PluginsPlugin AiEmbeddings

Tablestore​Tablestore

Tablestore Embedding Store

Always uses cosine distance as the distance metric

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-exp-03-07
      apiKey: "{{ kv('GEMINI_API_KEY') }}"
    embeddings:
      type: io.kestra.plugin.ai.embeddings.Tablestore
      endpoint:  "{{ kv('TABLESTORE_ENDPOINT') }}"
      instanceName:  "{{ kv('TABLESTORE_INSTANCE_NAME') }}"
      accessKeyId:  "{{ kv('TABLESTORE_ACCESS_KEY_ID') }}"
      accessKeySecret:  "{{ kv('TABLESTORE_ACCESS_KEY_SECRET') }}"
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md
Properties

Access Key ID

The access key ID used for authentication with the database.

Access Key Secret

The access key secret used for authentication with the database.

Endpoint URL

The base URL for the Tablestore database endpoint.

Instance Name

The name of the Tablestore database instance.

SubType

Metadata Schema List

Optional list of metadata field schemas for the collection.

Possible Values
SingleWordMaxWordMinWordSplitFuzzy
SubType string
Possible Values
LONGDOUBLEBOOLEANKEYWORDTEXTNESTEDGEO_POINTDATEVECTORFUZZY_KEYWORDIPJSONUNKNOWN
Possible Values
DOCSFREQSPOSITIONSOFFSETS
Possible Values
FLATTENNESTED
SubType string
SubType
Possible Values
EUCLIDEANCOSINEDOT_PRODUCT