update the code with review comments

Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/0b34cccd-f69a-4f68-bfa6-9a41256b63b5

Co-authored-by: WillemJiang <219644+WillemJiang@users.noreply.github.com>

backend/packages/harness/deerflow/agents/middlewares/summarization_middleware.py

@@ -10,6 +10,7 @@ from typing import Any, Protocol, override, runtime_checkable
 from langchain.agents import AgentState
 from langchain.agents.middleware import SummarizationMiddleware
 from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, RemoveMessage, ToolMessage
+from langchain_core.messages.utils import get_buffer_string
 from langgraph.config import get_config
 from langgraph.graph.message import REMOVE_ALL_MESSAGES
 from langgraph.runtime import Runtime
@@ -175,12 +176,84 @@ class DeerFlowSummarizationMiddleware(SummarizationMiddleware):
             ]
         }
 
+    @override
+    def _create_summary(self, messages_to_summarize: list[AnyMessage]) -> str:
+        """Generate summary without emitting streaming events to the client.
+
+        Suppresses callbacks to prevent the internal summarization LLM call from
+        producing visible AI message chunks in the frontend's ``messages-tuple``
+        stream (issue #2804).
+        """
+        if not messages_to_summarize:
+            return "No previous conversation history."
+
+        trimmed = self._trim_messages_for_summary(messages_to_summarize)
+        if not trimmed:
+            return "Previous conversation was too long to summarize."
+
+        formatted = get_buffer_string(trimmed)
+
+        try:
+            response = self.model.with_config(callbacks=[]).invoke(
+                self.summary_prompt.format(messages=formatted).rstrip(),
+                config={
+                    "metadata": {"lc_source": "summarization"},
+                    "callbacks": [],
+                },
+            )
+            return self._extract_summary_text(response)
+        except Exception as e:
+            return f"Error generating summary: {e!s}"
+
+    @override
+    async def _acreate_summary(self, messages_to_summarize: list[AnyMessage]) -> str:
+        """Generate summary without emitting streaming events to the client.
+
+        Suppresses callbacks to prevent the internal summarization LLM call from
+        producing visible AI message chunks in the frontend's ``messages-tuple``
+        stream (issue #2804).
+        """
+        if not messages_to_summarize:
+            return "No previous conversation history."
+
+        trimmed = self._trim_messages_for_summary(messages_to_summarize)
+        if not trimmed:
+            return "Previous conversation was too long to summarize."
+
+        formatted = get_buffer_string(trimmed)
+
+        try:
+            response = await self.model.with_config(callbacks=[]).ainvoke(
+                self.summary_prompt.format(messages=formatted).rstrip(),
+                config={
+                    "metadata": {"lc_source": "summarization"},
+                    "callbacks": [],
+                },
+            )
+            return self._extract_summary_text(response)
+        except Exception as e:
+            return f"Error generating summary: {e!s}"
+
+    def _extract_summary_text(self, response: Any) -> str:
+        # Prefer .text which normalizes list content blocks (e.g. [{"type": "text", "text": "..."}]).
+        # Fall back to .content for non-LangChain responses.
+        summary_text = getattr(response, "text", None)
+        if summary_text is None:
+            summary_text = getattr(response, "content", "")
+        return summary_text.strip() if isinstance(summary_text, str) else str(summary_text).strip()
+
     @override
     def _build_new_messages(self, summary: str) -> list[HumanMessage]:
         """Override the base implementation to let the human message with the special name 'summary'.
         And this message will be ignored to display in the frontend, but still can be used as context for the model.
         """
-        return [HumanMessage(content=f"Here is a summary of the conversation to date:\n\n{summary}", name="summary")]
+        return [
+            HumanMessage(
+                content=f"Here is a summary of the conversation to date:\n\n{summary}",
+                name="summary",
+                additional_kwargs={"hide_from_ui": True},
+            )
+        ]
 
     def _preserve_dynamic_context_reminders(
         self,

backend/tests/test_summarization_middleware.py

@@ -56,7 +56,8 @@ def _middleware(
     preserve_recent_skill_tokens_per_skill: int = 0,
 ) -> DeerFlowSummarizationMiddleware:
     model = MagicMock()
-    model.invoke.return_value = SimpleNamespace(text="compressed summary")
+    model.invoke.return_value = AIMessage(content="compressed summary")
+    model.with_config.return_value.invoke.return_value = AIMessage(content="compressed summary")
     return DeerFlowSummarizationMiddleware(
         model=model,
         trigger=trigger,
@@ -642,6 +643,69 @@ def test_memory_flush_hook_preserves_agent_scoped_memory(monkeypatch: pytest.Mon
     assert queue.add_nowait.call_args.kwargs["agent_name"] == "research-agent"
 
 
+# ---------------------------------------------------------------------------
+# Issue #2804: summary text must not leak to the frontend via streaming
+# ---------------------------------------------------------------------------
+
+
+def test_build_new_messages_sets_hide_from_ui() -> None:
+    """The summary HumanMessage must carry hide_from_ui so the frontend filters it."""
+    middleware = _middleware()
+    messages = middleware._build_new_messages("test summary")
+
+    assert len(messages) == 1
+    msg = messages[0]
+    assert msg.name == "summary"
+    assert msg.additional_kwargs.get("hide_from_ui") is True
+    assert "test summary" in msg.content
+
+
+def test_create_summary_suppresses_callbacks() -> None:
+    """_create_summary must bind callbacks=[] on the model AND pass callbacks=[]
+    in the invoke config to suppress inherited LangGraph stream callbacks."""
+    middleware = _middleware()
+
+    middleware._create_summary(_messages())
+
+    middleware.model.with_config.assert_called_once_with(callbacks=[])
+    bound = middleware.model.with_config.return_value
+    bound.invoke.assert_called_once()
+    call_config = bound.invoke.call_args.kwargs.get("config") or bound.invoke.call_args[1].get("config")
+    assert call_config is not None
+    assert call_config.get("callbacks") == []
+    assert call_config.get("metadata", {}).get("lc_source") == "summarization"
+
+
+@pytest.mark.anyio
+async def test_acreate_summary_suppresses_callbacks() -> None:
+    """_acreate_summary must bind callbacks=[] on the model AND pass callbacks=[]
+    in the ainvoke config to suppress inherited LangGraph stream callbacks."""
+    middleware = _middleware()
+    middleware.model.with_config.return_value.ainvoke = mock.AsyncMock(return_value=AIMessage(content="async summary"))
+
+    await middleware._acreate_summary(_messages())
+
+    middleware.model.with_config.assert_called_once_with(callbacks=[])
+    bound = middleware.model.with_config.return_value
+    bound.ainvoke.assert_called_once()
+    call_config = bound.ainvoke.call_args.kwargs.get("config") or bound.ainvoke.call_args[1].get("config")
+    assert call_config is not None
+    assert call_config.get("callbacks") == []
+    assert call_config.get("metadata", {}).get("lc_source") == "summarization"
+
+
+def test_before_model_summary_message_has_hide_from_ui() -> None:
+    """End-to-end: the emitted state update contains a summary message with hide_from_ui."""
+    middleware = _middleware()
+
+    result = middleware.before_model({"messages": _messages()}, _runtime())
+
+    emitted = result["messages"]
+    summary_msg = emitted[1]
+    assert summary_msg.name == "summary"
+    assert summary_msg.additional_kwargs.get("hide_from_ui") is True
+
+
 def test_memory_flush_hook_passes_runtime_user_id(monkeypatch: pytest.MonkeyPatch) -> None:
     queue = MagicMock()
     monkeypatch.setattr("deerflow.agents.memory.summarization_hook.get_memory_config", lambda: MemoryConfig(enabled=True))
@@ -659,3 +723,17 @@ def test_memory_flush_hook_passes_runtime_user_id(monkeypatch: pytest.MonkeyPatc
 
     queue.add_nowait.assert_called_once()
     assert queue.add_nowait.call_args.kwargs["user_id"] == "alice"
+
+
+def test_extract_summary_text_normalizes_list_content_blocks() -> None:
+    """AIMessage.content can be a list of content blocks; _extract_summary_text
+    must normalize to plain text via the .text property instead of producing
+    a Python repr like [{'type': 'text', 'text': 'summary'}]."""
+    middleware = _middleware()
+
+    response = AIMessage(content=[{"type": "text", "text": "A summary of the chat."}])
+    assert middleware._extract_summary_text(response) == "A summary of the chat."
+
+    # Plain string content still works
+    response_str = AIMessage(content="Plain summary")
+    assert middleware._extract_summary_text(response_str) == "Plain summary"