EverMem 스타일의 영구 메모리 에이전트 OS 구축 가이드: FAISS와 SQLite를 활용한 장단기 메모리 구현

def add_memory(self, role: str, text: str, meta: Optional[Dict[str, Any]] = None) -> str:
    // ...(중략)
    conn = sqlite3.connect(self.db_path)
    cur = conn.cursor()
    cur.execute(
        "INSERT OR REPLACE INTO memories (mid, role, text, created_ts, importance, tokens_est, meta_json) VALUES (?, ?, ?, ?, ?, ?, ?)",
        (mid, role, text, created_ts, importance, tokens_est, json.dumps(meta, ensure_ascii=False)),
    )
    conn.commit()
    conn.close()
    vec = self._embed([text])
    fid = self.next_faiss_id
    self.next_faiss_id += 1
    self.index.add(vec)
    self.id_map[fid] = mid
    self._persist_faiss()
    return mid

def _importance_score(self, role: str, text: str, meta: Dict[str, Any]) -> float:
    base = 0.35
    length_bonus = min(0.45, math.log1p(len(text)) / 20.0)
    role_bonus = 0.08 if role == "user" else 0.03
    pin = 0.35 if meta.get("pinned") else 0.0
    signal = meta.get("signal", "")
    signal_bonus = 0.18 if signal in {"decision", "preference", "fact", "task"} else 0.0
    q_bonus = 0.06 if "?" in text else 0.0
    number_bonus = 0.05 if any(ch.isdigit() for ch in text) else 0.0
    return float(min(1.0, base + length_bonus + role_bonus + pin + signal_bonus + q_bonus + number_bonus))

def consolidate(self) -> Optional[str]:
    // ...(중략)
    items_sorted = sorted(items, key=lambda x: (-(x.importance + 0.15 * (1.0 / (1.0 + (_now_ts() - x.created_ts) / 3600.0))), -x.created_ts))
    picked = items_sorted[:18]
    summary = self._compress_memories(picked, max_chars=520)
    // ...(중략)
    self.add_memory(
        role="system",
        text=f"Consolidated memory: {summary}",
        meta={"signal": "consolidation", "pinned": True, "importance": 0.95},
    )
    return cid