# gcp_vertex_ai_embeddings

> For the complete documentation index, see [llms.txt](https://docs.redpanda.com/llms.txt). Component-specific: [cloud-data-platform-full.txt](https://docs.redpanda.com/cloud-data-platform-full.txt)

---
title: gcp_vertex_ai_embeddings
page-beta-text: This is a beta feature. Beta features are available for testing and feedback. They are not supported by Redpanda and should not be used in production environments.
latest-operator-version: v26.1.4
latest-console-tag: v3.7.3
latest-connect-version: 4.93.0
latest-redpanda-tag: v26.1.9
docname: connect/components/processors/gcp_vertex_ai_embeddings
page-component-name: cloud-data-platform
page-version: master
page-component-version: master
page-component-title: Cloud
page-relative-src-path: connect/components/processors/gcp_vertex_ai_embeddings.adoc
page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/develop/pages/connect/components/processors/gcp_vertex_ai_embeddings.adoc
# Beta release status
page-beta: "true"
page-git-created-date: "2024-10-16"
page-git-modified-date: "2026-05-26"
release-status: beta - This is a beta feature. Beta features are available for testing and feedback. They are not supported by Redpanda and should not be used in production environments.
---

<!-- Source: https://docs.redpanda.com/cloud-data-platform/develop/connect/components/processors/gcp_vertex_ai_embeddings.md -->

**Available in:** Cloud, [Self-Managed](https://docs.redpanda.com/connect/components/processors/gcp_vertex_ai_embeddings/%20%22View%20the%20Self-Managed%20version%20of%20this%20component%22)

Generates vector embeddings to represent a text string, using the [Vertex AI API](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings).

```yml
# Configuration fields, showing default values
label: ""
gcp_vertex_ai_embeddings:
  project: "" # No default (required)
  credentials_json: "" # No default (optional)
  location: us-central1
  model: text-embedding-004 # No default (required)
  task_type: RETRIEVAL_DOCUMENT
  text: "" # No default (optional)
  output_dimensions: 0 # No default (optional)
```

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.

For more information, see the [Vertex AI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/embeddings).

## [](#fields)Fields

### [](#credentials_json)`credentials_json`

Set your Google Service Account Credentials as JSON.

> ⚠️ **CAUTION**
>
> This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see [Manage Secrets](https://docs.redpanda.com/cloud-data-platform/develop/connect/configuration/secret-management/) before adding it to your configuration.

**Type**: `string`

### [](#location)`location`

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

**Type**: `string`

**Default**: `us-central1`

### [](#model)`model`

The name of the LLM to use. For a full list of models, see the [Vertex AI Model Garden](https://console.cloud.google.com/vertex-ai/model-garden).

**Type**: `string`

```yaml
# Examples:
model: text-embedding-004

# ---

model: text-multilingual-embedding-002
```

### [](#output_dimensions)`output_dimensions`

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

**Type**: `int`

### [](#project)`project`

The ID of your Google Cloud project.

**Type**: `string`

### [](#task_type)`task_type`

Use the following options to optimize embeddings that the model generates for specific use cases.

**Type**: `string`

**Default**: `RETRIEVAL_DOCUMENT`

| Option | Summary |
| --- | --- |
| CLASSIFICATION | optimize for being able classify texts according to preset labels |
| CLUSTERING | optimize for clustering texts based on their similarities |
| FACT_VERIFICATION | optimize for queries that are proving or disproving a fact such as "apples grow underground" |
| QUESTION_ANSWERING | optimize for search proper questions such as "Why is the sky blue?" |
| RETRIEVAL_DOCUMENT | optimize for documents that will be searched (also known as a corpus) |
| RETRIEVAL_QUERY | optimize for queries such as "What is the best fish recipe?" or "best restaurant in Chicago" |
| SEMANTIC_SIMILARITY | optimize for text similarity |

### [](#text)`text`

The text you want to generate vector embeddings for. By default, the processor submits the entire payload as a string. This field supports [interpolation functions](https://docs.redpanda.com/cloud-data-platform/develop/connect/configuration/interpolation/#bloblang-queries).

**Type**: `string`