> For the complete documentation index, see [llms.txt](https://epsilla-inc.gitbook.io/epsilladb/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://epsilla-inc.gitbook.io/epsilladb/epsilla-vector-database/integrations/voyage-ai.md).

# 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="/files/oWFdQUhhhtZOCb9TkHUB" 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-instruct** | 1024       |
| **voyageai/voyage-finance-2**        | 1024       |
| **voyageai/voyage-multilingual-2**   | 1024       |
| **voyageai/voyage-law-2**            | 1024       |
| **voyageai/voyage-code-2**           | 1536       |
| **voyageai/voyage-large-2**          | 1536       |
| **voyageai/voyage-2**                | 1024       |

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

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

<figure><img src="/files/kmYZnEAvGPWrPFhS9pPy" alt=""><figcaption></figcaption></figure>