Elasticsearch is a powerful, open-source search and analytics engine based on Apache Lucene. It quickly stores, searches, and analyzes large amounts of data by creating indexes, rather than searching the text directly. With a document-based structure and easy-to-use REST APIs, it processes and returns data in JSON format, offering fast and scalable performance.

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Setup

Install Elasticsearch locally by running it on your machine. The simplest method is to use the official Elasticsearch Docker image. For more details, check the Elasticsearch Docker documentation.

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Example

This code initializes an ElasticsearchHandler to connect to an Elasticsearch server running on localhost with specified username and password. This setup allows for searching and managing data stored in Elasticsearch efficiently.

elastic_handler.py
import asyncio

from superagentx.handler.elastic_search import ElasticsearchHandler


async def create_index():
    elasticsearch_handler = ElasticsearchHandler(
        hosts="http://localhost:9200",
        username="<Elastic>",
        password="<Password>"
    )

    return await elasticsearch_handler.create(
        index_name="<INDEX_NAME>",
        document_id="<DOCUMENT_ID>",
        document={
            "@timestamp": "2099-11-15T13:12:00",
            "message": "GET /search HTTP/1.1 200 1070000",
        }
    )


async def main():
    res = await create_index()
    print(res)

if __name__ == '__main__':
    asyncio.run(main())

​
Result

Index Create Output:
{
  "_index": "project8",
  "_id": "project test",
  "_version": 1,
  "result": "created",
  "_shards": {
    "total": 2,
    "successful": 1,
    "failed": 0
  },
  "_seq_no": 0,
  "_primary_term": 1
}
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