Momento Cache is the world's first truly serverless caching service, offering instant elasticity, scale-to-zero capability, and blazing-fast performance.
Momento Vector Index stands out as the most productive, easiest-to-use, fully serverless vector index.
For both services, simply grab the SDK, obtain an API key, input a few lines into your code, and you're set to go. Together, they provide a comprehensive solution for your LLM data needs.
This page covers how to use the Momento ecosystem within LangChain.
Installation and Setup
- Sign up for a free account here to get an API key
- Install the Momento Python SDK with
pip install momento
Use Momento as a serverless, distributed, low-latency cache for LLM prompts and responses. The standard cache is the primary use case for Momento users in any environment.
To integrate Momento Cache into your application:
from langchain.cache import MomentoCache
Then, set it up with the following code:
from datetime import timedelta
from momento import CacheClient, Configurations, CredentialProvider
from langchain.globals import set_llm_cache
# Instantiate the Momento client
cache_client = CacheClient(
# Choose a Momento cache name of your choice
cache_name = "langchain"
# Instantiate the LLM cache
Momento can be used as a distributed memory store for LLMs.
Chat Message History Memory
See this notebook for a walkthrough of how to use Momento as a memory store for chat message history.
Momento Vector Index (MVI) can be used as a vector store.
See this notebook for a walkthrough of how to use MVI as a vector store.