fix(memory): preserve summaries when extraction returns invalid types (#8192)

Co-authored-by: xiaoyi <xyi74976-del@users.noreply.github.com>

backend/packages/harness/deerflow/agents/memory/backends/deermem/deermem/core/updater.py

@@ -2206,7 +2206,7 @@ class MemoryUpdater:
         user_updates = update_data.get("user", {})
         for section in ["workContext", "personalContext", "topOfMind", "cognitiveStyle"]:
             section_data = user_updates.get(section, {})
-            if not isinstance(section_data, dict) or not section_data.get("shouldUpdate") or not section_data.get("summary"):
+            if not isinstance(section_data, dict) or not section_data.get("shouldUpdate") or not isinstance(section_data.get("summary"), str) or not section_data["summary"]:
                 continue
             rejection_reason = _summary_scope_gate_reason(section_data)
             if rejection_reason is not None:
@@ -2221,7 +2221,7 @@ class MemoryUpdater:
         history_updates = update_data.get("history", {})
         for section in ["recentMonths", "earlierContext", "longTermBackground"]:
             section_data = history_updates.get(section, {})
-            if not isinstance(section_data, dict) or not section_data.get("shouldUpdate") or not section_data.get("summary"):
+            if not isinstance(section_data, dict) or not section_data.get("shouldUpdate") or not isinstance(section_data.get("summary"), str) or not section_data["summary"]:
                 continue
             rejection_reason = _summary_scope_gate_reason(section_data)
             if rejection_reason is not None:

backend/tests/test_memory_summary_value_types.py

@@ -0,0 +1,109 @@
+"""Malformed extractor summaries preserve existing user-global memory."""
+
+import json
+from pathlib import Path
+from typing import Any
+
+import pytest
+from langchain_core.messages import AIMessage, HumanMessage
+
+from deerflow.agents.memory.backends.deermem.deermem.config import DeerMemConfig
+from deerflow.agents.memory.backends.deermem.deermem.core.storage import (
+    FileMemoryStorage,
+)
+from deerflow.agents.memory.backends.deermem.deermem.core.updater import MemoryUpdater
+
+_SUMMARY_SECTIONS = [
+    ("user", "workContext"),
+    ("user", "personalContext"),
+    ("user", "topOfMind"),
+    ("user", "cognitiveStyle"),
+    ("history", "recentMonths"),
+    ("history", "earlierContext"),
+    ("history", "longTermBackground"),
+]
+
+
+class _Extractor:
+    def __init__(self, response: dict[str, Any]):
+        self.response = response
+        self.calls = 0
+
+    def invoke(self, prompt: Any, config: Any = None) -> AIMessage:
+        self.calls += 1
+        return AIMessage(content=json.dumps(self.response))
+
+
+@pytest.mark.parametrize("group,section", _SUMMARY_SECTIONS)
+@pytest.mark.parametrize(
+    "summary",
+    [
+        pytest.param(["Software engineer"], id="list"),
+        pytest.param({"occupation": "engineer"}, id="object"),
+        pytest.param(42, id="integer"),
+        pytest.param(1.5, id="float"),
+        pytest.param(True, id="boolean"),
+        pytest.param(None, id="null"),
+        pytest.param("", id="empty"),
+        pytest.param("Updated valid text", id="string"),
+    ],
+)
+def test_extracted_summary_value_preserves_memory_and_consumes_batch(tmp_path: Path, group: str, section: str, summary: Any) -> None:
+    config = DeerMemConfig(storage_path=str(tmp_path), retrieval_adapter="")
+    storage = FileMemoryStorage(config)
+    previous = {
+        "summary": "User is a software engineer",
+        "updatedAt": "2026-11-01T00:00:00Z",
+    }
+    storage.update_summaries({group: {section: previous}}, user_id="alice")
+    assert storage.reload("researcher", user_id="alice")[group][section] == previous
+
+    # A valid sibling update and fact must still commit beside a bad section.
+    sibling_group, sibling_section = ("history", "recentMonths") if group == "user" else ("user", "workContext")
+    response: dict[str, Any] = {
+        "user": {},
+        "history": {},
+        "newFacts": [
+            {
+                "content": "User prefers dark mode",
+                "category": "preference",
+                "confidence": 0.9,
+                "scope": "user",
+                "durability": "durable",
+                "authority": "descriptive",
+            }
+        ],
+    }
+    response[group][section] = {
+        "shouldUpdate": True,
+        "summary": summary,
+        "scope": "user",
+        "authority": "descriptive",
+    }
+    response[sibling_group][sibling_section] = {
+        "shouldUpdate": True,
+        "summary": "User prefers concise updates",
+        "scope": "user",
+        "authority": "descriptive",
+    }
+    model = _Extractor(response)
+    messages = [HumanMessage(content="Please remember that I prefer dark mode", id="message-1")]
+    updater = MemoryUpdater(config, storage, model)
+
+    assert updater.update_memory(messages, thread_id="thread-1", agent_name="researcher", user_id="alice") is True
+
+    # Reopen real storage so cache state cannot conceal a corrupted manifest.
+    reopened = FileMemoryStorage(config)
+    document = reopened.reload("researcher", user_id="alice")
+    assert [fact["content"] for fact in document["facts"]] == ["User prefers dark mode"]
+    assert document[sibling_group][sibling_section]["summary"] == "User prefers concise updates"
+    if isinstance(summary, str) and summary:
+        assert document[group][section]["summary"] == "Updated valid text"
+        assert document[group][section]["updatedAt"] != previous["updatedAt"]
+    else:
+        assert document[group][section] == previous
+
+    # The persisted watermark also survives a restart, avoiding paid re-extraction.
+    restarted_updater = MemoryUpdater(config, reopened, model)
+    assert restarted_updater.update_memory(messages, thread_id="thread-1", agent_name="researcher", user_id="alice") is True
+    assert model.calls == 1

docs/guide/memory.md

@@ -5,6 +5,10 @@ counter, including the omission marker and retained facts. Mixed-language text
 does not rely on an average character/token ratio; the existing guaranteed-fact
 allowance remains unchanged.
 
+Automatic DeerMem summary updates accept only nonempty strings. An invalid
+summary value preserves the existing section and its timestamp while valid facts
+and other summaries in the same extraction response can still be saved.
+
 Settings > Appearance > Language also supplies the preferred language for replies
 and new automatic DeerMem facts and summary updates on subsequent chat turns and
 replays. Explicit user language requests take precedence. Existing memories are