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https://github.com/bytedance/deer-flow.git
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* feat(memory): add structured reflection and correction detection * fix(memory): align sourceError schema and prompt guidance --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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@@ -14,6 +14,21 @@ from deerflow.config.memory_config import get_memory_config
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logger = logging.getLogger(__name__)
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_UPLOAD_BLOCK_RE = re.compile(r"<uploaded_files>[\s\S]*?</uploaded_files>\n*", re.IGNORECASE)
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_CORRECTION_PATTERNS = (
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re.compile(r"\bthat(?:'s| is) (?:wrong|incorrect)\b", re.IGNORECASE),
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re.compile(r"\byou misunderstood\b", re.IGNORECASE),
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re.compile(r"\btry again\b", re.IGNORECASE),
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re.compile(r"\bredo\b", re.IGNORECASE),
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re.compile(r"不对"),
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re.compile(r"你理解错了"),
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re.compile(r"你理解有误"),
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re.compile(r"重试"),
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re.compile(r"重新来"),
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re.compile(r"换一种"),
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re.compile(r"改用"),
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)
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class MemoryMiddlewareState(AgentState):
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"""Compatible with the `ThreadState` schema."""
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@@ -21,6 +36,22 @@ class MemoryMiddlewareState(AgentState):
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pass
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def _extract_message_text(message: Any) -> str:
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"""Extract plain text from message content for filtering and signal detection."""
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content = getattr(message, "content", "")
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if isinstance(content, list):
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text_parts: list[str] = []
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for part in content:
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if isinstance(part, str):
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text_parts.append(part)
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elif isinstance(part, dict):
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text_val = part.get("text")
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if isinstance(text_val, str):
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text_parts.append(text_val)
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return " ".join(text_parts)
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return str(content)
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def _filter_messages_for_memory(messages: list[Any]) -> list[Any]:
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"""Filter messages to keep only user inputs and final assistant responses.
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@@ -44,18 +75,13 @@ def _filter_messages_for_memory(messages: list[Any]) -> list[Any]:
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Returns:
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Filtered list containing only user inputs and final assistant responses.
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"""
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_UPLOAD_BLOCK_RE = re.compile(r"<uploaded_files>[\s\S]*?</uploaded_files>\n*", re.IGNORECASE)
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filtered = []
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skip_next_ai = False
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for msg in messages:
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msg_type = getattr(msg, "type", None)
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if msg_type == "human":
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content = getattr(msg, "content", "")
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if isinstance(content, list):
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content = " ".join(p.get("text", "") for p in content if isinstance(p, dict))
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content_str = str(content)
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content_str = _extract_message_text(msg)
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if "<uploaded_files>" in content_str:
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# Strip the ephemeral upload block; keep the user's real question.
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stripped = _UPLOAD_BLOCK_RE.sub("", content_str).strip()
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@@ -87,6 +113,25 @@ def _filter_messages_for_memory(messages: list[Any]) -> list[Any]:
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return filtered
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def detect_correction(messages: list[Any]) -> bool:
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"""Detect explicit user corrections in recent conversation turns.
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The queue keeps only one pending context per thread, so callers pass the
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latest filtered message list. Checking only recent user turns keeps signal
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detection conservative while avoiding stale corrections from long histories.
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"""
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recent_user_msgs = [msg for msg in messages[-6:] if getattr(msg, "type", None) == "human"]
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for msg in recent_user_msgs:
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content = _extract_message_text(msg).strip()
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if not content:
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continue
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if any(pattern.search(content) for pattern in _CORRECTION_PATTERNS):
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return True
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return False
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class MemoryMiddleware(AgentMiddleware[MemoryMiddlewareState]):
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"""Middleware that queues conversation for memory update after agent execution.
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@@ -150,7 +195,13 @@ class MemoryMiddleware(AgentMiddleware[MemoryMiddlewareState]):
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return None
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# Queue the filtered conversation for memory update
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correction_detected = detect_correction(filtered_messages)
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queue = get_memory_queue()
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queue.add(thread_id=thread_id, messages=filtered_messages, agent_name=self._agent_name)
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queue.add(
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thread_id=thread_id,
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messages=filtered_messages,
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agent_name=self._agent_name,
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correction_detected=correction_detected,
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)
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return None
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