fix - clean up in memory cache

litellm/caching.py

@@ -7,14 +7,20 @@
 #
 #  Thank you users! We ❤️ you! - Krrish & Ishaan
 
-import litellm
-import time, logging, asyncio
-import json, traceback, ast, hashlib
-from typing import Optional, Literal, List, Union, Any, BinaryIO
+import ast
+import asyncio
+import hashlib
+import json
+import logging
+import time
+import traceback
+from typing import Any, BinaryIO, List, Literal, Optional, Union
+
 from openai._models import BaseModel as OpenAIObject
+
+import litellm
 from litellm._logging import verbose_logger
 from litellm.types.services import ServiceLoggerPayload, ServiceTypes
-import traceback
 
 
 def print_verbose(print_statement):
@@ -57,10 +63,12 @@ class BaseCache:
 
 
 class InMemoryCache(BaseCache):
-    def __init__(self):
+    def __init__(self, default_ttl: Optional[float] = 60.0):
         # if users don't provider one, use the default litellm cache
-        self.cache_dict = {}
-        self.ttl_dict = {}
+        self.cache_dict: dict = {}
+        self.ttl_dict: dict = {}
+        self.default_ttl = default_ttl
+        self.last_cleaned = 0  # since this is in memory we need to periodically clean it up to not overuse the machines RAM
 
     def set_cache(self, key, value, **kwargs):
         print_verbose("InMemoryCache: set_cache")
@@ -70,6 +78,8 @@ class InMemoryCache(BaseCache):
 
     async def async_set_cache(self, key, value, **kwargs):
         self.set_cache(key=key, value=value, **kwargs)
+        if time.time() > self.last_cleaned:
+            asyncio.create_task(self.clean_up_in_memory_cache())
 
     async def async_set_cache_pipeline(self, cache_list, ttl=None):
         for cache_key, cache_value in cache_list:
@@ -78,6 +88,9 @@ class InMemoryCache(BaseCache):
             else:
                 self.set_cache(key=cache_key, value=cache_value)
 
+        if time.time() > self.last_cleaned:
+            asyncio.create_task(self.clean_up_in_memory_cache())
+
     def get_cache(self, key, **kwargs):
         if key in self.cache_dict:
             if key in self.ttl_dict:
@@ -121,8 +134,26 @@ class InMemoryCache(BaseCache):
         init_value = await self.async_get_cache(key=key) or 0
         value = init_value + value
         await self.async_set_cache(key, value, **kwargs)
+
+        if time.time() > self.last_cleaned:
+            asyncio.create_task(self.clean_up_in_memory_cache())
+
         return value
 
+    async def clean_up_in_memory_cache(self):
+        """
+        Runs periodically to clean up the in-memory cache
+
+        - loop through all keys in cache, check if they are expired
+        - if yes, delete them
+        """
+        for key in list(self.cache_dict.keys()):
+            if key in self.ttl_dict:
+                if time.time() > self.ttl_dict[key]:
+                    self.cache_dict.pop(key, None)
+                    self.ttl_dict.pop(key, None)
+        self.last_cleaned = time.time()
+
     def flush_cache(self):
         self.cache_dict.clear()
         self.ttl_dict.clear()
@@ -147,10 +178,12 @@ class RedisCache(BaseCache):
         namespace: Optional[str] = None,
         **kwargs,
     ):
-        from ._redis import get_redis_client, get_redis_connection_pool
-        from litellm._service_logger import ServiceLogging
         import redis
 
+        from litellm._service_logger import ServiceLogging
+
+        from ._redis import get_redis_client, get_redis_connection_pool
+
         redis_kwargs = {}
         if host is not None:
             redis_kwargs["host"] = host
@@ -886,11 +919,10 @@ class RedisSemanticCache(BaseCache):
 
     def get_cache(self, key, **kwargs):
         print_verbose(f"sync redis semantic-cache get_cache, kwargs: {kwargs}")
-        from redisvl.query import VectorQuery
         import numpy as np
+        from redisvl.query import VectorQuery
 
         # query
-
         # get the messages
         messages = kwargs["messages"]
         prompt = "".join(message["content"] for message in messages)
@@ -943,7 +975,8 @@ class RedisSemanticCache(BaseCache):
 
     async def async_set_cache(self, key, value, **kwargs):
         import numpy as np
-        from litellm.proxy.proxy_server import llm_router, llm_model_list
+
+        from litellm.proxy.proxy_server import llm_model_list, llm_router
 
         try:
             await self.index.acreate(overwrite=False)  # don't overwrite existing index
@@ -998,12 +1031,12 @@ class RedisSemanticCache(BaseCache):
 
     async def async_get_cache(self, key, **kwargs):
         print_verbose(f"async redis semantic-cache get_cache, kwargs: {kwargs}")
-        from redisvl.query import VectorQuery
         import numpy as np
-        from litellm.proxy.proxy_server import llm_router, llm_model_list
+        from redisvl.query import VectorQuery
+
+        from litellm.proxy.proxy_server import llm_model_list, llm_router
 
         # query
-
         # get the messages
         messages = kwargs["messages"]
         prompt = "".join(message["content"] for message in messages)
@@ -1161,7 +1194,8 @@ class S3Cache(BaseCache):
         self.set_cache(key=key, value=value, **kwargs)
 
     def get_cache(self, key, **kwargs):
-        import boto3, botocore
+        import boto3
+        import botocore
 
         try:
             key = self.key_prefix + key