Embeddings Tablestore

Embeddings Tablestore

Certified

Store embeddings in Alibaba Tablestore

Connects to Tablestore using access keys and writes embeddings with cosine distance. Uses the configured instance/endpoint; metadata schemas are optional. drop=true is not supported—manage cleanup in Tablestore.

yaml
type: io.kestra.plugin.ai.embeddings.Tablestore

Ingest documents into a Tablestore 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-001
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.Tablestore
      endpoint:  "{{ secret('TABLESTORE_ENDPOINT') }}"
      instanceName:  "{{ secret('TABLESTORE_INSTANCE_NAME') }}"
      accessKeyId:  "{{ secret('TABLESTORE_ACCESS_KEY_ID') }}"
      accessKeySecret:  "{{ secret('TABLESTORE_ACCESS_KEY_SECRET') }}"
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md
Installation

Our standard Docker images already include this plugin. If you use a -slim image or another setup, install it with the following command: 

kestractl plugins get io.kestra.plugin:plugin-ai --compatible-for $KESTRA_VERSION

For kestractl, use your Kestra version with --compatible-for, or specify an exact plugin version.

For Kestra CLI, replace LATEST with a specific version or version range to pin the plugin version.

Properties

Access Key ID

Alibaba Cloud access key ID used to authenticate against Tablestore. Store it as a Kestra secret rather than inline. No default: this property is required.

Access Key Secret

Alibaba Cloud access key secret paired with accessKeyId. Store it as a Kestra secret rather than inline. No default: this property is required.

Endpoint URL

Base URL of the Tablestore instance endpoint. No default: this property is required.

Instance name

Name of the Tablestore instance holding the embeddings. No default: this property is required.

Metadata schema list

Tablestore field schemas describing the metadata columns to index, so they can be filtered on at search time. Not set by default (no metadata indexed).

Definitions
analyzerstring
Possible Values
SingleWordMaxWordMinWordSplitFuzzy
analyzerParameter
dateFormatsarray
SubTypestring
enableHighlightingboolean
enableSortAndAggboolean
fieldNamestring
fieldTypestring
Possible Values
LONGDOUBLEBOOLEANKEYWORDTEXTNESTEDGEO_POINTDATEVECTORFUZZY_KEYWORDIPJSONFLATTENEDUNKNOWN
indexboolean
indexOptionsstring
Possible Values
DOCSFREQSPOSITIONSOFFSETS
isArrayboolean
jsonTypestring
Possible Values
FLATTENNESTEDOBJECT
sourceFieldNamesarray
SubTypestring
storeboolean
subFieldSchemasarray
vectorOptions
dataTypestring
dimensioninteger
metricTypestring
Possible Values
EUCLIDEANCOSINEDOT_PRODUCT

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