Event-Driven Declarative Orchestrator

Kestra Pinecone Plugin

Interact with Pinecone, a managed vector database, from your Kestra workflows.

Tasks

Task	Description
io.kestra.plugin.pinecone.CreateIndex	Create a serverless Pinecone index
io.kestra.plugin.pinecone.DeleteIndex	Delete a Pinecone index
io.kestra.plugin.pinecone.Upsert	Upsert vectors from an inline list or an ION file
io.kestra.plugin.pinecone.Query	Query by vector similarity (FETCH / FETCH_ONE / STORE)
io.kestra.plugin.pinecone.FetchVectors	Fetch specific vectors by ID
io.kestra.plugin.pinecone.DeleteVectors	Delete vectors by ID or clear a namespace
io.kestra.plugin.pinecone.DescribeIndexStats	Describe index statistics (vector counts per namespace)

Example

id: pinecone_pipeline
namespace: company.team

tasks:
  - id: create_index
    type: io.kestra.plugin.pinecone.CreateIndex
    apiKey: "{{ secret('PINECONE_API_KEY') }}"
    indexName: my-embeddings
    dimension: 1536
    metric: cosine
    cloud: aws
    region: us-east-1

  - id: upsert_vectors
    type: io.kestra.plugin.pinecone.Upsert
    apiKey: "{{ secret('PINECONE_API_KEY') }}"
    indexName: my-embeddings
    namespace: production
    vectors:
      - id: vec1
        values: [0.1, 0.2, 0.3]
        metadata:
          source: document_a

  - id: query_similar
    type: io.kestra.plugin.pinecone.Query
    apiKey: "{{ secret('PINECONE_API_KEY') }}"
    indexName: my-embeddings
    namespace: production
    topK: 10
    vector: [0.1, 0.2, 0.3]
    includeMetadata: true
    fetchType: FETCH

Local Development

To run integration tests locally, start the Pinecone emulator first:

docker compose -f docker-compose-ci.yml up -d
./gradlew test

Documentation

Full documentation: kestra.io/docs

Plugin Developer Guide: kestra.io/docs/plugin-developer-guide

License

Apache 2.0 © Kestra Technologies