Memcached is a free & open source, high-performance, distributed memory object caching system, generic in nature, but intended for use in speeding up dynamic web applications by alleviating database load.
This page covers how to use Memcached with langchain, using pymemcache as a client to connect to an already running Memcached instance.

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Installation and Setup

pip install pymemcache

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LLM Cache

To integrate a Memcached Cache into your application: 
from langchain.globals import set_llm_cache
from langchain_openai import OpenAI

from langchain_community.cache import MemcachedCache
from pymemcache.client.base import Client

llm = OpenAI(model="gpt-3.5-turbo-instruct", n=2, best_of=2)
set_llm_cache(MemcachedCache(Client('localhost')))

# The first time, it is not yet in cache, so it should take longer
llm.invoke("Which city is the most crowded city in the USA?")

# The second time it is, so it goes faster
llm.invoke("Which city is the most crowded city in the USA?")
Learn more in the example notebook