Embeddings KestraKVStore
CertifiedPrototype embeddings in Kestra KV
Embeddings KestraKVStore
Prototype embeddings in Kestra KV
Stores embeddings in-memory and persists them to Kestra namespace KV on completion. Suitable for small demos; not scalable. drop=true discards any previously saved KV snapshot.
type: io.kestra.plugin.ai.embeddings.KestraKVStoreExamples
Ingest documents into a KV embedding store.\nWARNING: the KestraKVStore embeddings are for quick prototyping only; since they are stored in a KV store and loaded into memory, this won't scale with large numbers of documents.
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.KestraKVStore
drop: true
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
kvName string
{{ flow.id }}-embedding-storeKV pair name
Key of the Kestra KV pair used to persist the in-memory embedding store between task runs. Defaults to {{ flow.id }}-embedding-store.
