""" Memory flush manager Triggers memory flush before context compaction (similar to clawdbot) """ from typing import Optional, Callable, Any from pathlib import Path from datetime import datetime class MemoryFlushManager: """ Manages memory flush operations before context compaction Similar to clawdbot's memory flush mechanism: - Triggers when context approaches token limit - Runs a silent agent turn to write memories to disk - Uses memory/YYYY-MM-DD.md for daily notes - Uses MEMORY.md (workspace root) for long-term curated memories """ def __init__( self, workspace_dir: Path, llm_model: Optional[Any] = None ): """ Initialize memory flush manager Args: workspace_dir: Workspace directory llm_model: LLM model for agent execution (optional) """ self.workspace_dir = workspace_dir self.llm_model = llm_model self.memory_dir = workspace_dir / "memory" self.memory_dir.mkdir(parents=True, exist_ok=True) # Tracking self.last_flush_token_count: Optional[int] = None self.last_flush_timestamp: Optional[datetime] = None self.turn_count: int = 0 # 对话轮数计数器 def should_flush( self, current_tokens: int = 0, token_threshold: int = 50000, turn_threshold: int = 20 ) -> bool: """ Determine if memory flush should be triggered 独立的 flush 触发机制，不依赖模型 context window: - Token 阈值: 达到 50K tokens 时触发 - 轮次阈值: 达到 20 轮对话时触发 Args: current_tokens: Current session token count token_threshold: Token threshold to trigger flush (default: 50K) turn_threshold: Turn threshold to trigger flush (default: 20) Returns: True if flush should run """ # 检查 token 阈值 if current_tokens > 0 and current_tokens >= token_threshold: # 避免重复 flush if self.last_flush_token_count is not None: if current_tokens <= self.last_flush_token_count + 5000: return False return True # 检查轮次阈值 if self.turn_count >= turn_threshold: return True return False def get_today_memory_file(self, user_id: Optional[str] = None) -> Path: """ Get today's memory file path: memory/YYYY-MM-DD.md Args: user_id: Optional user ID for user-specific memory Returns: Path to today's memory file """ today = datetime.now().strftime("%Y-%m-%d") if user_id: user_dir = self.memory_dir / "users" / user_id user_dir.mkdir(parents=True, exist_ok=True) return user_dir / f"{today}.md" else: return self.memory_dir / f"{today}.md" def get_main_memory_file(self, user_id: Optional[str] = None) -> Path: """ Get main memory file path: MEMORY.md (workspace root) Args: user_id: Optional user ID for user-specific memory Returns: Path to main memory file """ if user_id: user_dir = self.memory_dir / "users" / user_id user_dir.mkdir(parents=True, exist_ok=True) return user_dir / "MEMORY.md" else: # Return workspace root MEMORY.md return Path(self.workspace_dir) / "MEMORY.md" def create_flush_prompt(self) -> str: """ Create prompt for memory flush turn Similar to clawdbot's DEFAULT_MEMORY_FLUSH_PROMPT """ today = datetime.now().strftime("%Y-%m-%d") return ( f"Pre-compaction memory flush. " f"Store durable memories now (use memory/{today}.md for daily notes; " f"create memory/ if needed). " f"\n\n" f"重要提示:\n" f"- MEMORY.md: 记录最核心、最常用的信息（例如重要规则、偏好、决策、要求等）\n" f" 如果 MEMORY.md 过长，可以精简或移除不再重要的内容。避免冗长描述，用关键词和要点形式记录\n" f"- memory/{today}.md: 记录当天发生的事件、关键信息、经验教训、对话过程摘要等，突出重点\n" f"- 如果没有重要内容需要记录，回复 NO_REPLY\n" ) def create_flush_system_prompt(self) -> str: """ Create system prompt for memory flush turn Similar to clawdbot's DEFAULT_MEMORY_FLUSH_SYSTEM_PROMPT """ return ( "Pre-compaction memory flush turn. " "The session is near auto-compaction; capture durable memories to disk. " "\n\n" "记忆写入原则:\n" "1. MEMORY.md 精简原则: 只记录核心信息（<2000 tokens）\n" " - 记录重要规则、偏好、决策、要求等需要长期记住的关键信息，无需记录过多细节\n" " - 如果 MEMORY.md 过长，可以根据需要精简或删除过时内容\n" "\n" "2. 天级记忆 (memory/YYYY-MM-DD.md):\n" " - 记录当天的重要事件、关键信息、经验教训、对话过程摘要等，确保核心信息点被完整记录\n" "\n" "3. 判断标准:\n" " - 这个信息未来会经常用到吗？→ MEMORY.md\n" " - 这是今天的重要事件或决策吗？→ memory/YYYY-MM-DD.md\n" " - 这是临时性的、不重要的内容吗？→ 不记录\n" "\n" "You may reply, but usually NO_REPLY is correct." ) async def execute_flush( self, agent_executor: Callable, current_tokens: int, user_id: Optional[str] = None, **executor_kwargs ) -> bool: """ Execute memory flush by running a silent agent turn Args: agent_executor: Function to execute agent with prompt current_tokens: Current token count user_id: Optional user ID **executor_kwargs: Additional kwargs for agent executor Returns: True if flush completed successfully """ try: # Create flush prompts prompt = self.create_flush_prompt() system_prompt = self.create_flush_system_prompt() # Execute agent turn (silent, no user-visible reply expected) await agent_executor( prompt=prompt, system_prompt=system_prompt, silent=True, # NO_REPLY expected **executor_kwargs ) # Track flush self.last_flush_token_count = current_tokens self.last_flush_timestamp = datetime.now() self.turn_count = 0 # 重置轮数计数器 return True except Exception as e: print(f"Memory flush failed: {e}") return False def increment_turn(self): """增加对话轮数计数""" self.turn_count += 1 def get_status(self) -> dict: """Get memory flush status""" return { 'last_flush_tokens': self.last_flush_token_count, 'last_flush_time': self.last_flush_timestamp.isoformat() if self.last_flush_timestamp else None, 'today_file': str(self.get_today_memory_file()), 'main_file': str(self.get_main_memory_file()) } def create_memory_files_if_needed(workspace_dir: Path, user_id: Optional[str] = None): """ Create default memory files if they don't exist Args: workspace_dir: Workspace directory user_id: Optional user ID for user-specific files """ memory_dir = workspace_dir / "memory" memory_dir.mkdir(parents=True, exist_ok=True) # Create main MEMORY.md in workspace root if user_id: user_dir = memory_dir / "users" / user_id user_dir.mkdir(parents=True, exist_ok=True) main_memory = user_dir / "MEMORY.md" else: main_memory = Path(workspace_dir) / "MEMORY.md" if not main_memory.exists(): # Create empty file or with minimal structure (no obvious "Memory" header) # Following clawdbot's approach: memories should blend naturally into context main_memory.write_text("") # Create today's memory file today = datetime.now().strftime("%Y-%m-%d") if user_id: user_dir = memory_dir / "users" / user_id today_memory = user_dir / f"{today}.md" else: today_memory = memory_dir / f"{today}.md" if not today_memory.exists(): today_memory.write_text( f"# Daily Memory: {today}\n\n" f"Day-to-day notes and running context.\n\n" )