feat(memory): implement caching layer for memory operations (#98)
Add comprehensive caching layer for the Agent Memory System: - HotMemoryCache: LRU cache for frequently accessed memories - Python 3.12 type parameter syntax - Thread-safe operations with RLock - TTL-based expiration - Access count tracking for hot memory identification - Scoped invalidation by type, scope, or pattern - EmbeddingCache: Cache embeddings by content hash - Content-hash based deduplication - Optional Redis backing for persistence - LRU eviction with configurable max size - CachedEmbeddingGenerator wrapper for transparent caching - CacheManager: Unified cache management - Coordinates hot cache, embedding cache, and retrieval cache - Centralized invalidation across all caches - Aggregated statistics and hit rate tracking - Automatic cleanup scheduling - Cache warmup support Performance targets: - Cache hit rate > 80% for hot memories - Cache operations < 1ms (memory), < 5ms (Redis) 83 new tests with comprehensive coverage. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
463
backend/app/services/memory/cache/hot_cache.py
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463
backend/app/services/memory/cache/hot_cache.py
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# app/services/memory/cache/hot_cache.py
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"""
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Hot Memory Cache.
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LRU cache for frequently accessed memories.
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Provides fast access to recently used memories without database queries.
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"""
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import logging
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import threading
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from collections import OrderedDict
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from dataclasses import dataclass
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from datetime import UTC, datetime
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from typing import Any
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from uuid import UUID
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logger = logging.getLogger(__name__)
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def _utcnow() -> datetime:
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"""Get current UTC time as timezone-aware datetime."""
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return datetime.now(UTC)
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@dataclass
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class CacheEntry[T]:
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"""A cached memory entry with metadata."""
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value: T
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created_at: datetime
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last_accessed_at: datetime
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access_count: int = 1
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ttl_seconds: float = 300.0
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def is_expired(self) -> bool:
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"""Check if this entry has expired."""
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age = (_utcnow() - self.created_at).total_seconds()
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return age > self.ttl_seconds
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def touch(self) -> None:
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"""Update access time and count."""
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self.last_accessed_at = _utcnow()
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self.access_count += 1
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@dataclass
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class CacheKey:
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"""A structured cache key with components."""
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memory_type: str
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memory_id: str
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scope: str | None = None
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def __hash__(self) -> int:
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return hash((self.memory_type, self.memory_id, self.scope))
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def __eq__(self, other: object) -> bool:
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if not isinstance(other, CacheKey):
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return False
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return (
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self.memory_type == other.memory_type
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and self.memory_id == other.memory_id
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and self.scope == other.scope
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)
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def __str__(self) -> str:
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if self.scope:
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return f"{self.memory_type}:{self.scope}:{self.memory_id}"
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return f"{self.memory_type}:{self.memory_id}"
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@dataclass
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class HotCacheStats:
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"""Statistics for the hot memory cache."""
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hits: int = 0
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misses: int = 0
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evictions: int = 0
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expirations: int = 0
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current_size: int = 0
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max_size: int = 0
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@property
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def hit_rate(self) -> float:
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"""Calculate cache hit rate."""
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total = self.hits + self.misses
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if total == 0:
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return 0.0
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return self.hits / total
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def to_dict(self) -> dict[str, Any]:
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"""Convert to dictionary."""
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return {
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"hits": self.hits,
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"misses": self.misses,
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"evictions": self.evictions,
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"expirations": self.expirations,
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"current_size": self.current_size,
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"max_size": self.max_size,
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"hit_rate": self.hit_rate,
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}
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class HotMemoryCache[T]:
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"""
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LRU cache for frequently accessed memories.
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Features:
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- LRU eviction when capacity is reached
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- TTL-based expiration
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- Access count tracking for hot memory identification
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- Thread-safe operations
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- Scoped invalidation
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Performance targets:
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- Cache hit rate > 80% for hot memories
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- Get/put operations < 1ms
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"""
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def __init__(
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self,
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max_size: int = 10000,
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default_ttl_seconds: float = 300.0,
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) -> None:
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"""
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Initialize the hot memory cache.
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Args:
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max_size: Maximum number of entries
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default_ttl_seconds: Default TTL for entries (5 minutes)
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"""
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self._max_size = max_size
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self._default_ttl = default_ttl_seconds
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self._cache: OrderedDict[CacheKey, CacheEntry[T]] = OrderedDict()
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self._lock = threading.RLock()
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self._stats = HotCacheStats(max_size=max_size)
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logger.info(
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f"Initialized HotMemoryCache with max_size={max_size}, "
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f"ttl={default_ttl_seconds}s"
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)
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def get(self, key: CacheKey) -> T | None:
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"""
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Get a memory from cache.
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Args:
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key: Cache key
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Returns:
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Cached value or None if not found/expired
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"""
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with self._lock:
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if key not in self._cache:
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self._stats.misses += 1
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return None
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entry = self._cache[key]
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# Check expiration
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if entry.is_expired():
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del self._cache[key]
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self._stats.expirations += 1
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self._stats.misses += 1
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self._stats.current_size = len(self._cache)
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return None
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# Move to end (most recently used)
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self._cache.move_to_end(key)
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entry.touch()
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self._stats.hits += 1
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return entry.value
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def get_by_id(
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self,
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memory_type: str,
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memory_id: UUID | str,
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scope: str | None = None,
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) -> T | None:
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"""
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Get a memory by type and ID.
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Args:
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memory_type: Type of memory (episodic, semantic, procedural)
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memory_id: Memory ID
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scope: Optional scope (project_id, agent_id)
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Returns:
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Cached value or None if not found/expired
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"""
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key = CacheKey(
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memory_type=memory_type,
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memory_id=str(memory_id),
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scope=scope,
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)
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return self.get(key)
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def put(
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self,
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key: CacheKey,
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value: T,
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ttl_seconds: float | None = None,
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) -> None:
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"""
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Put a memory into cache.
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Args:
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key: Cache key
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value: Value to cache
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ttl_seconds: Optional TTL override
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"""
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with self._lock:
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# Evict if at capacity
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self._evict_if_needed()
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now = _utcnow()
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entry = CacheEntry(
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value=value,
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created_at=now,
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last_accessed_at=now,
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access_count=1,
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ttl_seconds=ttl_seconds or self._default_ttl,
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)
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self._cache[key] = entry
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self._cache.move_to_end(key)
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self._stats.current_size = len(self._cache)
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def put_by_id(
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self,
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memory_type: str,
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memory_id: UUID | str,
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value: T,
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scope: str | None = None,
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ttl_seconds: float | None = None,
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) -> None:
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"""
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Put a memory by type and ID.
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Args:
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memory_type: Type of memory
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memory_id: Memory ID
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value: Value to cache
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scope: Optional scope
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ttl_seconds: Optional TTL override
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"""
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key = CacheKey(
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memory_type=memory_type,
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memory_id=str(memory_id),
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scope=scope,
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)
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self.put(key, value, ttl_seconds)
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def _evict_if_needed(self) -> None:
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"""Evict entries if cache is at capacity."""
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while len(self._cache) >= self._max_size:
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# Remove least recently used (first item)
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if self._cache:
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self._cache.popitem(last=False)
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self._stats.evictions += 1
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def invalidate(self, key: CacheKey) -> bool:
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"""
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Invalidate a specific cache entry.
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Args:
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key: Cache key to invalidate
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Returns:
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True if entry was found and removed
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"""
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with self._lock:
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if key in self._cache:
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del self._cache[key]
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self._stats.current_size = len(self._cache)
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return True
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return False
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def invalidate_by_id(
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self,
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memory_type: str,
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memory_id: UUID | str,
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scope: str | None = None,
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) -> bool:
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"""
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Invalidate a memory by type and ID.
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Args:
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memory_type: Type of memory
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memory_id: Memory ID
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scope: Optional scope
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Returns:
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True if entry was found and removed
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"""
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key = CacheKey(
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memory_type=memory_type,
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memory_id=str(memory_id),
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scope=scope,
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)
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return self.invalidate(key)
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def invalidate_by_type(self, memory_type: str) -> int:
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"""
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Invalidate all entries of a memory type.
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Args:
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memory_type: Type of memory to invalidate
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Returns:
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Number of entries invalidated
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"""
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with self._lock:
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keys_to_remove = [
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k for k in self._cache.keys() if k.memory_type == memory_type
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]
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for key in keys_to_remove:
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del self._cache[key]
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self._stats.current_size = len(self._cache)
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return len(keys_to_remove)
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def invalidate_by_scope(self, scope: str) -> int:
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"""
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Invalidate all entries in a scope.
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Args:
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scope: Scope to invalidate (e.g., project_id)
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Returns:
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Number of entries invalidated
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"""
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with self._lock:
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keys_to_remove = [k for k in self._cache.keys() if k.scope == scope]
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for key in keys_to_remove:
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del self._cache[key]
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self._stats.current_size = len(self._cache)
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return len(keys_to_remove)
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def invalidate_pattern(self, pattern: str) -> int:
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"""
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Invalidate entries matching a pattern.
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Pattern can include * as wildcard.
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Args:
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pattern: Pattern to match (e.g., "episodic:*")
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Returns:
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Number of entries invalidated
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"""
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import fnmatch
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with self._lock:
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keys_to_remove = [
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k for k in self._cache.keys() if fnmatch.fnmatch(str(k), pattern)
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]
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for key in keys_to_remove:
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del self._cache[key]
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self._stats.current_size = len(self._cache)
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return len(keys_to_remove)
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def clear(self) -> int:
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"""
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Clear all cache entries.
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Returns:
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Number of entries cleared
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"""
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with self._lock:
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count = len(self._cache)
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self._cache.clear()
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self._stats.current_size = 0
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logger.info(f"Cleared {count} entries from hot cache")
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return count
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def cleanup_expired(self) -> int:
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"""
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Remove all expired entries.
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Returns:
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Number of entries removed
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"""
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with self._lock:
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keys_to_remove = [
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k for k, v in self._cache.items() if v.is_expired()
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]
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for key in keys_to_remove:
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del self._cache[key]
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self._stats.expirations += 1
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self._stats.current_size = len(self._cache)
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if keys_to_remove:
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logger.debug(f"Cleaned up {len(keys_to_remove)} expired entries")
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return len(keys_to_remove)
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def get_hot_memories(self, limit: int = 10) -> list[tuple[CacheKey, int]]:
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"""
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Get the most frequently accessed memories.
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Args:
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limit: Maximum number of memories to return
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Returns:
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List of (key, access_count) tuples sorted by access count
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"""
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with self._lock:
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entries = [
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(k, v.access_count)
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for k, v in self._cache.items()
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if not v.is_expired()
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]
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entries.sort(key=lambda x: x[1], reverse=True)
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return entries[:limit]
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def get_stats(self) -> HotCacheStats:
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"""Get cache statistics."""
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with self._lock:
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self._stats.current_size = len(self._cache)
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return self._stats
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def reset_stats(self) -> None:
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"""Reset cache statistics."""
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with self._lock:
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self._stats = HotCacheStats(
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max_size=self._max_size,
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current_size=len(self._cache),
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)
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@property
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def size(self) -> int:
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"""Get current cache size."""
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return len(self._cache)
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@property
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def max_size(self) -> int:
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"""Get maximum cache size."""
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return self._max_size
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# Factory function for typed caches
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def create_hot_cache(
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max_size: int = 10000,
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default_ttl_seconds: float = 300.0,
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) -> HotMemoryCache[Any]:
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"""
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Create a hot memory cache.
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Args:
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max_size: Maximum number of entries
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default_ttl_seconds: Default TTL for entries
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Returns:
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Configured HotMemoryCache instance
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"""
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return HotMemoryCache(
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max_size=max_size,
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default_ttl_seconds=default_ttl_seconds,
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)
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