Skip to main content

gcp_vertex_ai_embeddings

Generates vector embeddings to represent a text string, using the Vertex AI API.

This processor sends text strings to the Vertex AI API, which generates vector embeddings for them. By default, the processor submits the entire payload of each message as a string, unless you use the text field to customize it.

# Config fields, showing default values
processor:
  label: ""
  gcp_vertex_ai_embeddings:
    credentials_json: ""
    location: us-central1
    model: "" # No default (required)
    output_dimensions: 0
    project: "" # No default (required)
    task_type: RETRIEVAL_DOCUMENT
    text: ""

Examples​

Generate a vector embedding for each message payload using a chosen model.

processor:
  gcp_vertex_ai_embeddings:
    project: my-gcp-project
    model: text-embedding-004

Fields​

credentials_json​

Set your Google Service Account Credentials as JSON. :::warning Secret This field contains sensitive information that usually shouldn't be added to a config directly, read our secrets page for more info. :::

Type: string
Default: ""

location​

The location of the Vertex AI large language model (LLM) that you want to use.

Type: string
Default: "us-central1"

model​

The name of the LLM to use. For a full list of models, see the Vertex AI Model Garden.

Type: string

output_dimensions​

The maximum length of a generated vector embedding. If this value is set, generated embeddings are truncated to this size.

Type: int
Default: 0

project​

The ID of your Google Cloud project.

Type: string

task_type​

Optimize the embeddings that the model generates for a specific use case, such as document retrieval or similarity.

Type: string
Default: "RETRIEVAL_DOCUMENT"

text​

The text you want to generate vector embeddings for. By default, the processor submits the entire payload as a string.

Type: string
Default: ""