langchain/docs/integrations/momento.md
Michael Landis 7047a2c1af
feat: add Momento as a standard cache and chat message history provider (#5221)
# 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>
2023-05-25 19:13:21 -07:00

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Markdown

# Momento
This page covers how to use the [Momento](https://gomomento.com) 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](https://docs.momentohq.com/getting-started) and get an auth token
- Install the Momento Python SDK with `pip install momento`
## Wrappers
### Cache
The Cache wrapper allows for [Momento](https://gomomento.com) 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](https://gomomento.com) users in any environment.
Import the cache as follows:
```python
from langchain.cache import MomentoCache
```
And set up like so:
```python
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](../modules/memory/examples/momento_chat_message_history.ipynb) for a walkthrough of how to use Momento as a memory store for chat message history.