.assertEqual(
+            buffered_message,
+            "处理中：\n（执行了 2 次搜索，读取了 2 个文件）\n继续分析",
+        )
+
+    def test_openai_streaming_handler_flushes_pending_summary_to_queue(self):
+        async def _run():
+            handler = _OpenAIStreamingHandler()
+            queue: asyncio.Queue = asyncio.Queue()
+            handler.bind_queue(queue)
+            await handler.start_streaming()
+            handler.record_tool_call(
+                tool_name="read_file",
+                tool_message="读取文件: app.py",
+                tool_kwargs={"file_path": "/tmp/app.py"},
+            )
+            emitted = handler.flush_pending_tool_summary()
+            queued = await queue.get()
+            buffered_message = await handler.take()
+            return emitted, queued, buffered_message
+
+        emitted, queued, buffered_message = asyncio.run(_run())
+
+        self.assertEqual(emitted, "（读取了 1 个文件）\n")
+        self.assertEqual(queued, emitted)
+        self.assertEqual(buffered_message, emitted)
 
     def test_flush_sends_direct_message_via_threadpool(self):
         handler = StreamingHandler()