mirror of
https://github.com/bytedance/deer-flow.git
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4ba3167f48
* feat: flush memory before summarization * fix: keep agent-scoped memory on summarization flush * fix: harden summarization hook plumbing * fix: address summarization review feedback * style: format memory middleware
110 lines
4.2 KiB
Python
110 lines
4.2 KiB
Python
"""Shared helpers for turning conversations into memory update inputs."""
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from __future__ import annotations
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import re
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from copy import copy
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from typing import Any
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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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_REINFORCEMENT_PATTERNS = (
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re.compile(r"\byes[,.]?\s+(?:exactly|perfect|that(?:'s| is) (?:right|correct|it))\b", re.IGNORECASE),
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re.compile(r"\bperfect(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"\bexactly\s+(?:right|correct)\b", re.IGNORECASE),
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re.compile(r"\bthat(?:'s| is)\s+(?:exactly\s+)?(?:right|correct|what i (?:wanted|needed|meant))\b", re.IGNORECASE),
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re.compile(r"\bkeep\s+(?:doing\s+)?that\b", re.IGNORECASE),
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re.compile(r"\bjust\s+(?:like\s+)?(?:that|this)\b", re.IGNORECASE),
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re.compile(r"\bthis is (?:great|helpful)\b(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"\bthis is what i wanted\b(?:[.!?]|$)", re.IGNORECASE),
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re.compile(r"对[，,]?\s*就是这样(?:[。！？!?.]|$)"),
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re.compile(r"完全正确(?:[。！？!?.]|$)"),
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re.compile(r"(?:对[，,]?\s*)?就是这个意思(?:[。！？!?.]|$)"),
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re.compile(r"正是我想要的(?:[。！？!?.]|$)"),
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re.compile(r"继续保持(?:[。！？!?.]|$)"),
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)
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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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"""Keep only user inputs and final assistant responses for memory updates."""
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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_str = extract_message_text(msg)
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if "<uploaded_files>" in content_str:
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stripped = _UPLOAD_BLOCK_RE.sub("", content_str).strip()
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if not stripped:
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skip_next_ai = True
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continue
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clean_msg = copy(msg)
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clean_msg.content = stripped
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filtered.append(clean_msg)
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skip_next_ai = False
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else:
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filtered.append(msg)
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skip_next_ai = False
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elif msg_type == "ai":
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tool_calls = getattr(msg, "tool_calls", None)
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if not tool_calls:
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if skip_next_ai:
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skip_next_ai = False
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continue
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filtered.append(msg)
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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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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 content and 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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def detect_reinforcement(messages: list[Any]) -> bool:
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"""Detect explicit positive reinforcement signals in recent conversation turns."""
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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 content and any(pattern.search(content) for pattern in _REINFORCEMENT_PATTERNS):
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return True
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return False
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