async-semantic-llm-cache/semantic_llm_cache/backends/memory.py
2026-03-06 15:54:47 +01:00

179 lines
5.6 KiB
Python

"""In-memory storage backend."""
import sys
from typing import Any, Optional
from semantic_llm_cache.backends.base import BaseBackend
from semantic_llm_cache.config import CacheEntry
from semantic_llm_cache.exceptions import CacheBackendError
class MemoryBackend(BaseBackend):
"""In-memory cache storage with LRU eviction.
All operations are in-memory dict access — no I/O — so async methods
run directly in the event loop without thread offloading.
"""
def __init__(self, max_size: Optional[int] = None) -> None:
"""Initialize memory backend.
Args:
max_size: Maximum number of entries to store (LRU eviction when reached)
"""
super().__init__()
self._cache: dict[str, CacheEntry] = {}
self._access_order: dict[str, float] = {}
self._max_size = max_size
self._access_counter: float = 0.0
def _evict_if_needed(self) -> None:
"""Evict oldest entry if at capacity."""
if self._max_size is None or len(self._cache) < self._max_size:
return
if self._access_order:
lru_key = min(self._access_order, key=lambda k: self._access_order.get(k, 0))
del self._cache[lru_key]
del self._access_order[lru_key]
def _update_access_time(self, key: str) -> None:
"""Update access time for LRU tracking."""
self._access_counter += 1
self._access_order[key] = self._access_counter
async def get(self, key: str) -> Optional[CacheEntry]:
"""Retrieve cache entry by key.
Args:
key: Cache key to retrieve
Returns:
CacheEntry if found and not expired, None otherwise
"""
try:
entry = self._cache.get(key)
if entry is None:
self._increment_misses()
return None
if self._check_expired(entry):
await self.delete(key)
self._increment_misses()
return None
self._increment_hits()
self._update_access_time(key)
entry.hit_count += 1
return entry
except Exception as e:
raise CacheBackendError(f"Failed to get entry: {e}") from e
async def set(self, key: str, entry: CacheEntry) -> None:
"""Store cache entry.
Args:
key: Cache key to store under
entry: CacheEntry to store
"""
try:
self._evict_if_needed()
self._cache[key] = entry
self._update_access_time(key)
except Exception as e:
raise CacheBackendError(f"Failed to set entry: {e}") from e
async def delete(self, key: str) -> bool:
"""Delete cache entry.
Args:
key: Cache key to delete
Returns:
True if entry was deleted, False if not found
"""
try:
if key in self._cache:
del self._cache[key]
self._access_order.pop(key, None)
return True
return False
except Exception as e:
raise CacheBackendError(f"Failed to delete entry: {e}") from e
async def clear(self) -> None:
"""Clear all cache entries."""
try:
self._cache.clear()
self._access_order.clear()
except Exception as e:
raise CacheBackendError(f"Failed to clear cache: {e}") from e
async def iterate(
self, namespace: Optional[str] = None
) -> list[tuple[str, CacheEntry]]:
"""Iterate over cache entries, optionally filtered by namespace.
Args:
namespace: Optional namespace filter
Returns:
List of (key, entry) tuples
"""
try:
if namespace is None:
return list(self._cache.items())
return [
(k, v)
for k, v in self._cache.items()
if v.namespace == namespace and not self._check_expired(v)
]
except Exception as e:
raise CacheBackendError(f"Failed to iterate entries: {e}") from e
async def find_similar(
self,
embedding: list[float],
threshold: float,
namespace: Optional[str] = None,
) -> Optional[tuple[str, CacheEntry, float]]:
"""Find semantically similar cached entry.
Args:
embedding: Query embedding vector
threshold: Minimum similarity score (0-1)
namespace: Optional namespace filter
Returns:
(key, entry, similarity) tuple if found above threshold, None otherwise
"""
try:
candidates = [
(k, v)
for k, v in self._cache.items()
if v.embedding is not None
and not self._check_expired(v)
and (namespace is None or v.namespace == namespace)
]
return self._find_best_match(candidates, embedding, threshold)
except Exception as e:
raise CacheBackendError(f"Failed to find similar entry: {e}") from e
async def get_stats(self) -> dict[str, Any]:
"""Get backend statistics.
Returns:
Dictionary with size, memory usage, hits, misses
"""
base_stats = await super().get_stats()
memory_usage = sys.getsizeof(self._cache) + sum(
sys.getsizeof(k) + sys.getsizeof(v) for k, v in self._cache.items()
)
return {
**base_stats,
"size": len(self._cache),
"memory_bytes": memory_usage,
"max_size": self._max_size,
}