AI Chroma

AI Chroma
Certified
Store embeddings in Chroma

Connects to a Chroma HTTP instance using cosine distance; targets the given collection and drops it when drop=true.

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

Examples

Ingest documents into a Chroma 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.Chroma
      baseUrl: http://localhost:8000
      collectionName: embeddings
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md

Properties

baseUrl *string

The database base URL

collectionName *string

The collection name

Pinecone

Interact with Pinecone, a managed vector database, from your Kestra workflows. Create serverless indexes, upsert vectors, query by similarity, fetch or delete vectors by ID, and inspect index statistics.

AIData

Klaviyo

Tasks that interact with Klaviyo campaign APIs.

AIBusiness

AI ChromaCertifiedStore embeddings in Chroma

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