mirror of
https://github.com/hwchase17/langchain
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54 lines
1.5 KiB
Markdown
54 lines
1.5 KiB
Markdown
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# Momento
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This page covers how to use the [Momento](https://gomomento.com) ecosystem within LangChain.
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It is broken into two parts: installation and setup, and then references to specific Momento wrappers.
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## Installation and Setup
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- Sign up for a free account [here](https://docs.momentohq.com/getting-started) and get an auth token
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- Install the Momento Python SDK with `pip install momento`
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## Wrappers
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### Cache
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The Cache wrapper allows for [Momento](https://gomomento.com) to be used as a serverless, distributed, low-latency cache for LLM prompts and responses.
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#### Standard Cache
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The standard cache is the go-to use case for [Momento](https://gomomento.com) users in any environment.
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Import the cache as follows:
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```python
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from langchain.cache import MomentoCache
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```
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And set up like so:
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```python
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from datetime import timedelta
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from momento import CacheClient, Configurations, CredentialProvider
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import langchain
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# Instantiate the Momento client
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cache_client = CacheClient(
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Configurations.Laptop.v1(),
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CredentialProvider.from_environment_variable("MOMENTO_AUTH_TOKEN"),
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default_ttl=timedelta(days=1))
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# Choose a Momento cache name of your choice
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cache_name = "langchain"
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# Instantiate the LLM cache
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langchain.llm_cache = MomentoCache(cache_client, cache_name)
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```
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### Memory
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Momento can be used as a distributed memory store for LLMs.
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#### Chat Message History Memory
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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.
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