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# Add Momento as a standard cache and chat message history provider This PR adds Momento as a standard caching provider. Implements the interface, adds integration tests, and documentation. We also add Momento as a chat history message provider along with integration tests, and documentation. [Momento](https://www.gomomento.com/) is a fully serverless cache. Similar to S3 or DynamoDB, it requires zero configuration, infrastructure management, and is instantly available. Users sign up for free and get 50GB of data in/out for free every month. ## Before submitting ✅ We have added documentation, notebooks, and integration tests demonstrating usage. Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
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Momento
This page covers how to use the Momento ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific Momento wrappers.
Installation and Setup
- Sign up for a free account here and get an auth token
- Install the Momento Python SDK with
pip install momento
Wrappers
Cache
The Cache wrapper allows for Momento to be used as a serverless, distributed, low-latency cache for LLM prompts and responses.
Standard Cache
The standard cache is the go-to use case for Momento users in any environment.
Import the cache as follows:
from langchain.cache import MomentoCache
And set up like so:
from datetime import timedelta
from momento import CacheClient, Configurations, CredentialProvider
import langchain
# Instantiate the Momento client
cache_client = CacheClient(
Configurations.Laptop.v1(),
CredentialProvider.from_environment_variable("MOMENTO_AUTH_TOKEN"),
default_ttl=timedelta(days=1))
# Choose a Momento cache name of your choice
cache_name = "langchain"
# Instantiate the LLM cache
langchain.llm_cache = MomentoCache(cache_client, cache_name)
Memory
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.