# Elasticsearch

> [Elasticsearch](https://www.elastic.co/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.

## Installation and Setup

There are two ways to get started with Elasticsearch:

#### Install Elasticsearch on your local machine via docker

Example: Run a single-node Elasticsearch instance with security disabled. This is not recommended for production use.

```bash
    docker run -p 9200:9200 -e "discovery.type=single-node" -e "xpack.security.enabled=false" -e "xpack.security.http.ssl.enabled=false" docker.elastic.co/elasticsearch/elasticsearch:8.9.0
```

#### Deploy Elasticsearch on Elastic Cloud

Elastic Cloud is a managed Elasticsearch service. Signup for a [free trial](https://cloud.elastic.co/registration?storm=langchain-notebook).

### Install Client

```bash
pip install elasticsearch
```

## Vector Store

The vector store is a simple wrapper around Elasticsearch. It provides a simple interface to store and retrieve vectors.

```python
from langchain.vectorstores import ElasticsearchStore

from langchain.document_loaders import TextLoader
from langchain.text_splitter import CharacterTextSplitter

loader = TextLoader("./state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

embeddings = OpenAIEmbeddings()

db = ElasticsearchStore.from_documents(
    docs, embeddings, es_url="http://localhost:9200", index_name="test-basic",
)

db.client.indices.refresh(index="test-basic")

query = "What did the president say about Ketanji Brown Jackson"
results = db.similarity_search(query)
```