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Elasticsearch is a distributed, RESTful search and analytics engine. It provides a distributed, multi-tenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

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Installation and Setup

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Setup Elasticsearch

There are two ways to get started with Elasticsearch:

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Install Elasticsearch on your local machine

The easiest way to run Elasticsearch locally for development and testing is using the start-local script. This script sets up Elasticsearch using Docker with a simple one-line command. 
curl -fsSL https://elastic.co/start-local | sh
This creates an elastic-start-local folder. To start Elasticsearch: 
cd elastic-start-local
./start.sh
Elasticsearch will be available at http://localhost:9200. The password for the elastic user and API key are automatically generated and stored in the .env file in the elastic-start-local folder. If you only need Elasticsearch without Kibana, you can use the --esonly option: 
curl -fsSL https://elastic.co/start-local | sh -s -- --esonly
The start-local setup is for local testing only and should not be used in production. For production installations, refer to the official Elasticsearch documentation.

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Deploy Elasticsearch on Elastic Cloud

Elastic Cloud is a managed Elasticsearch service. Signup for a free trial.

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Install Client

pip install elasticsearch
pip install langchain-elasticsearch

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Embedding models

See a usage example. 
from langchain_elasticsearch import ElasticsearchEmbeddings

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Vector store

See a usage example. 
from langchain_elasticsearch import ElasticsearchStore

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Third-party integrations

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EcloudESVectorStore

from langchain_community.vectorstores.ecloud_vector_search import EcloudESVectorStore

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Retrievers

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ElasticsearchRetriever

The ElasticsearchRetriever enables flexible access to all Elasticsearch features through the Query DSL. See a usage example. 
from langchain_elasticsearch import ElasticsearchRetriever

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BM25

See a usage example. 
from langchain_community.retrievers import ElasticSearchBM25Retriever

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LLM cache

from langchain_elasticsearch import ElasticsearchCache

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Byte Store

See a usage example. 
from langchain_elasticsearch import ElasticsearchEmbeddingsCache

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Chain

It is a chain for interacting with Elasticsearch Database. 
from langchain_classic.chains.elasticsearch_database import ElasticsearchDatabaseChain
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