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313 lines (251 loc) · 10.4 KB
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import sys
from abc import ABC, abstractmethod
from typing import (
Optional,
Sequence,
Tuple,
)
from collections import OrderedDict
import diskcache
import llama_cpp.llama
from .llama_types import *
class BaseLlamaCache(ABC):
"""Base cache class for a llama.cpp model."""
def __init__(self, capacity_bytes: int = (2 << 30)):
self.capacity_bytes = capacity_bytes
@property
@abstractmethod
def cache_size(self) -> int:
raise NotImplementedError
def _find_longest_prefix_key(
self,
key: Tuple[int, ...],
) -> Optional[Tuple[int, ...]]:
pass
@abstractmethod
def __getitem__(self, key: Sequence[int]) -> "llama_cpp.llama.LlamaState":
raise NotImplementedError
@abstractmethod
def __contains__(self, key: Sequence[int]) -> bool:
raise NotImplementedError
@abstractmethod
def __setitem__(
self, key: Sequence[int], value: "llama_cpp.llama.LlamaState"
) -> None:
raise NotImplementedError
class LlamaRAMCache(BaseLlamaCache):
"""Cache for a llama.cpp model using RAM."""
def __init__(self, capacity_bytes: int = (2 << 30)):
super().__init__(capacity_bytes)
self.capacity_bytes = capacity_bytes
self.cache_state: OrderedDict[
Tuple[int, ...], "llama_cpp.llama.LlamaState"
] = OrderedDict()
@property
def cache_size(self):
return sum([state.llama_state_size for state in self.cache_state.values()])
def _find_longest_prefix_key(
self,
key: Tuple[int, ...],
) -> Optional[Tuple[int, ...]]:
min_len = 0
min_key = None
keys = (
(k, llama_cpp.llama.Llama.longest_token_prefix(k, key))
for k in self.cache_state.keys()
)
for k, prefix_len in keys:
if prefix_len > min_len:
min_len = prefix_len
min_key = k
return min_key
def __getitem__(self, key: Sequence[int]) -> "llama_cpp.llama.LlamaState":
key = tuple(key)
_key = self._find_longest_prefix_key(key)
if _key is None:
raise KeyError("Key not found")
value = self.cache_state[_key]
self.cache_state.move_to_end(_key)
return value
def __contains__(self, key: Sequence[int]) -> bool:
return self._find_longest_prefix_key(tuple(key)) is not None
def __setitem__(self, key: Sequence[int], value: "llama_cpp.llama.LlamaState"):
key = tuple(key)
if key in self.cache_state:
del self.cache_state[key]
self.cache_state[key] = value
while self.cache_size > self.capacity_bytes and len(self.cache_state) > 0:
self.cache_state.popitem(last=False)
class TrieNode:
"""A node in the prefix tree (Trie)."""
def __init__(self):
# Child nodes: {token_id: TrieNode}
self.children: Dict[int, "TrieNode"] = {}
# Stores the LlamaState if this node marks the end of a cached sequence.
self.state: Optional["llama_cpp.llama.LlamaState"] = None
class LlamaTrieCache(BaseLlamaCache):
"""
A Llama cache implementation using a Trie for O(K) prefix lookup
and an OrderedDict for O(1) LRU eviction.
- K = length of the query key (number of tokens)
- N = total number of items in the cache
This solves the O(N*K) lookup bottleneck of the linear scan cache.
"""
def __init__(self, capacity_bytes: int = (2 << 30)):
super().__init__(capacity_bytes)
self.root = TrieNode() # The root node of the Trie
self._current_size = 0 # O(1) tracking of cache size in bytes
# LRU Tracker:
# Key: Cached token sequence (Tuple[int, ...])
# Value: The *terminal* TrieNode for that key
self.lru_tracker: OrderedDict[
Tuple[int, ...], TrieNode
] = OrderedDict()
@property
def cache_size(self) -> int:
"""Returns the current total size of the cache in bytes (O(1))."""
return self._current_size
def _find_longest_prefix_node(
self, key: Tuple[int, ...]
) -> Tuple[Optional[TrieNode], Optional[Tuple[int, ...]]]:
"""
Finds the longest cached prefix for a given key in O(K) time.
Returns: (The matching TrieNode, The matching key)
"""
node = self.root
longest_prefix_node: Optional[TrieNode] = None
longest_prefix_key: Optional[Tuple[int, ...]] = None
current_prefix: List[int] = []
# Check if the empty prefix (root) is cached
if node.state is not None:
longest_prefix_node = node
longest_prefix_key = tuple(current_prefix)
for token in key:
if token not in node.children:
# Path ends, no further prefix matches
break
node = node.children[token]
current_prefix.append(token)
if node.state is not None:
# Found a valid, longer prefix; update our best match
longest_prefix_node = node
longest_prefix_key = tuple(current_prefix)
return longest_prefix_node, longest_prefix_key
def __getitem__(self, key: Sequence[int]) -> "llama_cpp.llama.LlamaState":
"""
Retrieves the state for the longest matching prefix in O(K) time.
Updates the LRU status.
"""
key_tuple = tuple(key)
node, prefix_key = self._find_longest_prefix_node(key_tuple)
if node is None or node.state is None or prefix_key is None:
raise KeyError(f"Key prefix not found in cache for: {key_tuple}")
# Move the accessed key to the end (most recently used) in O(1)
self.lru_tracker.move_to_end(prefix_key)
return node.state
def __contains__(self, key: Sequence[int]) -> bool:
"""Checks if any prefix of the key is cached in O(K) time."""
node, _ = self._find_longest_prefix_node(tuple(key))
return node is not None
def _prune(self, key: Tuple[int, ...]):
"""
(Helper) Removes a key and its state from the Trie.
Also removes empty parent nodes (branch pruning).
"""
path: List[Tuple[TrieNode, int]] = [] # Stores (parent_node, token)
node = self.root
# 1. Find the node and record the path
for token in key:
if token not in node.children:
return # Key not found
path.append((node, token))
node = node.children[token]
# 2. Remove the state
if node.state is None:
return # Node has no state
self._current_size -= node.state.llama_state_size
node.state = None
# 3. Prune empty parent nodes backward
for parent, token in reversed(path):
child = parent.children[token]
# If the child node is now empty (no children, no state), delete it
if not child.children and child.state is None:
del parent.children[token]
else:
# Node is still in use, stop pruning
break
def __setitem__(self, key: Sequence[int], value: "llama_cpp.llama.LlamaState"):
"""
Adds a (key, state) pair to the cache in O(K) time.
Handles LRU updates and eviction.
"""
key_tuple = tuple(key)
# 1. Find or create nodes for the key (O(K))
node = self.root
for token in key_tuple:
node = node.children.setdefault(token, TrieNode())
# 2. Check if updating an existing item
if node.state is not None:
self._current_size -= node.state.llama_state_size
# 3. Set new state and update O(1) size
node.state = value
self._current_size += value.llama_state_size
# 4. Update LRU tracker (O(1))
if key_tuple in self.lru_tracker:
self.lru_tracker.move_to_end(key_tuple)
else:
self.lru_tracker[key_tuple] = node
# 5. Eviction logic
while self._current_size > self.capacity_bytes and self.lru_tracker:
# Get the least recently used item in O(1)
evicted_key, _ = self.lru_tracker.popitem(last=False)
# Remove the evicted item from the Trie
self._prune(evicted_key)
# Alias for backwards compatibility
LlamaCache = LlamaRAMCache
class LlamaDiskCache(BaseLlamaCache):
"""Cache for a llama.cpp model using disk."""
def __init__(
self, cache_dir: str = ".cache/llama_cache", capacity_bytes: int = (2 << 30)
):
super().__init__(capacity_bytes)
self.cache = diskcache.Cache(cache_dir)
@property
def cache_size(self):
return int(self.cache.volume()) # type: ignore
def _find_longest_prefix_key(
self,
key: Tuple[int, ...],
) -> Optional[Tuple[int, ...]]:
min_len = 0
min_key: Optional[Tuple[int, ...]] = None
for k in self.cache.iterkeys(): # type: ignore
prefix_len = llama_cpp.llama.Llama.longest_token_prefix(k, key)
if prefix_len > min_len:
min_len = prefix_len
min_key = k # type: ignore
return min_key
def __getitem__(self, key: Sequence[int]) -> "llama_cpp.llama.LlamaState":
key = tuple(key)
_key = self._find_longest_prefix_key(key)
if _key is None:
raise KeyError("Key not found")
value: "llama_cpp.llama.LlamaState" = self.cache.pop(_key) # type: ignore
# NOTE: This puts an integer as key in cache, which breaks,
# Llama.longest_token_prefix(k, key) above since k is not a tuple of ints/tokens
# self.cache.push(_key, side="front") # type: ignore
return value
def __contains__(self, key: Sequence[int]) -> bool:
return self._find_longest_prefix_key(tuple(key)) is not None
def __setitem__(self, key: Sequence[int], value: "llama_cpp.llama.LlamaState"):
print("LlamaDiskCache.__setitem__: called", file=sys.stderr)
key = tuple(key)
if key in self.cache:
print("LlamaDiskCache.__setitem__: delete", file=sys.stderr)
del self.cache[key]
self.cache[key] = value
print("LlamaDiskCache.__setitem__: set", file=sys.stderr)
while self.cache_size > self.capacity_bytes and len(self.cache) > 0:
key_to_remove = next(iter(self.cache))
del self.cache[key_to_remove]
print("LlamaDiskCache.__setitem__: trim", file=sys.stderr)