📦 chore(cache): add cache module with cache manager, factory, base cache, and in-memory cache implementations
✨ feat(utils.py): add cache utility functions for memoization and file saving 🐛 fix(utils.py): fix cache folder creation to use the correct cache directory 🔧 chore(utils.py): refactor code to improve readability and remove unused imports
This commit is contained in:
Gabriel Luiz Freitas Almeida
parent
63a9b01bbc
commit
d5ad152250
6 changed files with 584 additions and 0 deletions
11
src/backend/langflow/services/cache/__init__.py
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11
src/backend/langflow/services/cache/__init__.py
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from . import factory, manager
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from langflow.services.cache.manager import cache_manager
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from langflow.services.cache.flow import InMemoryCache
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__all__ = [
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"cache_manager",
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"factory",
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"manager",
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"InMemoryCache",
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]
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84
src/backend/langflow/services/cache/base.py
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84
src/backend/langflow/services/cache/base.py
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import abc
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class BaseCache(abc.ABC):
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"""
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Abstract base class for a cache.
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"""
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@abc.abstractmethod
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def get(self, key):
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"""
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Retrieve an item from the cache.
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Args:
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key: The key of the item to retrieve.
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Returns:
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The value associated with the key, or None if the key is not found.
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"""
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@abc.abstractmethod
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def set(self, key, value):
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"""
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Add an item to the cache.
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Args:
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key: The key of the item.
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value: The value to cache.
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"""
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@abc.abstractmethod
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def delete(self, key):
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"""
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Remove an item from the cache.
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Args:
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key: The key of the item to remove.
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"""
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@abc.abstractmethod
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def clear(self):
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"""
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Clear all items from the cache.
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"""
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@abc.abstractmethod
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def __contains__(self, key):
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"""
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Check if the key is in the cache.
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Args:
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key: The key of the item to check.
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Returns:
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True if the key is in the cache, False otherwise.
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"""
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@abc.abstractmethod
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def __getitem__(self, key):
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"""
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Retrieve an item from the cache using the square bracket notation.
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Args:
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key: The key of the item to retrieve.
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"""
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@abc.abstractmethod
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def __setitem__(self, key, value):
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"""
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Add an item to the cache using the square bracket notation.
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Args:
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key: The key of the item.
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value: The value to cache.
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"""
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@abc.abstractmethod
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def __delitem__(self, key):
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"""
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Remove an item from the cache using the square bracket notation.
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Args:
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key: The key of the item to remove.
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"""
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11
src/backend/langflow/services/cache/factory.py
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11
src/backend/langflow/services/cache/factory.py
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from langflow.services.cache.manager import CacheManager
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from langflow.services.factory import ServiceFactory
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class CacheManagerFactory(ServiceFactory):
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def __init__(self):
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super().__init__(CacheManager)
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def create(self, settings_service):
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# Here you would have logic to create and configure a CacheManager
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return CacheManager()
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146
src/backend/langflow/services/cache/flow.py
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src/backend/langflow/services/cache/flow.py
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import threading
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import time
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from collections import OrderedDict
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from langflow.services.cache.base import BaseCache
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class InMemoryCache(BaseCache):
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"""
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A simple in-memory cache using an OrderedDict.
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This cache supports setting a maximum size and expiration time for cached items.
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When the cache is full, it uses a Least Recently Used (LRU) eviction policy.
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Thread-safe using a threading Lock.
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Attributes:
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max_size (int, optional): Maximum number of items to store in the cache.
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expiration_time (int, optional): Time in seconds after which a cached item expires. Default is 1 hour.
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Example:
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cache = InMemoryCache(max_size=3, expiration_time=5)
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# setting cache values
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cache.set("a", 1)
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cache.set("b", 2)
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cache["c"] = 3
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# getting cache values
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a = cache.get("a")
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b = cache["b"]
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"""
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def __init__(self, max_size=None, expiration_time=60 * 60):
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"""
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Initialize a new InMemoryCache instance.
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Args:
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max_size (int, optional): Maximum number of items to store in the cache.
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expiration_time (int, optional): Time in seconds after which a cached item expires. Default is 1 hour.
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"""
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self._cache = OrderedDict()
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self._lock = threading.Lock()
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self.max_size = max_size
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self.expiration_time = expiration_time
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def get(self, key):
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"""
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Retrieve an item from the cache.
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Args:
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key: The key of the item to retrieve.
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Returns:
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The value associated with the key, or None if the key is not found or the item has expired.
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"""
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with self._lock:
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if key in self._cache:
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item = self._cache.pop(key)
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if (
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self.expiration_time is None
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or time.time() - item["time"] < self.expiration_time
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):
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# Move the key to the end to make it recently used
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self._cache[key] = item
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return item["value"]
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else:
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self.delete(key)
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return None
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def set(self, key, value):
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"""
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Add an item to the cache.
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If the cache is full, the least recently used item is evicted.
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Args:
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key: The key of the item.
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value: The value to cache.
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"""
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with self._lock:
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if key in self._cache:
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# Remove existing key before re-inserting to update order
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self.delete(key)
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elif self.max_size and len(self._cache) >= self.max_size:
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# Remove least recently used item
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self._cache.popitem(last=False)
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self._cache[key] = {"value": value, "time": time.time()}
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def get_or_set(self, key, value):
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"""
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Retrieve an item from the cache. If the item does not exist, set it with the provided value.
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Args:
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key: The key of the item.
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value: The value to cache if the item doesn't exist.
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Returns:
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The cached value associated with the key.
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"""
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with self._lock:
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if key in self._cache:
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return self.get(key)
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self.set(key, value)
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return value
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def delete(self, key):
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"""
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Remove an item from the cache.
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Args:
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key: The key of the item to remove.
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"""
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# with self._lock:
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self._cache.pop(key, None)
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def clear(self):
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"""
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Clear all items from the cache.
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"""
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with self._lock:
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self._cache.clear()
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def __contains__(self, key):
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"""Check if the key is in the cache."""
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return key in self._cache
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def __getitem__(self, key):
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"""Retrieve an item from the cache using the square bracket notation."""
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return self.get(key)
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def __setitem__(self, key, value):
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"""Add an item to the cache using the square bracket notation."""
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self.set(key, value)
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def __delitem__(self, key):
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"""Remove an item from the cache using the square bracket notation."""
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self.delete(key)
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def __len__(self):
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"""Return the number of items in the cache."""
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return len(self._cache)
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def __repr__(self):
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"""Return a string representation of the InMemoryCache instance."""
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return f"InMemoryCache(max_size={self.max_size}, expiration_time={self.expiration_time})"
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153
src/backend/langflow/services/cache/manager.py
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153
src/backend/langflow/services/cache/manager.py
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from contextlib import contextmanager
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from typing import Any, Awaitable, Callable, List, Optional
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from langflow.services.base import Service
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import pandas as pd
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from PIL import Image
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class Subject:
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"""Base class for implementing the observer pattern."""
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def __init__(self):
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self.observers: List[Callable[[], None]] = []
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def attach(self, observer: Callable[[], None]):
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"""Attach an observer to the subject."""
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self.observers.append(observer)
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def detach(self, observer: Callable[[], None]):
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"""Detach an observer from the subject."""
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self.observers.remove(observer)
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def notify(self):
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"""Notify all observers about an event."""
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for observer in self.observers:
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if observer is None:
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continue
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observer()
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class AsyncSubject:
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"""Base class for implementing the async observer pattern."""
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def __init__(self):
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self.observers: List[Callable[[], Awaitable]] = []
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def attach(self, observer: Callable[[], Awaitable]):
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"""Attach an observer to the subject."""
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self.observers.append(observer)
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def detach(self, observer: Callable[[], Awaitable]):
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"""Detach an observer from the subject."""
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self.observers.remove(observer)
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async def notify(self):
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"""Notify all observers about an event."""
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for observer in self.observers:
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if observer is None:
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continue
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await observer()
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class CacheManager(Subject, Service):
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"""Manages cache for different clients and notifies observers on changes."""
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name = "cache_manager"
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def __init__(self):
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super().__init__()
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self._cache = {}
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self.current_client_id = None
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self.current_cache = {}
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@contextmanager
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def set_client_id(self, client_id: str):
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"""
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Context manager to set the current client_id and associated cache.
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Args:
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client_id (str): The client identifier.
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"""
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previous_client_id = self.current_client_id
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self.current_client_id = client_id
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self.current_cache = self._cache.setdefault(client_id, {})
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try:
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yield
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finally:
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self.current_client_id = previous_client_id
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self.current_cache = self._cache.get(self.current_client_id, {})
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def add(self, name: str, obj: Any, obj_type: str, extension: Optional[str] = None):
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"""
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Add an object to the current client's cache.
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Args:
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name (str): The cache key.
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obj (Any): The object to cache.
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obj_type (str): The type of the object.
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"""
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object_extensions = {
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"image": "png",
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"pandas": "csv",
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}
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if obj_type in object_extensions:
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_extension = object_extensions[obj_type]
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else:
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_extension = type(obj).__name__.lower()
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self.current_cache[name] = {
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"obj": obj,
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"type": obj_type,
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"extension": extension or _extension,
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}
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self.notify()
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def add_pandas(self, name: str, obj: Any):
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"""
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Add a pandas DataFrame or Series to the current client's cache.
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Args:
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name (str): The cache key.
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obj (Any): The pandas DataFrame or Series object.
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"""
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if isinstance(obj, (pd.DataFrame, pd.Series)):
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self.add(name, obj.to_csv(), "pandas", extension="csv")
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else:
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raise ValueError("Object is not a pandas DataFrame or Series")
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def add_image(self, name: str, obj: Any, extension: str = "png"):
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"""
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Add a PIL Image to the current client's cache.
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Args:
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name (str): The cache key.
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obj (Any): The PIL Image object.
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"""
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if isinstance(obj, Image.Image):
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self.add(name, obj, "image", extension=extension)
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else:
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raise ValueError("Object is not a PIL Image")
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def get(self, name: str):
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"""
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Get an object from the current client's cache.
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Args:
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name (str): The cache key.
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Returns:
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The cached object associated with the given cache key.
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"""
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return self.current_cache[name]
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def get_last(self):
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"""
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Get the last added item in the current client's cache.
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Returns:
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The last added item in the cache.
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"""
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return list(self.current_cache.values())[-1]
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cache_manager = CacheManager()
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179
src/backend/langflow/services/cache/utils.py
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179
src/backend/langflow/services/cache/utils.py
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import base64
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import contextlib
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import functools
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import hashlib
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import json
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import os
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import tempfile
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from collections import OrderedDict
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from pathlib import Path
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from typing import Any, Dict
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from appdirs import user_cache_dir
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CACHE: Dict[str, Any] = {}
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CACHE_DIR = user_cache_dir("langflow", "langflow")
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def create_cache_folder(func):
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def wrapper(*args, **kwargs):
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# Get the destination folder
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cache_path = Path(CACHE_DIR) / PREFIX
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# Create the destination folder if it doesn't exist
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os.makedirs(cache_path, exist_ok=True)
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return func(*args, **kwargs)
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return wrapper
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def memoize_dict(maxsize=128):
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cache = OrderedDict()
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def decorator(func):
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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hashed = compute_dict_hash(args[0])
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key = (func.__name__, hashed, frozenset(kwargs.items()))
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if key not in cache:
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result = func(*args, **kwargs)
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cache[key] = result
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if len(cache) > maxsize:
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cache.popitem(last=False)
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else:
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result = cache[key]
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return result
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def clear_cache():
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cache.clear()
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wrapper.clear_cache = clear_cache # type: ignore
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wrapper.cache = cache # type: ignore
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return wrapper
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return decorator
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PREFIX = "langflow_cache"
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@create_cache_folder
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def clear_old_cache_files(max_cache_size: int = 3):
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cache_dir = Path(tempfile.gettempdir()) / PREFIX
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cache_files = list(cache_dir.glob("*.dill"))
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if len(cache_files) > max_cache_size:
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cache_files_sorted_by_mtime = sorted(
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cache_files, key=lambda x: x.stat().st_mtime, reverse=True
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)
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for cache_file in cache_files_sorted_by_mtime[max_cache_size:]:
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with contextlib.suppress(OSError):
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os.remove(cache_file)
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def compute_dict_hash(graph_data):
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graph_data = filter_json(graph_data)
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cleaned_graph_json = json.dumps(graph_data, sort_keys=True)
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return hashlib.sha256(cleaned_graph_json.encode("utf-8")).hexdigest()
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def filter_json(json_data):
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filtered_data = json_data.copy()
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# Remove 'viewport' and 'chatHistory' keys
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if "viewport" in filtered_data:
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del filtered_data["viewport"]
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if "chatHistory" in filtered_data:
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del filtered_data["chatHistory"]
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# Filter nodes
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if "nodes" in filtered_data:
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for node in filtered_data["nodes"]:
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if "position" in node:
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del node["position"]
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if "positionAbsolute" in node:
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del node["positionAbsolute"]
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if "selected" in node:
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del node["selected"]
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if "dragging" in node:
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del node["dragging"]
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return filtered_data
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@create_cache_folder
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def save_binary_file(content: str, file_name: str, accepted_types: list[str]) -> str:
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"""
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Save a binary file to the specified folder.
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Args:
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content: The content of the file as a bytes object.
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file_name: The name of the file, including its extension.
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|
||||
Returns:
|
||||
The path to the saved file.
|
||||
"""
|
||||
if not any(file_name.endswith(suffix) for suffix in accepted_types):
|
||||
raise ValueError(f"File {file_name} is not accepted")
|
||||
|
||||
# Get the destination folder
|
||||
cache_path = Path(CACHE_DIR) / PREFIX
|
||||
if not content:
|
||||
raise ValueError("Please, reload the file in the loader.")
|
||||
data = content.split(",")[1]
|
||||
decoded_bytes = base64.b64decode(data)
|
||||
|
||||
# Create the full file path
|
||||
file_path = os.path.join(cache_path, file_name)
|
||||
|
||||
# Save the binary content to the file
|
||||
with open(file_path, "wb") as file:
|
||||
file.write(decoded_bytes)
|
||||
|
||||
return file_path
|
||||
|
||||
|
||||
@create_cache_folder
|
||||
def save_uploaded_file(file, folder_name):
|
||||
"""
|
||||
Save an uploaded file to the specified folder with a hash of its content as the file name.
|
||||
|
||||
Args:
|
||||
file: The uploaded file object.
|
||||
folder_name: The name of the folder to save the file in.
|
||||
|
||||
Returns:
|
||||
The path to the saved file.
|
||||
"""
|
||||
cache_path = Path(CACHE_DIR)
|
||||
folder_path = cache_path / folder_name
|
||||
|
||||
# Create the folder if it doesn't exist
|
||||
if not folder_path.exists():
|
||||
folder_path.mkdir()
|
||||
|
||||
# Create a hash of the file content
|
||||
sha256_hash = hashlib.sha256()
|
||||
# Reset the file cursor to the beginning of the file
|
||||
file.seek(0)
|
||||
# Iterate over the uploaded file in small chunks to conserve memory
|
||||
while chunk := file.read(8192): # Read 8KB at a time (adjust as needed)
|
||||
sha256_hash.update(chunk)
|
||||
|
||||
# Use the hex digest of the hash as the file name
|
||||
hex_dig = sha256_hash.hexdigest()
|
||||
file_name = hex_dig
|
||||
|
||||
# Reset the file cursor to the beginning of the file
|
||||
file.seek(0)
|
||||
|
||||
# Save the file with the hash as its name
|
||||
file_path = folder_path / file_name
|
||||
with open(file_path, "wb") as new_file:
|
||||
while chunk := file.read(8192):
|
||||
new_file.write(chunk)
|
||||
|
||||
return file_path
|
||||
Loading…
Add table
Add a link
Reference in a new issue