ElasticsearchElasticsearch
​ElasticsearchCertified

Elasticsearch Embedding Store

yaml
type: "io.kestra.plugin.ai.embeddings.Elasticsearch"

Ingest documents into an Elasticsearch embedding store (requires Elasticsearch 8.15+)

yaml
id: document_ingestion
namespace: company.ai

tasks:
  - id: ingest
    type: io.kestra.plugin.ai.rag.IngestDocument
    provider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-embedding-exp-03-07
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.Elasticsearch
      connection:
        hosts:
          - http://localhost:9200
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md
Properties
Definitions
hosts*Requiredarray
SubTypestring
Min items1

List of HTTP Elasticsearch servers

Must be a URI like https://example.com: 9200 with scheme and port

basicAuth

Basic authorization configuration

passwordstring

Basic authorization password

usernamestring

Basic authorization username

headersarray
SubTypestring

List of HTTP headers to be sent with every request

Each item is a key: value string, e.g., Authorization: Token XYZ

pathPrefixstring

Path prefix for all HTTP requests

If set to /my/path, each client request becomes /my/path/ + endpoint. Useful when Elasticsearch is behind a proxy providing a base path; do not use otherwise.

strictDeprecationModebooleanstring

Treat responses with deprecation warnings as failures

trustAllSslbooleanstring

Trust all SSL CA certificates

Use this if the server uses a self-signed SSL certificate

The name of the index to store embeddings