feat: redesign memory system — two-layer architecture with grep-based retrieval
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@@ -1,109 +1,30 @@
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"""Memory system for persistent agent memory."""
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from pathlib import Path
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from datetime import datetime
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from nanobot.utils.helpers import ensure_dir, today_date
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from nanobot.utils.helpers import ensure_dir
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class MemoryStore:
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"""
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Memory system for the agent.
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Supports daily notes (memory/YYYY-MM-DD.md) and long-term memory (MEMORY.md).
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"""
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"""Two-layer memory: MEMORY.md (long-term facts) + HISTORY.md (grep-searchable log)."""
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def __init__(self, workspace: Path):
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self.workspace = workspace
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self.memory_dir = ensure_dir(workspace / "memory")
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self.memory_file = self.memory_dir / "MEMORY.md"
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def get_today_file(self) -> Path:
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"""Get path to today's memory file."""
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return self.memory_dir / f"{today_date()}.md"
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def read_today(self) -> str:
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"""Read today's memory notes."""
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today_file = self.get_today_file()
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if today_file.exists():
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return today_file.read_text(encoding="utf-8")
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return ""
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def append_today(self, content: str) -> None:
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"""Append content to today's memory notes."""
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today_file = self.get_today_file()
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if today_file.exists():
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existing = today_file.read_text(encoding="utf-8")
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content = existing + "\n" + content
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else:
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# Add header for new day
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header = f"# {today_date()}\n\n"
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content = header + content
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today_file.write_text(content, encoding="utf-8")
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self.history_file = self.memory_dir / "HISTORY.md"
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def read_long_term(self) -> str:
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"""Read long-term memory (MEMORY.md)."""
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if self.memory_file.exists():
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return self.memory_file.read_text(encoding="utf-8")
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return ""
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def write_long_term(self, content: str) -> None:
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"""Write to long-term memory (MEMORY.md)."""
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self.memory_file.write_text(content, encoding="utf-8")
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def get_recent_memories(self, days: int = 7) -> str:
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"""
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Get memories from the last N days.
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Args:
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days: Number of days to look back.
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Returns:
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Combined memory content.
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"""
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from datetime import timedelta
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memories = []
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today = datetime.now().date()
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for i in range(days):
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date = today - timedelta(days=i)
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date_str = date.strftime("%Y-%m-%d")
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file_path = self.memory_dir / f"{date_str}.md"
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if file_path.exists():
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content = file_path.read_text(encoding="utf-8")
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memories.append(content)
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return "\n\n---\n\n".join(memories)
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def list_memory_files(self) -> list[Path]:
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"""List all memory files sorted by date (newest first)."""
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if not self.memory_dir.exists():
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return []
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files = list(self.memory_dir.glob("????-??-??.md"))
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return sorted(files, reverse=True)
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def append_history(self, entry: str) -> None:
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with open(self.history_file, "a", encoding="utf-8") as f:
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f.write(entry.rstrip() + "\n\n")
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def get_memory_context(self) -> str:
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"""
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Get memory context for the agent.
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Returns:
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Formatted memory context including long-term and recent memories.
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"""
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parts = []
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# Long-term memory
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long_term = self.read_long_term()
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if long_term:
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parts.append("## Long-term Memory\n" + long_term)
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# Today's notes
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today = self.read_today()
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if today:
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parts.append("## Today's Notes\n" + today)
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return "\n\n".join(parts) if parts else ""
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return f"## Long-term Memory\n{long_term}" if long_term else ""
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