AI MongoDBAtlas

AI MongoDBAtlas
Certified
Store embeddings in MongoDB Atlas

Uses MongoDB Atlas vector search with the provided collection/index; can optionally create the index and wait for readiness (up to 1 minute). Supply scheme/host and credentials; drop=true removes stored vectors.

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

Examples

Ingest documents into a MongoDB Atlas 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.MongoDBAtlas
      scheme: mongodb+srv
      username: "{{ secret('MONGODB_ATLAS_USERNAME') }}"
      password: "{{ secret('MONGODB_ATLAS_PASSWORD') }}"
      host: "{{ secret('MONGODB_ATLAS_HOST') }}"
      database: "{{ secret('MONGODB_ATLAS_DATABASE') }}"
      collectionName: embeddings
      indexName: embeddings
    fromExternalURLs:
      - https://raw.githubusercontent.com/kestra-io/docs/refs/heads/main/content/blogs/release-0-24.md

Properties

collectionName *string

Collection name

Collection that stores the embedding documents. No default: this property is required.

database *string

Database name

Name of the database holding the embeddings collection. No default: this property is required.

host *string

Host

Hostname of the MongoDB cluster, optionally with a port for the mongodb scheme. No default: this property is required.

indexName *string

Index name

Name of the Atlas Vector Search index used to query the collection. No default: this property is required.

scheme *string

Connection scheme

Scheme of the MongoDB connection string: mongodb+srv for Atlas clusters, mongodb for a direct connection. No default: this property is required.

createIndex booleanstring

Create the index

If true, create the Atlas Vector Search index when it does not already exist. Defaults to false, which assumes the index is provisioned beforehand.

metadataFieldNames array

SubTypestring

Metadata field names

Metadata keys to map into the vector search index so they can be filtered on. Not set by default, in which case no metadata index mapping is created.

options object

Connection string options

Extra options appended to the MongoDB connection string as query parameters. Not set by default.

password string

Password

Password of the database user. Store it as a Kestra secret rather than inline. Not set by default; omit it along with username for an unauthenticated connection.

username string

Username

User connecting to the MongoDB Atlas cluster. Not set by default; omit it along with password for an unauthenticated connection.