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Use docusaurus versioning with a callout, merged master as well @hwchase17 @baskaryan --------- Signed-off-by: Weichen Xu <weichen.xu@databricks.com> Signed-off-by: Rahul Tripathi <rauhl.psit.ec@gmail.com> Co-authored-by: Leonid Ganeline <leo.gan.57@gmail.com> Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru> Co-authored-by: Averi Kitsch <akitsch@google.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Martín Gotelli Ferenaz <martingotelliferenaz@gmail.com> Co-authored-by: Fayfox <admin@fayfox.com> Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> Co-authored-by: Dawson Bauer <105886620+djbauer2@users.noreply.github.com> Co-authored-by: Ravindu Somawansa <ravindu.somawansa@gmail.com> Co-authored-by: Dhruv Chawla <43818888+Dominastorm@users.noreply.github.com> Co-authored-by: ccurme <chester.curme@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: WeichenXu <weichen.xu@databricks.com> Co-authored-by: Benito Geordie <89472452+benitoThree@users.noreply.github.com> Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com> Co-authored-by: Kartik Sarangmath <kartik@thirdai.com> Co-authored-by: Sevin F. Varoglu <sfvaroglu@octoml.ai> Co-authored-by: MacanPN <martin.triska@gmail.com> Co-authored-by: Prashanth Rao <35005448+prrao87@users.noreply.github.com> Co-authored-by: Hyeongchan Kim <kozistr@gmail.com> Co-authored-by: sdan <git@sdan.io> Co-authored-by: Guangdong Liu <liugddx@gmail.com> Co-authored-by: Rahul Triptahi <rahul.psit.ec@gmail.com> Co-authored-by: Rahul Tripathi <rauhl.psit.ec@gmail.com> Co-authored-by: pjb157 <84070455+pjb157@users.noreply.github.com> Co-authored-by: Eun Hye Kim <ehkim1440@gmail.com> Co-authored-by: kaijietti <43436010+kaijietti@users.noreply.github.com> Co-authored-by: Pengcheng Liu <pcliu.fd@gmail.com> Co-authored-by: Tomer Cagan <tomer@tomercagan.com> Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
66 lines
2.2 KiB
Plaintext
66 lines
2.2 KiB
Plaintext
# Momento
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> [Momento Cache](https://docs.momentohq.com/) is the world's first truly serverless caching service, offering instant elasticity, scale-to-zero
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> capability, and blazing-fast performance.
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>
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> [Momento Vector Index](https://docs.momentohq.com/vector-index) stands out as the most productive, easiest-to-use, fully serverless vector index.
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>
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> 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.
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This page covers how to use the [Momento](https://gomomento.com) ecosystem within LangChain.
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## Installation and Setup
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- Sign up for a free account [here](https://console.gomomento.com/) to get an API key
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- Install the Momento Python SDK with `pip install momento`
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## Cache
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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.
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To integrate Momento Cache into your application:
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```python
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from langchain.cache import MomentoCache
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```
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Then, set it up with the following code:
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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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from langchain.globals import set_llm_cache
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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_API_KEY"),
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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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set_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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See [this notebook](/docs/integrations/memory/momento_chat_message_history) for a walkthrough of how to use Momento as a memory store for chat message history.
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```python
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from langchain.memory import MomentoChatMessageHistory
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```
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## Vector Store
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Momento Vector Index (MVI) can be used as a vector store.
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See [this notebook](/docs/integrations/vectorstores/momento_vector_index) for a walkthrough of how to use MVI as a vector store.
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```python
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from langchain_community.vectorstores import MomentoVectorIndex
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```
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