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Vertex AI Embedding Configuration

Vertex AI serves Google’s text embedding models from your own Google Cloud project, billed and governed alongside the rest of your cloud resources.

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Before you start

Create a service account with the Vertex AI User role and download a JSON key. The steps are the same as for Vertex AI text generation.

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Required Fields

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GCP Project ID *

The Google Cloud project that hosts Vertex AI. It must match the project_id inside your service account JSON.

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Service Account JSON *

Upload the JSON key file. Novaplan AI checks that it is valid JSON, contains type, project_id and private_key, and has "type": "service_account".

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Model Name *

The embedding model to use, for example text-embedding-004 or text-multilingual-embedding-002. Use a multilingual model if your documents are not all in English.

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Optional Fields

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Region

The Vertex AI region, for example us-central1. Default: us-central1

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Model Friendly Name

A label shown in the Novaplan AI interface so you can tell several configurations apart. If you leave it blank, the model name is used.

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Dimensions

The number of dimensions in the vectors this model produces. Novaplan AI uses it to size the vector collection.

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Is Multimodal

Turn this on if the model can embed images as well as text. It is off by default.

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Related

• Vertex AI for text generation
• Gemini for embeddings