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community: Memcached LLM Cache Integration #27323
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efriis
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langchain-ai:master
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prokopchukdim:memcached-integration
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Merged
community: Memcached LLM Cache Integration #27323
efriis
merged 10 commits into
langchain-ai:master
from
prokopchukdim:memcached-integration
Nov 7, 2024
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## Description This PR adds support for Memcached as a usable LLM model cache by adding the ```MemcachedCache``` implementation relying on the [pymemcache](https://github.com/pinterest/pymemcache) client. Unit test-wise, the new integration is generally covered under existing import testing. All new functionality depends on pymemcache if instantiated and used, so to comply with the other cache implementations the PR also adds optional integration tests for ```MemcachedCache```. Since this is a new integration, documentation is added for Memcached as an integration and as an LLM Cache. ## Issue This PR closes langchain-ai#27275 which was originally raised as a discussion in langchain-ai#27035 ## Dependencies There are no new required dependencies for langchain, but [pymemcache](https://github.com/pinterest/pymemcache) is required to instantiate the new ```MemcachedCache```. ## Example Usage ```python3 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?") ``` --------- Co-authored-by: Erick Friis <[email protected]>
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Description
This PR adds support for Memcached as a usable LLM model cache by adding the
MemcachedCache
implementation relying on the pymemcache client.Unit test-wise, the new integration is generally covered under existing import testing. All new functionality depends on pymemcache if instantiated and used, so to comply with the other cache implementations the PR also adds optional integration tests for
MemcachedCache
.Since this is a new integration, documentation is added for Memcached as an integration and as an LLM Cache.
Issue
This PR closes #27275 which was originally raised as a discussion in #27035
Dependencies
There are no new required dependencies for langchain, but pymemcache is required to instantiate the new
MemcachedCache
.Example Usage