Azure Embeddings

Azure Embeddings

Certified

Generate vector embeddings from text input

Use Azure AI Foundry to generate embeddings using a deployed model endpoint.

yaml
type: io.kestra.plugin.azure.aifoundry.Embeddings

Generate embeddings and log the result

yaml
    id: azure_ai_embeddings
    namespace: company.team
    tasks:
      - id: embed
        type: io.kestra.plugin.azure.aifoundry.Embeddings
        endpoint: "{{ secret('AZURE_AI_FOUNDRY_ENDPOINT') }}"
        apiKey: "{{ secret('AZURE_AI_FOUNDRY_API_KEY') }}"
        deploymentName: text-embedding-3-small
        inputs:
          - "The quick brown fox jumps over the lazy dog."
      - id: log_result
        type: io.kestra.plugin.core.log.Log
        message: "Embedding vector length: {{ outputs.embed.embeddings[0] | length }}"
Properties

The name of the deployment to use

Azure AI Foundry endpoint

The Azure AI Foundry project or model endpoint URL.

SubTypestring

The text inputs to generate embeddings for

Azure AI Foundry API key

API key for API-key authentication. When omitted, DefaultAzureCredential (Entra ID) is used instead.

Azure client ID

Client ID of the Azure app registration used with tenantId and clientSecret.

Azure client secret

Client secret of the Azure app registration used with tenantId and clientId.

Reference (ref) of the pluginDefaults to apply to this task.

Azure tenant ID

Azure Entra tenant ID used with clientId and clientSecret for service principal authentication.

SubTypearray

The generated embeddings, one list of floats per input text

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