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This plugin is currently in beta. While it is considered safe for use, please be aware that its API could change in ways that are not compatible with earlier versions in future releases, or it might become unsupported.

yaml
type: "io.kestra.plugin.langchain4j.rag.search"

Examples

yaml
id: search_embeddings_flow
namespace: company.team

tasks:
  - id: ingest
    type: io.kestra.plugin.langchain4j.rag.IngestDocument
    provider:
      type: io.kestra.plugin.langchain4j.provider.GoogleGemini
      modelName: gemini-embedding-exp-03-07
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.langchain4j.embeddings.KestraKVStore
    drop: true
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-22.md

  - id: search
    type: io.kestra.plugin.langchain4j.rag.Search
    provider:
      type: io.kestra.plugin.langchain4j.provider.GoogleGemini
      modelName: gemini-embedding-exp-03-07
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.langchain4j.embeddings.KestraKVStore
    query: "Feature Highlights"
    maxResults: 5
    minScore: 0.5
    fetchType: FETCH

Properties

embeddings *Elasticsearch KestraKVStore PGVector

maxResults *integerstring

minScore *numberstring

provider *AmazonBedrock Anthropic AzureOpenAI DeepSeek GoogleGemini GoogleVertexAI MistralAI Ollama OpenAI

query *string

fetchType string

Default NONE

Possible Values

STOREFETCHFETCH_ONENONE

Outputs

results array

SubType string

size integer

uri string

Format uri

Definitions

Google VertexAI Model Provider

endpoint *string

location *string

modelName *string

project *string

type *object

Azure OpenAI Model Provider

endpoint *string

modelName *string

type *object

apiKey string

clientId string

clientSecret string

serviceVersion string

tenantId string

Deepseek Model Provider

apiKey *string

modelName *string

type *object

baseUrl string

Default https://api.deepseek.com/v1

io.kestra.plugin.langchain4j.embeddings.Elasticsearch-ElasticsearchConnection

hosts *array

SubType string

Min items 1

basicAuth Elasticsearch-ElasticsearchConnection-BasicAuth

headers array

SubType string

pathPrefix string

strictDeprecationMode booleanstring

trustAllSsl booleanstring

Anthropic AI Model Provider

apiKey *string

modelName *string

type *object

OpenAI Model Provider

apiKey *string

modelName *string

type *object

baseUrl string

Ollama Model Provider

endpoint *string

modelName *string

type *object

io.kestra.plugin.langchain4j.embeddings.Elasticsearch-ElasticsearchConnection-BasicAuth

password string

username string

In-memory Embedding Store that then store its serialization form as a Kestra K/V pair

type *object

kvName string

Default {{flow.id}}-embedding-store

Google Gemini Model Provider

apiKey *string

modelName *string

type *object

Amazon Bedrock Model Provider

accessKeyId *string

modelName *string

secretAccessKey *string

type *object

modelType string

Default COHERE

Possible Values

COHERETITAN

PGVector Embedding Store

database *string

host *string

password *string

port *integerstring

table *string

type *object

user *string

useIndex booleanstring

Default false

Mistral AI Model Provider

apiKey *string

modelName *string

type *object

baseUrl string

Elasticsearch Embedding Store

connection *Elasticsearch-ElasticsearchConnection

indexName *string

type *object

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