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fix(memory): parse wrapped memory update json responses (#3252)
* fix(memory): parse wrapped memory update json responses * test(memory): format wrapped response coverage * fix(memory): guard malformed nested memory facts * fix(memory): require full update object when parsing responses * fix(memory): fail closed on unsafe partial removals * style(memory): format updater tests
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Lawrance_YXLiao
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@ -227,6 +227,110 @@ def _extract_text(content: Any) -> str:
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return str(content)
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_REQUIRED_MEMORY_UPDATE_TOP_LEVEL_KEYS = frozenset({"user", "history", "newFacts", "factsToRemove"})
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def _normalize_memory_update_fact(fact: Any) -> dict[str, Any] | None:
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"""Normalize a single fact entry from a model-produced memory update."""
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if not isinstance(fact, dict):
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return None
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raw_content = fact.get("content")
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if not isinstance(raw_content, str):
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return None
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content = raw_content.strip()
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if not content:
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return None
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raw_category = fact.get("category")
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category = raw_category.strip() if isinstance(raw_category, str) and raw_category.strip() else "context"
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raw_confidence = fact.get("confidence", 0.5)
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if isinstance(raw_confidence, bool):
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return None
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if isinstance(raw_confidence, str):
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raw_confidence = raw_confidence.strip()
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if not raw_confidence:
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return None
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try:
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raw_confidence = float(raw_confidence)
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except ValueError:
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return None
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elif isinstance(raw_confidence, (int, float)):
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raw_confidence = float(raw_confidence)
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else:
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return None
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if not math.isfinite(raw_confidence):
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return None
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normalized_fact = {
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"content": content,
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"category": category,
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"confidence": raw_confidence,
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}
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source_error = fact.get("sourceError")
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if isinstance(source_error, str):
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normalized_source_error = source_error.strip()
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if normalized_source_error:
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normalized_fact["sourceError"] = normalized_source_error
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return normalized_fact
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def _normalize_memory_update_data(update_data: dict[str, Any]) -> dict[str, Any]:
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"""Coerce parsed memory update data into the shape consumed by _apply_updates."""
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user = update_data.get("user")
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history = update_data.get("history")
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new_facts = update_data.get("newFacts")
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facts_to_remove = update_data.get("factsToRemove")
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normalized_facts_to_remove = [fact_id for fact_id in facts_to_remove if isinstance(fact_id, str)] if isinstance(facts_to_remove, list) else []
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normalized_new_facts = []
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dropped_new_fact = not isinstance(new_facts, list)
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if isinstance(new_facts, list):
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for fact in new_facts:
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normalized_fact = _normalize_memory_update_fact(fact)
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if normalized_fact is not None:
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normalized_new_facts.append(normalized_fact)
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else:
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dropped_new_fact = True
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if normalized_facts_to_remove and dropped_new_fact:
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raise json.JSONDecodeError(
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"Unsafe partial memory update: factsToRemove with malformed newFacts",
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json.dumps(update_data, ensure_ascii=False),
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0,
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)
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return {
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"user": user if isinstance(user, dict) else {},
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"history": history if isinstance(history, dict) else {},
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"newFacts": normalized_new_facts,
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"factsToRemove": normalized_facts_to_remove,
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}
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def _parse_memory_update_response(response_content: Any) -> dict[str, Any]:
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"""Parse the first valid memory-update JSON object from an LLM response.
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Some providers may wrap JSON in thinking traces, prose, or markdown fences
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even when prompted to return JSON only. This parser accepts safely
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extractable JSON objects but does not repair truncated or malformed JSON.
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"""
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response_text = _extract_text(response_content).strip()
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decoder = json.JSONDecoder()
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for match in re.finditer(r"\{", response_text):
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try:
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parsed, _end = decoder.raw_decode(response_text[match.start() :])
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except json.JSONDecodeError:
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continue
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if isinstance(parsed, dict) and _REQUIRED_MEMORY_UPDATE_TOP_LEVEL_KEYS.issubset(parsed):
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return _normalize_memory_update_data(parsed)
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raise json.JSONDecodeError("No valid memory update JSON object found", response_text, 0)
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# Matches sentences that describe a file-upload *event* rather than general
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# file-related work. Deliberately narrow to avoid removing legitimate facts
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# such as "User works with CSV files" or "prefers PDF export".
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@ -353,13 +457,7 @@ class MemoryUpdater:
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user_id: str | None = None,
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) -> bool:
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"""Parse the model response, apply updates, and persist memory."""
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response_text = _extract_text(response_content).strip()
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if response_text.startswith("```"):
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lines = response_text.split("\n")
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response_text = "\n".join(lines[1:-1] if lines[-1] == "```" else lines[1:])
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update_data = json.loads(response_text)
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update_data = _parse_memory_update_response(response_content)
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# Deep-copy before in-place mutation so a subsequent save() failure
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# cannot corrupt the still-cached original object reference.
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updated_memory = self._apply_updates(copy.deepcopy(current_memory), update_data, thread_id)
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@ -563,6 +563,28 @@ class TestUpdateMemoryStructuredResponse:
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model.invoke = MagicMock(return_value=response)
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return model
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def _run_update_with_response(self, content):
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updater = MemoryUpdater()
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mock_storage = MagicMock()
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mock_storage.save = MagicMock(return_value=True)
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with (
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patch.object(updater, "_get_model", return_value=self._make_mock_model(content)),
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patch("deerflow.agents.memory.updater.get_memory_config", return_value=_memory_config(enabled=True, fact_confidence_threshold=0.7, max_facts=100)),
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patch("deerflow.agents.memory.updater.get_memory_data", return_value=_make_memory()),
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patch("deerflow.agents.memory.updater.get_memory_storage", return_value=mock_storage),
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):
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msg = MagicMock()
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msg.type = "human"
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msg.content = "Remember that I prefer concise updates."
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ai_msg = MagicMock()
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ai_msg.type = "ai"
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ai_msg.content = "Got it."
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ai_msg.tool_calls = []
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result = updater.update_memory([msg, ai_msg], thread_id="thread-memory")
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return result, mock_storage
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def test_string_response_parses(self):
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updater = MemoryUpdater()
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valid_json = '{"user": {}, "history": {}, "newFacts": [], "factsToRemove": []}'
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@ -609,6 +631,82 @@ class TestUpdateMemoryStructuredResponse:
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assert result is True
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def test_wrapped_json_responses_parse(self):
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"""Memory update should tolerate provider wrappers around valid JSON."""
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valid_json = '{"user": {}, "history": {}, "newFacts": [{"content": "User prefers concise updates", "category": "preference", "confidence": 0.9}], "factsToRemove": []}'
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response_variants = [
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f"<think>Analyze the conversation first.</think>\n{valid_json}",
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f"<think>Analyze the conversation first.\n{valid_json}",
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f"Here is the memory update:\n{valid_json}",
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f"{valid_json}\nDone.",
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f"```json\n{valid_json}\n```",
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]
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for content in response_variants:
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result, mock_storage = self._run_update_with_response(content)
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assert result is True
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saved_memory = mock_storage.save.call_args.args[0]
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assert saved_memory["facts"][0]["content"] == "User prefers concise updates"
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def test_ignores_unrelated_json_before_memory_update(self):
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"""Parser should not select unrelated JSON objects before the memory update."""
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valid_json = '{"user": {}, "history": {}, "newFacts": [{"content": "Remember the actual update", "category": "context", "confidence": 0.9}], "factsToRemove": []}'
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response = f'Example object: {{"user": "alice"}}\nActual memory update:\n{valid_json}'
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result, mock_storage = self._run_update_with_response(response)
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assert result is True
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saved_memory = mock_storage.save.call_args.args[0]
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assert saved_memory["facts"][0]["content"] == "Remember the actual update"
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def test_invalid_json_response_is_skipped_without_saving(self):
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"""Truncated JSON should remain a safe skipped update, not guessed repair."""
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result, mock_storage = self._run_update_with_response('{"user": {}, "history": {}, "newFacts": [')
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assert result is False
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mock_storage.save.assert_not_called()
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def test_schema_guard_ignores_invalid_update_fields(self):
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"""Parsed JSON with bad field types should not break the memory update."""
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response = '{"user": "bad", "history": [], "newFacts": ["bad", {"content": "User works on DeerFlow", "category": "context", "confidence": 0.91}], "factsToRemove": "bad"}'
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result, mock_storage = self._run_update_with_response(response)
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assert result is True
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saved_memory = mock_storage.save.call_args.args[0]
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assert [fact["content"] for fact in saved_memory["facts"]] == ["User works on DeerFlow"]
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def test_fact_schema_guard_coerces_and_filters_nested_fields(self):
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"""Malformed fact entries should be normalized per fact, not fail the whole update."""
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response = (
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'{"user": {}, "history": {}, "newFacts": ['
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'{"content": " User likes async updates ", "category": 9, "confidence": "0.91", "sourceError": " parse issue "}, '
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'{"content": "skip invalid confidence", "category": "context", "confidence": "high"}, '
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'{"content": 12, "category": "context", "confidence": 0.9}, '
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'{"content": " ", "category": "context", "confidence": 0.9}'
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'], "factsToRemove": []}'
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)
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result, mock_storage = self._run_update_with_response(response)
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assert result is True
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saved_memory = mock_storage.save.call_args.args[0]
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assert len(saved_memory["facts"]) == 1
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assert saved_memory["facts"][0]["content"] == "User likes async updates"
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assert saved_memory["facts"][0]["category"] == "context"
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assert saved_memory["facts"][0]["confidence"] == 0.91
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assert saved_memory["facts"][0]["sourceError"] == "parse issue"
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def test_malformed_replacement_update_fails_closed(self):
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"""Malformed replacement facts should not turn remove+add into delete-only."""
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response = '{"user": {}, "history": {}, "newFacts": [{"content": "replacement fact", "category": "context", "confidence": "bad"}], "factsToRemove": ["fact_old"]}'
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result, mock_storage = self._run_update_with_response(response)
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assert result is False
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mock_storage.save.assert_not_called()
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def test_async_update_memory_delegates_to_sync(self):
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"""aupdate_memory should delegate to sync _do_update_memory_sync via to_thread."""
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updater = MemoryUpdater()
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