# Voyage AI

On Epsilla Cloud, you can enable Voyage AI integration by providing your Voyage AI API key (we securely manage your keys using AWS KMS):

<figure><img src="https://2532879721-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FM0ZX7fId7ifK45ldHWEp%2Fuploads%2Fgit-blob-0395aaeeacee39a9c5c2493d96ffd4c269b2592c%2FScreenshot%202024-05-18%20at%208.52.45%20AM.png?alt=media" alt=""><figcaption></figcaption></figure>

## Embeddings

Epsilla integrates with Voyage AI with the following embedding models:

| Name                                 | Dimensions |
| ------------------------------------ | ---------- |
| **voyageai/voyage-multimodal-3**     | 1024       |
| **voyageai/voyage-context-3**        | 1024       |
| **voyageai/voyage-3.5**              | 1024       |
| **voyageai/voyage-3.5-lite**         | 512        |
| **voyageai/voyage-3-large**          | 1024       |
| **voyageai/voyage-3**                | 1024       |
| **voyageai/voyage-3-lite**           | 512        |
| **voyageai/voyage-code-3**           | 1024       |
| **voyageai/voyage-large-2**          | 1536       |
| **voyageai/voyage-2**                | 1024       |
| **voyageai/voyage-code-2**           | 1536       |
| **voyageai/voyage-lite-02-instruct** | 1024       |

For Epsilla open source vector db, you just need to add a header in the data ingestion and semantic search queries [like this](https://epsilla-inc.gitbook.io/epsilladb/advanced-topics/embeddings#voyage-ai-embedding).

Then you can start using the voyageai embedding models during vector table schema creation:

<figure><img src="https://2532879721-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FM0ZX7fId7ifK45ldHWEp%2Fuploads%2Fgit-blob-4bcc7cd07acfb3bbd38b1381911b2792e41fc7d1%2FScreenshot%202024-01-31%20at%2012.10.07%20PM.png?alt=media" alt=""><figcaption></figcaption></figure>