MariaDB

MariaDB Embedding Store

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

Examples

Ingest documents into a MariaDB embedding store

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.MariaDB
      username: "{{ kv('MARIADB_USERNAME') }}"
      password: "{{ kv('MARIADB_PASSWORD') }}"
      databaseUrl: "{{ kv('MARIADB_DATABASE_URL') }}"
      tableName: embeddings
      fieldName: id
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md

Properties

createTable *booleanstring

Whether to create the table if it doesn't exist

databaseUrl *string

Database URL of the MariaDB database (e.g., jdbc: mariadb://host: port/dbname)

fieldName *string

Name of the column used as the unique ID in the database

password *string

The password

tableName *string

Name of the table where embeddings will be stored

username *string

The username

columnDefinitions array

SubType string

Metadata Column Definitions

List of SQL column definitions for metadata fields (e.g., 'text TEXT', 'source TEXT'). Required only when using COLUMN_PER_KEY storage mode.

indexes array

SubType string

Metadata Index Definitions

List of SQL index definitions for metadata columns (e.g., 'INDEX idx_text (text)'). Used only with COLUMN_PER_KEY storage mode.

metadataStorageMode string

Metadata Storage Mode

Determines how metadata is stored: - COLUMN_PER_KEY: Use individual columns for each metadata field (requires columnDefinitions and indexes). - COMBINED_JSON (default): Store metadata as a JSON object in a single column. If columnDefinitions and indexes are provided, COLUMN_PER_KEY must be used.

​Maria​D​B

MariaDB